Introduction

Housing satisfies one of the most important basic needs of human beings — the need for shelter. However, access to affordable and decent housing is not always guaranteed. Therefore, quite often, governments across the globe intervene to correct for what some view as a “market failure”. The main purpose of housing policy in a narrow sense is to deliver affordable, decent, and sustainable housing. Government applies a wide variety of tools to achieve this purpose. Nevertheless, each tool has its advantages and disadvantages. It is perfectly possible that by curing one problem another problem is created. Moreover, by producing opposite effects different policies can offset each other, resulting in inefficiencies.

In this study, I conduct an overview of a large empirical literature that investigates effects of various policies affecting housing market. Housing policies (including rent control, protection from eviction, housing rationing, housing allowances, provision of social housing, mortgage interest deduction, building codes, and land-use regulations) play the most important role in this respect. However, housing market performance is shaped not only by housing policies, but also by other policies, such as monetary, fiscal, and labor policies. Therefore, I do not confine myself to considering only the effects of housing policies, but prefer to examine all policies that are relevant from the standpoint of housing. My aim is to compare as comprehensive as possible range of potential effects of these policies and to draw some conclusions about an optimal policy mix.

The next section provides a detailed description of various housing policies tools. In section 3, the results of empirical studies are summarized. In section 4, possible outcomes of housing policies by leftist and liberal governments are examined. Finally, I attempt to figure out an optimal policy mix that provides socially acceptable effects with lowest costs.

Housing policy tools

There is a very wide variety of housing policies. Here, I intend to provide their systematic and comprehensive representation based on the aims and trade offs related to them. The policies are classified in terms of housing tenure (owner-occupied vs. rental housing) and in terms of the policy purposes (affordable vs. decent and sustainable housing). On the one hand, housing policies can promote certain tenure, but they generally do it at the expense of the other tenure. For example, public subsidies to facilitate formation of the homeownership can reduce the amount of resources available for the rental housing. On the other hand, there is a trade off between affordable housing vs. decent and sustainable housing. For instance, the state may raise the quality standards of housing (the minimum size of dwelling, availability of heating or air conditioning, or number of parking spaces), thus, making it more decent, or require the introduction of energy-saving measures (improvement of insulation or installation of solar batteries), thus, increasing the sustainability of the housing. At the same time, these measures will make housing more expensive and, therefore, less affordable.

The figure below presents a taxonomy of various housing policy tools in the form of an aims and trade offs cross. The red color denotes restrictive policies that constrain the behavior of market agents. The greenish color denotes stimulating policies implying that the government provides direct or indirect support in form of subsidies or tax deductions.

Taxonomy of housing policy tools

Taxonomy of housing policy tools

In the northeast quadrant, policies aimed at improving the affordability of rental housing are located. It is supposed to be attained using three restrictive policies (rent control, protection of tenants from eviction, and housing rationing) and two stimulating policies (housing allowances and social housing). The affordability of owner-occupied housing is thought to be achieved through two stimulating policies (direct homeownership subsidy and indirect subsidy in form of mortgage interest deduction) and through two restrictive policies (imputed rent tax and home purchase restrictions). In addition, there are two affordability policies that are applied to both rental and owner-occupied housing. These are second-home and vacancy taxes.

The southern part of the cross contains the policies whose purpose is to make the housing more decent and more sustainable. All these policies can be classified as restrictive. Specifically, one policy (macroprudential regulations) guarantees the sustainability of owner-occupied housing and one policy is aimed at the decent rental housing (habitability laws). The other five policies (capital gains tax, transfer tax, property tax, building codes, and land use regulations) are supposed to improve the decency and sustainability of all types of housing regardless of its tenure. These policies are explained in more detail below.

Stimulation of residential construction

The main purpose of the stimulation of residential construction policy is to expand the supply of housing, in particular of cheap homes. The rising supply should make housing more affordable. Other purposes are also pursued. It is, for example, a creation of a strong class of owners who are resistant against the communist propaganda. Especially in aging societies, the purpose of simulating policies is often the accumulation of wealth to provide for old age. Homeowners tend to have a lower housing cost burden than renters (Konstantin A. Kholodilin and Kohl 2023c). Thus, helping households to become homeowners will make them less vulnerable to rent increases as they age. Support of families, improvement of housing conditions, and fostering the economy through construction industry, among others, are also the goals of stimulating housing policy (Haas 2018). The policy of stimulating residential construction includes the following instruments: provision of state aid in form of construction subsidies and low or zero interest loans; provision of the state credit guarantees; reduction of the taxes and fees (particularly, land stamp duty); and provision of building land at lower prices or in form of a long-term leasing.

Using such instruments, the state intends to foster residential building and, first, provide low-income households with affordable housing. This housing — sometimes called social housing — can be both rental and owner-occupied. Sometimes (for example, in Spain in the 1940–1970s) the state builds rental housing that will subsequently be purchased by the tenants. In Iceland in the 1930–1970s, social workers’ houses were predominantly built as owner-occupied ones (Sveinsson 2004). The rent in social housing is subject to restrictions and is typically set at the level of the construction and operation costs plus a moderate markup representing a “fair profit” for the landlord. Admittance as a tenant in social housing requires proving that you have a low enough income. However, once moved in, tenant income is practically never tested again. As a result, households with increased income keep occupying social housing, even though they are formally no longer eligible for it, because their income exceeds the admittance threshold. For this reason, many low-income persons cannot gain access to social housing. The problem is that both verifying the income levels of households living in social housing and carrying out evictions are too costly. By decreasing its efficiency, this is one of the main disadvantages of social rental housing.

Perhaps the earliest example of social housing policy can be found in China during the Southern Song dynasty (1127–1279) (Bí 2013). The imperial authorities set up dianzhaiwu — an official entity that was in charge of managing, leasing, and maintaining public land and public housing (guanfang). This housing was provided to both the state officials and to ``normal citizens.’’

Housing allowances

Housing allowances are state subsidies paid to low-income households or, sometimes, directly to their landlords (for example, in the USA, where this aid is known as housing vouchers). The idea is to cover a part of the housing costs of such households in order to permit them to live in appropriate conditions. This policy can be considered to be an alternative or a complement to social housing policy. In this case, the means testing can be conducted on a continuous basis, with housing allowances adjusted in accordance with the changing income of the household. It is also a more flexible form of aid, since it allows the households to choose the dwelling where they would like to live more freely.

Protection of tenants from eviction

The purpose of the protection of tenants from eviction policy is to reduce eviction risks for the tenants. Prior to World War I, in most countries the corresponding legislation was very liberal. The relations between landlord and tenants were regulated mainly by their rental contract. The contracts could have a definite or indefinite duration. If the contract duration was definite, then after it was over, the landlord could evict the tenant without any formalities. During the contract term, eviction could only normally happen if the tenant violated certain conditions indicated in the contract or in the civil code. One such eviction reason could be the delayed payment of rent.

At that time, contracts, as a rule, were short term, typically up to one year. Under normal conditions, this did not cause too many problems for the tenants. However, in the extraordinary situations, such as wars, revolutions, natural catastrophes, etc., which led to an acute housing shortage, a loss of housing due to eviction could result in homelessness. Therefore, when faced with such situations, almost everywhere policy makers started introducing the following limitations to make the eviction of tenants more difficult: 1) automatic prolongation of the existing contracts upon their expiration, sometimes indefinitely, sometimes for a short period, which was, however, steadily extended with each new legal act; 2) prohibition for the landlords to break rental contracts, except for a more or less clearly identified set of reasons: e.g., non-payment of rent; urgent need of the landlord or his relatives to move into the dwelling occupied by the tenant; negligent treatment of the housing by the tenant; his unacceptable behavior with respect to other tenants or the owner; 3) setting the minimum duration of finite contracts; and 4) prohibition of short-term (less than 1 year) letting.

Rent control

The main purpose of rent control policy is the protection of tenants from rental increases. When housing becomes scarce, rents start growing because, in the short run, which can last several years, it is impossible to expand housing supply quickly. As rent is one of the most important components of household expenditures (in different countries, the share of the housing expenses varies around 15–30%), its increases strongly affect the purchasing power of the population.

Rent control appears to be one the oldest housing policies, the first use of it being documented as early as 48 BC in the Ancient Rome (Konstantin A. Kholodilin 2024b). This policy became very widespread and large-scaled during World War I. At the beginning of the war, the vast majority of urban populations in Europe and North America were tenants. Mass mobilization converted them into a powerful force, meaning that the authorities had to respect their interests. Therefore, in order to avoid social turmoil, governments froze prices for basic consumption goods and services, including housing rents. Initially, this policy was thought to serve as an interim emergency measure, which would be removed as soon as the housing market returned to normality. Nevertheless, once put in place, rent control was prolonged many times, ultimately remaining in effect for many decades.

Rent control includes: 1) rules regulating the setting of rent in newly concluded rental contracts (either immediately after construction of a dwelling is completed or after the previous contract is over); 2) rules regulating updating rent within the existing rental contracts; 3) exceptions, which specify either housing not subject to the regulations or the segments of the housing market subject to stricter controls.

Typically, researchers distinguish between first- and second-generation rent controls; see, for example, Blumberg, Robbins, and Baar (1974), Arnott (1995). Along with this dual classification, there are also alternative classifications (see the table below). In 2003, Arnott (2003) introduced a classification with three generations of rent control. While the definitions of the first and second generations remain unchanged, the third generation introduces a distinction whereby rent increases are limited exclusively during the term of the lease, but are unrestricted between different tenancies. Consequently, when a new tenant replaces the previous one, rents can be raised significantly higher than what would have been permitted by tying it to a cost of living index. Hubert (2003) suggests a model that distinguishes between two types: the transfer model and regulated tenure. This classification not only considers restrictions on rental rates but also limitations on landlords’ ability to evict tenants. In terms of rent regulations, they can be broadly associated with the first- and second-generation rent control, respectively. Additionally, the transfer model applies to a portion of the housing stock, while regulated tenure extends to nearly all dwellings. Consequently, the former represents a more stringent and intermediate regulation, whereas the latter offers greater flexibility yet remains more permanent. Nevertheless, many cases can be found in the history of rent control, where strict rent regulations remained in place for many decades. Thus, in my opinion, this classification does not always reflect the reality. Finally, Lind (2001) proposes an intricate classification, consisting of five classes of rent control: A, B, C, D, and E. These classes differ in the scope of protection (sitting tenants or all tenants) and the types of rent they safeguard against (rents exceeding market rates or specific forms of rent increases). While these three detailed classifications allow for a more realistic approach to existing regulations, they may prove overly intricate for practical application. Therefore, I find that the typology including two generations of rent control is parsimonious and yet powerful enough.

Arnott (2003) Hubert (2003) Lind (2001)
First generation: rent freeze, with perhaps intermittent upward adjustments only partially offsetting inflation Transfer model: The rent which can be legally charged for a dwelling is fixed below market rent, usually at its historical level. The tenant cannot be evicted except for a limited set of reasons, but may be granted the right to give notice to quit if the original contract prevented him from doing so. The coverage of the regulation is only partial, e.g., limited to the existing stock, certain regions, certain types of dwellings, or old leases. Type A: weak transaction cost-related rent regulation - Protecting a sitting tenant against rents higher than the market rent
Second generation: rents allowed to be increased annually by a certain percentage automatically (guideline rent increase provisions), and contained supplementary provisions which permitted rents to be further increased on a discretionary basis in response to some combination of cost increases (cost pass-through provisions), cashflow considerations (financial hardship provisions), and profitability concerns (rate of return provisions) Regulated tenure: Tenure laws provide the tenant with considerable (mandatory) security of tenure. Rent updating during the term is regulated but there are little or no restrictions on the initial rent. The legislation is meant to be permanent and almost comprehensive in its coverage. Type B: strong transaction cost-related rent regulation - Protecting sitting tenants against certain types of increases in market rents
Third generation: rent increases are controlled within a tenancy but are unrestricted between tenancies Type C: monopoly-related rent regulation - Protecting all tenants against rents higher than the market rent
Type D: smoothing changes in market rents - Rent regulation related to overshooting
Type E: protecting all tenants against certain types of increases in market rents - Segregation related rent regulation

First-generation rent control implies a rent freeze, where the rent is fixed at some basic level. There are different ways of determining basic rent: 1) rent for this or similar dwellings at some date; typically, prior to some crucial event (e.g., a war) or at the date of enactment of the corresponding legal act (e.g., in Germany, Poland, and Spain after WWI as well as on the territory of the former Russian Empire during WWI and Russian Civil War); 2) certain percentage of the taxable (book) value of the dwelling (for instance, in Chile and Portugal); 3) absolute value (for example, in Italy and the USSR); or 4) value calculated by the local authorities depending on the structural and locational characteristics of the dwelling (e.g., in the USSR). Only governments could change the basic rent from time to time. It could not only be raised in order to cover at least a part of the growing expenses of the landlords, but also decreased in reaction to political or economic crises. The basic rent was reduced, for instance, in Chile in 1925 in reaction to a tenants strike, in Italy in 1927 and 1934, in Germany in 1931 as a result of the Great Depression, as well as in Poland in 1935. First-generation rent controls emerged during World War I and remained in force as late as the 1970s, when they started being replaced with second-generation rent controls; however, rent freezes are still used in some countries, especially developing ones. Second-generation rent control implies a more or less free setting of rent when new contracts are concluded, but imposition of upper bounds on its growth rate within existing contracts. The upper bound of rent growth can be the rate of increase of the consumer prices during the preceding year (e.g., in Colombia, Czech Republic, France, Italy, Poland, and Spain), mortgage interest rate (in Switzerland), or an index of government bonds (in Brazil).

In contrast, second-generation rent controls are much more flexible. Typically, a market rent is set when the lease is signed. However, during the term of the contract, rent increases are limited by linking them to increases in the cost of living. Sometimes, even under second-generation rent controls, rents in newly concluded contracts can be subject to limitations. For example, since 2015, in areas with an acute housing shortage in Germany, new rent cannot exceed the average market rent for similar dwellings in the same neighborhood by more than 10%.

Housing rationing

During acute housing shortages, governments can impose measures like compulsory disposal of the housing in order to use fully the available housing stock. These measures include: registration of both dwellings and tenants in order to create a register of the available and becoming vacant dwellings as well as the creation of a waiting list for potential tenants; preservation of housing by banning the demolition of it or conversion of its use to non-residential purposes (for example, as office space or holiday dwellings for tourists); redistribution of housing by putting new tenants into unused or underutilized housing; setting the maximum housing consumption norms (for instance, the maximum floor area or number of rooms per person); mobility restrictions meaning the creation of obstacles to move into areas with an especially acute housing shortage, while facilitating migration to other areas; nationalization of private housing by transferring it into state property.

As shown, the rationing of housing implies that the government intends to manipulate both its supply and demand. The supply is protected or, to some extent, increased through a mobilization of the available premises (including non-residential ones that are appropriate for lodging) for their use as housing. At the same time, demand is reduced by limiting the freedom of mobility and by setting low norms of housing consumption.

The earliest example of using housing rationing that I could find refers to the requisitioning of all vacant premises and putting them the disposal of the inhabitants of the districts that suffered from bombardments as prescribed by a decree of Paris Commune of April 25, 1871 (Konstantin A. Kholodilin 2024b).

Housing purchase restriction

In 21st century, some cities started applying a policy of restricting home purchases that closely resembles housing rationing. The first city to implement it was Beijing in 2010 (Du and Zhang 2015). As far as I know, so far this policy has been only used in China. In fact, it could be considered as an instrument of housing rationing. However, I prefer to treat this policy separately because it applies to owner-occupied housing and not to rentals.

The housing policy restriction, also known as home-purchase limits, is a policy that limits the number of houses that each buyer can purchase. For example, in Guangzhou, households with a local hukou (a kind of permanent residence permit granted to reside in a particular municipality) cannot buy additional housing units if they own two or more homes and can only buy one additional housing unit if they own already one home (Jia, Wang, and Fan 2018).

Habitability

The quality of housing can affect the health of its occupants. Besides the structural characteristics of housing (volume, ventilation, natural lighting, etc.) that can be regulated by building codes, there are other important aspects related to the maintenance of residential units. In some jurisdictions, landlords can be required not just to deal with storage and removal of household waste, thus to keep maintaining sanitation, but also to provide repairs, a water supply, and adequate heat for housing (N. Willis et al. 2017). These aspects can be explicitly regulated by the so-called habitability laws. For example, in the USA, many state and local governments have regulations that require landlords “to provide housing free from any defects that might impact a tenant’s health or safety” (Vigdor and Williams 2022).

Taxation of real estate

Through tax policy, the state sets various property taxes and exemptions therefrom. In this way, it changes the relative cost of both owned and rented housing, thus affecting the choice of a particular tenure form by making it more or less attractive from a financial perspective. In many countries, tax policy is biased toward homeownership. For example, in the Netherlands and the USA, interest payments are subtracted from taxable income; thus, making the purchase of own housing using borrowed money very attractive. This can lead to the emergence of speculative price bubbles in real estate markets (Figari et al. 2017). As an offsetting measure, taxation of imputed rent can be used. However, this instrument is rarely used: for example, it is primarily found in The Netherlands, where it applies to all dwellings, and Greece, where it only applies to large dwellings.

What are the main taxes imposed on the property? The most important types of property taxes or tax exemptions include the land stamp duty, the tax on imputed rent, the mortgage interest deductibility, the capital gains tax, and the value added tax (VAT) on new homes as on other durables.

The tax on imputed rent is a tax that is imposed on the financial user value of an owner-occupied dwelling. The basic idea is that the homeowner obtains an additional income inflow, since he, unlike a tenant, does not pay housing rent. Therefore, this additional income must be taxed in order to restore the equal treatment relative to other incomes. Moreover, in case mortgage interest is deductible, the imposition of the tax on imputed rent means that the tax neutrality with respect to tenure security is guaranteed. The tax on imputed rent tends to have a negative impact on the incentives to buy a home. Thus, its removal can have an incentivizing influence on homeownership.

The mortgage interest deductibility (MIT) is often accompanied by the tax on imputed rent. The logic is that income-related costs, which are incurred when earning the corresponding income, should be deductible. For example, in case of car production, the state taxes not the total revenue, but the profit, which is a difference between the total revenue and total cost. Mortgage interests are treated as a part of costs. In some cases, the mortgage interests can be deductible in absence of the tax on imputed rent. The mortgage interest deductibility makes the purchase of an own home more attractive. This can, however, foster a build-up of speculative price bubbles.

The capital gains tax is a tax that is imposed on the capital gains, that is, the difference between the purchase and the sale price. Therefore, it is sometimes also called a speculation tax, for it should reduce the incentives to buy real estate with the sole purpose of reselling it at higher prices, which can lead to speculative bubbles. However, likewise, the capital gains tax makes the purchase of homes to live in less attractive. Therefore, this tax is often designed in such a way as to hinder speculations without negatively affecting those purchases made with the owner-occupation motive. For example, in Germany, capital gains tax must be paid, if the dwelling is resold within 10 years after the purchase date, but only within 2 years, if the owner actually resided there for this period.

The VAT on new homes is a tax imposed on the purchase price of a new dwelling. This tax makes the dwelling more expensive and, hence, its purchase less attractive. On the other hand, it has a similar logic as the tax on imputed rent: if the real estate is to be treated equally with other goods, it must be subject to VAT. The absence of VAT on new homes can be considered as a kind of subsidy targeted to the buyers of new homes.

There are two types of taxes that are imposed on real estate regardless of its tenure status. The real-estate transfer tax is levied on transmission of real estate from one owner to another. Typically, it covers the sales transactions, but in principle it can also be applied to donations and inheritance. This tax is levied only in the case of transaction. By contrast, property tax is a recurrent tax, for it is levied annually on the owner of the real estate.

Foreign-buyer tax (FBT) is a form of the real estate transfer tax. It is motivated by the speculative demand from non-residents buying properties and, thus, inflating property prices. The imposition of such a tax should discourage foreigners from investing in local real estate. The tax is basically equivalent to a transfer tax whose level depends on the nationality of the buyer. Foreign nationals are required to pay a much higher tax rate. In 2024, FBT has been applied in Australia (Brisbane and Cairns, Melbourne, and Sydney), Canada (British Columbia and Toronto), Hong Kong, and Singapore (Hartley et al. 2021; Pavlov, Somerville, and Wetzel 2023).

Property tax serves as a means of generating revenue to support the funding of public goods and services. It can also be used to foster both horizontal and vertical equity. Moreover, property tax can effectively incentivize sustainable practices within the residential sector, such as promoting sustainable land use (Taranu and Verbeeck 2022).

Split-rate tax is a specific form of the property tax. In this case, the land and structure located on it are taxed at different rates. Typically, the land is taxed at a higher rate than the structure. This differential is supposed to stimulate the landowners to build sooner and more densely (Taranu and Verbeeck 2022). Land value tax is an extreme case, where only the land — but no structures — is subject to taxation.

Vacancy tax is aimed at activating the empty premises (Baba, Ruiz-Varona, and Asami 2022). By imposing this tax the local government intends to encourage the owners of vacant housing to sell it or let it. Apparently, the first country that introduced a vacancy tax was France in 1999. Its example was followed by the UK in 2015, Catalonia (Spain) in 2015, and Vancouver in 2017 (Caracciolo and Miglino 2024).

Second-home tax is closely related to the vacancy tax. It can be imposed on both an owner or a tenant who, besides a main dwelling, possesses an additional dwelling, which is typically located in some other municipality. As a rule, the tax is raised by the municipality as a compensation of its infrastructural expenses, but can also be used a means to reduce an excess demand for housing.

Building codes

Building codes are intended to promote health, safety, and energy efficiency of housing. In particular, they address the following aspects of buildings: 1) structural system, fire and general safety, enclosure, interior environment, and materials; 2) potable water supply and waste systems; 3) combustion and mechanical equipment; 4) the installation of electrical wiring and equipment; 5) the installation of gas piping and gas-burning equipment; 6) consumption of energy by the building; and 7) building accessibility to the physically disabled. (Listokin and Hattis 2005). This policy can be traced back as far as the 6th century CE, when it was introduced in the Byzantine Empire (Hakim 2008).

Land use regulations

Land use regulations, or city planning policy, impose constraints on the spatial distribution and density of housing construction. In particular, such constraints typically include minimum lot sizes, population density restrictions, and urban growth boundaries. Additionally, land use regulation establishes zoning, which determines the use of each zone (residential, industrial, recreational, etc.). Moreover, within specific zones, additional restrictions can be imposed, for example, those concerning the height of buildings and housing density (total surface of housing per surface of the land plot). This regulation can reduce the price elasticity of housing supply (C. A. L. Hilber and Vermeulen 2016). The reason is that such regulations limit the expansion of housing supply. As a result, there will be reduced supply at higher prices.

Banking regulations

Banking regulations generally restrict the supply of mortgage loans. This policy uses two major tools: 1) restriction of the ability of banks and other financial institutions to issue mortgage loans by setting buffers and 2) limitation of provision of loans to individuals based on their income and debt. After the Great Recession of 2008–2009, many countries introduced macroprudential regulations — defined as a prudential tool that is designed to tackle systemic risk — in order to avoid the buildup of speculative housing price bubbles by limiting the provision of mortgages. Opponents of this policy argue that it leads to a widening of the gap between the rich and poor, since the latter have a lower purchasing capacity and, hence, are subject to the restraints imposed on mortgages to a larger extent.

Cerutti, Claessens, and Laeven (2017) distinguish between two classes of macroprudential policy tools: 1) borrower-targeted policies are policies aimed at borrowers’ leverage and financial positions (caps on the debt-to-income (DTI) ratio and the loan-to-value (LTV) ratio) and 2) financial-institutions-targeted policies are policies aimed at financial institutions’ assets or liabilities (limits on domestic currency loans, limits on foreign currency loans, countercyclical capital buffers, the leverage ratio for banks, time-varying (dynamic) loan-loss provisioning, margining requirements on secured financing and derivative transactions, reserve requirement ratios, a levy on financial institutions, capital surcharges on systemically important financial institutions, limits on interbank exposures, concentration limits, limits on open foreign exchange positions or currency mismatches, liquidity requirements/buffers, and loan-to-deposit ratios). In addition, Wilhelmsson (2022) examines an amortization requirement that requires households to repay a certain percentage of their debt, if their mortgage debt exceeds 50% of the housing value. This instrument can be classified as a borrower-targeted policy.

Effects of housing policies

Like any other policy, housing policies have their intended and unintended effects. Some policies have numerous effects. The empirical literature investigates at least a part of these effects. An overview of such literature would allow us to shed some light on the pros and cons of each policy. To find the relevant studies I draw upon two main sources of information: the previous literature reviews and the online research paper databases. I use the following studies with literature overviews: 1) rent control: Gilderbloom and Appelbaum (1988), J. D. Benjamin and Sirmans (1994), Gilderbloom and Markham (1996), B. Turner and Malpezzi (2003), Ye (2008), Jenkins (2009), Pastor, Carter, and Abood (2018), Kettunen and Ruonavaara (2021), and Gibb, Soaita, and Marsh (2022); 2) social housing: Dweik, Watson, and Woodhall-Melnik (2024); 3) housing allowances: Shroder (2002) and A. Owens (2017); 4) land use regulation: John M. Quigley and Rosenthal (2005), D. Lin and Wachter (2020), and Freemark (2023); 5) impact fees: Gregory S. Burge, Nelson, and Matthews (2007); 6) macroprudential regulations: Poghosyan (2020) and Araujo et al. (2024); and 7) monetary, macroprudential, and tax policies: C. Zhao and Liu (2023). In addition, I search six online research paper databases (Google Scholar, IDEAS/RePEc, JSTOR, Semantic Scholar, Social Science Research Network, and Web of Science) using the following keywords: “rent control”, “protection from eviction”, “short-term rental regulations”, “social housing”, “public housing”, “in-kind social subsidies”, “affordable housing programs”, “project-based housing programs”, “housing allowances”,1 “housing benefit”, “housing subsidies”, “housing vouchers”, “housing assistance”, “rental assistance”, “tenant-based housing programs”, “mortgage interest deduction”, “homeownership subsidies”, “zoning”, “urban growth boundaries”, “land-use regulations”, “land stamp duty”, “real estate transfer tax”, “property tax”, “impact fees”, etc. I tried to make the sample of housing policy studies as exhaustive as possible. However, I cannot guarantee that it is complete. Some studies, especially older and unpublished, could not be found or accessed. Also studies written in other languages than English can be underrepresented.

The findings analyzed in this study are based on the analysis of 949 empirical (710 published and 239 unpublished) studies. The figure below displays a word cloud illustrating the frequency of investigation of different policy tools, the most frequently studied being plotted in larger characters.

The present study considers 62 policy tools. As seen, rent control is by far the most “popular” policy tool among the researchers. The next to it tools, according to the number of studies devoted to them, are land use and housing allowance.

The vast majority of studies (about 90%) focuses on the effects of a single policy. Only 8 studies examine effects of more than two policies: Bradford and Bradford (2023), Causa and Pichelmann (2020), Chu (2018), De Jorge-Huertas and De Jorge-Moreno (2021), Kaas et al. (2021), Kutty (2005), Lauridsen, Nannerup, and Skak (2009), Silveira and Malpezzi (1991).

The map below shows geographical distribution of studies. The intensity of the greenish color reflects the number of studies available for the corresponding country. For the most cited countries, the exact number of studies is indicated.

Geographical distribution of studies

Geographical distribution of studies

Overall, the literature analyzed here covers 96 countries. The empirical studies on the effects of housing-relevant policies are available for all continents. However, the geographical distribution of studies is very uneven. While a very large part of the literature (about 53%) is devoted to the USA, very few studies are available for the whole African continent. The coverage is somewhat better for Europe. However, the number of studies is very low for such populous Asian countries as India with respect to their population size.

The next figure displays a word cloud of effects that can be potentially caused by these policies and are subject to the empirical research.

Overall, 228 effects are identified. The most prominent among them are price effects, namely effects exerted by policies on property price and rent.

Several important caveats are worth mentioning. First, different studies have varying quality in terms of both data and research design. While some of them employ carefully designed estimation techniques, other rely on descriptive methods that are less reliable and produce rather weak results. Therefore, a mere addition of their signs can introduce some distortion in the results.

Second, the classification of studies by effects is not always evident. As a rule, I take advantage of the wording used by the authors of the papers. However, given terminological differences, the same notion can appear in different studies under different names, thus, leading to an excessive number of categories. Although such a classification would very accurately describe the terms used by the authors of the studies, it would not be operational. Therefore, I must generalize when classifying the regulation effects. In some cases, it is much easier, for example, when effects on prices, supply, and quality of housing as well as on residential mobility are considered. In other cases, it is less evident, for instance, when the authors investigate the impact on inequality, net welfare, and allocation.

Third, the effects of a regulation can be complex and non-linear. For example, while having a significant impact in the short run, the regulation can lose its effect in the long run or change its sign to the opposite. Similarly, the effects can be different across the price segments of housing or income distribution quantiles.

Fourth, due to a possible incompleteness of the literature overview and of the literature itself, not all relevant effects may be indicated in figure above.

Restrictive rental housing policies

Figure below shows the overall effects and their direction of restrictive rental housing policies. Given a large number of policies potentially affecting the housing market, one single graph with all policy instruments would be difficult to decipher. Therefore, I split the policy tools in several subgroups, showing each in a separate figure. Each row corresponds to an effect, while each column refers to a policy. Above each column, the number of studies is reported that investigate effects of the corresponding policy. Given that some studies consider effect of several policies (e.g., social housing and housing allowances), the sum of these numbers exceeds the total number of studies examined here. The length of each bar reflects the relative attention devoted by researchers to the corresponding pair policy-effect as measured by the number of studies that investigate it. For each policy tool, this number of studies is divided by the total number of studies inspecting this policy tool. The color of bars shows the direction of the effect. Green (red) color denotes studies that found statistically significant positive (negative) effects. Yellow color denotes studies that did not find any statistically significant effect of the policy.

Effects of restrictive rental housing policies

Effects of restrictive rental housing policies

Overall, 4 housing policy instruments are discussed and 24 effects are identified. Some effects that are rarely investigated are filtered out: if there are less than four studies devoted to an effect, then it is not included in the figure.

Rent control. The most prominent effects of rent control are decline of rents for controlled dwellings, reduced residential mobility, lower construction, lower quality of housing, higher rents for uncontrolled dwellings, and lower property prices. For a detailed account on the literature on the effects of rent control see Konstantin A. Kholodilin (2024a).

Protection of tenants from eviction. By far the largest group of studies of eviction protection finds eviction-reducing effect. However, the number of studies on protection of tenants from evictions is very small.

Housing rationing. Likewise, the number of studies on housing rationing is small. They find a negative effect on property prices. Most of these studies refer to the recent policies prohibiting or restricting short-term rentals on the platforms like Airbnb, as the authorities suspect that they remove dwellings from the long-term rental housing market.

The figure below focuses on stimulating housing policies, such as housing allowances and social housing for rental dwellings as well as mortgage interest deduction and homeowner subsidy for homeowner-occupied dwellings.

Effects of stimulating housing policies

Effects of stimulating housing policies

Housing allowances. The most investigated potential effects of housing allowances (benefits) are related to employment, housing rent as well as neighborhood and housing quality. The numbers of studies that find positive and negative effects are comparable, while the largest group of studies did not find any statistically significant effects on employment. This reflects the complex interplay of incentives. On the one hand, as in case of other social subsidies, housing benefits could diminish incentives to work among subsidy receivers, as they can rely on the governmental support. Moreover, housing allowances are reduced proportionally with earnings of receivers. This is a typical incentive-distortion issue also observed for other types of subsidies. On the other hand, the subsidies could encourage employment because they increase stability, allowing to allocate more resources toward expenses related to employment (for example, transportation and childcare costs), which may be substantial labor market barriers for low-income households.

The housing allowances appear to increase rents. This effect reflects the fact that, due to the low elasticity of housing supply, the increase in demand for housing resulting from housing allowances does not translate into a one-to-one improvement of the size and quality of housing accessible to the subsidy receivers. There is some leakage resulting in the rent inflation.

The housing allowances also seem to not just improve neighborhood and housing quality but also increase housing size. They positively contribute to the mental health. Housing benefits can also lead to smaller household sizes by allowing the women to leave their partners in case of conflicts, since they are become less financially dependent.

Provision of social housing. Similarly, the most prominent effect of social, or public, housing seems to be the reduction of employment. Again, it is thought that in-kind subsidies, such as social housing, diminish incentives of its receivers to work. Interestingly, unlike the case of housing allowances, social housing appears to exert no positive price effects, probably due to its in-kind nature. Nevertheless, the number of studies is very limited, which undermines the reliability of these findings.

Mortgage interest deduction. The studies on the effects of mortgage interest deduction that represents a large item of government expenditure in some countries (e.g., in the USA) show that this policy can be not very efficient. It appears not affect homeownership, while leading to rising prices. Again, the low elasticity of housing supply translates a part of demand increase fueled by this indirect subsidy into housing price increases. There are some studies showing an improvement in the housing size and construction, but there are also studies that show negative welfare effects. All in all, most empirical study conclude that mortgage interest deduction is missing its objective.

Homeownership subsidy. The two major effects of homeownership subsidies that are considered in the empirical literature are property prices and urban sprawl. Both seem to be increased by the subsidies. However, the number of studies is still very little.

Effects of decent and sustainable housing policies

Effects of decent and sustainable housing policies

Building codes. The two most prominent effects of building codes are rising property prices and reducing electricity consumption. The price increases can be explained by two factors. First, building codes by imposing stronger restrictions on building standard drive up construction costs. Second, building codes create amenities, such as, for example, lower energy consumption, which are eventually (albeit probably not completely) capitalized in the real estate prices.

Land use policies. Land use policies increase property prices and diminish residential construction. On the one hand, by restricting construction they create a shortage of housing, thus, inflating prices. This means a worse affordability of housing. On the other hand, this effect results from the policies creating amenities and improving the neighborhood quality (Severen and Plantinga 2018).

Green subsidies and green building standards. Finally, there are still relatively few studies on the effects of green housing policies. The effects found in this literature are rather ambiguous.

Taxation of real estate

Figure below reports the estimated effects of real-estate taxes, including transfer, property, capital gains, vacancy, and foreign-buyer taxes and impact fee.

Effects of real estate taxes

Effects of real estate taxes

Real-estate taxes mainly appear to affect housing prices, housing sales volumes, residential mobility, and housing construction. In most cases, except improvement fees and vacancy taxes, researchers find predominantly negative effects. For improvement fees, the effect is rather positive, because the fee revenues are invested in infrastructure improvements that increase housing prices. In case of vacancy taxes, the evidence is rather mixed. Transfer, property, capital gains tax, and foreign-buyer taxes are likely to reduce the volume of sales of real estate. The effects of property taxes on residential construction are mixed: while property tax seems to reduce it, vacancy and foreign-buyer taxes appear to increase it.

Macroprudential regulations

The figure below shows the effects of five macroprudential regulations: debt-service-to-income (DSTI), loan-to-value (LTV), and loan-to-income (LTI) ratios; capital adequacy ratios (CAR), reserve requirements (RR), and countercyclical capital buffer (CCyB).

Effects of macroprudential regulations

Effects of macroprudential regulations

Overall, the number of empirical studies is rather limited. They focus on two effects of macroprudential regulations: on housing prices and credit volume. Both policies considered here exert negative impact on prices and loans.

Macroeconomic policies and housing market

Housing markets are not solely influenced by specific housing policies. In fact, broader macroeconomic policies wield a significant influence on them. Figure below shows the investigated effects of fiscal and monetary policies.

Effects of macroeconomic policies

Effects of macroeconomic policies

Fiscal policy appears to positively affect property prices, while negatively affect residential construction. The first effect can be explained by the inflationary impact of government expenditure, whereas the second effect is possibly related to the crowding out of the government consumption. An expansionary fiscal policy triggers increases in both prices and interest rates. Consequently, private investors face heightened costs, leading to a reduced willingness to build.

Monetary policy, on the other hand, manifests three effects. It increases housing rents and purchase prices while fostering growth in the housing construction sector. The surge in housing costs aligns with the overall inflationary impact associated with an expansionary monetary policy. Meanwhile, the boost in housing construction can be explained by the lower interest rates, which alleviate the interest burden and decrease the opportunity cost for investors. Consequently, this increases their rate of return and bolsters their motivation for investing in residential construction.

Labor market policies and housing market

Labor market, or employment, policies also exert a multifaceted impact on housing markets. The main channel is the income and its security that affects the demand for housing. Figure below displays the investigated effects of labor policies.

Figure: Effects of labor policies

Figure: Effects of labor policies

According to the literature, the major effect of the minimum wage regulation is the positive impact on housing rents. The unemployment benefit is much less investigated. It appears to reduce the number of foreclosures, since it provides monetary aid to the people in financial distress. Most of the few studies conducted conclude that job protection leads to an increase in the mortgage amount. By preventing the layoffs of employees this regulation supports the demand for housing and, hence, for mortgage loans.

Correlations between different policies

It would be extremely difficult to examine simultaneously the effects of all the housing policies used at a given time. However, in order to approximate the interactions between different policies, one could look at the correlations between their effects. From the review of the literature, we know what the dominant effects of each policy are and in which direction. For example, the majority of studies find that rent control lowers administered rents and reduces housing construction, while many studies of housing subsidies find that these subsidies increase rents, and the few studies that consider the effects of housing subsidies on construction find no statistically significant effect. For each policy and effect, a difference can be calculated between the number of studies with positive and negative effects. If more studies find positive (negative) effects, the balance will be positive (negative). If none of the studies find a statistically significant effect, or if the number of studies with positive and negative effects is equal, the net effect is zero.

Thus, for each policy there is a sequence of positive, negative and zero numbers that reflect its effects. If no study examined a particular effect of the policy, the effect is coded as a missing value. As a result, a correlation coefficient can be calculated for each pair of policies. Its sign would indicate whether the policies reinforce each other (positive sign), cancel each other out (negative sign) or have no relationship (zero). The size of the correlation coefficient would approximate the strength of the relationship between the two policies.

The figure below displays the correlation matrix of housing policies. The size of squares is proportional to the absolute value of correlation coefficients. The red color denotes negative correlations, while the blue color stands for positive correlations. Correlation coefficients whose \(p\)-value exceeds 0.05 are not shown.

Correlations between housing policies

Correlations between housing policies

There are many statistically significant correlation coefficients. Rent control is strongly and negatively correlated with housing allowances and, thus, both policies to some extent compensate each other.

Eviction protection is positively, although not very strongly correlated with social housing. This effect is possibly due to the higher residential stability that is created by both these policies.

The housing rationing policy is statistically significantly correlated three other policies: mortgage interest deduction, land use, and property tax. The correlation with two former policies is negative, while that with property tax is positive. Most likely this correlation is driven by the housing price effects. However, there a rather few studies investigating effects of housing rationing. Therefore, one should be careful when interpreting these correlation coefficients.

The social housing effects are positively correlated with mortgage interest deduction and land use, meaning that these policies are mutually enhancing, but negatively correlated with property and transfer taxes.

The effects of mortgage interest deductions appear to be quite similar to those of building code and land use regulations. In particular, they drive up housing prices and rents. In addition, both building codes and land use regulations seem to dampen new residential construction. Moreover, mortgage interest deduction is very strongly negatively correlated with property and transfer taxes. Again, the correlation is driven mainly by the property price effect.

The effects of land use regulations are almost perfectly negatively correlated with effects of property tax and strongly negatively correlated with effects of transfer tax. Hence, they compensate each other, mainly through their housing price effects.

Finally, property and transfer tax exert similar effects and, thus, complement each other.

Potential policy mix effects

Each governmental policy is applied together with many other policies. As seen above, these policies can have both similar and opposite effects. Thus, in some respects, different policies can be strengthen each other, while in other cases, they can compensate each other. Therefore, it would be useful to estimate the cumulative effects of various policy mixes.

There are few studies that investigate the impact of policy mixes. For instance, Kaas et al. (2021) consider the homeownership and welfare effects of transaction taxes, mortgage interest deduction, and social housing. They conclude that the combination of these three policies would reduce welfare. In some cases, policies adopted in other countries can affect the domestic housing market (Shi and Shi 2023; Nguyen, Le, and Nguyen 2024).

One idea is to consider housing policy combinations that governments representing both extremes of political spectrum would choose. Table below compares the preferences of two hypothetical governments (leftist and liberal) towards different housing policy tools.

Policy Left Liberal
rent control 1 0
eviction protection 1 1
housing rationing 1 0
housing allowance 1 1
social housing 1 0
mortgage deduction 0 1
building code 1 1
land use 1 1
property tax 1 0
transfer tax 1 0

I assume that a leftist government would be much more interventionist, with the exception of mortgage interest deduction, since this policy appears to exacerbate income inequality. By contrast, a liberal government would be eager to reject interventions in rent setting and distribution of housing and to replace social housing by person-based subsidies. In addition, I suppose that both kinds of governments would decide to keep protection from evictions, building code and land use regulations. The protection of tenants from evictions — at least in Western Europe — became an integral part of social legislation. Building codes and land use regulations are focused more on setting decent living standards and protecting the environment and, hence, can be appealing to both leftist and liberal governments. Moreover, a liberal government is more likely to remove real estate taxes, for they at least formally prefer a smaller government sector. However, situations are also imaginable where liberal governments choose to take advantage of real estate tax increases in order to reap the bonanza of house price increases.

Figure below compares cumulative effects across different aspects. Red bars denote the effects of leftist policy mix, whereas blue bars measure the effects of liberal policies. The cumulative effects are computed by adding up relative effects of each policy. For example, rent control, eviction protection, and social housing seem to decrease housing vacancies, while land use regulations appear to slightly increase them. In case of a leftist government, all these policies are employed. However, liberal government would apply only eviction protection and land use regulations. Thus, a liberal housing policy mix would have rather small vacancy-reducing effect. Given that it is impossible to measure the exact magnitude of each policy effect, these calculations are very rough. However, they can give insights into relative effects of left and liberal housing policies.

Potential cumulative effects of leftist and liberal housing policies

Potential cumulative effects of leftist and liberal housing policies

The policy mix of a left government would lead to lower rents, while that of a liberal government could result in higher overall rents. However, leftist policies could raise the rents in the sector not subject to rent control. The policies of both governments would dampen residential construction, but under liberal policies this effect would be weaker. Left government’s policy would be more inequality reducing than the liberal government’s policy. Left policies would reduce the quality of housing, while liberal policies would raise it. Both left and liberal policies would increase the size of dwellings, but liberal policy would have a stronger effect. The policies of both governments could reduce employment, but under the liberal government this effect would be smaller.

Appendix

The table below contains a list of all studies examined here. The first column reports the corresponding study. In the second and the third columns, the country ISO alpha 3 code is shown, followed by the place and time period of the investigation. Column four describes the type of data: micro- or macrodata alongside the level of aggregation used (households, dwellings, municipalities, or states). In column five, the estimation methods are reported. Columns six and seven show the investigated policy effect and its sign, according to the corresponding study. Finally, the last column indicates the policy under inspection.

Study Iso a3 Place and period Type of data Method Effect Effect sign RC generation Policy
Aastveit and Anundsen (2022) USA 263 US metropolitan areas, 1983–2007 macro: house price data from Federal Housing Finance Agency, households’ disposable income per capita, local CPIs, income, population, and migration from Moody’s Analytics’ Economy.com, supply elasticities from Saiz (2010) local projections model property price 1 – monetary policy
Aastveit, Juelsrud, and Getz Wold (2020) NOR Norway, 2003–2017 micro: administrative Norwegian tax data; house purchase prices from Land Registry difference-in-differences property price, household leverage, financial buffer -1, -1, -1 –, –, – LTV, LTV, LTV
Abel, Carrer, and Luque (2024) ESP Catalonia, 2020–2022 micro: data on rental and sale posts of Fotocasa from Atlas Real Estate Analytics; difference-in-differences supply, property sales, property price -1, 1, -1 2, 2, 2 rent control, rent control, rent control
Abreu et al. (2024) PRT Portugal, 2017–2019 micro: loan-level data from Portuguese Central Credit Register (Central de Responsabilidades de Crédito) of Banco de Portugal difference-in-differences household leverage -1 – LTV
Acharya et al. (2022) IRL Ireland, 2014–2016 macro: loan level data and security register from Central Bank of Ireland panel-data model lending to low-income borrowers, lending to hot housing markets, property price, lending to low-income borrowers, lending to hot housing markets, property price -1, -1, -1, -1, -1, -1 –, –, –, –, –, – LTV, LTV, LTV, LTI, LTI, LTI
Afonso and Sousa (2009) DEU, ITA, GBR, USA 4 OECD countries, 1970–2007 macro: GDP, GDP deflator, unemployment rate, average cost of financing the debt, housing price index, stock price index, government expenditures or government revenues from BIS and IMF Fully Simultaneous System approach in a Bayesian framework, vector autoregression volatility 1 – fiscal policy
Afshari and Salimi (2020) IRN Iran, 1993–2017 macro: data from Central Bank of the Islamic Republic of Iran vector autoregression property price, property price, property price -1, -1, -1 –, –, – LTV, RR, CAR
Agarwal et al. (2020) CHN 35 major cities in China, 2006–2015 micro: housing resale transaction data from one of the largest housing brokerage firms in our sample city; e date of the previous transaction of the unit from local housing registry office panel-data model, difference-in-differences tax evasion, misallocation, holding period 1, 1, 1 –, –, – capital gains tax, capital gains tax, capital gains tax
Agarwal, Ambrose, and Diop (2022) USA 208 MSAs across 41 continental US states, 2000–2008 micro: multifamily lease performance data on (lease start date, lease termination date, tenant move-in date, tenant move-out date, last transaction date), property locations (city, state, and zip code), and rent payments from Experian RentBureau; macro: minimum wage increase data from Aaronson, Agarwal, and French (2012) pooled difference-in-differences rental default, rent, mobility -1, 1, 1 –, –, – minimum wage, minimum wage, minimum wage
Agnello and Sousa (2013) BEL, FIN, FRA, DEU, ITA, NLD, PRT, ESP, GBR, USA 10 OECD countries, 1955–2007 macro: Housing Price Index from Bank for International Settlements; GDP from Bureau of Economic Analysis, Central Bank of Portugal, Office for National Statistics, International Financial Statistics; GDP deflator from IFS of the IMF; Primary Fiscal Deficit from Bureau of Economic Analysis, Central Bank of Portugal, Office for National Statistics, General Accounting Offices, Ministries of Finance, National Central Banks and National Statistical Institutes, Credit from IFS of the IMF; Stock Price Index from BIS and IFS of the IMF panel VAR property price -1 – fiscal policy
Ahern and Giacoletti (2022) USA St. Paul (Minnesota) and 5 surrounding counties, 2018–2022 micro: 150,000 real estate transactions difference-in-differences value, misallocation -1, 1 2, 2 rent control, rent control
Ahrend, Cournède, and Price (2008) AUS, BEL, CHE, DEU, DNK, ESP, FIN, FRA, GBR, GRC, IRL, ITA, JPN, NLD, NOR, NZL, PRT, USA Industrialized countries, 1985–2007 macro: OECD database descriptive analysis, correlation analysis property price -1 – monetary policy
Ahrens, Martinez-Cillero, and O’Toole (2019) IRL Ireland, 2008–2018 macro: rent index at the level of Local Electoral Areas difference-in-differences controlled rents -1 2 rent control
Ahuja and Nabar (2011) ? 49 emerging and advanced economies, 2000–2010 macro: regulation dummies; data on prime lending rate and the year-on-year growth rate of credit relative to GDP from IMF panel data model property price, property price, loan growth, loan growth 1, -1, -1, -1 –, –, –, – DSTI, LTV, DSTI, LTV
Akdoğan, Karacimen, and Yavuz (2019) AUS, AUT, BEL, CZE, DNK, DEU, ESP, EST, FIN, FRA, GRC, HUN, IRL, JPN, LTU, LVA, MEX, POL, PRT, SVK, SVN, TUR, USA 23 countries, 1990–2016 macro: housing credit data and GDP deflator from International Monetary Fund –International Featured Standards; GDP data and proxies for employment security (ratio of involuntary part-time workers to total labour force, and average job tenure length) from OECD; ratio of youth unemployment rate to total unemployment rate from World Bank fixed-effects panel data model loan growth 1 – job protection
Akinci and Olmstead-Rumsey (2018) AUS, AUT, BEL, CAN, DNK, FIN, FRA, DEU, GRC, ISL, IRL, ITA, JPN, LUX, MLT, NLD, NZL, NOR, PRT, ESP, SWE, CHE, GBR, CHN, HKG, IND, IDN, KOR, MYS, PHL, SGP, TWN, THA, ARG, BRA, CHL, COL, MEX, PER, URY, BGR, HRV, CZE, EST, HUN, LVA, LTU, POL, ROU, RUS, SVK, SVN, SRB, UKR, ISR, ZAF, TUR 57 countries, 2000–2013 macro: data on bank credit from Bank for International Settlements and Haver; housing credit data from BIS, central bank websites, Datastream and CEIC; coding of macroprudential policy measures by authors dynamic panel data model; Generalized Method of Moments; Least Square Dummy Variable loan growth, property price, loan growth, property price -1, -1, -1, -1 –, –, –, – LTV, LTV, DSTI, DSTI
Alam et al. (2019) ARG, AUS, AUT, BEL, BGR, BRA, CAN, CHE, CHL, CHN, COL, CRI, CZE, CYP, DNK, DEU, ESP, EST, FIN, FRA, GBR, GEO, GRC, HKG, HRV, HUN, IDN, IND, IRL, ISL, ISR, ITA, JPN, KAZ, KOR, LTU, LVA, LUX, MAR, MEX, MKD, MNG, MYS, NLD, NOR, NZL, PHL, POL, PRT, PRY, ROU, RUS, SAU, SGP, SVK, SVN, SWE, THA, TUR, UKR, USA, ZAF 63 countries, 1990–2016 macro: regulation indices from integrated Macroprudential Policy (iMaPP) database; macroeconomic data from Bloomberg, BIS, OECD propensity-score-based method, panel data model property price, property price, loan growth, loan growth -1, -1, -1, -1 –, –, –, – DSTI, LTV, DSTI, LTV
Albon (1978) AUS Canberra and Queanbeyan, 1973–1976 macro: Rent Control Office; 1971 Census data descriptive; simulation method uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Albouy and Ehrlich (2018) USA 230 metros in US, 2005–2010 macro: housing-price and wage indices for each metro area based on 1% samples from American Community Survey calibration model, OLS, instrumental variable property price 1 – land use
Allen et al. (2020) CAN Canada, 2005–2010 micro: data on mortgage contract, borrower, and lender from CMHC; household-level data from Canadian Financial Monitor survey linear regression; microsimulation model loan qualifications, first-time homebuyers, debt, loan qualifications, first-time homebuyers, debt -1, -1, -1, -1, -1, -1 –, –, –, –, –, – LTV, LTV, LTV, DSTI, DSTI, DSTI
Alm, Lai, and Li (2022) CHN 32 Chinese major cities, 2009–2016 macro: weekly divorce-related internet searches to measure people’s interest in divorce from Baidu; population density, average deposits, GDP per capita, sex ratio, unemployment rate from China City Yearbooks; housing price index from National Bureau of Statistics; strength of Confucian ideology – number of Confucian academies constructed during Ming-Qing dynasties difference-in-differences divorce 1 – home purchase restriction
Almeida, Campello, and Liu (2006) AUS, BEL, CAN, CHL, DNK, FIN, FRA, DEU, HKG, IRL, ISR, ITA, JPN, KOR, MYS, NLD, NZL, NOR, SGP, ESP, SWE, CHE, TWN, THA, GBR, USA 26 countries, 1970–1999 macro: data for rents from DRI (Global Insight); data on consumer expenditures on actual rentals for housing from national statistical offices, OECD, Eurostat, Euromonitor International; maximum LTVs from Jappelli and Pagano (1994) OLS; GMM; instrumental variable sensitivity of price to income, sensitivity of mortgage to income 1, 1 –, – LTV, LTV
Altavilla, Laeven, and Peydró (2020) BEL, DEU, ESP, FRA, ITA, LVA, LTU, MLT, AUT, PRT, SVN, SVK, ROU, CZE European countries, 2012–2017 micro: 140 million loan-level observations for households and more than 130 million loan-level observations for firms from ECB; macro: lending restriction measures in the EU from Budnik and Kleibl (2018) regression loan growth, loan growth -1, 1 –, – macroprudential policy, monetary policy
Alzúa et al. (2016) ARG Rosario, 2009–2015 micro: data on applicants from Registry of Permanent Registration (RUIP); registered (formal) employment records from social security database (SIPA) OLS; 2SLS employment -1 – subsidized homeownership programs
Ambrose et al. (2024) USA New York City, 2005 and 2008 micro: data on dwellings from New York City Housing and Vacancy Survey linear probability model non-compliance, discrimination 1, 1 2, 2 rent control, rent control
Ambrosius et al. (2015) USA 161 New Jersey communities, 2003 micro: Rent Control Survey of the New Jersey Tenants Organization and 2010 Census linear regression construction 0 2 rent control
An, Gabriel, and Tzur-Ilan (2021) USA USA, 2020 macro: ZIP code/county/state data from Federal Reserve Y-14M regulatory report, Opportunity Insight Economic Tracker, Census COVID-19 Household Pulse Survey panel-data model with fixed-effects, difference-in-differences mental health, food security, eviction 1, 1, -1 –, –, – eviction protection, eviction protection, eviction protection
Andolfatto and Rekkas (2023) CAN Metro Vancouver, Ottawa, Montreal, Victoria, Abbotsford, Atlanta, Boston, Chicago, Denver, Las Vegas, Los Angeles, Miami, New York City, San Diego, San Francisco, Seattle, Washington, London, 2005–2017 macro: Canadian Real Estate Association, Real Estate Board of Greater Vancouver, Fraser Valley Real Estate Board, British Columbia Research Estate Association; Federal Reserve Economic Data; HM Land Registry Open Data synthetic control method property price -1 – foreign-buyer tax
André et al. (2022) CAN, GBR, USA Canada, UK, USA, 1975–2018 macro: housing prices, real GDP, GDP deflator from OECD, non-energy commodity price index comes from World Bank Bayesian VAR, Markov Switching VAR property price 1 – monetary policy
Angjellari-Dajci et al. (2015) USA Duval County (Florida): 2002–2013 micro: 123,431 home sales from Northeast Florida Association of Realtors’ Multiple Listing Service hedonic regression property price -1 – property tax
Angst et al. (2025) USA Central and South Los Angeles, 2019 micro: door-to-door survey of tenants; market rents from Rentometer; macro: Gentrification Index from Urban Displacement Project; census block group and tract level data on poverty, median income, median gross rent, rent burden, housing types, race and citizenship from American Community Survey 5-Year Estimates 2015-2019 and 2010 Decennial Census; zip code-level data on Small-Area Fair Market Rents from US Department of Housing and Urban Development (HUD); market rents from Zillow Rent Index; annual changes in home prices from Federal Housing Finance Agency House Price Index; annual changes in adjusted gross income from Internal Revenue Service; census block group information on housing code violation cases from Los Angeles Department of Building and Safety between 2015 and 2019 probit model; ordered probit model harassment, maintenance 1, 0 2, 2 rent control, rent control
Anthony (2003) USA Florida counties, 1980–1995 macro: Florida Statistical Abstract, Florida Department of Community Affairs linear regression, time series analysis housing affordability -1 – land use
Antipa and Schalck (2010) FRA France, 1984–2006 macro: data on subsidies and taxes from French Ministry of Housing; data on residential investment from national accounts VECM housing investment 1 – fiscal policy
Appelbaum et al. (1991) USA 56 US cities, 1984 macro: HUD survey of homelessness in 60 metropolitan areas linear regression homelessness 0 2 rent control
Aregger et al. (2013) CHE 92 MS regions, 1985–2009 macro: spatial mobility regions data from SFSO panel data model property price, property price 1, 0 –, – capital gains tax, transfer tax
Arestis and González-Martı́nez (2015) ESP Spain, 1984–2014 macro: employment protection indicators (Strictness of employment protection - individual and collective dismissals (regular contracts) and Strictness of employment protection - temporary contracts) from OECD Employment database; data on gross national disposable income per head of population; gross fixed capital formation at 2010 prices: dwellings, price deflator domestic demand including stocks, employment, full-time equivalents: total economy (national accounts), employment, persons: all domestic industries from AMECO autoregressive distributed lag, error correction model housing investment 1 – job protection
Arestis and Gonzalez-Martinez (2019) ESP, GBR, IRL, NLD, USA Ireland, the Netherlands, Spain, UK, and USA, 1985–2013 macro: employment protection indicators from OECD; house prices from Federal Reserve Bank of Dallas autoregressive distributed lag, error correction model property price 1 – job protection
Armstrong, Skilling, and Yao (2019) NZL New Zealand, 2013–2017 micro: property unit-record data from CoreLogic difference-in-differences property price -1 – LTV
Aroonruengsawat, Auffhammer, and Sanstad (2012) USA 48 continental states, 1970–2006 macro: annual total electricity consumption for the residential sector in British Thermal Units (BTUs) from Energy Information Administration’s State Energy Data System, data on building codes from Building Codes Assistance Program OLS, panel-data model with fixed effects electricity consumption -1 – building code
Aroul and Hansz (2012) USA 2 cities of Texas, ? ? property price 1 – green building standards
Asquith (2019) USA San Francisco, 2003–2013 micro: building parcel by month dataset of evictions of San Francisco’s Planning Department instrumental variable linear probability model homeownership 1 2 rent control
Assaad, Krafft, and Rolando (2021) EGY Egypt, 2006 and 2012 micro: 2006 and 2012 waves of the Egypt Labor Market Panel Survey difference-in-differences marriage -1 1 rent control
Ater, Elster, and Hoffmann (2021) ISR Israel, 2009–2014 micro: administrative data from Israel Tax authority; all transacted properties and annual social and demographic characteristics of buyers and sellers from Central Bureau of Statistics hedonic regression, difference-in-differences, panel-data model rent, property sales, property price -1, -1, -1 –, –, – capital gains tax, capital gains tax, capital gains tax
Attia (2016) EGY unknown unknown unknown uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Auer, Matyunina, and Ongena (2022) CHE Switzerland, 2012–2015 micro: data on volume and characteristics of all commercial loans exceeding CHF 50,000 and granted by Swiss banks, to non-financial domestic companies, with loans exceeding CHF 2 billion from SNB’s Lending Rate Statistics difference-in-differences mortgage amount, interest rate, commercial lending -1, 1, 1 –, –, – CCyB, CCyB, CCyB
Ault, Jackson, and Saba (1994) USA New York City, 1968 micro: New York City Housing Vacancy Survey cross-sectional regression mobility -1 1 rent control
Ault and Saba (1990) USA New York City, 1965 and 1968 micro: New York City Housing and Vacancy Surveys hedonic regression; simulation model net welfare, misallocation 1, 1 1, 1 rent control, rent control
Autor, Palmer, and Pathak (2014) USA Cambridge (Massachusetts), 1995 micro: parcels of land cross-sectional regression value -1 1 rent control
Autor, Palmer, and Pathak (2019) USA Cambridge (Massachusetts), 1992–2005 macro: block-level crime statistics (crime counts per 1,000 square meters) of Cambridge Police Department panel-data model crime -1 1 rent control
Avrin (1977) USA San Francisco, 1950–1973 micro: records of the San Francisco assessor’s office on the sales of individual properties; City Engineer; Census 1961 time series analysis property price 1 – land use
Aydin and Brounen (2019) AUT, BEL, DNK, FRA, FIN, DEU, GRC, IRL, ITA, NLD, PRT, ESP, GBR 13 EU countries, 1980–2016 macro: residential energy (electricity or non-electricity) consumption per capita panel-data model with fixed effects, cointegration non-electricity consumption, electricity consumption -1, -1 –, – building code, building code
Aye et al. (2014) ZAF South Africa, 1966–2011 macro: real per capita GDP, real per capita consumption expenditure, real per capita government revenue, real per capita government spending, real per capita wages, real per capita nonresidential investment, three-month Treasury bill rate, real stock price index, real house price index, CPI from Quarterly Bulletins of the South African Reserve Bank, IMF International Financial Statistics Bayesian VAR property price, property price 0, 1 –, – fiscal policy, monetary policy
Bahaman-Oskooee et al. (2023) USA US states, 1988–2020 macro: house permits, money supply measured by M2, household’s income, mortgage interest rate from ? error correction model with asymmetry, non-linear ARDL construction 1 – monetary policy
Bai, Li, and Ouyang (2014) CHN 31 cities and provinces in China, 2011–2012 macro: home prices from National Development and Reform Commission OLS; HCW method property price 0 – property tax
Bailey (1999) GBR Aberdeen, Dundee, Edinburgh and Glasgow, 1987–1996 micro: advertisements for private rented accommodation appearing in newspapers and property guides descriptive analysis construction -1 – rent control
Ball et al. (2014) AUS Melbourne metropolitan area, 1996–2007 micro: data on land sales difference-in-differences property price 1 – land use
Ballesteros (2001) PHL Metro Manila, 1998 micro: Annual Poverty Incidence Survey linear regression rent burden, misallocation -1, 1 1, 1 rent control, rent control
Ballesteros, Ramos, and Magtibay (2016) PHL Metro Manila, 2014 micro: data of families from Family Income and Expenditure Survey (FIES) and the Annual Poverty Indicators Survey (APIS) hedonic regression misallocation 1 2 rent control
Bang and Kwon (2022) KOR South Korea, 2007–2017 macro: GDP, CPI, interest rate from Bank of Korea; land price and construction from Ministry of Land, Infrastructure, and Transport; transaction-based sales price index for apartment and partment transaction volume from Korea Real Estate Board; number of households from National statistical office factor-augmented vector autoregressive model house price cycle, house price cycle, house price cycle 1, 1, -1 –, –, – DSTI, LTV, transfer tax
Bania, Coulton, and Leete (2003) USA Cleveland/Cuyahoga County, 1996–1997 micro: administrative data linear regression earnings 0 – housing allowance
Banzhaf and Lavery (2010) USA 18 Pennsylvania jurisdictions, 1970–2000 macro: tax rates data from Center for the Study of Economics; Geolytics’ Neighborhood Change Database difference-in-difference-in-differences; panel-data model urban sprawl -1 – split-rate tax
Barnett (1979) USA Brown county (Wisconsin) and St. Joseph county (Indiana), 1973 and 1974 micro: data on renter and owner households from Housing Allowance Office records descriptive analysis rent 0 – housing allowance
Bartik, Gupta, and Milo (2023) USA 25% of all municipalities and 6% of all townships in the USA, 2021 macro: ordinance data from American Legal Publishing, Municode, and Ordinance.com; building permits data from Census Building Permits Survey; rent and price data from American Community Survey Large Language Models (Chat GPT-4 Turbo, Claude 3 Opus, and GPT-3.5 Turbo); correlation analysis rent, property price, construction 1, 1, -1 –, –, – land use, land use, land use
Barton (2020) USA City of Berkeley, 1978–1995 micro: US Census data descriptive analysis supply, homeownership -1, 1 2, 2 rent control, rent control
Basolo (2013) USA 2 LHAs in Orange County (California), 2002 micro: mail sample survey of voucher holders by Santa Ana Housing Authority and Orange County Housing Authority OLS; logit regression neighborhood quality, school quality 1, 1 –, – housing allowance, housing allowance
Basolo and Nguyen (2005) USA 2 LHAs in Orange County (California), 2002 micro: mail survey of voucher holders within the population receiving SAHA assistance ANOVA; OLS neighborhood quality 1 – housing allowance
Basten (2020) CHE Switzerland, 2008–2013 micro: mortgage applications and offers from online platform Comparis difference-in-differences mortgage rate, mortgage amount 1, 0 –, – CCyB, CCyB
Battistini et al. (2024) BEL, DEU, ESP, FRA, IRL, ITA, NLD, PRT NUTS2 and NUTS1 regions of 8 Euro area countries, 1999–2019 macro: data on real GDP, GDP deflator, real gross value added for the construction and manufacturing sectors, real compensation of employees, employment, and population from ARDECO database; homeownership rate and population density from Eurostat; house price levels, LTV ratios, LTI ratios and the share of fixed-rate mortgages across regions via the loan-level data from European DataWarehouse panel VAR property price 1 – monetary policy
Battistini et al. (2022) BEL, DEU, ESP, FRA, IRL, ITA, NLD, PRT NUTS2 and NUTS1 regions of 8 Euro area countries, 1999–2019 macro: data on real GDP, GDP deflator, real gross value added for the construction and manufacturing sectors, real compensation of employees, employment, and population from ARDECO database; homeownership rate and population density from Eurostat; house price levels, LTV ratios, LTI ratios and the share of fixed-rate mortgages across regions via the loan-level data from European DataWarehouse panel VAR construction, property price, construction 1, 1, 1 –, –, – monetary policy, unconventional monetary policy, unconventional monetary policy
Baye and Dinger (2021) DEU Germany, 2008–2018 micro: RWI-GEO-RED data based on residential real estate advertisements from ImmobilienScout24 multi-period difference-in-differences uncontrolled housing returns, controlled housing returns 1, -1 2, 2 rent control, rent control
Baye and Dinger (2022) DEU Germany, 2008–2018 micro: RWI-GEO-RED data based on residential real estate advertisements from ImmobilienScout24 multi-period difference-in-differences rent burden 1 2 rent control
Baye and Dinger (2024) DEU Germany, 2010–2019 micro: RWI-GEO-RED data based on residential real estate advertisements from ImmobilienScout24; property characteristics living space and year of construction in the latest available German 2011 census data; indicators of spatial and urban development from INKAR hedonic regression; staggered difference-in-differences uncontrolled rents, uncontrolled housing returns, controlled rent burden, controlled property price, controlled housing returns 1, 1, 1, 1, -1 2, 2, 2, 2, 2 rent control, rent control, rent control, rent control, rent control
Bei (2025) ESP, FRA Barcelona, 2015–2019 micro: listing data from Inside Airbnb Causal ARIMA; variation kernel density number of listings, number of listings, number of high-availability listings, number of high-availability listings, number of multi-listings, number of multi-listings -1, 0, -1, -1, 1, -1 –, –, –, –, –, – housing rationing, housing rationing, housing rationing, housing rationing, housing rationing, housing rationing
Bei and Celata (2023) AUT, DEU, DNK, ESP, FRA, GBR, GRC, ITA, NLD, PRT 16 European cities (Amsterdam, Barcelona, London, Paris, Berlin, Vienna, Brussels, Madrid, Copenhagen, Athens, Lisbon, Porto, Edinburgh, Rome, Florence, Venice), 2013–2019 macro: degree of stringency of regulations; micro: Airbnb listings from InsideAirbnb.com and TomSlee.net difference-in-differences; panel-data model number of listings, professionalization -1, -1 –, – housing rationing, housing rationing
Beitel (2007) USA San Francisco, 1967–1998 macro: data on multiunit housing production from city planning department; price index of single family homes from Real Estate Research Council of Northern California autoregressive model construction, property price 0, 0 –, – land use, land use
Bekkerman et al. (2023) USA 15 US metropolitan areas, 2015–2020 micro: Airbnb, Cherre (a real estate data analytics company), California Department of Housing and Community Development, Zillow, American Community Survey staggered difference-in-differences number of listings, construction -1, -1 –, – housing rationing, housing rationing
Belgodere and Casamatta (2023) FRA France, 2010–2020 macro: local tax data from Direction Générale des Finances Publiques; number of secondary residences in each locality from FIchier des LOgements par COMmunes; data on property values come from DV3F database synthetic difference-in-differences tax revenue, second homes 1, -1 –, – second-home tax, second-home tax
Bellettini, Taddei, and Zanella (2013) ITA 13 large Italian cities, 1993–2004 macro: real estate prices and market transactions in Italian cities from Nomisma database; data on non-market transactions (donations) from Ministry of Economy and Finance linear simultaneous equations model property price, donations, property sales, property price, donations, property sales -1, -1, 1, -1, -1, 1 –, –, –, –, –, – bequest tax, bequest tax, bequest tax, gift tax, gift tax, gift tax
Benbouzid et al. (2022) AUS, AUT, BEL, CAN, DNK, FRA, DEU, GRC, IND, ITA, JPN, KAZ, MYS, NLD, RUS, SAU, SGP, KOR, ESP, SWE, CHE, TUR, ARE, GBR, USA 25 countries, 2010–2019 macro: daily Credit Default Swaps (CDS), bank-level and country-level data from Thomson Reuters Eikon, DataStream, and ORBIS panel data model with fixed effects risk -1 – CCyB
John D. Benjamin, Coulson, and Yang (1993) USA Philadelphia and Montgomery County, 1987–1989 micro: 352 single-family home sales data from the local Multiple Listing Service hedonic regression property price -1 – transfer tax
Bentley et al. (2018) AUS Australia, 2001–2013 micro: longitudinal panel survey on tenure and health marginal structural models, machine learning mental health -1 – social housing
Bento et al. (2009) USA California, 1988–2005 macro: municipality-level data from California Construction Industry Research Board; Census Bureau; DataQuick News Service Custom Reports linear regression property price SFH, housing size of SFH, construction of SFH, construction of MFH 1, -1, 0, 1 –, –, –, – inclusionary zoning, inclusionary zoning, inclusionary zoning, inclusionary zoning
Bérard and Trannoy (2017) FRA France, 2000–2015 macro: departément-level data from Conseil Général de l’Environnement et du Développement Durable, RETT data from Service de Publicité Foncière difference-in-differences tax revenue, property sales 1, -1 –, – transfer tax, transfer tax
T. Berger et al. (2000) SWE Sweden, 1981–1993 micro: data on sales of owner-occupied homes from hedonic regression property price 1 – interest rate subsidy
L. M. Berger et al. (2008) USA USA, 1997–1999 micro: National Survey of America’s Families instrumental variable, 2SLS, probit residential crowding, residential crowding, rent burden, rent burden, mobility, mobility, food security, food security -1, -1, -1, 1, 0, -1, 0, 0 –, –, –, –, –, –, –, – social housing, housing allowance, social housing, housing allowance, social housing, housing allowance, social housing, housing allowance
Berkowitz and Hynes (1999) USA USA, 1990–1995 micro: data on every mortgage application taken by qualifying mortgage lenders Home Mortgage Discrimination Act dataset; annual mortgage rates from Federal Housing Finance Board’s Rates and Terms on Conventional Home Mortgages; macro: tdate unemployment rate from Selective Access Service of the Bureau of Labor Statistics logit model; panel-data model with fixed effects mortgage rate, mortgage denial -1, -1 –, – bankruptcy protection, bankruptcy protection
Berlemann and Freese (2013) CHE Switzerland, 1987–2008 macro: GDP and M3 from the OECD Main Economic Indicators database, CPI and 3-month LIBOR rate from Swiss National Bank; Swiss (Stock) Performance Index from Swiss Exchange; Real Estate Performance Index from Swiss Real Estate Institute (IZI-AG–CIFI SA); housing prices from Wuest and Partner vector autoregression rent, property price 1, 1 –, – monetary policy, monetary policy
Berry (2001) USA Dallas and Houston Primary Metropolitan Statistical Areas, 1990 macro: dissimilarity index at city level based on Census of Population and Housing descriptive segregation 0 – land use
Bertaud and Brueckner (2005) IND Bangalore, ? micro: ? simulation model consumer welfare -1 – land use
Besley, Meads, and Surico (2014) GBR UK, 2008–2010 micro: data on mortgage transactions (loan size, the date at which the mortgage is issued, the purchase price of mortgaged property and an independent surveyor’s valuation of the property) from Financial Services Authority difference-in-differences property sales -1 – transfer tax
Best and Kleven (2018) GBR UK, 2004–2012 micro: data on all (10 million) property transactions from Her Majesty’s Revenue and Customs; consumption information from U.K. Living Costs and Food Survey difference-in-differences; panel-data model property sales, consumer spending -1, -1 –, – transfer tax, transfer tax
Bettendorf and Buyst (1997) BEL Belgium, 1920–1939 macro: per capita expenditure data Rotterdam demand model rent burden -1 1 rent control
Bian, Chen, and Jiang (2025) USA New York City, 2002–2017 micro: household data from New York City Housing and Vacancy Survey linear probability model; probit; panel data model immigrant-native gap 1 2 rent control
Bibler, Teltser, and Tremblay (2021) USA San Francisco and Chicago metropolitan areas, 2014–2019 micro: daily Airbnb listings data on asking prices, availability, inferred bookings, and time-invariant property characteristics such as number of bedrooms, number of bathrooms, maximum number of guests, and reported coordinates for all properties from AirDNA; housing price and foreclosure data from Zillow Transaction and Assessment Dataset difference-in-differences value, supply, foreclosure -1, -1, 1 –, –, – housing rationing, housing rationing, housing rationing
Biljanovska and Chen (2025) ? 21 EU countries, 2010–2017 micro: household data from Household Finance and Consumption Survey; macro: data on macroprudential policy from ECB’s MaPPED dataset linear regression mortgage amount of lower-income households, mortgage amount of higher-income households, mortgage rate, mortgage rate, downpayment, value, value -1, -1, 0, 1, 1, -1, -1 –, –, –, –, –, –, – CAR, financial institutions levy, CAR, financial institutions levy, financial institutions levy, CAR, financial institutions levy
Bimonte and Stabile (2015) ITA Italian regions, 1980–2010 macro: Banca d’Italia; BCE; Scenari immobiliari; building permits from ISTAT error correction model; autoregressive distributed lag construction 0 – property tax
Bimonte and Stabile (2020) ITA Italian regions, 1980–2010 macro: regional data on building permits, housing stock, house prices, construction costs, population, GDP, and interest rate from ISTAT panel-data regression construction 0 – property tax
Bingley and Walker (2001) GBR UK, 1994–1998 micro: data on married and unmarried women from Britain Family Resources Survey multinomial probit model employment -1 – housing allowance
Block (1989) CAN Toronto and Vancouver, 1972-1988 macro: semiannual vacancy rates descriptive analysis vacancy -1 – rent control
Blossier (2012) FRA France, 1999 and 2008 macro: Recensement général de la population; tax info from Code général des impôts propensity score matching; OLS vacancy 0 – vacancy tax
Bø (2015) NOR Norway, 2010 micro: whole population data from Income Statistics on Persons and Families microsimulation; tax benefit model LOTTE tax revenue, property price, inequality 1, -1, -1 –, –, – imputed rent tax, imputed rent tax, imputed rent tax
Bolligera et al. (2024) CHE Canton of Bern, 2007–2016 micro: administrative tax data containing information about the tenure status, intrafamily wealth transfers and other household characteristics from ? linear probability model; panel data model homeownership -1 – macroprudential policy
Bonneval, Goffette-Nagot, and Zhao (2021) FRA Lyon, 1890–1968 micro: real estate property manager’s accounting books difference-in-differences for panel data uncontrolled rents, mobility, controlled rents 0, -1, -1 1, 1, 1 rent control, rent control, rent control
Bono and Trannoy (2019) FRA France, 2004–2010 micro: data on sales of building land from BNDP difference-in-differences property price 1 – social housing
Borbely (2022) GBR England, 2009–2017 micro: data on Housing Benefit claimants from Understanding Society (UK Household Longitudinal Study, UKHLS) survey difference-in-differences employment, labor force participation 0, 0 –, – housing allowance, housing allowance
Borck and Gohl (2021) DEU Berlin, 2013–2019 macro: GfK data at ZIP code level; Open Street Map; Mietspiegel data simulation model (spatial equilibrium model) net welfare, controlled rents -1, -1 1, 1 rent control, rent control
Borg, Passaro, and Hermo (2022) USA US states, 2010–2020 macro: census-block-level data on commuting patterns from LODES; USPS ZIP-code-level rent data from Zillow; federal-, state-, county-, and city-level statutory MW levels from Vaghul and Zipperer (2016) two-way fixed effects panel data model rent 1 – minimum wage
Borge and Rattsø (2014) NOR Norway, 1997–1999 micro: house transactions and with detailed housing characteristics (price, building year, square meters, the number of baths and water closets (WCs), type of house (e.g., detached house, apartment), and distance to the center of the municipality) from Statistics Norway; property tax payment for a standard family house with market value of Norwegian Krone 750,000 from survey by Norwegian Household Finances (Norsk Familieøkonomi) pooled OLS property price -1 – property tax
Boto-Garcia et al. (2023) ESP 78 municipalities of Asturias, 2013–2019 micro: records about the tourist accommodation supply from Tourist Information System of Asturias (SITA); macro: population size of the municipality, number of hotels in the municipality, number of restaurants and bars/cafés, general consumer price index and subindex for transportation from ? difference-in-differences vacation rental -1 – housing rationing
Steven C. Bourassa (1987) USA Pittsburgh, 1978–1984 macro: dollar value of building permit applications; consumer price index; resident employment; home mortgage interest rate; index of residential construction costs; land tax rate; improvement tax rate from ? linear regression construction, construction 0, -1 –, – land tax, improvement tax
Steven C. Bourassa (1990) USA Pittsburgh, McKeesport, and New Castle (Pennsylvania), 1978–1986 macro: dollar value of building permit applications; consumer price index; resident employment; home mortgage interest rate; index of residential construction costs; land tax rate; improvement tax rate from ? linear regression construction, construction 0, 0 –, – land tax, improvement tax
Steven C. Bourassa et al. (2013) AUS, AUT, BEL, CAN, CHE, DEU, ESP, FIN, FRA, GBR, GRC, IRL, ITA, JPN, KOR, NOR, NZL, POL, PRT, SGP, SWE, TWN, USA 24 countries, ? macro: national statistical offices linear regression homeownership, homeownership 0, -1 –, – mortgage deduction, imputed rent tax
Steven C. Bourassa and Hoesli (2010) CHE Switzerland, 1998 micro: Enquête sur les revenus et la consommation logit regression homeownership -1 2 rent control
Steven C. Bourassa and Yin (2008) USA 11 metropolitan areas (Baltimore, Birmingham, Houston, Minneapolis, Norfolk, Oakland, Rochester, Salt Lake City, San Francisco, San Jose and Tampa), 1998 micro: household data from AHS metropolitan sample surveys linear regression, logit, simulation property price, LTV, homeownership 1, 1, -1 –, –, – mortgage deduction, mortgage deduction, mortgage deduction
Boustan et al. (2023) USA 100 largest cities, 1970–2015 macro: consistent-boundary Census tract data from the Neighborhood Change Database OLS, panel-data model with fixed effects condominium property -1 – housing rationing
Boustanifar (2013) USA USA, 2004–2006 micro: household borrowing data from Panel Study of Income Dynamics linear probability model mortgage amount, foreclosure 0, -1 –, – bankruptcy protection, bankruptcy protection
Boutros and Vallé (2024) CAN Greater Toronto Area, 2015–2022 micro: Rental Market Survey and Secondary Rental Market Survey data from Canada Mortgage and Housing Corporation; high-rise real estate projects data from Urbanation Hotelling model of differentiated demand uncontrolled rents 1 – rent control
Braakmann and McDonald (2020) GBR England, 2009–2013 micro: property data from HM Land Registry, pre-reform proportion of vacant dwellings per local authority from the Department for Communities and Local Government and the pre-reform proportions of unemployed and public sector workers and recipients of other benefits difference-in-differences property price 1 – housing allowance
Bradford and Bradford (2021) USA USA, 2004–2016 macro: county-level data from Department of Housing and Urban Development, number of ordered evictions from Eviction Lab, indicator variables for the various state laws governing landlord-tenant relationships from Every Landlord’s Legal Guide and Every Tenant’s Legal Guide, Area Health Resource File panel-data model with fixed effects rent, rent, eviction, eviction 0, 0, -1, -1 –, –, –, – eviction protection, housing allowance, eviction protection, housing allowance
Bradford and Bradford (2023) USA 2200 counties in 46 states and the District of Columbia of USA, 2001–2018 macro: county-level data from Department of Housing and Urban Development, number of ordered evictions from Eviction Lab, indicator variables for the various state laws governing landlord-tenant relationships from Every Landlord’s Legal Guide and Every Tenant’s Legal Guide, Area Health Resource File panel-data model with fixed effects eviction, eviction, eviction -1, -1, 1 –, –, – eviction protection, social housing, housing allowance
Bradley (2017) USA Ann Arbor, Michigan, 1997–2010 micro: property sales data from panel of assessed and taxable values; property and transaction data from Ann Arbor Area Board of Realtors multiple listing service OLS, instrumental variable, 2SLS property price -1 – property tax
Bramley (1993) GBR 90 districts of England, 1981 macro: district-level data linear regression, simulation property price, property price, construction, construction 1, 1, -1, 1 –, –, –, – land use, mortgage deduction, land use, mortgage deduction
Breidenbach, Eilers, and Fries (2022) DEU Germany, 2013–2017 micro: object level rental price data from the RWI-GEO-RED event study housing quality, controlled rents -1, -1 2, 2 rent control, rent control
Brogaard and Roshak (2011) USA 137 metropolitan areas, 2005–2009 micro: home sales data from Zillow.com; macro: per-capita income, unemployment, and population from Bureau of Economic Analysis; home ownership and vacancy rates from Census Bureau difference-in-difference-in-differences property sales, property price 0, 1 –, – homebuyer tax credit, homebuyer tax credit
Brown, Chakrabarti, and Severino (2024) USA USA, 1999–2005 micro: consumers’ debt balances from New York Fed Consumer Credit Panel / Equifax; macro: interest rates from RateWatch; county and ZIP code-level income information from Internal Revenue Service; state-level House Price index from Federal Housing Finance Agency; unemployment levels and unemployment rates from Bureau of Labor Statistics; total medical expenses using the National Health Expenditure Accounts from Centers for Medicare and Medicaid Services; state-level changes in GDP and personal income from US Bureau of Economic Analysis; state-level bankruptcy filing statistics from Statistics Division of the Administrative Office of the US Courts; share of votes for the Democratic Party in the last House of Representatives election from Clerk of the House of Representative linear regression mortgage amount 0 – bankruptcy protection
Brueckner and Sridhar (2012) IND 101 Indian municipalities with populations of at least 10,000, 2006 macro: population and area from Census of India; individual cities’ land-use rules (FAR) from National Council of Applied Economic Research; household income levels from NCAER; agricultural income per capita from Government of India, Planning Commission linear regression urban sprawl, welfare 1, -1 –, – land use, land use
Bruegge, Deryugina, and Myers (2019) USA California, 2009–2015 micro: housing characteristics and socioeconomic characteristics of each dwelling’s occupants data from ReferenceUSA; American Community Survey microdata; premise-level electricity and natural gas usage data from four major California utilities: San Diego Gas & Electric, Pacific Gas and Electric, Southern California Edison, and Southern California Gas linear regression property price, housing size, electricity consumption 1, -1, -1 –, –, – building code, building code, building code
Bruneau, Christensen, and Meh (2016) CAN Canada, 1983–2014 macro: real consumption, residential investment, non-residential investment, and mortgage debt per capita; real house and capital prices; nominal short- and long-term interest rates; core CPI inflation rate; hours worked per capita, real wage and capacity utilization rate in both consumption and housing sectors from Statistics Canada New Keynesian model; Bayesian method; simulation property price, debt -1, -1 –, – LTV, LTV
Büchler and Lutz (2024) CHE Canton of Zurich, 1996–2020 micro: Federal Register of Buildings and Habitations, web-scraped asking rents data from Meta-Sys difference-in-differences; event study rent, construction 1, -1 –, – land use, land use
Buettner (2017) DEU all German Länder, 2002–2015 macro: state-level tax revenues panel-data model welfare, tax revenue -1, 1 –, – transfer tax, transfer tax
Burby et al. (2000) USA 155 US central cities and their metropolitan areas, 1985–1995 macro: city-level data on new single-family-detached and multi-family housing linear regression construction -1 – building code
Gregory S. Burge (2014) USA 61 Florida’s counties, 1994–2009 micro: data on land parcel sales and property characteristics from county parcel level tax rolls of Florida Department of Revenue; macro: data on population, income from Bureau of Economic Analysis; crime data from Florida Statistical Abstract; impact fee rates from Florida county governments fixed-effects panel data model land price -1 – impact fee
Gregory S. Burge et al. (2013) USA Albuquerque (New Mexico), 1991–2010 macro: data on permits, population, unemployment, construction, and housing prices from Albuquerque Planning Department; Federal Home Loan Mortgage Corporation; Rio Rancho Planning and Zoning Division; US Bureau of Labor and Statistics; US Bureau of the Census; US Federal Housing Finance Agency; US Federal Reserve System linear regression urban sprawl -1 – impact fee
Gregory S. Burge and Ihlanfeldt (2006b) USA 33 metropolitan counties in Florida, 1995–2004 macro: impact fee rates from planning offices for all Florida counties; property tax rolls of the individual counties from Florida Department of Revenue; Means City Construction Cost Indexes from ? fixed-effects panel data model construction 0 – impact fee
Gregory S. Burge and Ihlanfeldt (2006a) USA 41 Florida’s counties, 1993–2003 macro: impact fee rates from planning offices for all Florida counties; property tax rolls of the individual counties from Florida Department of Revenue; Means City Construction Cost Indexes from ? fixed-effects panel data model construction 1 – impact fee
Buurma-Olsen et al. (2025) NLD Netherlands, 2020 micro: complete register of all households from Statistics Netherlands generalized ordered probit misallocation 1 – social housing
Cai and Wang (2018) CHN China, 2005–2017 macro: industrial production data from DataStream; real loan rate from People’s Bank of China; real house prices from NBSC time-varying parameter VAR property price 1 – monetary policy
Caloia (2024) NLD Netherlands, 2012–2018 micro: Loan Level Data from De Nederlandsche Bank non-parametric analysis of distribution credit-constrained household 1 – LTV
J. Cao, Huang, and Lai (2015) CHN 70 Chinese cities, 2008–2013 macro: transaction price and rental rates from NBS, CEIC, China Real Estate Index System (CREIS) two-stage difference-in-differences property sales, property price -1, -1 –, – home purchase restriction, home purchase restriction
Q. Cao and Liu (2016) USA 55 urban areas in USA, 2001–2008 macro: data from Home Mortgage Disclosure Act; securitized subprime loans from the CoreLogic LoanPerformance; data on state foreclosure law variables collected by authors ordered probit model; multinomial logit regression risky mortgage, risky mortgage 1, -1 –, – bankruptcy protection, foreclosure laws
Capozza, Green, and Hendershott (1998) USA 63 US metropolitan areas, 1970–1990 macro: average combined (federal and state) marginal tax rates from public use micro samples (PUMS); data on rent, house price, property tax rates and other economic and demographic variables from Capozza and Seguin (1996) OLS; linear regression; simulation property price -1 – property tax
Caracciolo and Miglino (2024) CAN Vancouver, 2011–2021 macro: data on dwellings and households at different aggregate geographical levels from Census difference-in-differences vacancy, construction, rent -1, 0, 0 –, –, – vacancy tax, vacancy tax, vacancy tax
Caraiani et al. (2022) USA USA, 1975–2017 macro: GDP, real house price, real interest rate from FRED; housing market sentiment from Bork, Møller, and Pedersen (2020) quantile structural vector autoregression property price, property price 1, 1 –, – monetary policy, unconventional monetary policy
Cardinale Lagomarsino (2017) ARG Salto, 2001–2015 macro: data on reported domestic violence from Salto’s Centro de Asistencia a la Víctima; data on participation in formal job market and fertility from Argentina Social Security Agency (ANSES) OLS; 2SLS domestic violence 1 – subsidized homeownership programs
Carlson et al. (2012a) USA Wisconsin, 1999–2006 micro: administrative records from CARES and UI propensity score matching neighborhood quality, household size 1, -1 –, – housing allowance, housing allowance
Carlson et al. (2011) USA Wisconsin, 2001–2003 micro: administrative records from State of Wisconsin, data from the U.S. Census Bureau Monte Carlo simulations welfare 1 – housing allowance
Carlson et al. (2012b) USA Wisconsin, 1999–2006 micro: administrative records on low-income households from CARES and UI propensity score matching, difference-in-differences mobility, employment, earnings 1, 0, 0 –, –, – housing allowance, housing allowance, housing allowance
Carozzi, Hilber, and Yu (2024) GBR England and Wales, 2010–2019 micro: residential and all new build residential transactions from Land Registry Price Paid Data difference-in-discontinuities property price, construction 1, 0 –, – homeowner subsidy, homeowner subsidy
Carr and Koppa (2017) USA Houston, 2007–2011 micro: data on voucher recipients from Houston Housing Authority; arrest records from Houston Police Department linear regression crime 1 – housing allowance
Carroll and Yinger (1994) USA 147 towns and cities in the Boston SMSA, 1980 macro: Census of Population and Housing; Massachusetts Taxpayer’s Foundation; Massachusetts Department of Revenue hedonic regression, Box-Cox model rent 1 – property tax
Caudill (1993) USA New York City, 1968 micro: Housing and Vacancy Survey hedonic regression, frontier estimation uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Causa and Pichelmann (2020) AUS, AUT, BEL, CHE, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, GRC, HUN, IRL, ISL, ITA, LTU, LUX, LVA, NLD, NOR, POL, PRT, SVK, SVN, SWE, USA OECD EU countries, Australia, USA, 2012–2013 micro: household-level survey data from European Union Statistics on Income and Living Conditions (EU-SILC), Household, Income and Labour Dynamics in Australia (HILDA), American Housing Survey (AHS) probit model mobility, mobility, mobility, mobility, mobility -1, 1, 1, -1, -1 –, –, –, –, – rent control, social housing, housing allowance, transfer tax, job protection
Cebula (2009) USA Savannah (Georgia), 2000–2005 micro: Chatham County Property Tax Assessors Office; City of Savannah Property Tax Assessment Office hedonic regression property price -1 – property tax
Cerqueiro, Hacamo, and Raposo (2024) PRT Lisbon and Porto, 2010–2020 micro: data on age, education, gender, marital status from Portuguese Administrative Census dataset; labor market data from Quadros de Pessoal; social security, death records, employer-employee matched data from Statistics of Portugal difference-in-differences; panel-data model earnings -1 – rent control
Chakraborty et al. (2010) USA 6 metropolitan areas (Boston, Massachusetts; Miami–Dade County, Florida: Minneapolis–St Paul, Minnesota; Portland, Oregon; Sacramento, California; and Washington, DC), 1990–2000 macro: zoning constraints from current local zoning ordinances, comprehensive plans and GIS data; multifamily housing construction from US Census Bureau regression model, 2SLS construction -1 – land use
Chakraborty, Allred, and Boyer (2013) USA Boston (Massachusetts), Portland (Oregon), Miami (Florida), Washington (DC), Sacramento (California), Minneapolis–St. Paul (Minnesota), 2005–2008 macro: data on detailed municipal zoning maps and ordinances, subprime and foreclosed mortgages from RealtyTrac; and socioeconomic, physical, and fiscal characteristics of a community; S&P Case–Shiller Home Price Index; data on median home values and median household incomes from American Community Survey OLS; spatial autoregressive model foreclosure 1 – land use
Chan et al. (2025) HKG Hong Kong, 2021–2022 micro: data on residents of SDUs in old building, commonly known as “tong lau”, aged >18 living from paper questionnaires descriptive housing quality, rent, tenant confidence, housing stability 0, 0, 1, 1 –, –, –, – rent control, rent control, rent control, rent control
Chapelle, Vignolles, and Wolf (2018) FRA France, 2005–2013 macro: fiscal data on the housing stock from Fichier des Logements dans les Communes; data on housing unit transactions and prices from French solicitors (notaires) difference-in-differences property price, vacancy, construction 1, 1, 0 –, –, – social housing, social housing, social housing
Chapelle, Wasmer, and Bono (2021) FRA Paris, not indicated micro: Base d’Informations Economiques Notariales for real estate prices; online ads for new leases; the Répertoire du parc locatif social for the social housing sector; and Census for the share of social housing hedonic regression; simulation model misallocation 1 2 rent control
Chareyron, Ly, and Trouvé-Sargison (2021) FRA Greater Lyon area, 2014–2016 micro: data on real estate transactions from PERVAL difference-in-differences property price, old housing price, new housing price 0, -1, 1 –, –, – mortgage deduction, mortgage deduction, mortgage deduction
Y.-J. Chen (2000) TWN Taiwan, 1991 macro: Taiwan Housing Status Survey; Survey Report of Family Income and Expenditure; Annual Statistical Report of Housing Information; Taiwan Census Survey of Housing and Population simultaneous model; 3SLS property price -1 – vacancy tax
H. Chen (2017) USA USA, 1975–2012 macro: quarterly housing price indices from the Federal Housing and Finance Agency panel-data model volatility 0 – transfer tax
J. Chen and Enström Öst (2005) SWE Stockholm, Gothenburg, and Malmö, 1994–2002 micro: 1% sample from data on all recipients of housing allowances from Swedish National Insurance Department’s databank probit model homeownership 1 – housing allowance
S. Chen, Wei, and Huang (2019) CHN China, 2005–2014 macro: housing price index, industrial added value growth rate, CPI from Statistical Yearbook of China; 7-day interbank offered rate, money supply M2 from People’s Bank of China; real exchange rate from World Bank vector autoregression property price 1 – monetary policy
Y. Chen, Huang, and Tan (2021) USA 15 US cities, 2014–2016 micro: data from AirDNA; macro: data on regulations from LexisNexis and Airbnb difference-in-differences, GMM number of listings -1 – housing rationing
R. Chen, Jiang, and Quintero (2023) USA New York City, 2002–2017 micro: NYCHVS data on housing units and households hedonic regression, machine learning, propensity score inequality, controlled rents 1, -1 2, 2 rent control, rent control
Z. Chen et al. (2024) CHN Beijing, ? ? difference-in-differences property price, supply, inequality -1, -1, 1 –, –, – price constraint, price constraint, price constraint
Cheng (2022) HKG, SGP Hong Kong and Singapore, 2000–2017 macro: house price data from Urban Redevelopment Authority (Singapore); Rating and Valuation Department (Hong Kong); BIS, IMF WEO, World Bank WDI; FRED panel-data model property price, property price -1, -1 –, – transfer tax, LTV
Cheshire, Hilber, and Koster (2018) GBR 350 English Local Authorities, 1981, 1991, 2001, 2011 macro: vacancy rates data from UK Census panel-data model, instrumental variable vacancy, commute times 1, 1 –, – land use, land use
Cheshire and Sheppard (1989) GBR Darlington and Reading, 1984 micro: house price data from estate agents’ particulars; household survey data hedonic regression property price, land-plot size 1, -1 –, – land use, land use
R. Cheung, Ihlanfeldt, and Mayock (2009) USA 20 MSAs in Florida, 1995–2005 micro: geographic and sales data for single-family residences from Florida Department of Revenue’s abbreviated county tax rolls; regulation stringency index from survey of the chief planner of each city hedonic regression property price 1 – land use
K. S. Cheung, Monkkonen, and Yiu (2024) NZL Auckland, 2016–2021 micro: data on appraised property value, land area of parcels, existing floor area of dwellings, and maximum developable floor area based on the zoning code from Relab; median personal incomes from censuses; housing stock data from Auckland Council’s district valuation roll linear regression; difference-in-differences value 1 – land use
Chiang (2016) CHN China and its large cities Beijing, Shanghai, and Tianjin, 2001–2013 macro: data on residential rent from National Bureau of Statistics structural VAR rent 1 – monetary policy
M. Cho (1991) USA 10 magistral districts of Fairfax county (VA), ? macro: county-level data OLS property price 1 – land use
S.-H. Cho, Wu, and Boggess (2003) USA California, Idaho, Nevada, Oregon, and Washington, 1982–1992 micro: data on about 800,000 randomly selected sites from Natural Resource Inventories polychotomous choice-selectivity modeling system, multinomial logit model tax revenue, property price, government expenditure, development -1, 1, -1, -1 –, –, –, – land use, land use, land use, land use
S.-W. S. Cho and Francis (2011) USA USA, 1992–2007 micro: data from Survey of Consumer Finances simulation welfare, inequality -1, 0 –, – mortgage deduction, mortgage deduction
Choi and Soave (2025) CAN Canada, 2021 micro: data on children living in private dwellings from 2021 Canadian Census logit model housing affordability, overcrowding, housing quality, overcrowding (two-parent families), housing quality (two-parent families) 1, -1, 1, 1, -1 –, –, –, –, – social housing, social housing, social housing, social housing, social housing
Chowdhury and Mallik (2004) AUS Australia, 1986–2003 macro: Australian Bureau of Statistics error correction model property price 1 – housing allowance
Chow and Choy (2009) SGP Singapore, 1980–2008 macro: International Financial Statistics; Singapore Time Series database factor-augmented vector autoregression property price 1 – monetary policy
Chressanthis (1986) USA West Lafayette, 1960–1980 macro: home sales prices from multiple listings and settlement-contract sources provided by local realtor board time series analysis property price -1 – land use
Christofzik, Feld, and Yeter (2020) DEU all 402 German counties and county-free cities, 2007–2017 macro: Kreis-level data from ImmobilienScout24 via Research Data Center Ruhr at RWI; Deutsche Bundesbank event study property sales, property price -1, -1 –, – transfer tax, transfer tax
Chu (2018) TWN Taiwan, 2011–2015 macro: data on housing prices from Monthly Bulletin of Interior Statistics and transactions from Sinyi Realty Inc. DSGE property sales, property sales, property sales, property sales, property price, property price, property price, property price 0, -1, 0, -1, -1, -1, -1, -1 –, –, –, –, –, –, –, – transfer tax, property tax, LTV, monetary policy, transfer tax, property tax, LTV, monetary policy
Church (1974) USA Martinez (California), 1967-1970 micro: data on single-family homes from principal components analysis, OLS, 2SLS property price -1 – property tax
Chyn (2018) USA Chicago, 1994–2009 micro: building records from CHA; social assistance (i.e., TANF/AFDC, Food Stamps, and Medicaid) case files from Illinois Department of Human Services; unemployment insurance wage records from Illinois Department of Employment Security; arrest records from Illinois State Police; schooling outcomes from Chicago Public Schools and the National Student Clearinghouse 2SLS children’s outcomes, crime, labor force participation 1, -1, 1 –, –, – housing allowance, housing allowance, housing allowance
Clair (2022) GBR England, 2008–2019 micro: housing stock data from English Housing Survey difference-in-differences overcrowding -1 – housing allowance
Clark and Heskin (1982) USA Los Angeles, 1978–1980 micro: a sample of 4,094 tenants selected using random digit-dialing techniques contingency analysis value, mobility -1, -1 1, 1 eviction protection, rent control
Clarke and Gold (2024) CAN Montreal, Toronto, Calgary, Edmonton, and Vancouver, 1991–2016 micro: household level from Canadian census of the population panel data model; difference-in-differences; difference-in-difference-in-differences rent, housing quality 0, 1 –, – eviction protection, eviction protection
Coën and Pourcelot (2024) FRA, DEU, NLD, ESP, GBR 13 European cities (Paris, Lyon, Marseille, Berlin, Munich, Frankfurt, Amsterdam, Madrid, Barcelona, Seville, London, Birmingham and Manchester), 2000–2020 macro: ? SVAR property price, property price 1, 1 –, – monetary policy, unconventional monetary policy
Coffey et al. (2022) IRL Ireland, 2014–2020 macro: rent index at the level of Local Electoral Areas event study analysis; difference-in-differences controlled rents -1 2 rent control
Coffinet et al. (2012) FRA France, 1993–2009 micro: data on 231 French banks from French Prudential Supervisory Authority panel data simultaneous equations; Granger causality tests loan growth -1 – CCyB
Collinson and Ganong (2015) USA Dallas, 1990–2013 micro: HUD internal administrative database called PIC containing anonymous household identifier, address, building covariates, contract rent received by landlord, and landlord identifier difference-in-differences rent, housing quality 1, 0 –, – housing allowance, housing allowance
Coombs, Sarafoglou, and Crosby (2012) USA Savannah (Georgia), 2000–2005 micro: home sales from Savannah Board of Realtors’ Multiple Listing Service; property tax data for all of the single-family houses from Chatham County Property Tax Assessors Office and the City of Savannah Property Tax Assessment Office hedonic regression property price -1 – property tax
Corcoran and Heflin (2003) USA Michigan metro area, 1997–1998 micro: data from Women’s Employment Study OLS; logit employment, earnings, employment, earnings 0, 0, 0, 0 –, –, –, – housing allowance, housing allowance, social housing, social housing
Corradin et al. (2016) USA USA, 1996–2006 micro: household data from Survey of Income and Program Participation of the US Census Bureau linear model home equity 1 – bankruptcy protection
Corsetti, Duarte, and Mann (2022) AUT, BEL, FIN, FRA, DEU, IRL, ITA, LUX, NLD, PRT, ESP 11 Euro Area states, 1999–2016 macro: 90 area-wide measures such as prices, output, investment, employment and housing, as well as 342 individual country time series for the 11 early adopters of the Euro from dynamic factor model rent, property price -1, 1 –, – monetary policy, monetary policy
Costello (2006) AUS Perth metropolitan region, 1988–2005 micro: WA Valuation Land and Property Database weighted repeat-sales model; time series regression property sales -1 – transfer tax
Coulson, Le, and Shen (2020) USA 50 U.S. states and the District of Columbia, 2005–2016 macro: city-level data from own construction, American Housing Survey, Census Bureau, Zillow, Eviction Lab at Princeton University panel-data model with fixed effects, instrumental variable vacancy, supply, rent, eviction -1, -1, 1, -1 –, –, –, – eviction protection, eviction protection, eviction protection, eviction protection
Crafton (1980) USA 22 US states, 1971–1975 macro: quarterly building permit and monthly residential construction data from ? linear regression construction -1 – usury ceilings
Cronin and McQuinn (2016) IRL Ireland, 1980–2014 macro: data from ? time series analysis price-to-rent ratio 1 – LTV
Crowe et al. (2013) USA 243 US metropolitan areas, 1998–2007 macro: house price data from FHFA (formerly OFHEO); data on property tax rates from NHBA; other data from US Census Bureau and BEA linear regression; 2SLS; instrumental variable volatility, property price -1, -1 –, – property tax, property tax
Cuellar (2019) USA East Palo Alto, Glendale, Oakland, San Diego (California), 2000–2016 macro: eviction data from Eviction Lab; socioeconomic and demographic data from ? difference-in-differences eviction -1 – eviction protection
Cuerpo, Kalantaryan, and Pontuch (2014) BEL, BGR, DNK, EST, IRL, GRC, ESP, FRA, ITA, LTU, NLD, POL, FIN, SWE, GBR 15 EU member states, 1970–2011 macro: indices of rent controls and tenant-landlord relations constructed by authors and macroeconomic data from Eurostat (?) panel data model, error correction model volatility, volatility 1, 0 –, – rent control, eviction protection
Cunningham and Engelhardt (2008) USA USA, 1996 and 1998 micro: data from Current Population Survey difference-in-differences mobility -1 – capital gains tax
Currie and Yelowitz (2000) USA USA, 1992–1994 micro: SIPP, Public Use Microdata Samples instrumental variable model housing quality, children’s outcomes 1, 1 –, – social housing, social housing
M. A. Curtis (2011) USA USA, 1980, 1990, 2000 micro: data of Integrated Public Use Microdata Series from US Census multinomial logit household size -1 – housing allowance
Q. Curtis (2014) USA 62 state-border CBSAs of USA, 2005–2006 micro: loan data from Core Based Statistical Areas; mortgage application and origination data from Home Mortgage Disclosure Act datasets; subprime lender classification from Department of Housing and Urban Development; macro: foreclosure law index by author pooled OLS with clustered standard errors risky mortgage -1 – foreclosure laws
Czarnecki (2023) NLD 478 Dutch municipalities, 2008–2022 macro: annual property prices from Centraal Bureau vor de Statistiek; property tax rates from Centrum voor Onderzoek van de Economie van de Lagere Overheden panel-data model with two-way fixed effects property price -1 – property tax
Dachis, Duranton, and Turner (2012) CAN Toronto, 2006–2008 micro: single-family houses data from Multiple Listing Service regression discontinuity design; difference-in-differences welfare, property sales, property price -1, -1, -1 –, –, – transfer tax, transfer tax, transfer tax
Damen (2014) BEL, NLD, GBR, USA, SWE, NOR, FIN, DNK 8 OECD countries, 1980–2009 macro: OECD database vector autoregression property price 1 – mortgage deduction
Damen and Goeyvaerts (2021) BEL Belgium, 2009–2020 micro: building data from universe of transactions from the General Administration of Patrimonium Documentation panel-data model with two-way fixed effects property sales, property price, construction 0, 1, 0 –, –, – mortgage deduction, mortgage deduction, mortgage deduction
Daminger (2021a) DEU 72 German labor market regions, 1996–2017 macro: labor market regions from BBSR; population statistics from the federal and state statistical offices difference-in-differences, triple differences, instrumental variable urban sprawl 1 – homeowner subsidy
Daminger (2021b) DEU Kreisfreie Städte, 2008–2020 micro: rental advertisement data is from Ruhr Research Data Center at the RWI triple differences rent -1 – homeowner subsidy
Daminger and Dascher (2023) DEU largest German cities, 2002–2017 macro: population data on cities’ administrative subdivisions from BBSR and KOSTAT difference-in-differences urban sprawl 1 – homeowner subsidy
Dastrup, McDonnell, and Reina (2012) USA USA, 2003, 2005, 2007, and 2009 micro: tenants’ self-reported data from American Housing Survey multivariate regression energy expenditure, energy expenditure 0, 0 –, – social housing, housing allowance
Dauth, Mense, and Wrede (2024) DEU 5 major cities in Bavaria, 2000–2017 micro: data on 465 subsidized rental housing projects from Institut für Arbeitsmarkt- und Berufsforschung nonparametric event study difference-in-differences; linear probability model; Cox proportional hazard regression commuting distance, human capital, mobility, housing cost 0, 1, 1, -1 –, –, –, – social housing, social housing, social housing, social housing
Davidoff and Leigh (2013) AUS 8 states and territories, 1993–2005 macro: postcode-level data from Australian Property Monitors instrumental variable; panel-data model property sales, property price -1, -1 –, – transfer tax, transfer tax
M. Davis (2019) USA 3,141 counties in the USA, 2015 micro: data of residential property transactions assembled from public deeds records by CoreLogic, loan-level HMDA data hedonic regression, two-stage GMM welfare 0 – mortgage deduction
J. Davis (2021) USA New York City, 2000–2010 macro: neighborhood level data on proportion of non-Hispanic whites; proportion of the total tax lot area in a census tract that was upzoned between 2002 and 2009 from NYC Department of City Planning; neighborhood amenities; neighborhood demographics and life cycle factors from NYC Department of City Planning, NYC Department of Finance, NYC Department of Transportation, U.S. Census Bureau; neighborhood housing characteristics from NYU Furman Center beta regression segregation 1 – land use
Dawkins (2024) USA 451 counties, 2009–2016 macro: eviction filings from Eviction Lab; HUD subsidy programs or the Low Income Housing Tax Credit; Wharton Residential Land Use Regulatory Index linear regression eviction 1 – land use
Carvalho de Andrade Lima and da Mota Silveira Neto (2019) BRA Brazilian municipalities, 2000–2010 macro: data on urban policies that each city adopts from the survey of Basic Municipal Information (MUNIC) by Brazilian Institute of Geography and Statistics (IBGE); population density, population growth, urbanization and industrialization rates, average years of schooling, percentage of blacks, working age, immigrants, voter turnout, and percentage of homeowners, percentages of households with sewer, electricity and running water, share of property taxes in relation to total municipal revenues from ? hedonic regression; propensity-score matching rent, supply 1, 0 –, – land use, land use
De Araujo, Barroso, and Gonzalez (2020) BRA Brazil, 2012–2014 micro: data on loans, endorsements, and lines of credit granted by all Brazilian financial institutions to individuals and corporate entities from Credit Information System (SCR) of Central Bank of Brazil (BCB); data on each natural person that has at least one documented employment relationship from official employment register (RAIS) of Brazilian Ministry of Labor and Employment two-stage difference-in-differences value, mortgage arrears -1, -1 –, – LTV, LTV
Deason and Hobbs (2011) USA 48 continental US states, 1986–2008 macro: code adoption data from Department of Energy’s Building Energy Codes Program at the Pacific Northwest Laboratory; residential energy consumption and greenhouse gas emissions at the state level from ? linear regression energy consumption -1 – building code
DeBorger (1985) BEL Liege (Belgium), early 1970s micro: household survey data linear regression, simulation (Stone-Geary utility function) space, overall consumption 1, 1 –, – social housing, social housing
de Haan and Mastrogiacomo (2020) NLD Netherlands, 1996–2015 micro: Loan Level Data from De Nederlandsche Bank logit default rate, default rate -1, -1 –, – LTV, DSTI
De Jorge-Huertas and De Jorge-Moreno (2021) ESP Spain, 1977–2019 macro: monthly price and rent indices from Instituto Nacional de Estadística interrupted time series regression; Box–Cox transformation; Granger causality test property price, rent, property price, rent, property price, rent -1, -1, 0, 0, 0, 0 –, –, –, –, –, – land policy, land policy, rent control, rent control, eviction protection, eviction protection
Delang and Lung (2010) HKG Hong Kong, 1991 and 2001 macro: census-tract-level aggregate data multiple linear regression model poverty concentration 0 – social housing
Del Negro and Otrok (2007) USA 48 contiguous US states, 1986–2005 macro: house prices from OFHEO, per capita personal income from Bureau of Economic Analysis, PCE index, measures of monetary policy, total reserves, Federal Funds rate, GDP deflator, real GDP from FRED, 30-year mortgage rate from Haver Analytics Bayesian dynamic factor model property price 1 – monetary policy
Demary (2010) AUS, DNK, FIN, FRA, DEU, JPN, NLD, ESP, GBR, USA 10 OECD countries, 1970–2005 macro: data on real house price index, the GDP deflator, GDP, short-term interest rate from OECD vector autoregression property price 1 – monetary policy
Dempsey and Plantinga (2013) USA 19 Oregon cities, 1990, 2000, 2009 micro: land plots panel-data model, difference-in-differences development -1 – land use
Denary et al. (2021) USA New Haven (Connecticut), 2017–2020 micro: 400 low-income individuals data from Qualtrics survey ANOVA, generalized estimating equation model, panel-data model with fixed effects mental health 1 – housing allowance
Deng, Zhou, and Wang (2025) CHN 35 major Chinese cities, 2010–2023 macro: average transaction price, transaction area, transaction amount, and residential investment within real estate investment from CRIC database; land transfer area designated for affordable housing purposes from China Land Market Network; China Economic Uncertainty Index from ? panel-data model; instrumental variables property price, property sales, housing investment -1, 1, -1 –, –, – social housing, social housing, social housing
Desai, Elliehausen, and Steinbuks (2013) USA USA, 1998–2006 macro: state-level data on mortgage performance from the Mortgage Bankers Association’s National Delinquency Survey panel-data model with fixed effects foreclosure rate, default rate, foreclosure rate, default rate -1, -1, -1, 1 –, –, –, – bankruptcy protection, bankruptcy protection, foreclosure laws, foreclosure laws
DeSalvo (1971) USA New York City, 1968 micro: New York City Housing and Vacancy Survey linear regression rent burden -1 1 rent control
Diamond, McQuade, and Qian (2019) USA San Francisco, 1990–2016 micro: entire address history of individuals from Infutor dynamic neighborhood choice model uncontrolled rents, mobility, homeownership 1, -1, 1 2, 2, 2 rent control, rent control, rent control
Dias and Duarte (2019) USA USA, 1981–2017 macro: data on industrial production, CPI, 1-year Treasury rate, excess bond premium, vacancy rate, and homeownership rate from FRED and Jarociński and Karadi (2020) structural VAR, FAVAR vacancy, rent, homeownership 1, -1, 1 –, –, – monetary policy, monetary policy, monetary policy
Ding (2013) CHN Beijing, 2000–2002 macro: land price per square meter, housing price per square meter, total square meters of land lot, total square meters of floor space, the FAR, and location information for each commercial housing sales from Beijing Land Resource and Management Bureau simulation; piece-wise regression; 2SLS; instrumental variable; non-linear least square property price, construction -1, -1 –, – land use, land use
Dolls, Fuest, Krolage, et al. (2021) DEU Germany, 2005–2019 micro: data on 17 million properties from F+B linear regression property price -1 – transfer tax
Dolls, Fuest, Neumeier, et al. (2021) DEU Berlin, 2017–2021 micro: data on housing prices and rents from Immowelt.de linear regression, entropy-balancing weighting uncontrolled rents, supply, property price for controlled dwellings, property price, controlled rents 1, -1, -1, 1, -1 1, 1, 1, 1, 1 rent control, rent control, rent control, rent control, rent control
Domènech and Zoğal (2020) AND Andorra, 2018 micro: data on all the Airbnb listings from DataHippo; data on all the official tourist accommodation from official guide of Tourism Department of the Andorra Government spatial bivariate correlation; k-means clustering analysis number of listings 0 – housing rationing
Domènech-Arumı́, Gobbi, and Magerman (2022) BEL Flanders, 2006–2022 micro: 5.4 million observations of cadastral data (date of transaction, exact address, year of construction, last year of renovation, nature of the real estate (e.g., house, apartment, studio), construction type (e.g., detached house), floor in which the dwelling is located, a measure of quality (mediocre, normal, or luxurious), number of garages, number bathrooms, number of housing units, availability of attic, size of living area, availability of central heating) from Federal Service of Finances difference-in-differences property price, inequality -1, 1 –, – transfer tax, transfer tax
Dong (2024) USA Portland (Oregon), 2000–2017 micro: zoning and development status of individual land parcels from Portland Metro’s Regional Land Information System; block-group-level data on neighborhood environment of each parcel from Census 2000; employment data from Longitudinal Employer-Household Dynamics propensity score matching, Kaplan-Meier survival curves, log-rank test construction -1 – land use
Donnelly, McLanahan, and Brooks-Gunn (2017) USA large U.S. cities, 1998–2000 micro: data from the Fragile Families and Childwellbeing Study logit, Coarsened Exact Matching eviction, eviction -1, -1 –, – social housing, housing allowance
Donner (2024a) SWE central districts of Stockholm, 2021–2022 micro: data on all allocated rental apartments from Stockholm Housing Agency; apartment numbers from Svensk Faktakontroll.se; data on transactions of owner-occupied apartments from real estate listing service Booli hedonic regression misallocation, housing size 1, 1 1, 1 rent control, rent control
Donner (2024b) SWE Stockholm, 2003–2023 micro: data on all apartments mediated by the agency from Stockholm Housing Agency linear regression youth displacement 1 2 rent control
Donner and Kopsch (2023) SWE central Stockholm (Sweden), 2011–2016 micro: Stockholm Housing Agency data on apartments from both private and public landlords and on households hedonic regression misallocation, controlled rents 1, -1 1, 1 rent control, rent control
Doojav and Damdinjav (2021) MNG Ulaanbaatar, 2013–2018 micro: housing price index from Tenkhleg Zuuch LLC real estate agency, household income from Household Socio-Economic Survey by National Statistical Office; micro: CPI from National Statistical Office hedonic regression, vector error correction model, difference-in-differences property price 1 – interest rate subsidy
Dowall and Landis (1982) USA San Francisco Bay Area, 1977–1979 micro: housing sales records from Society of Real Estate Appraisers linear regression property price, property price 1, 0 –, – land use, property tax
Downs (2002) USA 86 major MSAs, 1990–2000 macro: sales of existing single-family homes data from NationalAssociation of Realtors and Freddie Mac linear regression property price 0 – land use
Du, Yin, and Zhang (2022) CAN Toronto, Vancouver, Atlanta, Beijing, Boston, Chicago, Hong Kong, London, Los Angeles, New York City, San Diego, San Francisco, Seattle, Shanghai, Sydney, Vienna, and Washington, D.C., 2000–2017 macro: New Housing Price Index, Teranet–National Bank House Price Index, MLS average price, MLS Home Price Index; Property Sales and Assessment Database regression discontinuity design property price -1 – foreign-buyer tax
Du and Zhang (2015) CHN Beijing, Shanghai and Chongqing (treatment) and Tangshan, Qinhuangdao, Baotou, Jinzhou, Jilin, Yangzhou, Bengbu, Anqing, Quanzhou, Jiujiang, Ganzhou, Yantai, Jining, Luoyang, Pingdingshan, Yichang, Xiangfan, Yueyang, Changde, Guilin and Beihai (control), 2008–2011 macro: Newly-Built House Price Indexes from National Bureau of Statistics of China counterfactual analysis property price, property price -1, -1 –, – home purchase restriction, property tax
Dujardin and Goffette-Nagot (2005) FRA Lyon, 1999 micro: French Population Census simultaneous probit model employment 0 – social housing
Dujardin and Goffette-Nagot (2009) FRA Lyon, 2002 micro: French Population Census simultaneous probit model, instrumental variable model employment 0 – social housing
R. E. Dumm, Sirmans, and Smersh (2011) USA Miami-Dade County (Florida), 2000–2007 micro: data on owner-occupied, single-family homes from Miami-Dade County Tax Collector’s office hedonic regression property price 1 – building code
R. Dumm, Sirmans, and Smersh (2012) USA Jacksonville (Florida), 2003–2008 micro: home sales data and census of Population and Housing regarding household size and median household income hedonic regression property price 1 – building code
Dunn, Quigley, and Rosenthal (2005) USA California, 1997–2002 micro: project-level data on structure of costs for newly constructed dwellings for Low-Income Housing Tax Credit linear regression, instrumental variable regression, 2SLS construction cost, construction 1, -1 –, – minimum wage, minimum wage
Dursun-de Neef, Schandlbauer, and Wittig (2023) AUT, BEL, BGR, HRV, CYP, CZE, DNK, EST, FIN, FRA, DEU, GRC, HUN, IRL, ITA, LVA, LTU, LUX, MLT, NLD, POL, PRT, ROU, SVK, SVN, ESP, SWE, LIE, GBR, NOR European Single Market, Great Britain, and Norway, 2018–2020 micro: data on bank and country characteristics from SNL Financial; number of COVID-19 cases for each country, expressed by the quarterly incidence rate per 1000 people, from Our World in Data difference-in-differences loan growth -1 – CCyB
Dusansky, Ingber, and Karatjas (1981) USA 62 school districts in New York State, 1970 macro: Census of Population and Housing; Annual Educational Summary simultaneous equation model, 2SLS rent 1 – property tax
Duso et al. (2024) DEU Berlin, 2014–2019 micro: Airbnb listings from InsideAirbnb; asking rents data from Empirica; macro: LOR-level data from OpenStreetMap and FIS-Broker panel-data model, instrumental variable, Lasso regression number of nights, number of listings -1, -1 –, – housing rationing, housing rationing
Dutta, Gandhi, and Green (2022) IND 4 states of India (Gujarat, Karnataka, Maharashtra, and West Bengal), 2001–2011 macro: aggregate district-level data from the Census of India and National Sample Survey Organization household-level consumption and employment surveys panel-data model mobility, inequality -1, 1 1, 1 rent control, rent control
Dirk W. Early (1998) USA 15 US cities, 1985–1988 micro: American Housing Survey logit homelessness 0 – housing allowance
Dirk W. Early and Olsen (1998) USA 44 US metropolitan areas, 1985–1988 macro: housing survey + micro: homelessness survey TSLS; logit homelessness -1 – rent control
Dirk W. Early and Phelps (1999) USA 49 US metropolitan statistical areas, 1984–1996 micro: American Housing Survey hedonic regression, panel data model uncontrolled rents 1 – rent control
Eckert (1977) USA Brookline (Massachusetts), 1968–1976 micro: ? linear regression tax base, housing quality, homeownership -1, 0, -1 1, 1, 1 rent control, rent control, rent control
Eerola et al. (2021) FIN Finland, 2005–2016 micro: population register data from Statistics Finland difference-in-differences mobility -1 – transfer tax
Eerola and Lyytikäinen (2021) FIN Finland, 2008–2013 micro: data on all HA recipients and their dwellings from KELA instrumental variables regression with discontinuities rent 0 – housing allowance
Eicher (2008) USA Seattle, Vancouver, Kent, Everett, and Tacoma (Washington State), 1989–2006 macro: Wharton Residential Land Use Regulation Index from Wharton database linear regression property price 1 – land use
Eicher (2024) USA 250 major US cities, 1989–2006 macro: data on Standard and Poor’s/Case-Shiller Home Price Index; Shelter Component of the Consumer Price Index from US Bureau of Labor Statistics; city-level data from Wharton database and Census Bureau’s Public-Use Microdata Sample; Wharton Residential Land Use Regulation Index from Wharton Regulatory Database linear regression property price 1 – land use
Eichholtz, Korevaar, and Lindenthal (2022) BEL, FRA, GBR, NLD Amsterdam, London, Paris, and the combined Belgian cities, 1920–2020 macro: city-level data panel-data model rent burden -1 – rent control
Eickmeier and Hofmann (2013) USA USA, 1987–2007 macro: real GDP growth, GDP deflator inflation, effective Federal Funds rate, M1, M2, 232 financial variables comprising 69 property prices, 62 stock market indices, 50 money, capital, and loan interest rates and spreads, 2 monetary aggregates, and 49 series from private nonfinancial sector balance sheets from FRED factor-augmented vector autoregression property price 1 – monetary policy
Ejarque and Kristensen (2015) DNK Denmark, 2010 micro: administrative register data on all housing units and their occupants from Statistics Denmark OLS; TSLS rent burden, controlled rents -1, -1 2, 2 rent control, rent control
Elbourne (2008) GBR UK, 1987–2003 macro: data on prices, retail sales, a short term interest rate, money supply, the house price index, the nominal exchange rate, commodity prices, and the Federal Funds Rate from International Financial Statistics database at the IMF, UK Office of National Statistics, Halifax Bank, and Commodity Research Bureau structural VAR property price 1 – monetary policy
Elinder and Persson (2017) SWE Sweden, 2006–2008 micro: data on housing sales from Swedish land surveying office and Svensk Mäklarstatistik AB difference-in-differences, hedonic regression property price 0 – property tax
Ellen et al. (2007) USA New York City, 1977–2000 micro: address-specific data from HUD User on the number of units created through the Section 8 project-based, Section 202, and the LIHTC programs; all public housing developments from the New York City Housing Authority; sales prices for all apartment buildings, condominium apartments, and single-family homes selling in the city between 1974 and 2002 difference-in-differences, hedonic regression property price 0 – social housing
Ellen, Lens, and O’Regan (2012) USA 10 US cities, 1996–2008 macro: neighborhood-level crime data; household-level data on voucher holders and public housing tenants nationwide from HUD panel-data model crime 0 – housing allowance
Elliott (1981) USA 30+ San Francisco Bay area communities, 1969–1976 macro: price data from Security Pacific National Bank; population data from California Statistical Abstract; growth controls from California State Office of Planning linear regression property price 1 – land use
Engelhardt (1996) CAN Canada, 1978, 1982,1984, and 1986 micro: Canadian Family Expenditure Surveys probit model household saving, national saving 1, 1 –, – tax subsidy, tax subsidy
Engerstam (2017) FIN, SWE 3 major urban areas in Sweden and 6 major urban areas in Finland, 2000–2015 macro: macroeconomic and demographic statistics; regulation indices linear regression volatility 1 2 rent control
England, Zhao, and Huang (2013) USA all cities and towns of New Hampshire, 1985–2006 macro: property tax rates from authors’ collection; real per pupil expenditure on elementary public schools; personal income data at the town level from U.S. Census Bureau; zoning dummy; micro: physical characteristics and construction years for new single-family homes from local assessors regression model housing size, housing size -1, 1 –, – property tax, land use
Eriksen (2009) USA California, 1999–2005 micro: project-level data from National Council of State Housing Agencies descriptive analysis construction cost 1 – social housing
Eriksen and Ross (2013) USA USA, 1998–2000 micro: HUD and the Census IPUMS data linear regression neighborhood quality 1 – housing allowance
Eriksen and Ross (2015) USA USA, 1997–2003 micro: data on rental housing units from American Housing Survey panel-data model rent 0 – housing allowance
Ermini and Santolini (2017) ITA 72 Italian functional urbanized areas, 1991–2001 macro: population size, disposable income, commuting costs, agricultural land rent, stock of housing built before 1919 per square km, percentage of elderly people over 64 years old, young people under 15 years old, ratio between the number of households with 6+ members and the total number of households, immigrants, educated persons, national parks from ? OLS; TSLS urban sprawl, housing size 1, 1 –, – property tax, property tax
Evans-Cowley et al. (2009) USA 63 Texas cities Dallas-Fort Worth metroplex, 1999 micro: data on 46,420 new and existing homes from multiple listing service; macro: city population from Texas State Data Center; total city tax revenue and debt from Texas Municipal League 1999 report hedonic regression property price 1 – impact fee
Evans, Sullivan, and Wallskog (2016) USA Chicago, 2010–2012 micro: data on calls for assistance from Homelessness Prevention Call Center; data on entries into and exits from housing facilities for the homeless from Homeless Management Information System intention-to-treat effect homelessness -1 – homeless aid
Fack (2006) FRA France, 1973–2002 micro: Enquête Logement difference-in-differences space, rent, housing quality 0, 1, 0 –, –, – housing allowance, housing allowance, housing allowance
Falk and Scaglione (2024) CHE 10 Swiss cities, 2017–2018 micro: data on Airbnb rentals from AirDNA difference-in-differences; conditional logit model; conditional fixed-effects Poisson regression number of listings of whole dwellings, number of listings of rooms, number of listing days, revenue per listing, occupancy rate of holiday dwellings 0, 1, -1, -1, -1 –, –, –, –, – housing rationing, housing rationing, housing rationing, housing rationing, housing rationing
Fallis and Smith (1985b) CAN Toronto, 1982 micro: survey of dwellings and households descriptive analysis uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Fallis and Smith (1985a) CAN Toronto CMA, 1982 micro: random sample of 175 private buildings containing 6 or more units subject to rent control, and 140 private buildings containing 6 or more units not subject to rent control hedonic regression uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Z. Fan (2016) CHN China, 2005–2011 ? ? divorce 1 – home purchase restriction
J. Fan et al. (2021) CHN 282 prefecture-level cities in China, 2004–2016 macro: housing price data from China Statistical Yearbook for Regional Economy; data on land supply area from China Land and Resources Statistical Yearbook; data on GDP, investment, population density, financial pressure from China City Statistical Yearbook similar to difference-in-differences property price 1 – land use
Fang and Tian (2020) CHN 243 Chinese cities, 2006–2010 macro: city-level construction land quotas were obtained from provincial-level second land use master plans; land quotas from websites of news media associated with local governments; actual expansion of construction land at the city level were collected from the China Land and Resources Almanac; other city characteristics from China City Statistical Yearbook; service terms of city politicians from www.xinhuanet.com difference-in-differences urban sprawl -1 – construction land quotas
Feeny et al. (2012) AUS Australia, 2001–2006 micro: Household Income and Labour Dynamics in Australia (HILDA) random effects logit panel model employment 0 – housing allowance
Fenelon et al. (2017) USA USA, 1999–2012 micro: National Health Interview Survey data, US Department of Housing and Urban Development (HUD) administrative records principal components analysis, logit health, health 1, 0 –, – social housing, housing allowance
Fenelon et al. (2018) USA USA, 2001, 2004–2012 micro: National Health Interview Survey and U.S. Department of Housing and Urban Development administrative data linear regression, logit mental health, mental health 1, 0 –, – social housing, housing allowance
Fenelon et al. (2021) USA USA, 1999–2001 and 2004–2012 micro: information on the number of missed school days due to illness or injury in the past year for school-aged children from National Health Interview Survey, Sample Child questionnaire negative binomial regression, naïve and pseudo-waitlist models children’s outcomes, children’s outcomes, children’s health, children’s health 1, 1, 1, 1 –, –, –, – housing allowance, social housing, housing allowance, social housing
Fenelon, Slopen, and Newman (2022) USA USA, 1999–2014 micro: data on HUD-assisted households from National Health Interview Survey (NHIS) linked to administrative records from HUD, neighborhood data from American Community Survey linear regression neighborhood quality, neighborhood quality -1, 1 –, – social housing, housing allowance
Ferentinos, Gibberd, and Guin (2023) GBR England and Wales, 2015–2019 micro: data on transaction of properties from HM Land Registry; the energy performance of these properties from public register on Energy Performance Certificates; and demographic characteristics of the regions in which they are located from geodemographic classifications difference-in-differences, propensity score matching property price -1 – climate policy
Fertig and Reingold (2007) USA USA, 1998–2000 micro: data on families living and eligible for living in public housing from Fragile Families and Child Wellbeing Study instrumental variable model mother’s overweight, mother’s health status, domestic violence 1, -1, 0 –, –, – social housing, social housing, social housing
Fetter (2016) USA 51 US cities, 1940–1946 macro: monthly rent index of National Industrial Conference Board; data on rents from intercensal housing surveys by the Census Bureau and the Bureau of Labor Statistics linear regression homeownership 1 1 rent control
Field et al. (2008) IND Ahmedabad, 2002 macro: riots, incidents of violence; 2,440 parts that fall within the 11 electoral jurisdictions that contain at least one mill linear regression mobility -1 1 rent control
W. Fischer (2000) USA USA, 1986–1992 micro: Panel Survey on Income Dynamics linear regression employment -1 – housing allowance
M. M. Fischer et al. (2021) USA 417 USA core-based statistical areas, 1997–2012 macro: Zillow Home Value Index, housing starts, industrial production index, CPI, one-year government bond rate, spreads (10-year treasury yield minus the federal funds rate, the prime mortgage spread calculated over 10-year government bond yields and the Gilchrist and Zakrajšek (2012) excess bond premium) from FRED factor-augmented vector autoregression property price 1 – monetary policy
Fisher (2022) USA Los Angeles and Bay Area (California), 2017–2020 micro: property transaction data from ? difference-in-differences, hedonic regression property sales, property price 0, 0 2, 2 rent control, rent control
Fisher (2023) USA Los Angeles MSA, micro: Los Angeles County Office of the Assessor instrument variables; dynamic discrete choice model; hedonic regression redevelopment 1 – property tax
Fitzenberger and Fuchs (2017) DEU West Germany, 1984–2011 micro: SOEP households linear regression; quantile regression controlled rents -1 2 rent control
Flambard (2019) FRA France, 2013 micro: enquête Logement of Insee probit model rent arrears 0 – housing allowance
Follain and Giertz (2016) USA 129 MSAs, 1980–2010 macro: data from Federal Housing Finance Agency, Bureau of Labor Statistics, Bureau of Economic Analysis, and Standard & Poor’s; median property tax liability for owner-occupants divided by the median owner estimate of the house’s value from American Community Survey vector error correction model, descriptive analysis speculative bubble -1 – property tax
Chaves Fonseca (2019) USA Los Angeles county (California), 2014–2017 micro: Airbnb listings synthetic control method rent, number of listings 0, -1 –, – housing rationing, housing rationing
Forouzandeh (2023) USA New York City, 1991, 1993,…, 2017 micro: data on 18,000 housing units (full or vacant) and their tenants from New York City Housing and Vacancy Surveys; data on employment by industry and occupation, and average commute time from Census Transportation Planning Packages; data on residence and workplace area characteristics from Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics linear regression, difference-in-differences, fixed effects panel regression model housing quality, controlled rents -1, -1 2, 2 rent control, rent control
Fraenkel (2020) USA Ohio, 2002–2014 macro: school-district level data on home sales, foreclosure, and loan records from Zillow ZTRAX; Ohio Department of Taxation; school district boundaries from Census Bureau’s TIGER database random forest regression mobility, foreclosure 1, 0 –, – transfer tax, transfer tax
Fratantoni and Schuh (2003) USA US regions, 1986–1996 macro: implicit deflator for nonhousing GDP, implicit deflator for housing investment, real per-capita nonhousing GDP, real per-capita housing investment, federal funds rate, nominal interest rate on conventional 30-year mortgages heterogeneous-agent VAR property price, housing investment 1, 1 –, – monetary policy, monetary policy
Freedman and McGavock (2015) USA , 2004–2009 micro: data on all areas eligible for tax credit enhancements under the LIHC from HUD; poverty rates and median household income from American Community Survey; macro: neighborhood characteristics from 2000 Decennial Census linear regression; instrumental variables poverty, income 1, -1 –, – social housing, social housing
Freedman and Owens (2011) USA USA, 2000–2007 macro: data on areas qualifying for larger tax credits and on low-income housing developments subsidized by the LIHTC program from U.S. Department of Housing and Urban Development; data on poverty and income from Census Bureau instrumental variables; OLS; panel data model violent crime, property crime -1, 0 –, – social housing, social housing
Freeman and Rohe (2000) USA USA, 1980–1990 macro: census tract data propensity model, regression model segregation 0 – social housing
Freemark (2020) USA Chicago, 2010–2018 micro: all property transactions from Illinois Department of Revenue; building permits and zoning classifications from City of Chicago hedonic regression, difference-in-differences property price, construction -1, 0 –, – land use, land use
Fritzsche and Vandrei (2016) DEU Berlin, Brandenburg, Bremen, Rhineland-Palatinate, Saarland and Saxony-Anhalt, 2005–2014 micro: data on single-family housing from the Property Valuation Committees (Gutachterausschüße) panel-data regression property sales -1 – transfer tax
Fu, Qian, and Yeung (2013) SGP Singapore, 1995–2010 micro: data on all property transactions lodged with the Singapore Land Authority from Urban Redevelopment Authority REALIS database difference-in-differences, hedonic regression volatility, property sales 1, -1 –, – transfer tax, transfer tax
Furth and Gonzalez (2019) USA 265 California jurisdictions, 2012–2018 macro: survey data on land use regulation in California from Terner Center for Housing Innovation factor analysis (noniterated principal axis); linear regression supply 0 – land use
Furukawa and Onuki (2022) USA 17 US cities, 2014–2018 macro: friendliness of the regulation index constructed by authors; number of reviews Airbnb by guests and number of existing housing units rented entirely on Airbnb from InsideAirbnb; home prices, rents, home occupancy rates, number of total housing units from American Community Survey; ratio of the lodging industry in the total payroll of a city from U.S. Census Bureau’s 2016 County Business Patterns; the word frequency of “rent” in webpages discussing STR issues descriptive analysis rent, property price, occupancy rate of holiday dwellings, number of listings 0, 0, -1, -1 –, –, –, – housing rationing, housing rationing, housing rationing, housing rationing
Gaffney (2021) USA East Palo Alto, 2000, 2006, 2011–2019 micro: American Community Survey (ACS); Census data; ACS Data Profiles - Housing Characteristics data difference-in-differences homeownership, homeownership 0, 0 2, 2 rent control, eviction protection
Gandhi, Green, and Patranabis (2022) IND 4 states of India (Gujarat, Karnataka, Maharashtra, and West Bengal), 2001–2011 macro: aggregate district-level data from the Census of India and National Sample Survey Organization household-level consumption and employment surveys panel-data model vacancy -1 1 rent control
Ganong and Shoag (2017) USA states in the continental US (omitting Hawaii and Alaska), 1940–2010 micro: household data from Census and American Community Survey panel-data model property price, migration, income convergence, construction 1, -1, -1, -1 –, –, –, – land use, land use, land use, land use
Gao, Kong, and Hu (2022) CHN 30 regions in China, 1999–2020 macro: national and regional monthly data from Wind database factor-augmented VAR property price 1 – monetary policy
Garcia, Miller, and Morehouse (2021) USA LA County, 2014–2019 macro: Zillow Home Value Index from Zillow.com; micro: Airbnb listing data from InsideAirbnb.com and Tomslee.net; Google Trends data for “Airbnb”; number of food and accommodation establishments (NAICS 72) in each zip code in 2010 from ZIP Code Business Patterns data released by the US Census panel-data model property price 1 – housing rationing
Gardner and Asquith (2025) USA San Francisco, 2007–2016 micro: database of eviction notices filed with the San Francisco Rent Board regression discontinuity design eviction 1 2 rent control
Garz and Schneider (2023a) DNK, SWE Denmark and Sweden, 2015–2019 micro: data on Airbnb hosts come from AirDNA difference-in-differences number of listings, listing price -1, 1 –, – housing rationing, housing rationing
Garz and Schneider (2023b) NOR, SWE Norway and Sweden, 2015–2019 micro: data on Airbnb hosts, rentals, and prices from AirDNA difference-in-differences number of listings, listing price 0, 0 –, – housing rationing, housing rationing
Garza and Lizieri (2016) COL Bogota, 2000–2010 macro: land prices from Lonja de Propiedad Raíz de Bogota; rate of the LVDT per UPZ/year from City Planning Department; total amount of square meters built, land availability from Inventario Estadistico of Secretaría Distrital de Planeación; floor-to-area ratio from cadastral database; newly built housing prices from local housing magazine La Guía Inmobiliaria; home burglary from Observatorio de Seguridad spatial error model; panel-data model property price, construction -1, 0 –, – impact fee, impact fee
Gauß et al. (2022) DEU Berlin, Munich, and Hamburg, 2017–2019 micro: data on Airbnb listings from AirDNA difference-in-differences reservation days, number of listings, number of listing days -1, -1, -1 –, –, – housing rationing, housing rationing, housing rationing
Geddes and Holz (2025) USA San Francisco, 1990–2000 macro: data on each unit’s address, the number of units in the building, and the year the building was built for all residential units in the San Francisco Assessor’s Secure Housing Roll; zip code level number of eviction notices and wrongful eviction claims from the San Francisco Rent Board. continuous treatment difference-in-differences design eviction 1 2 rent control
Geddes and Holz (2024) USA San Francisco, 1990–2000 macro: number of newly rent controlled units from San Francisco Tax Assessor’s Office; intimate partner violence using data on the number of hospitalizations resulting from assaults from California’s Department of Health Care Access and Information; ZIP code-level characteristics from 1990 and 2000 Census continuous treatment difference-in-differences design domestic violence -1 2 rent control
Gelting (1967) DNK Denmark, 1940 and 1960 macro: construction statistics descriptive analysis construction -1 1 rent control
Geshkov and DeSalvo (2012) USA 182 US urbanized areas, 2000 macro: US Census linear regression urban sprawl, urban sprawl -1, -1 –, – land use, impact fee
Gholizadeh (2014) USA, GBR, CAN, SWE, IRL, ESP, NOR, NZL, AUS, JPN, FRA, FIN, CHE, DNK, NLD, DEU, ITA, IRN 18 countries, 1991–2004 macro: data on taxes, interest rate, liquidity, per-capita national income from World Development Indicators; data of price-to-rent ratio and housing price from Habitat website; exchange rate and international financial data from IFS; data for interest rate from Iranian Central Bank panel-data model speculative bubble -1 – capital gains tax
Gholizadeh and Kamyab (2010) USA, GBR, CAN, SWE, IRL, ESP, NOR, NZL, AUS, JPN, FRA, FIN, CHE, DNK, NLD, DEU, ITA, IRN 18 countries, 1991–2004 macro: data on taxes, interest rate, liquidity, per-capita national income from World Development Indicators; data of price-to-rent ratio and housing price from Habitat website; exchange rate and international financial data from IFS; data for interest rate from Iranian Central Bank panel-data model speculative bubble -1 – monetary policy
Gibb (1994) GBR Edinburgh and Glasgow, 1988 and 1992 micro: newspaper advertisements from Glasgow Herald and the Scotsman mean-comparison; linear regression construction -1 0 rent control
Gibbons and Manning (2006) GBR England, 1994–2002 micro: household data from Family Resources Survey (FRS) and the Survey of English Housing (SOEH) difference-in-differences rent 1 – housing allowance
Gibbs and Kemp (1993) GBR UK, 1988 micro: Family Expenditure Survey simulation inequality -1 – housing allowance
Giertz, Ramezani, and Beron (2021) USA Dallas County (Texas), 2014–2016 micro: administrative data on home sales from Dallas Central Appraisal District hedonic regression property price -1 – property tax
Gilderbloom (1986) USA 63 New Jersey cities, 1970 and 1980 macro: Census data linear regression controlled rents 0 2 rent control
Gilderbloom and Markham (1996) USA 125 New Jersey cities, 1970–1990 macro: Census data linear regression housing quality, controlled rents, construction 0, -1, 0 2, 2, 2 rent control, rent control, rent control
Gilderbloom and Ye (2007) USA 76 New Jersey cities, 2003 micro: Rent Control Survey of the New Jersey Tenants Organization linear regression housing quality, construction 0, 0 2, 2 rent control, rent control
Gillespie et al. (2024) IRL Ireland, 2010–2023 micro: property sales and rental listing from Daft.ie; registrations of new and renewing tenancies from Residential Tenancies Board panel-data model property sales, rent transaction volume 1, -1 –, – rent control, rent control
Gissy (1997) USA 50 US cities macro: 1984 Housing and Urban Development survey WLS homelessness -1 2 rent control
Edward L. Glaeser (2003) USA 8 cities in California and 7 cities in New Jersey, 1970 and 1990 micro: New York City Housing and Vacancy Survey; macro: US Census and 1991 HUD Report to Congress on Rent Control linear regression segregation -1 2 rent control
Edward L. Glaeser, Gyourko, and Saks (2005) USA 21 MSAs, 1998–1999 micro: single-family homes that are owner occupied from AHS hedonic regression property price 1 – land use
Edward L. Glaeser and Gyourko (2002) USA central cities of 45 MSAs, 1989 macro: metropolitan areas data from Wharton Land Use Control Survey, American Housing Survey linear regression property price 1 – land use
Edward L. Glaeser and Luttmer (2003) USA New York City, 1993 micro: American Housing Survey; New York City Housing and Vacancy Survey cross-sectional regression misallocation 1 2 rent control
Edward L. Glaeser and Shapiro (2003) USA USA, 1965–2001 macro: CPI inflation rate data from www.freelunch.com; homeownership rate from US Census linear regression homeownership 0 – mortgage deduction
Edward L. Glaeser and Ward (2009) USA Greater Boston, 1980–2004 micro: data from Pioneer Institute’s Housing Regulation Database for Massachusetts Municipalities in Greater Boston linear regression property price, construction 1, -1 –, – land use, land use
Gobillon and Le Blanc (2008) FRA France, 1992–1996 micro: National Housing Survey and National Wealth Survey from INSEE system of equations housing quality, homeownership 0, 1 –, – homeowner subsidy, homeowner subsidy
Goetz (1995) USA San Francisco, 1960–1991 macro: annual data on the number of multifamily-housing units constructed time series analysis construction 1 2 rent control
Gold (2018) USA USA, 1970–2009 micro: Panel Study of Income Dynamics, census tract-level data from Longitudinal Tract Database panel-data model with fixed and random effects mobility, mobility -1, 0 –, – social housing, housing allowance
Gold (2020) USA USA, 1968–1997 micro: data on children from Panel Study of Income Dynamics and its Assisted Housing Database panel-data model with random effects housing cost burden -1 – social housing
Gonçalves (2020) PRT Lisbon and Porto, 2015–2019 micro: data on properties from National Short-Term Rental Registry, administrative data from Confidencial Imobili´ario difference-in differences, event-study designs property sales, property price -1, -1 –, – housing rationing, housing rationing
Gonçalves, Peralta, and Pereira dos Santos (2022) PRT Lisbon, 2015–2019 macro: neighborhood-level data on all daily new registered housing units from National Short-Term Rental Registry (RNAL), sales and prices from Confidencial Imobiliário, Inside Airbnb, Lisboa Aberta difference-in-differences, event-study designs property price -1 – housing rationing
Gorea, Kryvtsov, and Kudlyak (2022) USA 43 states and the District of Columbia, 2000–2019 micro: data on home listings and sales from CoreLogic Multiple Listing Service Dataset hedonic regression; local projections property price 1 – monetary policy
Goujard (2011) FRA Paris, 1998, 2002, 2003, 2004, 2005, 2006 and 2007 micro: data on public housing stock from surveys by regional planning agency DREIF; administrative records on new and planed social housing units from City of Paris; Data on property sales from Commission of Parisian Notaries, BIEN difference-in-differences property price -1 – social housing
Graham and Read (2023) AUS Australia, 1991–2020 macro: data from ABS; CoreLogic; RBA local projection; instrumental variables property price 1 – monetary policy
Green (1999) USA Waukesha county (Wisconsin), 1990 macro: municipal level data on median housing prices and rents from Census OLS rent, property price 1, 1 –, – land use, land use
Green, Malpezzi, and Mayo (2005) USA 45 U.S. metropolitan areas, 1979 –1996 macro: Fannie Mae repeat-sales index of house prices linear regression price elasticity -1 – land use
Greenaway-McGrevy (2023) NZL Auckland urban area, 1993–2022 macro: data on new tenancies from Ministry of Housing and Urban Development; data on rental bonds lodged by with central government agencies from Ministry of Housing and Urban Development synthetic control method rent 1 – land use
Greenaway-McGrevy (2024) NZL Auckland urban area, 1991–2022 macro: permits for new dwellings by sector of control from Statistics New Zealand synthetic control method public construction -1 – land use
Greenaway-McGrevy and Phillips (2023) NZL Auckland, 2010–2021 micro: annual building permits issued for new dwelling units from Auckland Council difference-in-differences construction -1 – land use
Greenhalgh-Stanley and Rohlin (2013) USA USA, 2002, 2004, 2006, 2008 micro: individual-level data from Health and Retirement Study; macro: homestead exemption level of each state data from appendix of How to File for Chapter 7 Bankruptcy pooled regression; panel-data model homeownership, home equity 1, 1 –, – bankruptcy protection, bankruptcy protection
Grimes and Chressanthis (1997) USA 200 US cities, 1990 macro: census data TSLS homelessness 1 – rent control
Grislain-Letrémy and Trevien (2014) FRA France, 1987–2012 macro: Rents and Charges survey, zoning for housing subsidies, the sociodemographic composition of municipalities, the agglomeration population data from survey instrumental variable model (2SLS) supply, rent, housing quality 0, 1, 1 –, –, – housing allowance, housing allowance, housing allowance
Grislain-Letrémy and Trevien (2022) FRA France, 2000–2016 macro: Rents and Charges survey, zoning for housing subsidies, the sociodemographic composition of municipalities, agglomeration population data from Housing survey; other variables relative to municipalities from French Ministries of Housing, of Culture, Corine Land Cover, French National Geographic Institute, French fund for family allowances instrumental variable supply, rent, housing quality 1, 1, 0 –, –, – housing allowance, housing allowance, housing allowance
Grösche (2010) DEU Germany, 2005–2006 micro: data on 5988 tenant households from SOEP; macro: temperature data from Deutscher Wetterdienst seemingly unrelated regression energy expenditure 0 – housing allowance
Groiss and Syrichas (2025) DEU Germany, 2007–2023 micro: asking prices and rents from RWI-GEO-RED; macro: CPI and population from Destatis; unemployment rates from Bundesagentur für Arbeit; short- and long-term interest rates from Refinitiv and ECB Data Portal; monthly wage measures from IAB; land availability from IOER; planning zone regulation intensity from Pehlke and Siedentop (2021) hedonic regression; instrumental variable; panel local projection property price, rent, property price, rent 1, 1, 1, 1 –, –, –, – monetary policy, monetary policy, unconventional monetary policy, unconventional monetary policy
Gross (2020) USA cities in California, Massachusetts, and New Jersey, 1970–2000 macro: census tract data nearest neighbor matching teen pregnancy, teen incarceration -1, -1 –, – rent control, rent control
Gross (2021) USA cities in California, Massachusetts, and New Jersey, 1970–2000 macro: census tract data nearest neighbor matching mobility, inequality -1, -1 2, 2 rent control, rent control
Gruber, Jensen, and Kleven (2021) DNK Denmark, 1980–2011 micro: administrative data for the full Danish population difference-in-differences property price, housing size, homeownership, debt 1, 1, 0, 1 –, –, –, – mortgage deduction, mortgage deduction, mortgage deduction, mortgage deduction
Grundl and Kim (2021) USA USA, 2007–2014 micro: data on individual house transactions and characteristics of individual houses from CoreLogic Real Estate Data difference-in-differences property price, property sales, construction, homeownership 1, 1, 1, 0 –, –, –, – guarantees on homeownership, guarantees on homeownership, guarantees on homeownership, guarantees on homeownership
Gu (2022) CHN Chongqing and Shanghai, 2005–2020 macro: ? difference-in-differences consumer spending 1 – property tax
Gubits et al. (2018) USA USA, 2010–2012 micro: data on 2282 families from Family Options Study linear regression homelessness 0 – housing allowance
Günnewig-Mönert and Lyons (2024) USA New York City, 1918–1926, 1930 micro: over 12,000 rental listings from New York Times; records of 125 district judges from NYC Official City directory regression discontinuity design; event study controlled rents -1 1 rent control
Gunnelin et al. (2024) SWE all 290 municipalities of Sweden, 2012–2023 micro: record of all households from Swedish tax authority; assessment information for all properties, including all single-family owner-occupied properties from property assessment register; records of all rental and cooperative apartments from apartment register OLS vacancy 1 2 rent control
N. Gupta (2020) CHE Switzerland, 1999–2014 macro: CHF LIBOR rate, real mortgage rates, rents reference rates from from Swiss National Bank; trading prices for Swiss futures contract on the three-month CHFLIBOR from Datastream + micro: household data from Swiss Household Panel spatial lag panel fixed effects model homeownership 1 – monetary policy
R. Gupta et al. (2012) USA USA, 1968–2003 macro: income, industrial production, measure of capacity, employment and unemployment, prices relating to both consumer and producer goods and services, wages, inventories and orders, stock prices, interest rates for different maturities, exchange rates, money aggregates, consumer confidence, housing starts, total new private housing units, residential building permits, mobile home shipments, single-family existing home sales and their median prices from US Census Bureau and National Association of Realtors large-scale Bayesian vector autoregressive model property price 1 – monetary policy
Guy, Hysom, and Ruth (1985) USA Fairfax County (Virginia), 1972–1980 micro: data on townhouse clusters linear regression property price -1 – social housing
Gyódi, Mazur, and Cocola-Gant (2025) ESP Barcelona, 2015–2023 micro: data on Airbnb listings from Inside Airbnb; data on HUT licenses from online database of the City Council of Barcelona OLS number of listings -1 – housing rationing
Gyourko and Linneman (1989) USA New York City, 1968 micro: New York City Housing and Vacancy Survey hedonic regression mobility, homeownership -1, -1 1, 1 rent control, rent control
Gyourko and Linneman (1990) USA New York City, 1968 micro: New York City Housing and Vacancy Survey logit regression housing quality -1 1 rent control
Hager, Hilbig, and Vief (2022) DEU Berlin, 2009–2021 micro: online apartment ads, mail survey of tenants and homeowners pre-registered regression discontinuity, regression kink design NIMBYism -1 1 rent control
Hahn et al. (2022) DEU Berlin, 2018–2021 micro: asking prices and rents from Value AG and Immobilienscout24 difference-in-differences uncontrolled rents, supply, controlled rents 1, -1, -1 1, 1, 1 rent control, rent control, rent control
Haider, Anwar, and Holmes (2016) CAN City of Toronto and Greater Toronto Area, 2002–2011 macro: monthly housing sales data from Market Watch, the Toronto Real Estate Board’s monthly statistical bulletin OLS unregulated property sales, property sales 1, -1 –, – transfer tax, transfer tax
Hamilton (2021) USA Baltimore-Washington region, 1994–2017 macro: permitted housing units from the US Census Bureau’s Building Permits Survey; demographic control variables from American Community Survey and decennial census; data on median per-square-foot house prices from Zillow difference-in-differences property price, construction 1, 0 –, – inclusionary zoning, inclusionary zoning
Hammitt et al. (1999) USA USA, 1993 micro: household data from Residential Energy Consumption Survey linear regression, macroeconomic model, damage function model property price, health 1, 1 –, – building code, building code
Han, Ngai, and Sheedy (2022) CAN Greater Toronto Area, 2006–2018 micro: housing sales and leasing transactions data from Multiple Listing Service regression discontinuity design, moving hazard function mobility, homeownership -1, -1 –, – transfer tax, transfer tax
A. Hanson (2012a) USA 6 largest metropolitan areas, 2007 micro: dwelling-level data from American Housing Survey OLS, instrumental variable, regression discontinuity, and sample selection estimation housing size, homeownership 1, 0 –, – mortgage deduction, mortgage deduction
A. Hanson (2012b) USA USA, 2004 micro: data on purpose of the loan (home purchase), the amount of the loan (to determine if it exceeds the limit), and the interest rate charged by the lender from FFIEC Home Mortgage Disclosure Act data OLS; regression kink design interest rate 1 – mortgage deduction
J. Hanson (2022) USA US states, 2015–2019 micro: household data from American Community Survey linear probability model number of burdened households -1 – minimum wage
A. Hanson and Martin (2014) USA USA, 2007 macro: data at ZIP code level on the universe of tax filers from IRS weighted least squares, instrumental variable welfare -1 – mortgage deduction
Harkness and Newman (2006) USA USA, 1996 and 2001 micro: HUD data combined with CPS for comparison group descriptive analysis, linear regression employment 0 – housing allowance
Harrison et al. (2021) USA 5-country metropolitan Atlanta (Georgia), 2016 micro: lists of subsidized multifamily rental properties from National Housing Preservation Database and HUD multifamily contracts database linear regression eviction -1 – housing allowance
Hartley et al. (2021) AUS, CAN, NZL Greater Toronto, Greater Vancouver, Sydney, Melbourne, New Zealand, 2010–2020 macro: house price data from Australian Bureau of Statistics; CREA; Zillow; Dallas Fed International House Price Database; BIS synthetic control method property price -1 – foreign-buyer tax
Hatch (2021) USA USA, 1981–2014 micro: March supplements of the Current Population Survey difference-in-difference-in-differences mobility -1 – eviction protection
He (2014) HKG Hong Kong, 1999–2012 macro: financial statistics linear regression, demand‑supply system property price, loan growth, household leverage 0, -1, -1 –, –, – LTV, LTV, LTV
Heffley and Santerre (1985) USA 101 New Jersey cities macro: city-level data from ? linear regression controlled rents 0 – rent control
Heikkila (1990) CAN Toronto, 1977, 1979, 1981 micro: household data from Canadian Qualify of Life Survey simulation welfare 0 – mortgage deduction
Heinberg and Oates (1970) USA 23 towns and cities in the metropolitan Boston region, 1960 macro: Massachusetts Federation of Taxpayers Association; Massachusetts Department of Commerce OLS, 2SLS rent 0 – property tax
Heintze et al. (2006) USA USA, 1997–1999 micro: National Survey of America’s Families 2SLS, 3SLS, probit employment 0 – housing allowance
Hembre (2018) USA USA, 2001–2012 macro: first-time homebuyer time-series from American Housing Survey; data on all FHA mortgage originations and their performance from Department of Housing and Urban Development difference-in-differences first-time homebuyers, mortgage delinquency 1, 0 –, – homebuyer tax credit, homebuyer tax credit
Hembre and Dantas (2022) USA USA, 2014–2019 micro: household data from American Community Survey TAXSIM simulation mortgage amount, homeownership -1, -1 –, – property tax, property tax
Hendershott, Pryce, and White (2002) USA UK, 1988–1991 and 1995–1998 micro: Council of Mortgage Lenders (CML) 5% random sample of mortgage loan origination data logit LTV, cost of capital 1, 1 –, – mortgage deduction, mortgage deduction
Hendershott and Pryce (2006) GBR UK, 1995–1998 micro: Council for Mortgage Lenders’ annual survey of 5% of all mortgage originations censored regression LTV 1 – mortgage deduction
Hepburn et al. (2023) USA 31 cities, 2020–2021 macro: administrative data on case filings from Eviction Tracking System difference-in-differences eviction -1 – eviction protection
Herrero Ballesta (2025) ESP 151 municipalities of Spain, 2021 macro: data on properties that are not used as a primary residence and are instead utilised temporarily, such as during vacations or weekends, for at least 15 days per year from National Institute of Statistics; housing prices and other characteristics of the real estate market from Idealista; short-term rental regulation measures by author linear regression second homes -1 – housing rationing
Heskin, Levine, and Garrett (2000) USA 4 California cities (Berkeley, East Palo Alto, Santa Monica and West Hollywood), 1980 and 1990 macro: census blocks spatial lag regression mobility, homeownership, controlled rents -1, 1, -1 2, 2, 2 rent control, rent control, rent control
Heylen (2013) BEL Flanders, 2005 micro: administrative data on housing allowances and social housing from Flemish administration (Department RWO) and the Flemish agency for Social Housing (VMSW) simulation inequality, inequality -1, 1 –, – housing allowance, homeowner subsidy
Heylen and Haffner (2012) BEL, NLD Flanders and Netherlands, 2005–2006 micro: Housing Survey of Kenniscentrum voor Duurzaam Woonbeleid; WoON 2006 Housing Survey; income data from Dutch tax records residual income approach inequality, inequality -1, 1 –, – housing allowance, mortgage deduction
C. A. Hilber and Lyytikäinen (2017) GBR UK, 1996–2008 micro: household data from British Household Panel Survey; Land Registry transaction price data regression discontinuity design mobility -1 – transfer tax
C. A. Hilber and Turner (2014) USA 1984–2007 micro: data on families from PSID; mortgage subsidy rate from Federal Housing Finance Agency; mortgage interest rates and housing prices from Federal Housing Finance Agency linear probability model homeownership 0 – mortgage deduction
C. A. L. Hilber and Vermeulen (2016) GBR England, 1974–2008 macro: Local Planning Authorities regulatory data from public records, physical constraints data from satellite imagery, historical population density and employment by industry from the Census panel-data model, instrumental variable volatility, price elasticity 1, 1 –, – land use, land use
Hirsch (1981) USA 34 SMSAs, 1974–1975 micro: SMSA Annual Housing Survey hedonic regression welfare -1 – habitability laws
Hirsch (1988) USA 9 cities in Los Angeles county (California), 1976–1981 micro: pairs of sale and resale data of identical properties from the roll of the Assessor of Los Angeles County linear regression value -1 1 rent control
Hirsch, Hirsch, and Margolis (1975) USA 50 SMSAs, 1968–1972 micro: survey of 5,000 households by University of Michigan Survey Research Center; macro: rents from Census; construction costs from Boeckh Index; dummies for states with repair and deduct laws, rent withholding and retaliatory eviction laws, receivership laws linear regression rent, rent 0, 0 –, – habitability laws, eviction protection
Hirsch and Law (1979) USA 39 SMSAs, 1960–1975 macro: proportion of the occupied housing stock in substandard condition, per-capita income from Annual Housing Survey, Bureau of the Census; habitability laws dummies linear regression housing quality 1 – habitability laws
Ho et al. (2023) HKG Hong Kong, ? micro: transaction-level data from ? ? property sales, property price -1, -1 –, – capital gains tax, capital gains tax
Hobbs (2020) USA 2924 US counties, 2002–2016 macro: county-level data on evictions from Eviction Lab database; maximum weekly benefits and maximum benefit duration for each state from the Significant Provisions of State Unemployment Insurance Laws; data on trigger notices from US Department of Labor Employment and Training Administration; data on county-level unemployment rates from the Bureau of Labor Statistics Local Area Unemployment Statistics; real GDP per capita from Bureau of Economic Analysis; Housing Price Index from Federal Housing Finance Agency; state-level unemployment rate from Bureau of Labor Statistics, Local Area Unemployment Statistics; state annual wages from Bureau of Labor Statistics, Quarterly Census of Employment and Wages regression model eviction 1 – unemployment benefit
Hoebeeck and Inghelbrecht (2017) BEL Belgium, 2010 micro: Household Finance and Consumption Survey 3SLS, simultaneous equations model property price, mortgage rate, mortgage maturity, mortgage amount 0, 0, 0, 1 –, –, –, – mortgage deduction, mortgage deduction, mortgage deduction, mortgage deduction
Hoebeeck and Smolders (2014) BEL Belgium, 2001–2010 micro: household data difference-in-differences property price, homeownership 1, 0 –, – mortgage deduction, mortgage deduction
Hofstetter, Tovar, and Urrutia (2011) COL Colombia, 2006–2010 micro: bank-level data from Superintendencia Financiera de Colombia, mortgage loan data from FRECH OLS, 2SLS, panel data model mortgage rate, mortgage amount 1, 1 –, – interest rate subsidy, interest rate subsidy
Hortas-Rico (2015) USA 107 MSAs, 1990 and 2000 micro: US Census Bureau; Census of Population and Housing; American Housing Survey regression model, 2SLS, principal components analysis city blight -1 – land use
Horton (2023) USA USA, 2013–2019 micro: public records on house sales, property tax assessments, proprietary data from CoreLogic database; mortgage applications from Home Mortgage Disclosure Act event study design property price, construction, property price, construction 0, -1, 0, 1 –, –, –, – property tax, property tax, mortgage deduction, mortgage deduction
Hou, Wang, and Zhu (2022) CHN 31 provinces in China, 2009–2020 macro: data from China Statistical Yearbook; China Stock Market and Accounting Research Database; China Tax Yearbook; Economic Policy Uncertainty instrumental variable model property price -1 – property tax
Howell, Mughan, and Singla (2024) AUS New South Wales, 2015–2019 micro: transaction-level data from Australian Property Monitors unconditional quantile regression; difference-in-differences property price, property sales -1, -1 –, – foreign-buyer tax, foreign-buyer tax
Hoyt, Coomes, and Biehl (2011) USA USA, 1980–2003 macro: data on housing and building permits from U.S. Census Bureau; state-level housing price index from Office of Federal Housing Enterprise Oversight; Wharton Residential Land Use Regulatory Index seemingly unrelated regression property prices, construction -1, 0 –, – property tax, property tax
Hsieh and Moretti (2015) USA 220 metropolitan areas, 1964, 1965, 2008, 2009 macro: County Business Patterns data spatial equilibrium model output, employment -1, -1 –, – land use, land use
Hsu, Matsa, and Melzer (2018) USA US states, 1991–2010 macro: state-level data on benefit schedule from United States Department of Labor; mortgage delinquency from Survey of Income and Program Participation long-difference changes, fixed-effects panel data model foreclosure -1 – unemployment benefit
J. Hu (2018) CAN Toronto and Vancouver, 1997–2018 macro: Statistics Canada; Bloomberg; Thomson Reuters DataStream difference-in-differences value, value, construction, construction 0, 0, 1, 1 –, –, –, – vacancy tax, foreign-buyer tax, vacancy tax, foreign-buyer tax
F. Z. Y. Hu and Chou (2015) HKG Hong Kong, 2001 and 2011 micro: Hong Kong Population Census linear regression, stratified rental equivalence methods poverty -1 – social housing
Y. Huang and Milcheva (2022) GBR England, 2018–2021 micro: residential housing transactions data from HM Land Registry’s Price Paid Data, Zoopla, Energy Performance of Buildings Data difference-in-differences property sales, property price -1, -1 –, – transfer tax, transfer tax
H. Huang and Tang (2012) USA 327 cities in US, 2000–2009 macro: metropolitan level data - Zillow hedonic price index, House Price Index from Federal Housing Finance Agency, WRLURI OLS volatility 1 – land use
Huber and Punzi (2020) JPN, GBR, USA, Euro Area 3 OECD countries and Euro Area, 1980–2014 macro: real consumption, CPI, real residential investments, real house price index, real mortgage loans, credit spread, shadow interest rate, short-term interest rate from Bureau of Economic Analysis, Eurostat, BIS, ECB, national central banks time-varying parameter vector autoregression with stochastic volatility property price 1 – unconventional monetary policy
Hülsewig and Rottmann (2021) AUT, DEU, ESP, FIN, FRA, IRL, ITA, NLD, PRT 9 Euro Area countries, 2010–2019 macro: data domestic mortgage loans, lending rates from ECB; GDP from Eurostat; nominal house prices from Bank of International Settlements local projection property price 1 – unconventional monetary policy
S. Hughes (2020) USA 51 US states, 2005–2017 micro: American Community Survey data on income (total household and personal wage and salary income), tenure choice (renting or owning), monthly rent or owner housing costs, and demographic characteristics from IPUMS; macro: law changes from US Department of Labor and National Council of State Legislatures triple differences rent burden, income, housing consumption -1, 1, 1 –, –, – minimum wage, minimum wage, minimum wage
G. Hughes and McCormick (1981) GBR UK, 1973 micro: individual household data from General Household Survey logit model mobility -1 – social housing
Hyslop and Rea (2019) NZL Auckland, 2003–2007 micro: administrative records of all AS claimants difference-in-differences, quantile regression, panel regression rent 1 – housing allowance
Iacoviello and Minetti (2003) FIN, SWE, GBR Finland, Sweden, UK, 1972–1999 macro: GDP from IMF, residential property prices from BIS, 3-month money market rate, treasury bill rate from Datastream vector autoregression property price 1 – monetary policy
Iannello (2024) ITA Italy, 1915–1978 and 19 Italian cities, 1953–1975 macro: controlled and uncontrolled rents from Istat descriptive analysis inflation -1 1 rent control
Iannello, Caudill, and Mixon (2025) ITA Florence, 1950–1963 micro: data on apartments from linear regression controlled rents -1 – rent control
Igan and Kang (2011) KOR Korea’s regions, 2002–2010 macro: house prices, transaction volumes, and mortgage loans from Bank of Korea and Korea National Statistical Office; proportion of realtors reporting that the number of sellers exceeds the number of buyers from Realtors Association time series analysis property sales, property sales, property price, property price -1, -1, -1, 0 –, –, –, – LTV, DSTI, LTV, DSTI
Ihlanfeldt (2007) USA 105 cities in Florida, 2000–2002 micro: sales data from property tax rolls with housing characteristics OLS, 2SLS property price, housing size 1, 1 –, – land use, land use
Ihlanfeldt and Boehm (1983) USA 55 US SMSAs, 1976 micro: household data from Panel Study of Income Dynamics logit homeownership -1 – property tax
Ihlanfeldt and Shaughnessy (2004) USA Dade County (Florida), 2001 micro: data on new and existing single-family homes and undeveloped residential land from Dade County Property Appraiser tax roll hedonic regression property price, land price 1, -1 –, – impact fee, impact fee
Iqbal and Vitner (2013) USA USA, 2000–2010 macro: housing starts data from US Department of Commerce Census Bureau, home prices from Federal Housing Finance Agency and S and P/Case-Shillery, fed funds rate, Current Account-to-GDP ratio linear regression property price, construction 0, 1 –, – monetary policy, monetary policy
R. Jackson (1993) USA Brookline (Massachusetts), 1980–1988 macro: data on health code violations and building permits descriptive analysis supply, housing quality -1, -1 1, 1 rent control, rent control
K. Jackson (2016) USA California cities, 1970–1995 macro: city-level data from two surveys of California land use officials; annual data on the number of new construction permits issued in each city in California come from the California Housing Foundation’s Construction Industry Research Board panel-data model with fixed effects construction -1 – land use
K. K. Jackson (2018) USA 366 cities in California, 2000, 2006, 2012 macro: city-level data on Zillow hedonic price index OLS property price 1 – land use
O. Jackson and Kawano (2015) USA USA, 1994–1999 macro: homeless counts and tract-specific information on household income, household size, population, race and ethnicity, gender, marital status, age, education, unemployment rates, poverty rates, median rent, and rental vacancy rates from 2000 Decennial US Census; data on LIHTC developments from HUD’s LIHTC Database fuzzy regression discontinuity design; instrumental variable homelessness 0 – social housing
Jacob (2004) USA Chicago, 1992–2002 micro: student records for each semester that a student was enrolled in a ChiPS school from Chicago Public Schools; all public housing developments in the city, including building addresses and the number of units per building from Chicago Housing Authority OLS children’s outcomes 0 – social housing
Jacob, Kapustin, and Ludwig (2015) USA Chicago, 1997–2003 micro: student-level school records from Chicago Public Schools; unemployment insurance (UI) system; social program participation of youth and parents from IDHS; criminal behavior data from Illinois State Police; Medicaid claims data from Center for Medicare and Medicaid Services linear regression (intention to treat) school quality, neighborhood quality 0, 0 –, – housing allowance, housing allowance
Jacob and Ludwig (2012) USA Chicago, 1997–2005 micro: application forms for housing vouchers 2SLS employment, earnings -1, -1 –, – housing allowance, housing allowance
Jacobs (1994) USA New York City, 1987 micro: New York City Housing and Vacancy Survey hedonic regression inequality, controlled rents, controlled rents -1, -1, 0 1, 1, 2 rent control, rent control, rent control
Jacobsen and Kotchen (2013) USA Gainesville (Florida), 2004–2006 micro: residential utility data for households (monthly billing data) from GainesvilleGreen.com linear regression gas consumption, electricity consumption -1, -1 –, – building code, building code
Jakob (2020) CAN British Columbia, 2005–2019 macro: Home Price Index representative house prices by month and municipality from Greater Vancouver real estate board difference-in-differences property price -1 – foreign-buyer tax
James (2024) USA 143 jurisdictions in California, 1990–2021 macro: characteristics of 150 inclusionary housing programs from California Coalition for Rural Housing’s “Inclusionary Housing Programs in California” database; population and housing data from State of California Department of Finance; percentage registered to the Democratic and Republican parties data from California Secretary of State report of registration OLS; 2SLS; instrumental variable supply 0 – inclusionary zoning
Jansen and Mills (2013) USA 268 MSAs in USA, 1996–2008 macro: data on employment, income, and population from MSA Profile of US Department of Commerce; Land Index based on survey of city managers (community’s approach to growth, zoning restrictions, density requirements, and the length of time to get new projects approved) from Gyourko, Saiz, and Summers (2008); housing price data came from OFHEO panel-data model; simultaneous equations model property price, population, real income, employment 1, -1, -1, -1 –, –, –, – land use, land use, land use, land use
Jappelli and Pistaferri (2007) ITA Italy, 1989–2002 micro: Survey of Household Income and Wealth difference-in-differences, probit, tobit mortgage amount 0 – mortgage deduction
Jarociński and Smets (2008) USA USA, 1987–2007 macro: real GDP, GDP deflator, commodity prices, federal funds rate, M2, we include real consumption, real residential investment, real house prices, long-term interest rate spread from FRED, Global Financial Data Bayesian VAR property price, housing investment 1, 1 –, – monetary policy, monetary policy
Jarosiewicz (1984) USA Cambridge (Massachusetts), 1983 micro: random sample of the entire list of rent controlled units; Cambridge Street List Book descriptive analysis misallocation, controlled rents 1, -1 1, 1 rent control, rent control
Jia, Wang, and Fan (2018) CHN Guangzhou, 2008–2011 micro: resale housing transaction data from National Bureau of Statistics of the People’s Republic of China; WIND Information Company hedonic regression property price 1 – home purchase restriction
Jiang, Quintero, and Yang (2025) USA New York City, 2002–2017 micro: NYCHVS data on housing units and households instrumental variable model unemployment 1 2 rent control
Jin, Wagman, and Zhong (2024) USA Chicago, Atlanta, Boston, Los Angeles, 2016–2020 micro: STR listings data from AirDNA; macro: Census Tract-level demographic data from 2015-2019 American Community Survey; binary variable indicating whether a census tract is located in a city’s downtown based on Origin and Destination data from Longitudinal Employer-Household Dynamics; NOAA weather data and Google search patterns; list of prohibited buildings and the list of restricted residential zones from Chicago’s city government; Research total hotel booking revenues from Smith Travel staggered difference-in-differences number of listings, listing price, hotel revenues, crime -1, 0, 0, 0 –, –, –, – housing rationing, housing rationing, housing rationing, housing rationing
D. G. Johnson (1951) USA USA, 1935–1950 micro: data on incomes of homeowners and tenant nonfarm families from Federal Reserve Board; Survey of Consumer Finance; data on money income by sources from Consumer Purchases Study descriptive analysis inequality 0 – rent control
G. Johnson et al. (2019) AUS Australia, 2011 micro: Journeys Home Limited Release file joint random effect probit homelessness -1 – social housing
Jud (1980) USA City of Charlotte (North Carolina), 1976 micro: data on real estate parcels from Master Appraisal File by the tax supervisor of Mecklenburg County, North Carolina hedonic regression property price 1 – land use
Jun (2006) USA Portland, 1990 and 2000 macro: census block groups linear regression property price 0 – land use
Jung and Lee (2017) KOR 73 districts across the Seoul metropolitan area and the non-Seoul metropolitan cities, 2006–2015 macro: house transaction prices, trading frequencies and total numbers of households from the Ministry of Land, Infrastructure and Transport event study design property price, property price -1, -1 –, – LTV, DSTI
Kaas et al. (2021) DEU Germany, 1995–2015 micro: household labor income data from SOEP heterogeneous agent model welfare, welfare, welfare, homeownership, homeownership, homeownership 1, 0, 1, -1, -1, 1 –, –, –, –, –, – transfer tax, social housing, mortgage deduction, transfer tax, social housing, mortgage deduction
Kahn, Vaughn, and Zasloff (2010) USA California, 1970–2000 macro: census-tract data from Urban Institute and Census Geolytics’ Neighborhood Change Database regression discontinuity design, panel-data model population density, gentrification 1, 1 –, – land use, land use
Kalousová and Evangelist (2019) USA Detroit metro area (Michigan), 2009–2010, 2011, 2013 micro: Michigan Recession and Recovery Study data from stratified random sample panel of English-speaking adults aged 19 to 64 adjusted Wald tests for continuous variables, logit, negative binomial regression health 0 – housing allowance
Kang et al. (2024) CHN Chinese counties, 2010–2018 micro: data on the area of housing and the price of housing units from China Family Panel Survey; data on household home purchase demand from China Household Finance Survey; macro: city-level socioeconomic characteristics from China Counties Economic Statistical Yearbook, China City Statistical Yearbook, and provincial statistical yearbooks difference-in-differences; panel-data model; logit housing wealth inequality -1 – property tax
Kangasharju (2010) FIN Finland, 1994-2003 micro: household data from Statistics of Income Distribution survey - interviewer-administered survey that followed a sample of Australian welfare recipients exposed to homelessness or housing insecurity linear regression, nearest neighbor matching rent 1 – housing allowance
Karpestam (2022) SWE Sweden, 2016–2017 micro: Longitudinal integration database for health insurance and labour market studies logit regression mobility -1 2 rent control
Kattenberg and Hassink (2017) NLD Netherlands, 2006–2008 micro: database recording all employees (SSB Banen), self-employed (SSB Zelfstandigen) and households on rent support (Raamwerk huurtoeslag of the Ministry of Internal Affairs); the WRG woonruimteregister verrijkt linear probability regression mobility, misallocation, homeownership -1, 1, 0 1, 1, – rent control, rent control, rent control
Katz and Rosen (1987) USA 64 communities in San Francisco Bay Area (California), 1979 micro: records of house sales from Society of Real Estate Appraisers hedonic regression property price 1 – land use
Keene et al. (2020) USA New Haven (Connecticut), 2017–2018 micro: 400 low-income individuals data from Qualtrics Justice Housing and Health Study survey ANOVA, logit regression health 1 – housing allowance
Kellogg and La Cumbre-Gibbs (2023) USA 48 continental states, 2015–2017 macro: annual total electricity consumption for the residential sector in British Thermal Units (BTUs) from the Energy Information Administration’s State Energy Data System, data on building codes from Building Codes Assistance Program OLS, panel-data model with fixed effects gas consumption, electricity consumption 1, -1 –, – building code, building code
Kelly, McCann, and O’Toole (2018) IRL Ireland, 2003–2010 micro: data from Central Bank of Ireland’s Loan Level Data linear regression; simulation model property price, property price, property price -1, -1, -1 –, –, – LTV, LTI, DSTI
Kendall and Tulip (2018) AUS Brisbane, Melbourne, Perth, Sydney, 1999–2016 micro: house sale prices hedonic regression property price 1 – land use
Kenyon et al. (2020) USA 16 school districts of Franklin County (Ohio), 1998–2015 macro: school-district level data from Franklin County Auditor’s office; US Census regression analysis property price -1 – property tax
Kessler (2019) USA 50 US states, 1991–2010 macro: state-level data on benefit schedule from United States Department of Labor; mortgage delinquency from Survey of Income and Program Participation; All-Transactions House Price Index (STHPI) from Federal Housing Finance Agency; data on state real GDP per capita from Bureau of Economic Analysis long-difference changes, fixed-effects panel data model foreclosure 0 – unemployment benefit
Khan and Reza (2013) USA USA, 1963–2007 macro: Bureau of Economic Analysis; US Census Bureau factor-augmented VAR property price 1 – fiscal policy
Konstantin A. Kholodilin, Limonov, and Waltl (2021) RUS St. Petersburg, 1880–1917 micro: newspaper advertisements time series analysis mobility, controlled rents -1, -1 1, 1 rent control, rent control
Konstantin A. Kholodilin et al. (2022) ESP Catalonia, 2017–2022 micro: sale and rent announcements from idealista difference-in-differences uncontrolled rents, supply, controlled rents 0, 0, -1 2, 2, 2 rent control, rent control, rent control
Jacobo Ostapchuk and Kholodilin (2022) ARG Argentina, 1927–2017 macro: data on rents OLS; MARS controlled rents -1 1 rent control
Konstantin A. Kholodilin and Kohl (2023a) AUS, BEL, CAN, CHE, DEU, DNK, ESP, FIN, FRA, GBR, ITA, JPN, NLD, NOR, PRT, SWE, USA 15 countries, 1910–2016 macro: macroeconomic and demographic statistics; regulation indices panel-data model homeownership 1 – rent control
Konstantin A. Kholodilin and Kohl (2023b) AUS, BEL, DNK, FIN, FRA, DEU, ITA, JPN, NLD, NOR, PRT, ESP, SWE, CHE, GBR, USA 16 developed countries 1910–2017 and 44 developing countries 1980–2017 macro: macroeconomic and demographic statistics; regulation indices panel-data model construction -1 – rent control
Konstantin A. Kholodilin and Kohl (2023c) AUS, BEL, CAN, CHE, DEU, DNK, ESP, FIN, FRA, GBR, ITA, JPN, NLD, NOR, PRT, SWE, USA 16 countries, 1900–2016 macro: macroeconomic and demographic statistics; regulation indices panel-data model inequality -1 – rent control
J.-L. Kim, Greene, and Kim (2014) USA Los Angeles (California), 2003–2011 micro: 110 single-family houses linear regression electricity consumption -1 – building code
Jin-Hyuk Kim, Leung, and Wagman (2017) USA Anna Maria Island (Florida), 1998–2015 micro: parcel identification numbers from Manatee County’s GIS, public records and information about residential building characteristics from Manatee County’s property database, property-appraisal data from Manatee County Tax Collector database panel-data model property price -1 – housing rationing
S. Kim, Hwang, and Lee (2022) KOR South Korea, 2020 micro: household data from Korea Housing Survey regression analysis satisfaction, satisfaction, housing cost burden, housing cost burden 1, -1, -1, 1 –, –, –, – housing allowance, social housing, housing allowance, social housing
S. Kim et al. (2023) KOR South Korea, 2015–2020 micro: data on living conditions and welfare needs of various population groups according to age, income, and other demographic characteristics from Korean Welfare Panel Study panel-data model rent burden -1 – housing allowance
Jae Hong Kim and Hewings (2013) USA 40 large US metropolitan areas, 1990–2000 macro: land use regulation index of Saks (2008); population and employment data from Census Bureau and Census Transportation Planning Package; National Highway Planning Network simultaneous equation system labor mobility -1 – land use
Kinghan, McCarthy, and O’Toole (2022) IRL Ireland, 2013–2016 micro: loan-level data on lending at the 5 main Irish banks, accounting for 90% of the Irish mortgage market from Central Bank of Ireland’s loan-level dataset and Central Bank of Ireland’s Monitoring Templates dataset difference-in-differences household leverage, downpayment -1, 1 –, – LTV, LTV
Kling, Liebman, and Katz (2007) USA Baltimore, Boston, Chicago, Los Angeles, and New York, 2002 micro: administrative data from state and county agencies in California, Illinois, Maryland, Massachusetts, and New York; from impact evaluation survey intent-to-treat effects; OLS; 2SLS neighborhood quality, earnings, physical health, mental health 1, 0, 0, 1 –, –, –, – housing allowance, housing allowance, housing allowance, housing allowance
Kluge, Kucsera, and Lorenz (2024) AUT Austria, 2015–2021 micro: household data from EU-SILC hedonic model; propensity score matching controlled rents, controlled rents -1, -1 –, – social housing, rent control
Knaap (1985) USA Washington and Clackamas counties of Portland (Oregon), 1979–1980 micro: vacant single-family homesites hedonic regression property price 1 – land use
Koeniger, Lennartz, and Ramelet (2022) ITA, DEU, CHE Italy, Germany, Switzerland and 20 Italian regions, 2000–2016 micro: household-level data from German Socioeconomic Panel (SOEP), Italian Survey of Household Income and Wealth (SHIW), Swiss Household Panel (SHP); macro: three-month Euribor instead of the overnight interest swaps from ECB and SNB, market expectations about policy rates from TickDataMarket linear probability model, linear regression rent, property price, homeownership -1, 1, 1 –, –, – monetary policy, monetary policy, monetary policy
Koirala, Bohara, and Li (2013) USA USA, 2007 micro: data on housing units from American Community Survey; macro: state-level residential building energy-efficiency codes as policy measures were obtained from Building Codes Assistance Project two-layer (multilevel) econometric model electricity consumption, gas consumption, oil consumption -1, -1, -1 –, –, – building code, building code, building code
Koirala, Bohara, and Berrens (2014) USA USA, 2007 micro: household data from American Community Survey linear regression, probit, heteroskedastic seemingly unrelated estimation rent, net implicit price, energy expenditure 1, 1, -1 –, –, – building code, building code, building code
Kok, Monkkonen, and Quigley (2014) USA 110 cities in San Francisco Bay Area, 1990–2000 macro: mean sales price from DataQuick OLS property price 1 – land use
Koning and Ridder (1997) NLD Netherlands, 1985–1986 micro: household data from Housing Needs Survey structural model space 1 – housing allowance
Kontokosta (2014) USA Montgomery County, Maryland and Suffolk County (New York), 1980–2000 macro: census-tract level data from Montgomery County Planning Department; Department of Housing and Community Affairs; Housing Opportunities Commission; Maryland State Department of Assessments and Taxation; Maryland State Department of Planning; Suffolk County Department of Planning; Department of Affordable Housing; Long Island Housing Partnership, the Community Development Corporation of Long Island; village and town planning officials; census data are from GeoLytics Neighborhood Change Database; geographic information system files from NYS GIS Clearinghouse and Montgomery County Department of Technology; data on LIHTC units and HUD program units from US Department of Housing and Urban Development Low Income Housing Tax Credit database and Picture of Subsidized Housing database propensity score matching; linear regression; logit racial integration, income integration 1, 1 –, – inclusionary zoning, inclusionary zoning
Koo and Kim (2025) KOR Greater Seoul, 2018–2022 micro: transaction data from Ministry of Land, Infrastructure and Transport difference-in-differences controlled rents 1 2 rent control
Koo and Kim (2024) KOR Greater Seoul, 2018–2022 micro: transaction data from Ministry of Land, Infrastructure and Transport difference-in-differences controlled rents 1 2 eviction protection
Korevaar and Koudijs (2023) NLD Amsterdam, 1732–1811 micro: Amsterdam City Archives; Dutch National Archives linear regression property price -1 – property tax
Koshkin (2024) USA USA, 2019 macro: city-level data from National Longitudinal Land Use Survey OLS homeownership 1 – land use
Koster (2024) GBR England, 1995–2017 macro: number of dwellings per postcode in 2011 from Office of National Statistics; information on greenbelts and energy performance certificates from Department for Communities and Local Government; universe of housing transactions in England from Land Registry linear regression; boundary-discontinuity design welfare, property price 1, 1 –, – land use, land use
Koster, van Ommeren, and Rietveld (2012) NLD Rotterdam, 1985–2007 micro: property data from NVM (Dutch Association of Real Estate Agents); Basisadminstratie Adressen en Gebouwen weighted regression property price 1 – land use
Koster, van Ommeren, and Volkhausen (2021) USA Los Angeles County (California), 2014–2018 micro: Airbnb listings data from Insideairbnb panel regression-discontinuity design, difference-in-differences property price, number of listings -1, -1 –, – housing rationing, housing rationing
Kotchen (2017) USA Gainesville (Florida), 2004–2014 micro: residential utility data for households (monthly billing data) from GainesvilleGreen.com linear regression, difference-in-differences gas consumption, electricity consumption -1, 0 –, – building code, building code
Krol and Svorny (2005) USA New Jersey, 1980, 1990, and 2000 macro: census tract data cross-sectional regression commute times 1 1 rent control
Krolage (2023) DEU Bavaria 50 km within interstate border, 2016–2018 micro: data on 307,517 houses and 273,786 apartments offered for sale from real estate consultancy firm F+B; data on 58,278 households from German Income and Expenditure Survey (Einkommens- und Verbrauchsstichprobe); municipality-level administrative data on authorized residential construction projects (Statistik der Baugenehmigungen) difference-in-differences property price, construction 1, 1 –, – homeowner subsidy, homeowner subsidy
Krumwiede, Zimmermann, and Eason (2007) USA US states, 1991 micro: tax return information for US taxpayers from EY Model File linear model equity -1 – mortgage deduction
Kuang et al. (2024) GBR UK, 2022 micro: experimental survey on Prolific, macro: county-level data on house price index from HM Land Registry ANOVA; linear regression house price expectations, house price expectations, intention to buy home, intention to buy home -1, -1, -1, -1 –, –, –, – LTV, LTI, LTV, LTI
Kukk and Levenko (2024) EST Estonia, 2016–2021 micro: loan-level data from internal database of the Estonian central bank simulation of counterfactual distribution loan growth -1 – DSTI
Kumar (2021) IND Mumbai, 2017–2018 micro: self-conducted household survey OLS housing quality, employment, education, earnings 1, 1, 1, 1 –, –, –, – housing allowance, housing allowance, housing allowance, housing allowance
Kunovac and Zilic (2022) HRV Croatia, 2015–2019 micro: data on the universe of residential transactions (residential property type (only house or apartment/flat), price and size, location, time of sale, year of construction (build), condition of the dwelling, indicators for foreign (non-Croatian) seller and buyer) from Tax Administration of the Ministry of Finance hedonic regression, difference-in-differences property sales, property price, homeownership 0, 1, 0 –, –, – homeowner subsidy, homeowner subsidy, homeowner subsidy
Kuttner and Shim (2016) AUS, CHN, HKG, IND, IDN, JPN, KOR, MYS, NZL, PHL, SGP, THA, TWN, BGR, HRV, CZE, EST, HUN, LVA, LTU, POL, ROU, RUS, SRB, SVK, SVN, TUR, UKR, ARG, BRA, CHL, COL, MEX, PER, ISR, ZAF, CAN, USA, AUT, BEL, DNK, FIN, FRA, DEU, GRC, ISL, IRL, ITA, LUX, MLT, NLD, NOR, PRT, ESP, SWE, CHE, GBR 57 countries, 1980–2011 macro: housing prices and household credit data from BIS, CEIC, and Datastream, macroeconomic data from IMF, survey by the Committee on the Global Financial System on macroprudential policy panel data model, mean group regression, event study analysis property price, property price, property price, loan growth, loan growth, loan growth 0, 0, -1, -1, 0, 0 –, –, –, –, –, – DSTI, LTV, housing taxes, DSTI, LTV, housing taxes
Kutty (2005) USA USA, 1999 micro: American Housing Survey logit poverty, poverty, poverty -1, -1, 0 –, –, – housing allowance, social housing, rent control
Laferrère and Le Blanc (2004) FRA Urban areas, 1985-1999 micro: Enquête trimestrielle sur les Loyers et charges - representative sample of all dwellings located in urban areas hedonic regression rent 1 – housing allowance
Lai and Milcheva (2023) GBR UK, 2014–2017 micro: Residential property transactions data from England and Wales Land Registry Price Paid Database, WhenFresh/Zoopla Dataset from Consumer Data Research Centre difference-in-differences rent, property sales, property price 1, -1, -1 –, –, – transfer tax, transfer tax, transfer tax
Lall, Wang, and Da Mata (2007) BRA 123 Brazilian cities, 1980–2000 macro: data on formal housing stock from ? OLS; seemingly unrelated regression slum 1 – land use
Lambie-Hanson (2008) USA Berkeley, Albany, Oakland, and Alameda County (California), 1980, 1990, 2000, 2006 micro: Census data from decennial reports; 2006 American Community Survey descriptive analysis mobility, homeownership, controlled rents, construction 0, 1, -1, -1 2, 2, 2, 2 rent control, rent control, rent control, rent control
J. Landis and Reina (2021) USA 336 metropolitan areas, 2000-2018 macro: data on monthly gross rent of tenants and monthly housing expenditures of homeowners from U.S. Census Bureau; nonfarm employment data from U.S. Bureau of Labor Statistics; rents data from American Community Survey; regulation indices from Brookings Institution, Wharton Regulatory Land Use Restrictiveness Index, and Urban Institute multiple regression rent, property price 1, 1 –, – land use, land use
Lang (2015) USA Los Angeles County, 1993–2007 micro: assessment data on each apartment building with at least 5 housing units from Los Angeles County Tax Assessor; database from Department of Housing and Urban Development; macro: average rent by census tract from 1990 Decennial Census panel-data model building size 1 – social housing
Lastrapes (2002) USA USA, 1964–1999 macro: data on M1, 3-month treasury bill rate, industrial production index, producer price index for all commodities, 30-year conventional mortgage loan rate, effective fed funds rate, total reserves adjusted for reserve requirements, nonborrowed reserves plus extended credit, Commodity Research Bureau Spot Index from DRI/Citibase; new houses sold, median sales price of new houses sold, existing single-family home sales, median sales price of existing single-family homes from National Association of Realtors vector autoregression property price, property sales 1, 1 –, – monetary policy, monetary policy
Laufer and Tzur-Ilan (2021) ISR Israel, 2010–2011 micro: administrative data on the universe of household purchases of residential properties from Israel Tax Authority; loan-level mortgage data from Bank of Israel difference-in-differences property price -1 – risk weights
Lauridsen, Nannerup, and Skak (2009) DNK Denmark, 1999–2004 macro: data on municipalities from Statistical Bank at Statistics Denmark; Key Figure Base [Nøgletalsbasen] at the Ministry of the Interior; Ministry of Urban and Housing Affairs’ 2000 report on regulation of housing rents; Danish Tax Authority’s 2004 report on property sales prices pooled SUR model with time-specific coefficients and spatial autocorrelation homeownership, homeownership, homeownership -1, -1, -1 1, 1, 1 rent control, social housing, housing allowance
Lazzarin (1990) CAN Vancouver, 1974–1989 macro: time series descriptive analysis tax base, supply, housing quality, homeownership -1, 0, 0, 0 1, 1, 1, 1 rent control, rent control, rent control, rent control
Le Blanc, Laferrère, and Pigois (1999) FRA France, 1996–1997 micro: Enquête Logement, INSEE simulation welfare -1 – social housing
C.-M. Lee, Culhane, and Wachter (1999) USA Philadelphia, 1989–1991 micro: HUD, Philadelphia Planning Commission, Board of Revision of Taxes in Philadelphia linear regression property price, property price -1, -1 –, – housing allowance, social housing
W. S. Lee and Ma (2023) USA USA, 1981–2007 macro: GDP, Personal Consumption Expenditures deflator, federal funds rate, real house prices, private consumption, investment, residential investment, employment, real wages from FRED vector autoregression, state-dependent local projection property price, housing investment 1, 1 –, – monetary policy, monetary policy
S. Lee et al. (2022) KOR Korea, 2017–2021 macro: chonsei price index from Housing Price Trend Survey of Korea Real Estate Board and KB panel-data model; forward expanding Shapley decomposition uncontrolled rents 1 2 rent control
Leech (2012) USA USA, 2002 and 2004 micro: National Longitudinal Study of Youth stratified propensity method youth violence, youth violence, youth drug consumption, youth drug consumption -1, -1, 0, -1 –, –, –, – social housing, housing allowance, social housing, housing allowance
Lees (2019) NZL New Zealand, 2012–2016. micro: sales prices from Auckland Council; unit record sales for other major New Zealand cities including Christchurch, Hamilton, Palmerston North, Queenstown, Tauranga, and Wellington from CoreLogic; construction costs for each city from New Zealand Building Economist hedonic model property price 1 – land use
Leguizamon and Christafore (2021) USA 42 Metropolitan Statistical Areas, 2000 and 2010 macro: data on 12,576 census tracts from Decennial Census and American Community Survey; WRLURI regulation indices OLS property price, gentrification 1, -1 –, – land use, land use
Lens (2014) USA 215 US cities, 1997–2008 macro: vouchers, LIHTCs, public housing and HOPE VI from HUD; Uniform Crime Report data from FBI; socioeconomic characteristics from US census panel-data model crime 0 – housing allowance
Lens (2018) USA US counties and MSAs with population greater than 100,000, 2007–2010 micro: American Community Survey; HUD’s Picture of Subsidized Households OLS burdened households, burdened households -1, -1 –, – social housing, housing allowance
Lepers (2024) ARG, AUS, AUT, BEL, BGR, BRA, CAN, CHE, CHL, CHN, COL, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, GRC, HKG, HRV, HUN, IDN, IND, IRL, ISR, ITA, JPN, KOR, LTU, LUX, LVA, MEX, MYS, NOR, NLD, NZL, POL, PRT, ROU, RUS, SGP, SVK, SVN, SWE, THA, TUR, TWN, USA, ZAF 51 countries, 1990–2016 macro: regulation indices from author’s construction; household credit from IMF Global Debt Database; OECD panel-data model loan growth 1 – mortgage deduction
Levine (1999) USA 490 Californian cities and counties, 1980–1990 macro: surveys of cities and counties linear regression supply, construction -1, -1 –, – rent control, land use
Levine, Grigsby III, and Heskin (1990) USA Santa Monica (California), 1987 micro: Survey of Rent-Controlled Households descriptive analysis rent burden, length of tenure -1, 1 1, 1 rent control, rent control
S.-M. Li and Yu (1990) HKG Hong Kong, 1975–1985 micro: Census and Statistics Department, Hong Kong Housing Authority, Rating and Valuation Department simulation inequality -1 – social housing
S. Li (2018) CHN 30 provinces in China, 2007–2015 macro: data from China Statistical Yearbook of Territorial Resources, China Statistical Yearbook of Real Estate, China Statistical Yearbook and China Statistical Yearbook of Employment and Population panel-data model property price 1 – fiscal policy
V. J. Li, Cheng, and Cheong (2017) CHN 70 large- and medium- sized cities, 2014–2015 macro: housing price data from National Bureau of Statistics of China Mobility Probability Plot property price -1 – home purchase restriction
Y. Li et al. (2020) CHN 5 counties around around Beijing in Langfang, 2014–2019 micro: second-hand housing transaction data from Lianjia Network regression discontinuity design property price 0 – home purchase restriction
X. Li, Nam, and Chang (2024) CHN Chongqing, 2015–2021 micro: housing transaction data (listing and sold prices, transaction date, address, building age, elevator provision, property size, apartment floor, and interior decoration) from Lianjia; government (land) revenue and (public housing) expenditure, and household socioeconomic data from Chongqing Municipal Bureau of Land Resources and Housing Administration, Chongqing Statistical Yearbook publications, and 2020 Chinese Census fuzzy regression discontinuity; 2SLS property price 0 – property tax
J. Li and Florez Perez (2021) CHN Chongqing and Shanghai, 2010 and 2018 micro: China Family Panel Survey difference-in-differences property price 0 – property tax
W. Li and Yu (2022) USA USA, 2015–2019 micro: housing related data from Zillow Group; house price indices for different housing market segments from CoreLogic Solutions; individual income tax data come from IRS; credit score of all mortgage borrowers and fixed mortgage interest rates faced by new borrowers from Black Knight McDash; macro: unemployment from Bureau of Labor Statistics; total employment from Census of Employment and Wages; county-to-county migration from FRB New York Consumer Credit Panel/Equifax; county-level Senate general election information from Princeton University difference-in-differences property sales, property price, emigration, construction -1, -1, 1, -1 –, –, –, – property tax, property tax, property tax, property tax
Lim et al. (2011) ARG, AUT, BRA, BGR, CAN, CHL, CHN, COL, HRV, FRA, HKG, HUN, IND, IDN, IRL, ITA, KOR, LBN, MYS, MEX, MNG, NZL, NGA, NOR, PER, POL, PRT, ROU, RUS, SRB, SGP, SVK, ZAF, ESP, SWE, CHE, THA, TUR, URY 49 countries, 2000–2010 macro: credit growth data from IFS; data on use of macroprudential instruments from IMF survey on country authorities panel data model, GMM Arellano-Bond estimator loan growth -1 – LTV
D. Lin and Wachter (2020) USA California cities, 2012–2017 micro: sales data from Zillow Transaction and Assessment Dataset instrumental variable, two-stage GMM property price 1 – land use
H. Lin (2024) USA New York, 2017–2021 micro: housing maintenance code violations from New York City’s OpenData portal; Rent Controlled Housing information from Rent Guideline Board of New York City; records of FOIA requests from New York State Department of Community Housing Renewal; American Community Survey spatial clustering analysis; spatial regression housing quality -1 – rent control
S.-H. Lin and Hsieh (2021) TWN 20 cities in Taiwan, 1982–2016 macro: Survey of family income and expenditure; Taiwan economic journal; Census and statistics report seemingly unrelated regression, 2SLS supply, supply, supply, supply 0, -1, 0, -1 –, –, –, – property tax, property tax, property tax, property tax
E. Y. Lin and White (2001) USA USA, 1992–1997 micro: data on mortgage and home improvement loans from Home Mortgage Disclosure Act dataset linear probability model credit denial -1 – bankruptcy protection
Lind (2003) SWE Sweden, 1995–2001 macro: completed housing units descriptive before-and-after comparison construction -1 1 rent control
Lind and Hellström (2006) SWE Malmö and Stockholm, 1992–2000 macro: Area Profiles of the Statistics Sweden; data of one of the major municipal housing companies (Svenska Bostäder) Bayesian analysis segregation 0 1 rent control
Linneman (1987) USA New York City, 1981 micro: 3379-observation sample of renters from New York City Housing and Vacancy Survey hedonic regression mobility, mobility, inequality -1, 0, -1 1, 2, 1 rent control, rent control, rent control
Y. Liu (2022) CHN China, 2001–2020 macro: Real Estate Climate Index, inflation, GDP, Shanghai Composite Closing Index, monetary policy uncertainty index from Wind database time-varying parameter VARX property price 1 – monetary policy
Zhi Liu and Li (2025) CHN 35 major Chinese cities, 2009–2019 macro: data on housing transaction volumes, prices, GDP, and total population from China Statistical Yearbooks; land supply, we use gross floor area allowed with land concession for residential use from China Real Estate Index System simultaneous equations model; 3SLS property price, property sales, volatility -1, -1, 1 –, –, – home purchase restriction, home purchase restriction, home purchase restriction
Zheng Liu and Pepper (2023) USA USA, 1988–2019 macro: rent index from Zillow and Haver Analytics; monetary policy surprises from Bauer and Swanson (2023) local projections model rent 1 – monetary policy
Locke, Butsic, and Rissman (2017) USA townships in Michigan, 1970–2010 macro: housing units, income from US Census Bureau; Minnesota Population Center; zoned status from Institute for Public Policy and Social Research propensity score matching; panel-data model supply, supply in rich regions -1, 1 –, – land use, land use
Locks and Thuilliez (2023) FRA metropolitan France, 2012 micro: data on population using accommodation and/or meal distribution services from survey by National Institute for Statistics and Economic Studies (INSEE) and National Institute for Demographic Studies regression discontinuity design homelessness -1 – minimum income
Löffler and Siegloch (2021) DEU 1500 German municipalities, 2008–2015 micro: data on rental prices from ImmobilienScout24; macro: municipality-level data on municipal property tax rates, municipal budgets, municipal annual expenditures, population, land use, owners of housing stock, number of individuals registered as unemployed, and county-level GDP from Federal Statistical Office and Statistical Offices of the Länder; municipal-level average wages from IAB; labor market regions (Arbeitsmarktregionen) from BBSR event study design rent 1 – property tax
Lomonosov (2022) USA New Jersey, 2012–2020 micro: New Jersey Department of the Treasury difference-in-differences; repeat sales model property price, mortgage amount -1, -1 –, – property tax, property tax
Lu, Zhang, and Hong (2021) CHN Beijing, Shanghai, Guangzhou, Hangzhou, and Wuhan, 2008–2017 micro: project-level aggregation of new home transaction records from Chinese Real Estate Index System discrete choice model, structural model of household preference, simultaneous equations model welfare, property price -1, -1 –, – home purchase restriction, home purchase restriction
Luciani (2015) USA USA, 1982–2010 macro: 12 different categories: industrial production, CPI, producer price index, monetary aggregates, banking, GDP and its components, housing sector, productivity and cost, interest rate, employment, population, business/fiscal, and financial markets from FRED structural dynamic factor model property price, construction 1, 1 –, – monetary policy, monetary policy
Lui (2007) HKG Hong Kong, 2001 micro: data on living quarters Hong Kong Population Census simulation inequality -1 – social housing
Lui and Suen (2011) HKG Hong Kong, 2001 micro: data on living quarters Hong Kong Population Census probit model mobility -1 – social housing
Lundberg et al. (2021) USA U.S. cities with populations over 200,000, 1998–2000 micro: data on children born in hospitals from Fragile Families and Child Wellbeing Study model-based imputation approach (parametric g-formula) eviction -1 – social housing
Lundborg and Skedinger (1998) SWE Sweden, 1984–1990 micro: house owners data from Level of Living Surveys unknown mobility 0 – capital gains tax
Luo and Wang (2021) CHN Hangzhou, 2016–2018 macro: ? difference-in-differences property price 1 – talent housing policies
Lutz (2015) USA New Hampshire, 1996–2003 macro: building permit data for new single-family homes from US Census Bureau; sales price data from New Hampshire Housing Finance Authority; property tax data from Department of Revenue Administration; reform gramt data from New Hampshire Departments of Education and Revenue Administration; land use regulation from New Hampshire Office of Energy and Planning and Richard England panel-data model construction -1 – property tax
Lux, Sunega, and Boelhouwer (2009) CZE Czech Republic, 2002 micro: Family Budget Survey simulation inequality -1 – housing allowance
Lyons (2018) IRL Ireland, 2000–2016 macro: sale and rental price data from Central Statistics Office; individual rental listings from daft.ie and from Evening Herald newspaper; ratio of mortgage credit to household deposits from Central Bank of Ireland error correction model property price -1 – LTV
Lyu (2024) CHN Shanghai, 2010–2014 macro: neighborhood (xiaoqu) level housing prices from Cityre Data; amenity data from Baidu/Google Maps API; district-level data on population, housing investment and consumption from China County Statistical Yearbook difference-in-differences; event-study design property price -1 – property tax
Lyytikäinen (2008) FIN Finland, 1990, 1995, 1998, and 2001 micro: data on households from Household Expenditure Survey by Statistics Finland descriptive analysis space, net welfare 0, -1 –, 1 housing allowance, rent control
Lyytikäinen (2009) FIN Finland, 1998–2006 macro: municipality-level panel data from ALTIKA database; property tax rates from Association of Finnish Local and Regional Authorities (Kuntaliitto) fixed-effects Poisson model construction 1 – split-rate tax
MacLennan (1978) GBR Glasgow, 1968–1975 micro: week-by-week pattern of newspaper advertisements for furnished lets; survey of rental sector tenants in the city of Glasgow; University of Glasgow Lodgings Register time series linear regression supply -1 1 rent control
Malard and Poulhes (2020) FRA Paris, 2015–2017 micro: survey of Olap including information on rents and its determinants logit regression; hedonic linear regression controlled rents 0 2 rent control
Malpezzi (1996) USA 133 US metropolitan areas, 1990 macro: MSA-level data OLS segregation, segregation, rent, rent, property price, property price, neighborhood quality, neighborhood quality, homeownership, homeownership, construction, construction 0, 0, 1, 1, 1, 1, 0, 0, -1, -1, -1, -1 –, –, –, –, –, –, –, –, –, –, –, – rent control, land use, rent control, land use, rent control, land use, rent control, land use, rent control, land use, rent control, land use
Malpezzi (1998) EGY Cairo, 1981 micro: survey of 500 households in Cairo hedonic linear regression; dynamic equations side payments, controlled rents 1, -1 1, 1 rent control, rent control
Malpezzi and Ball (1993) ARG, AUS, AUT, BGD, BEL, BFA, BOL, BRA, CAN, COL, DEU, DNK, DZA, ECU, EGY, ESP, FIN, FRA, GHA, GBR, GTM, HKG, HND, IDN, IND, IRE, IRQ, ISR, JAM, JOR, KEN, LKA, MEX, MMR, MYS, NGA, NOR, PAK, PAN, PHL, PRT, SWE, SGP, SYR, THA, TUN, TUR, TZA, URY, USA, VEN 51 countries, 1985 macro: country-level data linear regression rent, property price, housing investment -1, 1, -1 –, –, – rent control, rent control, rent control
Malpezzi, Chun, and Green (1998) USA all 272 MSAs, 1990 micro: dwelling data linear and quadratic 2SLS, hedonic regression rent, property price 1, 1 –, – land use, land use
Malpezzi and Green (1996) USA MSAs, 1990 macro: data from Joint Center; Wharton Residential Land Use Regulation Index OLS rent of low-cost dwelling, property price of low-cost dwelling, vacancy of low-cost dwelling 1, 1, -1 –, –, – rent control, rent control, land use
Malpezzi and Tewari (1991) IND Bangalore, 1974 micro: household survey data descriptive analysis net welfare, controlled rents -1, -1 –, – rent control, rent control
Malpezzi and Vandell (2002) USA USA, 1987–2001 macro: tax credit activity from annual report of the National Council of State Housing Agencies; housing stock, vacancy rates, demographic data, and poverty rates from Census; per-capita income and population from Bureau of Economic Analysis; other subsidized housing data from HUD OLS; instrumental variable construction, construction 0, 0 –, – social housing, housing allowance
Maltman and Greenaway-McGrevy (2024) NZL Hutt City, Wellington City, Porirua, Kapiti Coast, 1995–2022 macro: residential building data from Statistics New Zealand synthetic control method construction -1 – land use
Man and Bell (1996) USA 21 cities in Phoenix metropolitan area (Arizona), 1987–1988 micro: selling prices and physical housing characteristics from sales tape compiled by Arizona Department of Revenue; fiscal variables from Arizona Joint Select Committee on State Revenue and Expenditures; demographic and social-economic data from population surveys by US Census Bureau 2SLS property price -1 – sales tax
Mancuso et al. (2003) USA San Mateo, Santa Clara, and Santa Cruz counties (California), 1999–2000 macro: county administrative data from Case Data System; data on historical receipt of Aid to Families with Dependent Children or TANF from state Medi-Cal Eligibility Data System; historical earnings levels from Unemployment Insurance Base Wage File; micro: survey of families probit employment, earnings 1, -1 –, – housing allowance, housing allowance
Margaris (2024) GBR England and Wales, 1997–2014 macro: retail price index industrial production, national house price index from Bank of England; real regional gross value added from Economics Statistics Center of Excellence; regional house prices and transactions from HM LandRegistry factor-augmented VAR property price -1 – monetary policy
Mark and Goldberg (1981) CAN Vancouver area, 1977–1978 micro: data on 307 transactions from Assessment Authority of British Columbia linear regression property price 0 – land use
Mark and Goldberg (1986) CAN Vancouver, 1957–1980 macro: neighborhood-level data from British Columbia Assessment Authority OLS property price 0 – land use
Marks (1984) CAN Vancouver, 1978 micro: 3885 apartments in the City of Vancouver (“Vancouver proper”) hedonic regression value -1 2 rent control
Martin (2018) USA USA, 2011-2015 micro: data from Census Bureau’s American Community Survey (ACS); Internal Revenue Service’s Statistics of Income division; National Bureau of Economic Research TAXSIM model; Tax Policy Center; Zillow; proprietary loan-servicing data from Black Knight Financial Services’ McDash Analytics NBER TAXSIM simulation property price -1 – property tax
Martin and Hanson (2016) USA USA, 2011 macro: ZIP-code-level data from Internal Revenue Service (IRS); Statistics of Income (SOI); American Housing Survey (AHS) WLS, user-cost model simulation property price 1 – mortgage deduction
Martins and Villanueva (2006) PRT Portugal, 1998–2001 micro: household survey data from Inquérito ao Emprego; administrative records of outstanding debt levels from Central de Risco de Crédito triple differences probability to borrow 1 – interest rate subsidy
Maser, Riker, and Rosett (1977) USA Monroe County (New York), 1950, 1960, 1971 micro: data on physical characteristics and terms of sale from Monroe County Clerk’s Office; on assessed value, zoning, and variance history from local municipal offices; on the use on the parcel and its neighboring properties from either visual inspection (1971 only) or Polk’s Rochester City Directory linear regression property price 0 – land use
Mast and Wilson (2013) USA Charlotte-Mecklenburg County, 2000–2009 micro: data on household property, violent, residential burglary, and street crimes quantile regression crime 1 – housing allowance
Mathur (2007) USA cities and towns of King County (Washington), 1991–2000 micro: all sales of existing single-family homes from tax assessor files for sales of residential buildings, parcels, and real property hedonic regression property price 1 – impact fee
Mathur (2019) USA King County (Washington), 2004–2006 micro: single-family homes two-stage quantile spatial regression property price 1 – land use
Mathur, Waddell, and Blanco (2004) USA 38 cities and towns of King County (Washington), 1991–2000 micro: data on all new single-family housing sales from county tax assessor’s office hedonic regression property price 1 – impact fee
Matsaganis and Flevotomou (2007) NLD, SWE, FIN, ITA, GRC Netherlands, Sweden, Finland, Italy and Greece, 1995–2001 micro: 1995 wave of the European Community Household Panel for Greece (1994 incomes); 1996 Bank of Italy Household Income Survey (1995 incomes); 2000 wave of the Statistics Netherlands Socio-Economic Panel Survey (1999 incomes); 2001 Statistics Finland Income Distribution Survey (2001 incomes); 2001 Statistics Sweden Income Distribution Survey (2001 incomes) microsimulation tax-benefit model EUROMOD inequality 1 – mortgage deduction
Mavropoulos (2021) DEU Berlin, 2015–2017 micro: short-term listings from InsideAirbnb, long-term listings from Immobilienscout24.de linear regression, instrumental variable regression, Generalized Method of Moments short-term earnings, long-term earnings 1, 0 –, – housing rationing, housing rationing
Mavropoulos, Koetter, and Marek (2021) DEU Germany, 2007–2017 micro: 33 million real estate online Immobilienscout24 listings from RWI Research Data Center Ruhr; macro: unemployment rates per NUTS3-region from Bundesagentur für Arbeit; microprudential supervisory reports data on mortgage lending from Deutsche Bundesbank hedonic regression, 2SLS, instrumental variable, GMM rent, property price, loan growth 0, -1, -1 –, –, – housing rationing, transfer tax, transfer tax
Mayer and Somerville (2000) USA 44 MSAs, 1985–1996 macro: metropolitan areas data OLS, GLS price elasticity, construction -1, -1 –, – land use, land use
McCann and Durante (2022) IRL Ireland, 2015–2018 micro: loan-level data from Monitoring Template data of Central Bank of Ireland difference-in-differences household leverage, downpayment, value -1, 1, 0 –, –, – LTV, LTV, LTV
McClure (1978) USA Cambridge (Massachusetts), 1975 micro: partial Census covering 4% of population; Rent Control Board Master File that contains data on the location of all controlled apartments and the rents allowed for those apartments regression analysis profitability, inequality -1, 0 1, 1 rent control, rent control
McDonald and Stokes (2015) USA USA, 2000–2010 macro: housing price series from S&P/Case Shiller ten-city composite index, federal funds rate, federal government deficit from US Department of the Treasury, unemployment rate from US Bureau of Labor Statistics, foreclosure rate from Zillow, interest rate on standard fixed payment 30-year mortgages from Federal Home Loan Bank, initial interest rate on one-year adjustable rate mortgages from Freddie Mac Primary Mortgage Market Survey, net international capital flow from US Department of the Treasury TIC survey vector autoregression property price, property price 1, 1 –, – monetary policy, fiscal policy
McGibany (1991) USA 71 counties in Wisconsin, 1978–1989 macro: data from U.S. Bureau of the Census, Housing Units Authorized by Building Permits; National Planning Association Data Services; Citibank Economic Database; Wisconsin Department of Revenue, Cities, Towns and Villages Local Financing; Office of Thrift Supervision, Federal Housing Finance Board, Terms on Conventional Home Mortgages; Bureau of Labor Statistics; 1983 County and City Databook linear regression construction -1 – property tax
McMillan and Carlson (1977) USA 65 small incorporated Wisconsin cities, 1970 macro: Census of Housing; Census of Population; State Bureau of Municipal Audit OLS; 2SLS property price 0 – property tax
McQuillan and Peach (2019) USA USA, 2017–2018 macro: average and median property taxes on owner-occupied homes from American Housing Survey; new home sales from ? descriptive property sales -1 – property tax
Meador (1982) USA USA, 1973–1976 macro: Federal Home Loan Bank Board’s monthly survey of conventional home mortgages on new and existing homes; Federal Reserve Bulletin yield on long-term government bond; SMSA-level data on net savings and loan assbtiation mortgage sales linear regression mortgage rate 1 – judicial foreclosure
Means and Stringham (2012) USA California cities, 1980, 1990, and 2000 macro: data on housing and community characteristics from U.S. Census and Minnesota Population Center’s National Historical Geographic Information System; data on affordable housing mandate adoption dates from California Coalition for Rural Housing and Non-Profit Housing Association of Northern California; average home sale prices for each city from RAND California Statistics website; California Department of Housing and Community Development survey from J. D. Landis (2000); comprehensive statewide surveys of California municipality zoning laws from Glickfeld and Levine (1992) panel-data model property price, supply 1, -1 –, – inclusionary zoning, inclusionary zoning
Mengle (1985) USA 8 SMSAs (Boston, Detroit, Minneapolis-St. Paul, Newark, Paterson-Clifton-Passaic, Philadelphia, Pittsburgh, and Washington), 1974 and 1978 micro: data on 8281 dwellings from Annual Housing Survey logit regression housing quality -1 2 rent control
Mense, Michelsen, and Kholodilin (2018) DEU German municipalities, 2011–2016; Bavarian municipalities in the years 2010–2016; German municipalities, 2008–2016 micro: Internet advertisements; macro: sales of developed vacant plots of land, Demolition and Conversion Statistics difference-in-differences value, uncontrolled rents, supply, controlled rents 1, 1, 1, -1 2, 2, 2, 2 rent control, rent control, rent control, rent control
Mense, Michelsen, and Kholodilin (2022) DEU German municipalities, 2011–2016 micro: Internet advertisements difference-in-differences, discontinuity-in time design uncontrolled rents, mobility, demolitions, controlled rents 1, -1, 1, -1 2, 2, 2, 2 rent control, rent control, rent control, rent control
Merritt and Farnworth (2021) USA USA, 2016 macro: state- and block group-level data from Princeton University’s Eviction Lab, the American Community Survey linear mixed-effects model eviction -1 – eviction protection
Meyers et al. (1995) USA Boston, 1992 micro: 203 children who visited Boston City Hospital ED multiple stepwise regression children’s health 1 – housing allowance
Mhadi and Pinto (2018) CAN Greater Vancouver Region, 2015–2016 micro: individual residential property transactions from Landcor Data Corporation difference-in-difference; regression discontinuity design property sales, property price -1, -1 –, – transfer tax, transfer tax
Milcheva and Sebastian (2016) BEL, FIN, FRA, DEU, IRL, ITA, NLD, PRT, ESP 9 Euro area countries, 1999–2008 macro: consumer price index, real private consumption expenditure, real residential gross fixed capital formation, real house prices, short-term money market rate from International Financial Statistics of the IMF, OECD, and Bank for International Settlements vector autoregression property price, housing investment 0, 1 –, – monetary policy, monetary policy
Mildner (1991) USA New York, 1987 micro: Housing and Vacancy Survey two-stage probit welfare, welfare -1, -1 1, 2 rent control, rent control
Miles (2021) USA USA, 1974–2021 macro: government spending, GDP, ten-year Treasury interest rate, Federal Funds Rate, consumption expenditures, private non-residential investment, housing investment from FRED vector autoregression, local linear projection property sales, property price, housing investment, construction 1, 0, 1, 0 –, –, –, – fiscal policy, fiscal policy, fiscal policy, fiscal policy
Min (2021) KOR Korea, 2015–2021 : data from Real Estate Trade Management System ? uncontrolled rents 1 2 rent control
Mistrulli et al. (2023) ITA Italian provinces, 2013–2017 micro: 84,951 mortgages subscribed by a major Italian bank to buy or renovate a first or second home; job- conditions of all Italian workers employed in private firms, and retired workers from INPS difference-in-differences mortgage amount, LTV 1, 1 –, – job protection, job protection
Mitchell (2004) USA Pennsylvania and New Jersey, 1970–1990 land-area data from Delaware Valley Regional Planning Commission; data from decennial censuses of U.S. Census Bureau multivariate regression segregation 1 – land use
Miyazaki and Sato (2014) JPN Japan, ? macro: prefecture-level data from ? system GMM property price, land price -1, 0 –, – property tax, property tax
Mo (2019) HKG Hong Kong, 1999–2016 macro: private residential retail price index and real estate related tax income from Hong Kong Special Administrative Region multiple regression analysis property price, property price -1, 1 –, – transfer tax, property tax
Monk and Whitehead (1999) GBR Fenland, North Hertfordshire, South Cambridgeshire, 1981–1991 macro: data on land and house prices and housing production descriptive analysis (comparative statics) property price, construction 1, -1 –, – land use, land use
Monkkonen, Lens, and Manville (2020) USA 252 cities and 19 counties of California, 2013–2017 macro: land-use regulations from Terner California Residential Land Use Survey; measure of zoned capacity from Housing Element of each city’s General Plan linear regression (OLS); Tobit construction -1 – land use
Monràs and Montalvo (2022) ESP Catalonia, 2016–2021 micro: 400,000+ dwellings in Catalonia (INCASOL and AHC) hedonic regression; panel data model supply, controlled rents -1, -1 2, 2 rent control, rent control
Jofre Monseny, Martı́nez Mazza, and Segú (2023) ESP Catalonia, 2016–2021 macro: average rental prices and the number of agreements signed for 230 municipalities difference-in-differences; event-study design supply, controlled rents 0, -1 2, 2 rent control, rent control
Montalvo (2010) ESP municipalities of Spain, 2001 and 2005 macro: ratio of vacant urban land over total urban land; total employment growth; number of immigrants; proportion of rental units over total available housing units; housing prices; population size linear regression property price 0 – land use
B. Moon (2024) KOR South Korea, 2020–2021 micro: data on contracts for the sale or lease of real estate from official registries regression discontinuity in time share of monthly rental lease type, chonsei deposit to price ratio 1, 1 –, – eviction protection, eviction protection
C.-G. Moon and Stotsky (1993) USA New York City, 1978–1987 micro: housing units Tobit; panel data model housing quality -1 1 rent control
Moorhouse (1969) USA New York City, 1940–1966 micro: data on buildings linear regression housing quality, housing quality 0, -1 1, 1 rent control, rent control
Moorhouse (1972) USA New York City, 1940–1957 micro: data on 35 buildings, containing 1682 apartments linear regression housing quality -1 1 rent control
Morawetz and Klaiber (2024) AUT Vienna, 2012 and 2019 macro: income data on 1329 block-groups from Statistik Austria; urban green areas and location of metro stations from city and open GIS-data regression with spatial fixed effects segregation -1 1 rent control
Morin et al. (2023) FRA Paris, 2018–2022 micro: asking rents from SeLoger difference-in-differences controlled rents -1 2 rent control
Mukhija et al. (2010) USA Los Angeles and Orange Counties, 1980–2005 macro: data on the structure and productivity of programs from academic publications, city Web sites, public reports and documents, including General Plans (particularly the Housing Elements of the Plans), and reports to City Council; data on the number of affordable housing units produced through the Tax Credits program from Southern California Association of Governments; permit data from Construction Industry Research Board; unemployment data from California Economic Development Department linear regression construction 0 – inclusionary zoning
Munch and Svarer (2002) DNK Denmark, 1992–1999 micro: 10% random sample of adult population proportional hazard model mobility -1 1 rent control
M. P. Murray et al. (1991) USA Los Angeles, 1983-1990 macro: Housing Assistance Supply Experiment; Annual Housing Survey simulation model supply, housing quality, homeownership, controlled rents -1, -1, 1, -1 1, 1, 1, 1 rent control, rent control, rent control, rent control
Cameron Murray and Limb (2023) AUS Brisbane, 1996, 2001, 2006, 2011, 2016 micro: data on 25,775 sites from ABS Census data for Brisbane panel data model? property price, development 0, 0 –, – land use, land use
Cecile Murray and Schuetz (2019) USA cities in California, 2013–2017 macro: regulation measures from Terner California Residential Land Use Survey; city-level demographic and economic characteristics from American Community Survey; data on multifamily permits issued from the Census Bureau’s New Residential Construction Series Tobit construction -1 – land use
Muth and Wetzler (1976) USA USA, 1966–1967 micro: data on new single-family houses from Federal Housing Administration regression analysis property price 1 – building code
Nagar and Segal (2014) ISR Israel, 1999–2010 macro: data on housing prices and rents, population, housing stock, unemployment rate, housing starts/completions, monetary interest rate, real long-term interest rate, exchange rate of shekel from Central Bureau of Statistics error correction model, difference equation model, instrumental variable, 2SLS rent, property price 1, 1 –, – monetary policy, monetary policy
Nagle (2003) USA Massachusetts, 1999–2000 micro: survey data from Center for Survey Research at University of Massachusetts at Boston descriptive employment, earnings, employment, earnings 1, -1, 1, -1 –, –, –, – housing allowance, housing allowance, social housing, social housing
Nagpal and Gandhi (2024) IND Mumbai, 2014–2022 micro: universe of permit applications filed with the Municipal Corporation of Greater Mumbai; unit-level sales prices from PropEquity; proprietary database of mortgage applications from one of India’s largest private mortgage lenders difference-in-differences property price, housing size, construction 1, 1, -1 –, –, – land use, land use, land use
Nagy (1995) USA New York City, 1978–1987 micro: 1978, 1981, 1984, and 1987 New York Housing and Vacancy Surveys hazard model mobility -1 1 rent control
Nagy (1997) USA New York City, 1978–1987 micro: 1978, 1981, 1984, and 1987 New York Housing and Vacancy Surveys hazard model; hedonic regression mobility -1 1 rent control
Naikoo, Ahmed, and Ishtiaq (2021) IND India, 2009–2018 macro: housing price index, real effective exchange rate, GDP, interest rate autoregressive distributed lag (ARDL) property price 0 – monetary policy
Nallathiga (2006) IND Mumbai, 1994–1999 macro: ward-level data of public goods and services, demographic details and budgetary detail from ?; FSI variations from DCR handbook of the Municipal Corporation of Greater Mumbai; residential property prices from MMRDA linear regression property price 1 – land use
Nath (1984) IND City of Calcutta, 1970–1980 micro: records of the Office of Rent Controller descriptive analysis tax base -1 – rent control
A. C. Nelson (1988) USA Portland, 1983–1986 micro: data on sales of vacant parcels of land hedonic regression property price 1 – land use
E. Nelson (2024) USA Chicago, 2006–2016 macro: crime data from Uniform Crime Reporting of FBI; count of crimes occurring within a census tract from Chicago Police Department’s CLEAR; data on whether or not a census tract is a Low-Income Housing Tax Credit Qualified Census Tract from HUD panel data model crime -1 – social housing
Newman, Holupka, and Harkness (2009) USA USA, 1970–1995 micro: PSID combined with HUD data on project-based recipients propensity score matching employment, earnings 0, 0 –, – housing allowance, housing allowance
Newman and Harkness (2000) USA USA, 1968–1990 micro: Panel Study of Income Dynamics (PSID)-Assisted Housing Database 2SLS (instrumental variable) children’s outcomes 0 – housing allowance
Newman and Holupka (2017) USA USA, 1995–2007 micro: longitudinal data from the Panel Study of Income Dynamics, Census, American Community Survey, administrative data U.S. Department of Housing and Urban Development propensity score matching, instrumental variable, quantile regression children’s outcomes, children’s outcomes 0, 0 –, – housing allowance, social housing
Newman and Holupka (2021) USA USA, 1997–2005 micro: Panel Study of Income Dynamics (PSID), PSID’s Child Development Supplements (CDS), PSID-Assisted Housing Database (PSID-AHD) propensity weights, instrumental variable children’s outcomes, children’s health 1, 1 –, – social housing, social housing
Noam (1982) USA >1100 US cities and towns, 1970 macro: locality-level data from International City Managers’ Association OLS, 2SLS property price 1 – building code
Novan, Smith, and Zhou (2022) USA Sacramento (California), 2008–2013 micro: residential consumers data on hourly electricity consumed at each individual premise from linear regression electricity consumption -1 – building code
Nsafoah and Dery (2024) CAN Canada, 2002–2022 macro: Bloomberg; Bank of Canada; FRED; Bank of International Settlements; Statistics of Canada Bayesian VAR model property price, property price 1, 1 –, – monetary policy, unconventional monetary policy
Oates (1969) USA New Jersey municipalities, 1960 macro: data on housing from Census of Housing; population from Census of Population; effective property tax rates, population density, and family income from Beck (1963); percentage of new housing, homownership rate from Municipal Yearbook 2SLS property price -1 – property tax
Oates and Schwab (1997) USA 15 cities and metropolitan areas in the general region containing Pittsburgh, 1960–1989 macro: Office of the City Controller linear regression construction 1 – split-rate tax
Öst, Söderberg, and Wilhelmsson (2014) SWE Sweden, 2008 micro: 400,000+ household data from GeoSweden database for 2008 linear regression segregation -1 2 rent control
Öst and Johansson (2023) SWE Stockholm metropolitan statistical area, 2001–2015 micro: lottery data and household data from Swedish population register panel data, 2SLS employment, earnings -1, -1 –, – rent control, rent control
Oliviero and Scognamiglio (2019) ITA 6213 Italian municipalities, 2010–2012 macro: municipal level data from Italian Real Estate Market Observatory (OMI); property tax rates and deductions chosen by each municipality from Institute for Local Finance and Economy (IFEL); municipal characteristics from the 2011 Population and Housing Census; municipal elections from Ministry of the Interior; municipal balance sheet from the database AIDA PA by Bureau Van Dijk 2SLS; difference-in-differences property price -1 – property tax
Olsen (1972) USA New York, 1968 micro: 1968 New York City Housing and Vacancy Survey cross-sectional regression net welfare -1 1 rent control
Olsen et al. (2005) USA USA, 1995–2002 micro: PSID combined with HUD data on recipients linear regression earnings -1 – housing allowance
O’Meara (2015) AUS, CAN, DNK, JPN, NZL, NOR, SWE, CHE, GBR, USA 10 OECD countries, 1970–2013 macro: real disposable income per capita, total population of the country, real mortgage interest rate, supply of new dwellings, real cost of renting a property, permits issued for the construction of new housing units, total cost of residential construction, real residential investment from OECD Economic Outlook and Main Economic Indicators databases, IMF International Financial Statistics database system of equations, error correction model, Seemingly Unrelated Regression, vector autoregression property price 1 – monetary policy
P. Ong (1998) USA California, 1993–1994 micro: survey by California’s Department of Social Services Tobit employment, employment 1, 0 –, – housing allowance, social housing
R. Ong et al. (2017) AUS 252 Australian LGAs, 2005–2014 macro: housing starts data for LGA units OLS construction 1 – land use
Oni (2008) NGA Lagos State, 1997–2007 micro: survey of Estate Surveyors; property pages of newspapers and magazines in Lagos metropolis ANOVA controlled rents 0 1 rent control
Orr (1968) USA 31 towns and cities in the metropolitan Boston region, 1960 macro: Massachusetts Federation of Taxpayers Association; Massachusetts Department of Commerce linear regression; OLS rent 0 – property tax
Orr (1970) USA 31 towns and cities in the metropolitan Boston region, 1960 macro: Massachusetts Federation of Taxpayers Association; Massachusetts Department of Commerce linear regression; 2SLS rent 1 – property tax
Ortiz-Villavicencio, Sánchez, and Fernández (2024) NZL Auckland, 2011–2016 micro: sales transactions data from ? difference-in-differences property price, property price of low-cost dwelling, property price of high-cost dwelling 0, -1, 1 –, –, – inclusionary zoning, inclusionary zoning, inclusionary zoning
Ostas (1976) USA 15 large SMASs of USA, 1965–1970 macro: credit term data from Federal Home Loan Bank Board News of Federal Home Loan Bank Board; Credit Manual of Commercial Laws from National Association of Credit Management and Consumer Credit Manual and Commerce Clearing House; Annual Report of the Federal Home Loan Bank Board from Federal Home Loan Bank’Board; long-term (10 year) U.S. government bond rates from Federal Reserve Bulletin of Federal Reserve System; monthly data on the number of building permits authorized for single-units dwellings by SMSA from Construction Reports of U.S. Department of Congress linear regression LTV, construction -1, -1 –, – usury ceilings, usury ceilings
O’Toole (2023) IRL Ireland, 2016–2019 macro: local electoral areas difference-in-differences, error correction controlled rents -1 2 rent control
O’Toole, Martinez-Cillero, and Ahrens (2021) IRL Ireland, 2007–2018 micro: 614,004 RTB registered tenancy agreements from Q3 2007 until Q3 2018 difference-in-differences fixed effects model controlled rents -1 2 rent control
Oust (2018a) NOR Norway, 1970–2011 micro: newspaper advertisements linear regression controlled rents 0 1 rent control
Oust (2018b) NOR Norway, 1970–2008 micro: newspaper advertisements panel regression search cost, misallocation 1, 1 1, 1 rent control, rent control
Overton and Rico (2020) FRA France, 2004–2015 micro: proprietary data from French Prudential Supervision Authority (ACPR) of Banque de France, containing 4,700,000 housing credit lines underwritten from 1994 to 2015 in France proportional hazard model panel model mortgage delinquency -1 – monetary policy
M. F. Owens and Baum (2009) USA USA, 1979–2002 micro: National Longitudinal Survey of Youth linear regression, logit employment 0 – housing allowance
Ozdamar and Giovanis (2017) GBR UK, 1991–2009 micro: household data from British Household Panel Survey probit panel-data model with fixed effects (life satisfaction approach) mental health 1 – housing allowance
Paciorek (2013) USA MSAs, 2005 macro: repeat-sales indices from Federal Housing Finance Agency; Consumer Price Index; mean house price in each city from 2000 Census; Wharton Residential Land Use Regulation Index instrumental variable; simulations volatility 1 – land use
Painter (2001) USA USA, 1984, 1991, 1992 micro: household data from Survey of Income and Program Participation linear regression employment, employment -1, -1 –, – housing allowance, social housing
Palmon and Smith (1998) USA 50 subdivisions of Houston (Texas), 1989 micro: data on sold single-family detached houses from Multiple Listing Service of Houston’s Board of Realtors non-linear hedonic regression property price -1 – property tax
Pankratz, Nelson, and Morrison (2017) CAN Waterloo region (Ontario), 2014 micro: survey of people experiencing chronic homelessness mixed model analyses of variance housing quality 1 – housing allowance
Park (2024) AUS, AUT, BEL, CAN, DNK, FIN, FRA, DEU, HUN, ITA, LVA, NLD, NZL, NOR, POL, SVN, ESP, SWE, CHE, GBR, USA 21 countries, 2016–2020 micro: Gallup World Poll; macro: OECD Social Expenditure Database and OECD Affordable Housing Database multilevel regression housing hardship of older adults, housing hardship of older adults -1, -1 –, – rent control, social housing
Parkhomenko (2018) USA USA, 1980–2007 macro: metropolitan area data on number of workers, wages, and housing prices from 5% samples of the Census and 3% sample of the American Community Survey; Wharton Residential Land Use Regulatory Index spatial equilibrium model; simulation inequality, property price, labor misallocation, output 1, 1, 1, -1 –, –, –, – land use, land use, land use, land use
Parolin (2021) USA USA, 2014–2018 macro: data on student homelessness for each public school district from Department of Education; access to cash assistance from University of Kentucky’s Center on Poverty Research database multilevel mixed-effects model with random effects homelessness -1 – TANF
Parra (2022) USA USA, 2006–2009 micro: court records from Public Access to Court Electronic Records system; foreclosure data from RealtyTrac; data on gender, race, address, judgment lien, real property records, bankruptcy information, personal business, and criminal filings from LexisNexis Public Records regression discontinuity design homeownership, foreclosure 1, -1 –, – bankruptcy protection, bankruptcy protection
Pavlov, Somerville, and Wetzel (2023) CAN British Columbia, 2015–2017 micro: transaction data from BC Ministry of Finance PTT information; BC Assessments property information difference-in-differences property price -1 – foreign-buyer tax
Pellegrino, Piacenza, and Turati (2011) ITA Italy, 2006 micro: household data from IT-SILC Survey; Bank of Italy Survey of Household Income and Wealth microsimulation inequality 1 – imputed rent tax
Peng, Liu, and Tian (2021) CHN 11 Chinese cities, ? macro: ? difference-in-differences property price 0 – talent housing policies
Pennell et al. (2022) USA New York City, 2013–2020 micro: energy audit dataset of 7,328 multifamily buildings greater than 50,000 square feet from Energy Efficiency Reports; data on properties receiving local, state, or federal housing subsidies from NYU Furman Center’s Subsidized Housing Database multivariate regression energy burden 0 – social housing
Peña and Ruiz-Castillo (1984) ESP Madrid, 1974 micro: survey of 4067 housing units in the Madrid Metropolitan Area hedonic regression; simulation model misallocation 1 1 rent control
Peterson (1974) USA Boston, 1971 micro: actual transaction price data on individual properties from ? hedonic regression property price 1 – land use
Petkova and Weichenrieder (2017) DEU all German Länder, 2003–2014 macro: state-level indices of property transactions and average purchase prices from GEWOS GmbH, Hamburg; Destatis panel-data model property sales, property price -1, 0 –, – transfer tax, transfer tax
Peydró et al. (2020) GBR UK, 2012–2018 micro: data on the universe of newly issued mortgages in the UK from PSD001 (Product Sales Database 001); stock of mortgages in the UK from PSD007 (Product Sales Database 007); balance sheet and income statement data from lenders; data on housing transactions from HM Land Registry’s Price Paid Data difference-in-differences LTI, lending to low-income borrowers, property price, default rate -1, -1, -1, -1 –, –, –, – LTI, LTI, LTI, LTI
Pfeiffer (2018) USA USA, 2001, 2004, 2008 micro: data on US residents age 15 and older living in a household, meaning they are not deployed in the military or living in institutionalized settings from Survey of Income and Program Participation linear regression, logit, propensity score matching health, health 1, 1 –, – housing allowance, social housing
Phaup and Hinton (1981) USA Schenectady County (New York), 1969–1976 macro: ? linear regression mortgage amount -1 – usury ceilings
Phillips and Goodstein (2000) USA 37 US cities, 1993–1996 macro: city level OLS property price 1 – land use
Pinto Hernández, Rodrı́guez Iglesias, and Moreno Adalid (2025) ESP Catalonia, Madrid, Andalucía, Aragón, Asturias and Valencia, 2019–2024 micro: rental prices from Observatorio del Alquiler; macro: regional-level GDP data from Bank of Spain; Consumer Price Index data from Spanish National Institute of Statistics (INE) and Bank of Spain difference-in-differences controlled rents 0 2 rent control
Plassmann and Tideman (2000) USA 219 Pennsylvania municipalities, 1972–1994 macro: building permits from Bureau of the Census Markov chain Monte Carlo method construction 1 – split-rate tax
Poghosyan (2020) AUT, BEL, BGR, HRV, CYP, CZE, DNK, EST, FIN, FRA, DEU, GRC, HUN, IRL, ITA, LVA, LTU, LUX, MLT, NLD, POL, PRT, ROU, SVK, SVN, ESP, SWE, GBR 28 EU countries, 1990–2018 macro: lending restriction measures in the EU from Budnik and Kleibl (2018) local projections method property price, property price, loan growth, loan growth -1, -1, -1, -1 –, –, –, – DSTI, LTV, DSTI, LTV
Polat and Dogruel (2015) TUR Turkey, 2010–2014 macro: ? DSGE property price, property price 0, 0 –, – monetary policy, macroprudential policy
Pollakowski (1997) USA New York City, 1993 micro: NYCHVS data hedonic regression mobility -1 2 rent control
Pollakowski (2003) USA Cambridge (Massachusetts), 1993–1998 micro: set of all building permits issued in Cambridge; record of rent-controlled buildings in the city; database of all properties within the city from the city’s Residential Property Assessor linear regression housing quality, construction -1, -1 1, 1 rent control, rent control
Pollakowski et al. (2022) USA USA, 1997–2005 micro: data from Census Bureau, including administrative files and censuses, from HUD’s Public and Indian Housing Information Center linear regression, panel-data model lifetime earnings, lifetime earnings, adult incarceration, adult incarceration, adult employment, adult employment 1, 1, -1, -1, 1, 1 –, –, –, –, –, – social housing, housing allowance, social housing, housing allowance, social housing, housing allowance
Pollakowski and Wachter (1990) USA Montgomery county (Washington DC), 1982–1987 micro: housing and land data, land-use constraints are the Montgomery County Planning Board OLS property price 1 – land use
Poterba, Weil, and Shiller (1991) USA 39 US cities and regions, 1980–1989 macro: per capita income from Census Bureau; age structure from March Current Population Survey; quality-adjusted house prices and federal marginal tax rate at which households can deduct mortgage interest and property taxes from National Association of Realtors; repeat sales price index from Case-Shiller database; expected inflation rate from NBER linear regression, panel-data model property price 0 – mortgage deduction
Prentice and Scutella (2020) AUS Australia, 2011–2014 micro: data from nationally representative longitudinal survey of a sample of welfare recipients Journeys Home; Household, Income and Labour Dynamics in Australia (HILDA) survey quasi-experimental approach (econometrics of program evaluation) physical health, mental health, incarceration, employment, education 0, 0, 0, 0, 0 –, –, –, –, – social housing, social housing, social housing, social housing, social housing
Preston and Reina (2021) USA Philadelphia (Pennsylvania), 2009–2017 micro: multifamily properties with 5 or more rental units panel-data model eviction -1 – social housing
Qiu, Lyu, and Tian (2024) CHN 69 large and medium-sized cities in China, 2001–2016 macro: regional innovation indicator from “FIND Report on City and Industrial Innovation in China (2017)”; average wage, disposable income per capita, local housing prices, personal income levels, housing expenditure, personal intentions toward long-term residency, willingness to transfer hukou, structural economic composition, financial loans, foreign direct investment, real GDP per capita, financial expenditures on science from Macroeconomic and Real Estate Database of the State Information Center staggered difference-in-differences property price 1 – talent housing policies
Quayes (2010) USA USA, 1971–2006 macro: data on housing sales and median house sale prices from Census Bureau; data on personal income, CPI and mortgage interest rates from St. Louis Federal Reserve Bank linear regression property sales -1 – capital gains tax
John M. Quigley (1990) USA 50 US cities, 1984 macro: HUD survey of homelessness in 60 metropolitan areas linear regression homelessness 0 – rent control
John M. Quigley, Raphael, and Rosenthal (2008) USA 86 cities in the San Francisco Bay Area, 2000 micro: online survey of builders and developers hedonic regression (OLS, instrumental variable) rent, property price 1, 1 –, – land use, land use
John M. Quigley and Raphael (2005) USA 407 cities in California, 1990–2000 macro: regulation measures from survey of California land-use officials; micro: household data from Census Public Use Microdata Samples hedonic regression property price, construction 1, -1 –, – land use, land use
Rabiega, Lin, and Robinson (1984) USA Portland, 1963–1978 micro: property data from Housing Authority of Portland linear regression property price 1 – social housing
Rahal (2016) CAN, CHE, JPN, NOR, SWE, GBR, USA, Euro Area 8 OECD countries, 2007–2014 macro: GDP, retail sales, industrial production, investment in private dwellings, CPI from OECD; house price, mortgage rates from Oxford Economics panel vector autoregression property price, housing investment 1, 1 –, – unconventional monetary policy, monetary policy
Rapaport (1992) USA New York City, 1981–1987 micro: 1981, 1984, and 1987 New York City Housing and Vacancy Surveys OLS vacancy 0 2 rent control
Rappoport (2019) USA 269 US metropolitan areas, 2017–2018 micro: individual-level mortgage origination records from McDash Analytics; income information from Federal Financial Institutions Examination Council, Home Mortgage Disclosure Act (Public Data); macro: tax return statistics by income group from the ZIP Code Data from IRS, Statistics of Income Division; data on house price indices from SandP Dow Jones Indices LLC TAXSIM simulation property price -1 – property tax
Reeves et al. (2016) GBR UK, 2009–2013 micro: data on individuals from Annual Population Survey difference-in-differences mental health 1 – housing allowance
Reina and Kontokosta (2017) USA New York City, 2013 micro: data on all large multifamily properties larger than 4500 m2 from Subsidized Housing Information Project; building characteristics data, including building size, building age, and whether and when a building was last altered, among others features, from New York City Department of City Planning’s Primary Land Use Tax Output multivariate regression energy consumption, energy consumption 1, 1 –, – social housing, housing allowance
Reingold (1997) USA Chicago, 1986 micro: Urban Poverty and Family Life Survey logit regression employment 0 – social housing
Reingold, Van Ryzin, and Ronda (2001) USA Atlanta, Boston, Detroit, Los Angeles, 1992–1994 micro: household data from Multi-City Study of Urban Inequality structural equation model social capital, employment 0, 0 –, – social housing, social housing
Reitsma (2022) NLD Rotterdam, 2021–2022 micro: data from advertisement website Funda.nl difference-in-differences time on market, property price 0, 0 –, – housing rationing, buy-up protection
Riccio and Orenstein (2003) USA Atlanta, ? micro: administrative data ? employment, earnings 0, 0 –, – social housing, social housing
Ricks (2021) USA USA, 1960 micro: sample of white men, born between 1923Q1–1932Q4 from Census Microdata local-linear regression marriage, homeownership 1, 1 –, – loan guarantee, loan guarantee
Riley (2012) USA USA, 1998–2004 macro: zip-code-level house price estimates from Fannie Mae; micro: proprietary mortgage origination data for a representative sample of low-income US homeowners who received community reinvestment mortgages from Community Advantage Program linear mixed-effects models volatility, risk 1, 1 –, – land use, land use
Robertson, Dejean, and Suire (2021) FRA Bordeaux, 2016–2020 micro: Airbnb listings difference-in-differences, spatial discontinuity design reservation days, number of nights -1, -1 –, – housing rationing, housing rationing
Robins (1974) USA 77 SMSAs of USA, 1970 macro: housing starts from National Association of Homebuilders; personal income from Survey of Current Business; index of comparative living costs for an intermediate budget from Bureau of Labor Statistics; population levels from U.S. Bureau of the Census; housing prices-value of single-family owner-occupied housing from Census of Population and Housing OLS homeownership -1 – usury ceilings
Robstad (2018) NOR Norway, 1994–2013 macro: GDP, inflation, credit, exchange rate, house prices, interest rate from Statistics Norway, Norges Bank, Eiendomsmeglerforetakenes forening, Finn.no, Eiendomsverdi Bayesian structural VAR model property price 1 – monetary policy
Roistacher (1992) USA New York City, 1987 micro: New York City Housing and Vacancy Survey hedonic regression misallocation 1 2 rent control
Rosen (1989) USA USA, 1970–1988 macro: national and state level time series model, cross-section regression, simulation homeownership 1 – mortgage deduction
Rosenberg et al. (2020) FIN Finland, 2009–2018 macro: GDP, HICP, house prices, building permits per capita, mortgage interest rates, monetary policy rate, central bank’s total assets per capita from structural vector autoregression (SVAR) property price, property price 1, 1 –, – monetary policy, unconventional monetary policy
Ross, Shlay, and Picon (2012) USA USA, 2009 micro: American Housing Survey ordered logit satisfaction, neighborhood quality, housing quality 1, -1, 1 –, –, – housing allowance, housing allowance, housing allowance
Jonathan T. Rothwell (2009) USA 50 MSAs, 1990, 2000 and 2009 macro: population density, median home price, median rent, % manufacturing, and rural housing units from US Census; Wharton Land Regulation Index, Density Restriction index from Gyourko, Saiz, and Summers (2008); Average Permitted Density from Pendall, Puentes, and Martin (2006); Wharton Index 1990 and State Regulatory Index from Malpezzi (1996) OLS; instrumental variable; 2SLS property price 1 – land use
Jonathan T. Rothwell and Massey (2009) USA 49 largest MSAs, 1980–2000 macro: metropolitan regions data from ? OLS, 2SLS segregation 1 – land use
Roudnitski and Sarkar (2025) AUS Sydney, 2019–2023 micro: property-level data from InsideAirbnb; macro: median weekly rent from Department of Communities and Justice NSW; number of rental bonds from Department of Families fairness and housing Victoria; school-level data from Australian Curriculum, Assessment and Reporting Authority; LGA-level crime data from NSW Bureau of Crime Statistics and Research and Crime Statistics Agency Victoria; SA2-level data on economic resource from Australian Bureau of Statistics difference-in-differences rent 1 – housing rationing
Roy, Anderson, and Schmidt (2006) USA USA, 1994–2003 macro: Statistics of Income Bulletin; U.S. Housing Market Conditions of U.S. Department of Housing and Urban Development; Federal Reserve Bulletin of Board of Governors of the Federal Reserve System; Bureau of Labor Statistics; Bureau of Economics Analysis multi-equation model, time series model property sales, property sales -1, 1 –, – property tax, mortgage deduction
Rubaszek, Stenvall, and Uddin (2025) CAN, GBR, USA, SWE, NOR, AUS, NZL, CHE, DEU 9 OECD member states, 1996–2019 macro: rent control index from Konstantin A. Kholodilin (2020), macroeconomic data from FRED, OECD, Fed Dallas, SECO interacted panel VAR volatility, volatility 0, 0 –, – rent control, eviction protection
Ruiz and Vargas-Silva (2016) USA USA, 1963–2011 macro: real GDP per capita, real private consumption per capita, real government expenditures per capita (spending, defined as government consumption expenditures and gross investment), government revenues (revenue, defined as government current receipts), real non-residential investment, federal funds rate, real adjusted reserves, house prices, GDP deflator, housing activity from Bureau of Economic Analysis, Census Bureau, Board of Governors of the Federal Reserve System vector autoregression property price, housing investment, construction 0, -1, -1 –, –, – fiscal policy, fiscal policy, fiscal policy
Rydell and Neels (1985) USA Los Angeles, 1979–1990 macro: city level simulation model housing quality, controlled rents -1, -1 2, 2 rent control, rent control
Sá and Wieladek (2010) USA USA, 1979–2006 macro: data on interest rates, GDP, ROW variables, and CPI from Pesaran, Schuermann, and Smith (2009); data on household consumption expenditure from IMF International Financial Statistics; data on private residential investment from Federal Reserve Economic Data; data on national house price index from Federal Housing Finance Agency vector autoregression property price 1 – monetary policy
Sagalyn and Sternlieb (1972) USA New Jersey, 1970–1971 ? ? property price 1 – land use
Sagner and Voigtländer (2023) DEU Berlin, 2016–2020 micro: rental and purchase asking price data on a dwelling level by Value AG difference-in-differences value, supply, controlled rents 0, -1, -1 1, 1, 1 rent control, rent control, rent control
Sai (2022) USA all counties in Indiana and bordering counties, 1998–2006 macro: House Price Indices for single-family dwellings from Federal Housing Finance Agence; National Historical Geographic Information System; Integrated Public Use Microdata Series event study; difference-in-differences property price, property price -1, 0 –, – property tax, property tax
Saks (2008) USA 82 metropolitan areas, 1980–2000 macro: Wharton Urban Decentralization Project, Regional Council of Governments survey, International City Management Association survey, Fiscal Austerity and Urban Innovation survey, National Register of Historic Places, American Institute of Planners panel-data model with fixed effects, vector autoregression property price, employment, earnings, construction 1, -1, 1, -1 –, –, –, – land use, land use, land use, land use
Salvi and Syz (2011) CHE 2571 Swiss municipalities, 1998–2008 macro: municipal data from ? count regression green construction 0 – green subsidy
Sánchez and Andrews (2011) AUS, AUT, BEL, CHE, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, GRC, HUN, IRL, ISL, ITA, LUX, NLD, NOR, POL, PRT, SVN, SWE, USA 25 OECD countries, 2007 micro: household data from EU Statistics of Income and Living Conditions probit model mobility -1 – rent control
Santolini (2023) ITA 6458 Italian municipalities, 2001–2007 macro: municipal data on divorces and marital separations from Istat OLS; instrumental variable divorce, marital separation 1, 1 –, – property tax, property tax
Saraswat (2021) USA USA, 1995–2000 micro: data on labor market outcomes and self-reliance comes from publicly available 5% sample of the 2000 census; housing data from States Department of Housing and Urban Development; macro: qualified census tract data from public use micro area OLS; 2SLS labor force participation, employment, income 1, 1, 1 –, –, – social housing, social housing, social housing
Sayag and Zussman (2020) ISR Jerusalem, 2005–2011 micro: apartment data from rental notices collected by a private company from Internet sites, newspapers, etc. hedonic regression, difference-in-differences rent 1 – housing allowance
Schapiro et al. (2022) USA New Haven (Connecticut), 2017–2019 micro: household data from JustHouHS ANOVA, generalized estimating equations housing stability, housing stability, housing quality, housing quality, housing autonomy, housing autonomy, housing affordability, housing affordability 1, 1, 1, 1, 1, 1, 1, 1 –, –, –, –, –, –, –, – housing allowance, social housing, housing allowance, social housing, housing allowance, social housing, housing allowance, social housing
Schmidt (2022) NLD Netherlands, 2010–2019 micro: data from DNB Household Survey heterogeneous agents model mobility, homeownership -1, -1 –, – transfer tax, transfer tax
Schneider and Wrede (2023) DEU German Länder, 2007–2014 macro: municipality-level data from Destatis; micro: individual-level data from SOEP spatial regression discontinuity design, panel-data model mobility, homeownership -1, 0 –, – transfer tax, transfer tax
Schnier and Trounstine (2018) USA 232 US metro areas, 1970 and 2011 macro: conjoint survey experiment on Amazon’s Mechanical Turk platform, 1970 Census of Population and Housing and the 2011 American Community Survey OLS, instrumental variable segregation 1 – land use
Schone (1994) USA USA, ? micro: data on single mothers from Survey on Income and Program Participation multiple-equation system, simulation employment -1 – social housing
Schuetz (2009) USA Massachusetts, 2000–2005 macro: regulation measures from Local Housing Regulation Database; data on rents, prices, and building permits from Census; city council from MA Department of Housing and Community Development instrumental variable construction -1 – land use
Schuetz (2007) USA Massachusetts, 2000–2005 macro: regulation measures from Local Housing Regulation Database; data on rents, prices, and building permits from Census; city council from MA Department of Housing and Community Development OLS construction -1 – land use
Schuetz, Meltzer, and Been (2011) USA San Francisco and Suburban Boston Areas, macro: survey conducted in 2002 by the California Coalition for Rural Housing and the Nonprofit Housing Association of California; supplementary telephone survey in 2007 with municipal officials in approximately 35 jurisdictions by Furman Center; data on inclusionary zoning in Massachusetts from Local Housing Regulation Database panel-data model property price, construction 1, 0 –, – inclusionary zoning, inclusionary zoning
A. Schwartz (1999) USA New York City, 1987–1997 macro: community-district level data from Department of Housing Preservation and Development descriptive vacancy, crime -1, -1 –, – social housing, social housing
A. E. Schwartz et al. (2006) USA New York City, 1987–2000 micro: data on housing project from Department of Housing Preservation and Development difference-in-differences neighborhood quality 1 – social housing
S. I. Schwartz, Hansen, and Green (1981) USA Petaluma, Rohnert Park, and Santa Rosa (California), 1969–1977 micro: home sales data from ? randomized controlled experiment, linear regression property price 1 – land use
A. E. Schwartz et al. (2020) USA New York City, 2005–2011 micro: data on 88,000 school-age voucher recipients and longitudinal public school records from HUD, New York City Department of Education (NYCDOE), New York City Department of Finance (NYCDOF), New York City Department of Buildings, and American Community Survey (ACS) panel-data model with fixed effects children’s outcomes 1 – housing allowance
Schwegman and Yinger (2020) USA New York City, Buffalo, and Rochester, 1975–1994 micro: housing unit data from American Housing Survey; macro: historical city-level property tax rates from New York City Department of Finance, property assessment offices of Buffalo and Rochester panel data model rent 1 – property tax
Schweitzer et al. (2023) USA New York City, 1991, 1993,…, 2017 micro: home data from New York City Housing and Vacancy Survey Bayes regularization, multivariate analysis of variance, multivariate multiple regression model housing quality, housing quality, housing quality -1, -1, -1 1, 2, – rent control, rent control, housing allowance
Segal and Srinivasan (1985) USA 51 metropolitan areas, 1975–1978 macro: average sales prices data from Federal Home Loan Bank Board 2SLS, simultaneous equations model property price 1 – land use
Segú (2020) FRA France, 1995–2005 micro: data on 30 million housing units from FIchier des LOgements par COMmune difference-in-differences, propensity score matching vacancy -1 – vacancy tax
Seiler, Siebert, and Yang (2023) USA Irvine (California), ? micro: ? ? rent -1 – housing rationing
Seko (2019) JPN Japan, 1980–2006 micro: Keio Household Panel Survey proportional hazard model mobility, mobility -1, -1 2, 2 rent control, eviction protection
Seko and Sumita (2007a) JPN Japan, 1980–2006 micro: household longitudinal data from Keio Household Panel Survey hazard model mobility, mobility -1, -1 –, – eviction protection, capital gains tax
Seko and Sumita (2007b) JPN Japan, 2004–2006 micro: 3 waves of Japanese household longitudinal data (Keio Household Panel Survey, KHPS) covering all of Japan conditional logit; hedonic regression net welfare 1 2 eviction protection
Seltzer (2024) USA 45 US municipalities, 2002–2018 macro: number of repair violations from various municipal governments; LTV ratios, interest rates, number of units per building, building ages, Zillow index, DSCR, occupancy rates from Real Capital Analytics panel-data model; difference-in-differences maintenance -1 2 rent control
SEO (2025) NLD Netherlands, 2013–2023 micro: housing situation of households from CBS; macro: financing burden percentage from Nibud, DNB difference-in-differences; simulation property price, probability to buy, property price, probability to buy -1, -1, -1, -1 –, –, –, – LTI, LTI, LTV, LTV
Seo and Park (2021) KOR South Korea, 2007–2018 micro: household data from Korean Welfare Panel Study logit food security, food security -1, 1 –, – social housing, housing allowance
Severen and Plantinga (2018) USA coastal area of Southern California, 1989–2014 micro: data on all recent commercial multifamily real estate transactions in coastal Southern California spatial regression discontinuity design, spatial difference-in-differences rent income, property price 1, 1 –, – land use, land use
Shaefer et al. (2020) USA USA, 2001–2015 micro: household-level data from Current Population Survey; macro: counts of cash assistance cases from Center on Budget and Policy Priorities; the number of families with children below poverty from Current Population Survey; number of homeless students from National Center for Homeless Education logit homelessness -1 – TANF
Shan (2010) USA USA, 1992–2004 micro: household-level panel data from Health and Retirement Study instrumental variable elderly mobility 1 – property tax
Shan (2011) USA 16 affluent towns within the Boston metropolitan area, 1982–2008 micro: transaction data on single-family houses from Warren Group difference-in-differences property sales -1 – capital gains tax
Shang and Saffar (2023) USA US states, 1984–1999 micro: household mortgage debt data from SIPP; macro: adoption by states of wrongful discharge laws (good faith, implied contract, and public policy) difference-in-differences mortgage amount 1 – job protection
Shanks (2021) USA 341 towns of Massachusetts (USA), 2021 micro: single-family houses data from Massachusetts Standardized Assessors’ Parcels database; land use data from MassGIS; demographic and housing attribute data from US Census Bureau at the block level; Bilateral travel times between all block group pairs from Open Source Routing Machine; school district quality from Niche.com and ClearGov.com; macro: bylaw documents from various municipalities’ websites natural language processing (dictionary method, sentiment analysis, Latent Dirichlet Allocation); spatial regression discontinuity design supply, property price, land-plot size -1, 1, -1 –, –, – land use, land use, land use
Sheffrin and Turner (2001) USA USA, 1985–1995 micro: household-level data from American Housing Survey GARCH-M; simulation volatility, user cost, welfare -1, 1, -1 –, –, – capital gains tax, capital gains tax, capital gains tax
Shertzer, Twinam, and Walsh (2018) USA Chicago, 2000–2012 macro: Chicago Metropolitan Agency for Planning’s 2005 land use inventory; Environmental Protection Agency’s Toxics Release Inventory; Chicago’s 2012 zoning classification map; block-level demographic data from the 2000 US census; transaction prices for single-family homes in Chicago for the years 2000–2012 from DataQuick Information Systems; Chicago Zoning Board’s 1922 land use survey; maps of Chicago’s 1923 zoning ordinance; enumeration district-level demographic data aggregated from the 1920 US Census linear regression; spatial discontinuity design separation of uses 1 – land use
Shinn et al. (1998) USA New York City, 1988 and 1993 micro: family data from interviews logit homelessness, homelessness -1, -1 –, – housing allowance, social housing
Shlay and Rossi (1981) USA Chicago metropolitan area, 1960–1970 macro: census tract data linear regression segregation, homeownership 0, 1 –, – land use, land use
Shulman (1981) USA Santa Monica (California), 1970–1978 macro: median prices descriptive analysis value, controlled rents -1, -1 1, 1 rent control, rent control
Silveira and Malpezzi (1991) BRA Metropolitan region of Rio de Janeiro, 1980 micro: Household Survey Data linear regression; simulation model profitability, profitability, controlled rents -1, -1, -1 1, 1, 1 eviction protection, housing rationing, rent control
Simmons and Kovacs (2018) USA towns Moore and Norman (Oklahoma), 2012–2015 micro: Multiple Listing Services data from Midwest City-Dell CityMoore Board of Realtors and MLS OK Inc.; new building permits from the cities of Moore and Norman; macroeconomic data from the Bureau of Labor Statistics, Bureau of Economic Analysis; mortgage interest rates from Federal Home Loan Mortgage Corporation difference-in-differences property price, construction 0, 0 –, – building code, building code
Simmons-Mosley and Malpezzi (2006) USA New York City, 1991, 1993, 1996, and 1999 micro: New York City Housing and Vacancy Surveys logit model; survival model; proportional hazard model mobility -1 2 rent control
Simon and Toussaint (2025) FRA Lille, Brest, Clermont-Ferrand, Dijon, Nancy, Nantes, Nice, Orleans, Rennes, Rouen, Saint-Etienne, Toulon, Toulouse, Tours, 2018–2022 micro: data on gross rents from CLAMEUR; data on notarial housing transactions from DV3F mass appraisal model; generalized additive model; decision tree; difference-in-differences controlled rents, controlled rents for big dwellings, capital gains, controlled housing returns 0, 1, -1, 1 2, 2, 2, 2 rent control, rent control, rent control, rent control
Sims (2007) USA Boston, 1985–1998 micro: MSA data from the American Housing Survey difference-in-differences housing quality, conversion, controlled rents, construction -1, 1, -1, 0 1, 1, 1, 1 rent control, rent control, rent control, rent control
Sims (2011) USA Cambridge, 1985–1998 micro: demographic data from the 1990 and 2000 census records for all census tracts in Cambridge and the nearby Middlesex County communities; city administrative records; American Housing Survey’s Boston metropolitan sample first-difference regression segregation 1 1 rent control
Sinai and Waldfogel (2005) USA USA, 1970, 1980, 1990 macro: Census place and MSA-level data from the decennial census and from the Department of Housing and Urban Development linear regression supply, supply 1, 1 –, – housing allowance, social housing
Singell and Lillydahl (1990) USA Loveland (Colorado), 1983–1985 micro: data on home sales from Issues of Mortgage Banking; National Association of Realtors, Economics and Research Division; McGraw Hill Information Systems Company, Construction Information hedonic regression, OLS property price -1 – impact fee
D. Singh (2019) USA New York City, 2006–2008 unknown unknown rent, gentrification, construction -1, -1, -1 –, –, – property tax, property tax, property tax
B. Singh (2020) IND 33 Indian cities, 2010–2019 macro: city-level data on house price indices, mortgage interest rates, mortgage loans, construction costs, GDP deflator from Reserve Bank of India; National Housing Bank; UN Population Statistics database Arellano-Bond dynamic panel-data model property price -1 – LTV
Skak and Bloze (2013) DNK Denmark, 2004 micro: 20% sample of the rental market hedonic regression uncontrolled rents, controlled rents 1, -1 1, 1 rent control, rent control
Skidmore and Peddle (1998) USA DuPage County (Illinois), 1977–1992 macro: data on new homes, municipal finances, impact fees, and other municipal characteristics from State Wide Summaly of Municipal Finances in Illinois, Illinois Counties and Incorporated Municipalities, and interviews with authorities from each of the municipalities panel data model with fixed effects construction -1 – impact fee
Slemrod, Weber, and Shan (2017) USA D.C., 1999–2010 micro: all residential housing transactions from CoreLogic; D.C. Office of Tax Revenue difference-in-differences welfare 0 – transfer tax
Slintáková and Klazar (2018) AUT, BEL, DNK, FIN, FRA, DEU, ITA, IRL, LUX, NLD, PRT, ESP, SWE, GBR 14 EU countries, 2004–2013 macro: data on GDP and financial worth, mortgage interest payment as a portion of household income, young and old dependency ratios from HYPOSTAT; OECD; EUROSTAT; ILO panel data model with fixed effects household leverage 0 – mortgage deduction
Smith (1988) CAN Ontario, 1975–1986 macro: CMHC Toronto Office “Rental Apartment Vacancy Survey” descriptive before-and-after comparison uncontrolled rents, housing quality, homeownership, controlled rents, construction 1, -1, 1, -1, -1 2, 2, 2, 2, 2 rent control, rent control, rent control, rent control, rent control
Smith and Tomlinson (1981) CAN Ontario, 1975–1980 macro: Teela Reports Apartment Surveys; CMHC Toronto Office “Rental Apartment Vacancy Survey” descriptive before–and–after comparison vacancy, homeownership, construction -1, 1, -1 2, 2, 2 rent control, rent control, rent control
Smolders (2010) BEL 588 Belgian communities, 1997–2007 macro: ? panel-data model construction -1 – gift tax
Somerville, Wang, and Yang (2020) CHN Chengdu, Guangzhou, Hefei, and Qingdao, 2009–2012 macro: aggregated transaction data from Chinese Real Estate Index System difference-in-differences property sales, property price -1, 0 –, – foreign-buyer tax, foreign-buyer tax
Sommer and Sullivan (2018) USA USA, 1975–2009 macro: autocorrelation coefficient from Panel Study of Income Dynamics; average selling costs for housing from Consumer Expenditure Survey; median property tax rate from American Community Survey; median wage from Current Population Survey simulation; SMM welfare, property price, mortgage amount, homeownership -1, 1, 1, -1 –, –, –, – mortgage deduction, mortgage deduction, mortgage deduction, mortgage deduction
J. Song (2021) USA USA, 2009–2019 macro: index of minimum lot sizes applied to single-family homes based on structural breaks in constructed lot sizes by zoning district and Census Block Group levels from CoreLogic Tax Assessor data boundary discontinuity design property price, rent, segregation 1, 1, 1 –, –, – land use, land use, land use
Y. Song et al. (2021) CHN Chinese cities, 2015 macro: green building map in China and local government websites; GDP per capita, city fiscal revenue, real estate investment, proportion of urban college graduates from China City Statistical Yearbooks; regulations and policies from multiple governmental websites (including both provincial and municipal Bureau of Housing and Planning Bureau websites) and web search using Baidu negative binomial regression green construction, green construction 1, 1 –, – green building standards, green subsidy
Y. Song and Zenou (2006) USA US cities, 2000 macro: data on size of urbanized areas, population, income, agricultural rent, commuting cost, property tax from US Census; data on state aid to schools from National Center for Education Statistics OLS, instrumental variable, 2SLS urban sprawl -1 – property tax
Spader, Schuetz, and Cortes (2016) USA Cleveland, Chicago and Denver, micro: property-level data on the location, activity type, and timing of NSP activities from HUD; macro: crime data from local police department difference-in-differences crime -1 – neigbhorhood stabilization
Speyrer (1989) USA Houston (Texas), ? micro: ? hedonic regression property price 1 – land use
Splinter (2019) USA USA, 1964–2016 macro: national data from Bureau for Economic Analysis time series model business cycle 1 – mortgage deduction
Sridhar (2010) IND 50 India’s major urban agglomerations, 1981 and 1991 macro: data on land area and population of the central city (defined as the municipal corporation limits of the city) and the UA from Census of India; data on household income from National Council of Applied Economic Research; data on regulations pertaining to the maximum FARs constructed by authors using Internet and assistance of the Ministry of Urban Development density gradients; linear regression urban sprawl -1 – land use
Stacy and Davis (2022) USA Alexandria (Virginia), 2000–2020 micro: administrative data from the city of Alexandria about multifamily affordable housing developments that began assistance between 2000 and 2020 and sales data from the Zillow Transaction and Assessment Dataset (ZTRAX) - properties that were sold more than once linear regression, repeat sales model property price 1 – social housing
Stacy et al. (2023) USA USA, 2000–2017 macro: US newspaper articles; data on per-city counts of addresses from US Postal Service; data on demographics, rents, and units affordable to households of different incomes from US Census machine learning; panel data model supply, rent -1, 1 –, – land use, land use
Stacy et al. (2025) USA 27 metropolitan areas, 2000–2021 macro: text-based rent control index extracted from NewsBank database; micro: Census microdata on affordable housing units; Section 8 income data from 2000 Decennial Census and 5-year American Community Survey machine learning; difference-in-differences; panel data model rental housing supply, cheap rental housing supply, high-price rental housing supply -1, 1, -1 –, –, – rent control, rent control, rent control
Stanga, Vlahu, and Haan (2020) AUS, BEL, BRA, CAN, CZE, DNK, ESP, FRA, GBR, GRC, HKG, HUN, IRL, ITA, MEX, MYS, NLD, PHL, POL, PRT, ROU, SWE, SGP, SVK, THA, USA 26 countries, 2000–2014 macro: unemployment comes from World Bank World Development Indicators; data on house prices from Bank for International Settlements and European Mortgage Federation; spread between the long-term government bond yield and the rate of treasury bills from IMF International Financial Statistics and FRED Economic Data; macro-prudential policy index from Cerutti, Claessens, and Laeven (2017); index of institutional quality based on five selected indicators of institutional quality which capture judicial efficiency, bankruptcy regulation and property protection from World Bank’s Doing Business database; data on loan type (fixed vs. variable mortgage rate), average maturity (in years), bank funding type (retail vs. other sources such as covered bonds or securitization), and degree of lender recourse (full recourse vs. no or partial recourse) comes from Cerutti, Dagher, and Dell’Ariccia (2017) and European Mortgage Federation; data on tax deductibility of interest payments from Cerutti, Dagher, and Dell’Ariccia (2017) and International Bureau of Fiscal Documentation panel-data regression mortgage arrears, mortgage arrears, mortgage arrears, mortgage arrears -1, -1, -1, -1 –, –, –, – macroprudential policy, LTV, bankruptcy protection, property regulation
Sternlieb and Hughes (1980) USA Fort Lee, 1970–1977 macro: valuations by land-use category from Fort Lee Assessors Office descriptive analysis value, tax base -1, -1 2, 2 rent control, rent control
St. John (1990) USA Alameda county (California), 1970–1988 micro: apartment building sales hedonic regression value, value 0, -1 2, 1 rent control, rent control
Stohs, Childs, and Stevenson (2001) USA Orange and Sacramento counties (California), DuPage County (Illinois), and areas of Boston (Massachusetts), 1995–2000 macro: tract-level data from Census Bureau by Census Tract; micro: real estate transaction data from American Real Estate Solutions linear regression mobility 1 – property tax
Stoloff (2002) USA USA, 1986–1993 micro: Panel Study of Income Dynamics; 1990 Decennial Census event history analysis of transitions; propensity score matching; logit unemployment 1 – social housing
Struyk (1988) JOR Jordan, 1986 micro: national housing survey (current housing unit, length of tenure, occupant, economic activity, household expenditure) with 2300 observations linear regression vacancy, net welfare 1, -1 1, 1 rent control, rent control
Su et al. (2018) CHN China, 2001–2016 macro: short-term international capital flows from China Economic Information Network, housing prices from Research and Set database, M2 from PBOC, GDP, industrial added value from Wind database continuous wavelet method property price 1 – monetary policy
Suher (2016) USA New York City, 2012–2015 micro: data on individual New York City property tax bills; data on assessed values and building and unit characteristics from New York City Department of Finance Real Property Assessment Database; sales prices from New York City Department of Finance Automated City Register Information System difference-in-differences non-resident owners -1 – second-home tax
W. Sun et al. (2017) CHN Beijing, 2005–2011 micro: resale and rental transaction datasets from broker company WoAiWoJia regression discontinuity design rent transaction volume, rent, property sales, property price, price-to-rent ratio 0, 0, -1, -1, -1 –, –, –, –, – home purchase restriction, home purchase restriction, home purchase restriction, home purchase restriction, home purchase restriction
C.-Y. Sun et al. (2019) TWN Taiwan, 2010–2018 micro: 37 cases of residential buildings with green building certification and 36 cases of general residential buildings from government public information websites and architectural professional magazines descriptive analysis construction cost 1 – green building standards
Sung and Kim (2023) KOR 58 municipalities in Seoul Metropolitan Area, 2020–2022 macro: municipalities panel-data model uncontrolled rents, rent -1, 1 2, – rent control, monetary policy
Surico and Trezzi (2019) ITA Italy, 2010–2012 micro: Survey on Households Income and Wealth linear regression consumer spending -1 – property tax
Susin (2002) USA 108 MSAs, 1993 micro: American Housing Survey hedonic regression rent 1 – housing allowance
Susin (2005) USA USA, 1996–1999 micro: SIPP combined with administrative data on housing assistance receipt propensity score matching household size, earnings -1, -1 –, – housing allowance, housing allowance
Svarer, Rosholm, and Munch (2005) DNK Denmark, 1997–2000 micro: 10% random sample of the Danish adult population (demographic, socioeconomic, and physical characteristics) competing risks duration model mobility -1 1 rent control
Szumilo and Vanino (2021) GBR Greater London Authority, 2013–2017 macro: postcode-level data on mortgage lending by banks from UK Finance; data on Help To Buy mortgages from Department for Communities and Local Government; data on all transactions of residential dwellings from Land Registry panel data model; regression discontinuity design; spatial discontinuity loan growth 1 – homeowner subsidy
R. Tan (2021) USA Manhattan (New York City), 1989–2000 micro: complaints received by the Department of Housing Preservation and Development and the Department of Buildings and building information scraped from NYC public databases regression discontinuity; difference-in-differences housing quality -1 2 rent control
Y. Tan, Wang, and Zhang (2020) CHN 25 cities in China, 2002–2012 micro: data on residential land sales from official listings posted on www.landlist.cn; data on residential development projects that had new property for sale as of May 2012 from www.Soufun.com 2SLS; panel-data regression supply, property price -1, 1 –, – land use, land use
Teitz (1994) USA 7 Californian cities, 1970, 1980, and 1990 macro: US Census data at city level descriptive analysis mobility, homeownership, controlled rents -1, 1, -1 1, 1, 1 rent control, rent control, rent control
Thiel and Zaunbrecher (2023) NLD Netherlands, 2015–2019 micro: register data with demographic information about every person registered at a Dutch muncipality from Gbapersoontab; register data with information about the household that a person belongs to, his position in the household, and start and end date of the household from Gbahuishoudensbus; register data about the incomes of all households from Inhatab; register data about the wealth of all households from Vehtab; register data with address information for all persons from GBAADRESOBJECTBUS; coordinates for each house in the Netherlands from Vslcoordtab; register data with property values of all houses from Eigendomwozbagtab; register data with the type of property (rental or owner-occupied) and type of owner (Own house, Housing association, Other landlord) from Eigendomtab; register data about the life-cycle of houses with information about usage, size, date of modification, and year of construction of houses from Levcyclwoonnietwoonbus; register data on energy and gas usage of houses from Energieverbruiktab; register data with sales prices for all house sales as registered with the Cadastre from Bestaandekoopwoningen; data on rent and service costs of rental housing from Huurenquete; housing situation and preferences of respondents from Woon; register data about housing, households, and persons from Woonbase; macro: DSTI norms from Nibud Financieringslastnormen triple differences probability to rent -1 – DSTI
Thomschke (2016) DEU Berlin, 2015–2016 micro: asking rents from empirica-systeme quantile regression, counterfactual distribution, difference-in-differences, changes-in-changes misallocation, controlled rents 1, -1 2, 2 rent control, rent control
Thomschke (2019) DEU Hamburg, Düsseldorf, Cologne, Munich, Berlin and Leipzig (Germany), 2012–2017 micro: advertisements of empirica-systeme difference-in-differences supply, controlled rents -1, -1 2, 2 rent control, rent control
Thornberg et al. (2016) USA Californian cities, 2000–2013 macro: 2000 Census; the 2013 three-year estimates from the American Community Survey; metropolitan area income from the U.S. Bureau of Economic Analysis, population estimates from the California Department of Finance; median home prices from DataQuick linear regression uncontrolled rents, supply, controlled rents 1, -1, 0 –, –, 2 rent control, rent control, rent control
Thorson (1997) USA McHenry County (Illinois), 1971–1994 macro: jurisdiction-level data on the number of permits issued OLS construction -1 – land use
Thurston (2020) CAN Greater Vancouver and Toronto, 2009–2019 macro: data on housing prices and the number of homes sold on a monthly basis from Canadian Real Estate Association; Multiple Listing Service difference-in-differences property sales, property price, property price -1, -1, -1 –, –, – foreign-buyer tax, transfer tax, foreign-buyer tax
Tidemann (2018) USA USA, 1985–2017 macro: state statutory minimum wage laws; data on fair market rent series of rents for low-skilled worker from Department of Housing and Urban Development; outgoing rotation group (MORG) wage data from Current Population Survey; county population from 2005–2016 American Community Survey pooled event study rent -1 – minimum wage
Tiwari and Hasegawa (2001) JPN Tokyo, 1993 micro: households data from Housing Survey of Japan non-linear hedonic regression, GCES utility function welfare 1 – social housing
Tomassini, Wolf, and Rosina (2003) ITA Italy, 1998 micro: Indagine Multiscoposulle Famiglie ‘‘Famiglia, soggetti sociali e condizione dell’infanzia’’ multinomial logit parent-child proximity 1 – housing allowance
Tracey and Van Horen (2021) GBR 379 local authority districts in England, Wales and Scotland, 2005–2017 macro: district-level data on house prices UK Land Registry Price Paid Dataset; micro: household-level data from UK Living Cost and Food Survey; loan-level mortgage data from Product Sales Database panel data model property sales, consumer spending 1, 1 –, – homeowner subsidy, homeowner subsidy
Tran (2021) CAN Vancouver and 24 cities, 1998–2020 macro: Statistics Canada synthetic control method crime -1 – vacancy tax
Trounstine (2020) USA all 4568 incorporated cities in metropolitan areas, 1968–2011 macro: demographic data from the Census of Population and Housing panel-data model with fixed effects segregation 1 – land use
Tsai (2013) GBR UK, 1986–2011 macro: housing price from Nationwide, money supply from Datastream threshold error correction model, ARCH, GJR-GARCH property price 1 – monetary policy
Tsatsaronis and Zhu (2004) AUS, BEL, CAN, DNK, FIN, FRA, DEU, IRL, ITA, JPN, NLD, NOR, ESP, SWE, CHE, GBR, USA 17 OECD countries, 1970–2003 macro: house price growth, growth rate of GDP, CPI, real short-term interest rate, term spread (difference in yield between a long-maturity government bond and the short rate), growth rate in inflation-adjusted bank credit from BIS structural vector autoregression property price 1 – monetary policy
Tse and Webb (1999) HKG Hong Kong, 1967–1997 macro: data on returns and transaction tax rate from Hong Kong Annual Digest of Statistics vector error correction model housing return, housing return -1, -1 –, – transfer tax, capital gains tax
Tsharakyan and Zemčı́k (2016) CZE Czech Republic, 2005–2008 micro: Family Accounts of the Czech Household Budget Survey multinomial probit model homeownership -1 1 rent control
Tsoodle and Turner (2008) USA 44 metropolitan statistical areas, 2001–2003 micro: housing-unit data from American Housing Survey; macro: city-level data from National League of Cities hedonic regression rent 1 – property tax
Tucker (1991) USA 56 US cities, 1984 macro: HUD survey of homelessness in 60 metropolitan areas linear regression homelessness 1 1 rent control
Margery Austin Turner (1990) USA D.C., 1985–1987 micro: telephone interviews with renters; financial statements for controlled rental properties; questionnaires completed by owners and managers; inventory of all additions and losses from the D.C. rental stock; one year’s history of housing code enforcement activity for controlled rental properties, volume and case-by-case disposition of housing provider and tenant petitions; and application and participation data for the District’s Tenant Assistant Program; data on households and housing conditions from the American Housing Survey regression analysis profitability, controlled rents 0, -1 2, 2 rent control, rent control
Matthew A. Turner, Haughwout, and Van Der Klaauw (2014) USA 138 metropolitan statistical areas, 1983–2009 micro: parcels of land hedonic regression property price -1 – land use
Twinam (2018) USA Seattle, 1920–2015 macro: land use data from 1920–52 from surveys by the Seattle City Planning Commission; modern data on land use from King County GIS database; demographic data from decennial census counts digitized by Ancestry.com linear regression separation of uses 1 – land use
Valentin (2021) USA New Orleans, 2004–2018 macro: data on dwellings offered for short-term rental from AirDNA aggregated at the census tract level duration model, panel-data model property price -1 – housing rationing
Van Bekkum et al. (2024) NLD Netherlands, 2010–2012 micro: data on household income and balance sheets (including property ownership records) from Central Bureau for Statistics; universe of property transactions from Land Registry (Kadaster); proprietary mortgage servicing data from Dutch software company and from European Datawarehouse linear regression household leverage, homeownership -1, -1 –, – LTV, LTV
Vandenbussche, Vogel, and Detragiache (2015) ALB, BGR, CZE, EST, HRV, HUN, LTU, LVA, POL, ROU, RUS, SRB, SVK, SVN, TUR, UKR 16 CESEE countries, 2002–2011 macro: housing prices data from Bank for International Settlements panel data regression, error correction model property price, property price -1, -1 –, – CAR, RR
van den Noord (2005) AUT, BEL, FIN, FRA, DEU, GRC, IRL, ITA, LUX, NLD, PRT, ESP 12 Euro area countries, 1999 macro: European Tax Handbook linear regression volatility -1 – transfer tax
Plas (2021) AUT, BEL, DEU, DNK, FRA, FIN, ISL, LUX, NLD, NOR, SWE, GBR 35 Corop regions of the Netherlands, 1995–2020; 9 European countries, 2005–2020 macro: House Price Index from Corop; House Price Index from Eurostat difference-in-differences; synthetic control property price 0 – gift tax
van Dijk (2019) NLD Amsterdam, 2013–2016 micro: application data from Platform Woningcorporaties Noordvleugel Randstad — associations that maintain and distribute public housing in the Amsterdam metropolitan region; administrative data from Statistics Netherlands panel-data model employment, earnings -1, -1 –, – housing allowance, housing allowance
Vandrei (2018) DEU Land Brandenburg, 2011–2017 micro: transaction sales prices from Superior Property Valuation Committee of Brandenburg regression discontinuity design value -1 2 rent control
Vangeel, Defau, and De Moor (2020) BEL three Belgian regions, 1995–2015 macro: regional data from Statistics Belgium (Statbel) panel-data model with fixed-effects property price 1 – mortgage deduction
Vangeel, Defau, and De Moor (2022) BEL, DNK, FIN, FRA, DEU, GRC, ITA, IRL, NOR, PRT, ESP, SWE, NLD, GBR 14 European countries, 1990–2015 macro: country-level data from World Bank, Eurostat panel-data model property price 1 – mortgage deduction
van Holm (2020) USA New Orleans, 2015–2019 micro: Airbnb listings data from InsideAirbnb hedonic regression, regression of total number of listings number of listings -1 – housing rationing
Holsteijn (2023) NLD Netherlands, 2020–2021 micro: value of the home in WOZ values, whether the surveyor (or the partner of the surveyor) received a Jubelton (binary), how much the Jubelton was worth (categorical) and possible control variables from WoonOnderzoek Nederland hedonic regression housing size -1 – gift tax
van Nes (2020) NLD Amsterdam, 2008–2017 micro: property data from Nederlandse Vereniging van Makelaars en Taxateurs, aggregate database created by ValueMetrics containing information on properties from Dutch housing corporations, CBS difference-in-differences, hedonic regression property price 1 – social housing
Van Ommeren and Van Leuvensteijn (2005) NLD Netherlands, 1990–1996 micro: data on 75,000 Dutch households from ncome Panel Research hazard-rate model, duration model mobility -1 – transfer tax
Van Ryzin, Kaestner, and Main (2003) USA New York City, 1995–1996 micro: local survey data logit employment 0 – housing allowance
Vansteenkiste (2007) USA 31 biggest US states, 1986–2005 macro: house prices from Office of Federal Housing Enterprise Oversight, personal consumption expenditure deflator less food and energy, real income per capita, real interest rates from Bureau of Economic Analysis global vector autoregression property price 1 – monetary policy
Van Zandt and Mhatre (2013) USA Dallas, 2003–2006 micro: apartment complexes having 10 or more HCV households spatial lag model crime 0 – housing allowance
Vargas-Silva (2008) USA USA and regions Northeast, Midwest, South and West, 1965–2005 macro: number of new privately owned housing units starts (housing starts) from U.S. Census Bureau, real private residential fixed investment (residential investment) from Bureau of Economic Analysis, real GDP, house prices, price deflator, commodity price, Federal Funds Rate, nonborrowed reserves, total reserves vector autoregression property price, housing investment, construction 1, 1, 1 –, –, – monetary policy, monetary policy, monetary policy
Venkataraman (2014) IND Bengaluru, 2007–2011 micro: transactions with land plots hedonic regression property price 0 – land use
Verbist and Grabka (2017) DEU Germany, 1994–2012 micro: SOEP households logit inequality, inequality -1, -1 –, – housing allowance, social housing
Vigdor and Williams (2022) USA US metropolitan areas, 1960–2017 micro: data on rental units from Census American Community Survey panel data model; difference-in-differences rent 1 – habitability laws
Viren (2013) FIN Finland, 1989–2008 micro: household data from Finnish Income Distribution survey panel-data model space, rent 1, 1 –, – housing allowance, housing allowance
Vitaliano (1985) USA 5 counties of New York State, 1950 micro: 1950 Survey of Rents log-linear regression housing quality -1 1 rent control
Wadud, Bashar, and Ahmed (2012) AUS Australia, 1974–2008 macro: GDP, CPI, house price index, material costs, number of new houses from Australian Bureau of Statistics, federal funds rate from US Federal Reserve Bank structural vector autoregression property price, construction 0, 1 –, – monetary policy, monetary policy
X. Wang et al. (2019) CHN Chongqing, 2016 micro: data of survey conducted by Chongqing University, Chongqing Municipal Commission of Urban-Rural Development, and State Grid Chongqing Electric Power Company linear regression; logit; average treatment effect on the treatment electricity consumption -1 – building code
S. Wang et al. (2020) CHN China, 1999–2014 macro: House price growth rate, China housing sentiment index, Consumer Confidence Index, area of land purchased in the current month, industrial value added, M2, market benchmark interest rate from National Bureau of Statistics of the People’s Republic of China; policy uncertainty index from Baker, Bloom, and Davis (2016) (www.policyuncertainty.com) logistic smooth transition vector autoregression property price 1 – monetary policy
L. Wang et al. (2024) CHN 273 cities in China, 2004–2018 macro: China Land Network; City Statistical Yearbook; China Statistical Yearbook; China Financial Yearbook difference-in-differences property price, property sales 0, -1 –, – home purchase restriction, home purchase restriction
J. Wang and Zhang (2019) CAN Vancouver and Toronto, 2013–2019 macro: house price index from ? difference-in-differences property price, condo price 0, -1 –, – vacancy tax, vacancy tax
Warsame, Wilhelmsson, and Borg (2010) SWE all 6 regions of Sweden, 1975–2004 macro: housing construction, income per capita, factor price indices, CPI from ? instrumental variable, seemingly unrelated regression construction 1 – interest rate subsidy
Wasi and White (2005) USA metropolitan areas in California, Florida, and Texas, 1970, 1980, 1990, 2000 micro: household data from Integrated Public Use Microdata Series difference-in-differences; difference-in-difference-in-differences mobility 1 – property tax
Wassmer (2016) USA US urbanized areas, 2000–2010 macro: Social Explorer; Minnesota Taxpayers Association; FBI Uniform Crime Report panel-data model urban sprawl 1 – property tax
Wassmer and Williams (2021) USA US MSAs, 2012–2015 macro: Wharton Residential Land Use Regulatory Index; residential land price from Federal Housing Finance Agency; data on population, housing, and GDP from American Community Survey and Bureau of Economic Analysis regression model property price 1 – land use
Weber and Lee (2020) AUS, AUT, CAN, CHE, DEU, DNK, ESP, FIN, FRA, GBR, IRL, ITA, NLD, NOR, NZL, SWE, USA 18 states, 1973–2014 macro: macroeconomic and demographic statistics; regulation indices panel-data model controlled rents, controlled rents -1, -1 1, 2 rent control, rent control
Welkers (2023) NLD Rotterdam, 2021–2023 micro: data on housing transactions from real estate announcement website Funda difference-in-differences rent, property price 1, -1 –, – buy-up protection, buy-up protection
Wenner (2018) EST, LVA Tallinn and Riga, 2000–2014 macro: data from the Estonian and Latvian national statistical offices descriptive analysis urban sprawl -1 – land value tax
Werczberger (1988) ISR Israel, 1957–1986 macro: various indicators from different sources descriptive analysis homeownership 1 1 rent control
Werczberger (1997) CHE Switzerland, 1920–1990 macro: various indicators from different sources informal descriptive analysis homeownership 0 1 rent control
Verma and Hendra (2003) USA Los Angeles County, 1998 micro: data on assisted and unassisted leavers from California Medi-Cal Eligibility Data System; employment data from California Employment Development Department; data on housing assistance status Multifamily Tenant Characteristics System and Tenant Rental Assistance Certification System; cross-sectional follow-up survey data linear regression employment, earnings 1, 1 –, – housing allowance, housing allowance
Wen and Zhao (2019) CHN Xi’an and 62 other cities, 2015–2018 macro: average prices of residential stock houses1 obtained from China Real Estate Information Network of State Information Centre; CPI from National Bureau of Statistics; GDP per capita, residential land price, population density, and proportion of tertiary industry from Economy Prediction System synthetic control method property price 1 – talent housing policies
Wessel, Schmidt-Kessen, and Hukal (2024) AUS, BEL, DEU, DNK, ESP, FRA, GBR, GRC, NLD, PRT, SWE 13 European cities (Amsterdam, Athens, Barcelona, Berlin, Brussels, Copenhagen, Lisbon, London, Madrid, Paris, Stockholm, Venice, Vienna), 2015–2019 micro: listings, reviews, as well as metadata from Inside Airbnb; macro: economic and social indicators from Eurostat difference-in-differences with synthetic controls number of listings -1 – housing rationing
White (1986) USA New York City, 1974–1976 macro: neighborhood-level data from New York City Department of City Planning linear regression ownership abandonment 1 – property tax
Wilhelmsson (2022) SWE Sweden, 2008–2019 micro: transaction data on single-family houses and tenant-owner dwellings from association of brokers Mäklarstatistik AB hedonic regression; regression discontinuity design property price, property price 0, -1 –, – LTV, amortization
Wilhelmsson, Andersson, and Klingborg (2011) SWE Sweden, 1994–2006 macro: observed vacancy rates of municipal housing companies in 274 municipalities OLS; TSLS vacancy -1 1 rent control
K. G. Willis, Malpezzi, and Tipple (1990) GHA Kumasi, 1986 micro: a random sample of 1461 households covering 6330 people (1.3% of the total population of Kumasi) and 279 landlords in 1986 linear regression supply, controlled rents -1, -1 1, 1 rent control, rent control
Wolch and Gabriel (1981) USA San Francisco Bay Area suburban cities, 1976 macro: housing and population data from Bureau of Census; local public finance data from; local land-use policy from Association of Bay Area Governments and Gabriel, Katz, and Wolch (1980) multiple regression, OLS property price 1 – land use
T. Wong et al. (2011) AUS, CAN, GRC, HKG, KOR, MYS, PHL, PRT, SGP, ESP, THA, USA, GBR 13 countries, 1991–2010 macro: mortgage delinquency ratio data from the respective central banks, data on property prices, GDP, government bond yields, and the GDP deflator from BIS, CEIC, and IMF panel data model, GARCH property price, mortgage delinquency, household leverage 0, -1, -1 –, –, – LTV, LTV, LTV
S. K. Wong et al. (2021) HKG Hong Kong, 1991–2017 macro: rental index from Rating and Valuation Department of Hong Kong; GDP from Census and Statistics Department of Hong Kong; interest rate, domestic credit, tender price indices, net injection into the interbank market through market operations from Hong Kong Monetary Authority Error Correction Model, Seemingly Unrelated Regression property price, property price -1, 1 –, – LTV, transfer tax
Woo and Joh (2015) USA Austin (Texas), 2000–2009 macro: neighborhood-level crime data adjusted interrupted time series – difference-in-differences crime -1 – social housing
Woo, Joh, and Van Zandt (2016) USA cities of Charlotte (North Carolina) and Cleveland (Ohio), 1996–2007 micro: data for housing turnover and sales price for Charlotte from Mecklenburg County Assessor’s Office; data for Cleveland from Northeast Ohio Community and Neighborhood Data for Organizing; Picture of Subsidized Households data from US Department of Housing and Urban Development Cox hazard model; difference-in-differences neighborhood stability -1 – social housing
M. Wood, Turnham, and Mills (2008) USA USA, 1999–2006 micro: data on households from surveys probit model space, neighborhood quality, mobility, marriage, household size, homelessness 1, 1, 1, 0, -1, -1 –, –, –, –, –, – housing allowance, housing allowance, housing allowance, housing allowance, housing allowance, housing allowance
G. Wood, Ong, and Dockery (2009) AUS Australia, 1982, 1990, 1996, 2000 and 2002 micro: SIHC survey logit model employment -1 – social housing
J. Wu and Cho (2007) USA California, Idaho, Nevada, Oregon, and Washington, 1982–1997 micro: site-level land use data from Natural Resource Inventories logit model land supply -1 – land use
G. Wu, Guo, and Niu (2023) CHN 35 Chinese cities, 2010–2019 macro: population and GDP from China City Statistical Yearbook; housing price from WIND spatial Durbin model, spatial regression uncontrolled property price 1 – home purchase restriction
Y. Wu and Li (2018) CHN 97 cities, 2010–2014 macro: WIND database; National Bureau of Statistics of China; China City Statistical Yearbook; the SouFang Website Website difference-in-differences property sales, property price, housing investment, construction -1, -1, 0, 0 –, –, –, – home purchase restriction, home purchase restriction, home purchase restriction, home purchase restriction
Xhignesse and Verbist (2022) BEL Belgian municipalities, 2012 micro: data on household income from EUROMOD and EU-SILC; Gini coefficient, head count rate, income gap ratio microsimulation model urban sprawl 1 – mortgage deduction
Xiao and Zhou (2023) CHN China, ? micro: data on households from ? difference-in-differences, triple differences rent income 1 – property tax
Xie (2024) USA US MSAs, 1990–2007 macro: fed funds rate, output growth, inflation, excess bond premium, Freddie Mac House Price Index from ?; housing construction permits from Census Building Permits Survey panel structural VAR; local projections property price, property price 1, 1 –, – monetary policy, unconventional monetary policy
Yagan (2013) USA continental USA, 2006 and 2011 micro: data on males aged 25-59 from American Community Survey (ACS), Internal Revenue Service Statistics of Income Databank, a population panel of U.S. tax returns covering years 1996–2011 linear regression migration -1 – mortgage deduction
Yamagishi (2019) USA USA, 1984–2018 macro: county-level data on fair market rent series from the Department of Housing and Urban Development long-differences specification, panel data model, distributed lag model rent 1 – minimum wage
Yamagishi (2021) JPN Japan, 2002–2012 macro: prefecture-level data on all apartments posted on At Home event study, difference-in-differences, panel data model rent 1 – minimum wage
Yan and Hongbing (2018) CHN 43 cities across 30 provinces in China, 2017 macro: daily data for the area and numbers of sold residential houses, GDP per capita, permanent population from WIND database difference-in-differences, propensity score matching property sales, property price -1, -1 –, – home purchase restriction, home purchase restriction
Z. Yang and Hawley (2022) USA Pennsylvania, 1990–2018 macro: market values from Pennsylvania State Tax Equalization Board; land values from M. A. Davis et al. (2021) panel-data model property price, land price 1, -1 –, – split-rate tax, split-rate tax
Y. Yang and Mao (2019) USA 28 major US cities, 2015–2016 macro: Airbnb supply data (the number of Airbnb units and total number of available days) from AirDNA; tourism and hotel demand variables from TripAdvisor; city-level hotel price data in 2015 from hotel price index on Hotels.com; data on the number of hotel rooms in each zip code from Smith Travel Research Hotel Census Database; residential housing supply and demand data from 2015 American Community Survey; city-level home-sharing regulation scores from Roomscore project mixed-effects negative binomial model number of listings 0 – housing rationing
Q. Yang and Yang (2019) CAN Toronto and Vancouver, 2009–2019 macro: Real Estate Board of Greater Vancouver; Toronto Real Estate Board; price data from REBGV and TREB MLS difference-in-differences property price, condo price 0, -1 –, – vacancy tax, vacancy tax
Yelowitz (2001) USA USA, 1990–1993 micro: SIPP and CPS panel-data model labor force participation -1 – social housing
Yeon, Song, and Lee (2020) USA New York City and Washington DC, 2016–2017 micro: anonymized annual property (hotels) data from STR difference-in-differences hotel performance 1 – housing rationing
Yeon et al. (2022) USA New York City and Washington DC, 2014–2017 micro: Airbnb listings difference-in-differences short-term earnings -1 – housing rationing
Yıldırım and Yağcibaşi (2019) TUR Turkey, 2010–2017 macro: house price index, interest rate on residential mortgage loans, interest rate on residential loans, issued in terms of Turkish Lira, GDP, share of government expenditure in GDP from Central Bank of the Republic of Turkey ARDL bounds test property price 1 – fiscal policy
Yiu (2023) AUS, CAN, DEU, FRA, GBR, ITA, JPN, KOR, NZL, USA 10 OECD countries, 2015–2022 macro: house prices, GDP growth rates, unemployment rates, nominal short- and long-term interest rates, inflation rates from OECD panel data model property price 1 – monetary policy
Yun and Choi (2025) KOR Korea, 2019–2022 micro: data on 85,703 households from Household Income and Expenditure Survey difference-in-difference-in-differences side payments 1 2 rent control
Yuxin, Yuanyuan, and Ho (2018) USA 15 US cities, 2014–2016 micro: Airbnb data; macro: data on household income, vacancy ratio, household number, ethnic ratio, hotel size, crime rate, and airport traffic from ? two-step difference-in-differences number of listings 1 – housing rationing
Jeffrey E. Zabel and Dalton (2011) USA 187 cities and towns in Greater Boston area, 1987–2006 micro: data on transactions of single-family homes from Warren Group hedonic regression, difference-in-differences with structural break property price 1 – land use
Jeffrey E. Zabel and Paterson (2006) USA 400 FIPS places of California, 1990–2004 macro: place-level data on the total number of permits granted for single-family units from CIRB; house price data from DataQuick Information Systems; data on average wage per job, employment, and per capita income from the Regional Economic Accounts of Bureau of Economic Analysis; fair market market rents from HUD; GIS data on FIPS places from Census Bureau difference-in-differences; panel data model; hedonic regression property price 1 – land use
Zapatka and Castro Galvao (2022) USA New York City, 1991–2008 micro: New York City Housing Vacancy Survey logit, hedonic regression rent burden -1 2 rent control
C. Zhang (2015) CHN 186 Chinese cities, 2002–2009 micro: Chinese urban household survey OLS; panel data model rent burden of low-income households, residual income of low-income households, housing consumption of low-income households -1, 1, 1 –, –, – housing rationing, housing rationing, housing rationing
Z. Zhang (2017) CHN Beijing and Shenzhen, 2006–2016 macro: HPI in Beijing, government expenditure, CPI from National Bureau of Statistics of China; data on exchange rates of Chinese yuan to one US dollar from Federal Reserve Economic Data (FRED) vector autoregression; GMM property price 1 – monetary policy
Licheng Zhang (2024) CHN China, 2005–2018 macro: house prices from Bank for International Settlements; GDP growth data from China Stock Market and Accounting Research database; financial stress index from Asian Development Bank smooth local projections property price 1 – monetary policy
Jixuan Zhang and Deng (2022) CHN 30 provinces in China, 2002–2016 macro: National Bureau of Statistics of the People’s Republic of China panel model; GMM property price, consumer spending 1, 1 –, – transfer tax, transfer tax
Li Zhang, Wu, and Liu (2018) CHN 285 Chinese cities, 2008–2015 macro: GDP per capita from China City Statistical Yearbook; central heating in winter in the city; average schooling year from National Population Census in 2010; per-capita floor area of housing transactions from China Statistical Yearbook for Regional Economy Tobit model; Cox proportional hazard model green construction 0 – green subsidy
W. Zhang et al. (2021) CHN 58 Chinese cities, ? macro: housing price indices panel data model uncontrolled property price 1 – home purchase restriction
Liguo Zhang et al. (2023) CHN 70 large and medium-sized Chinese cities, 2013–2019 macro: urban housing prices and related economic data from China City Statistical Yearbook and China Regional Economic Statistical Yearbook difference-in-differences property price 1 – talent housing policies
Jinyu Zhang et al. (2025) CHN 64 Chinese cities, 2009–2012 macro: ? Bayesian synthetic control rent -1 – property tax
D. Zhao, McCoy, and Du (2016) USA counties or cities of Arlington, Hampton, King George, Lynchburg, Petersburg, Wytheville, Abingdon, Chesapeake, Christiansburg, Orange, Richmond, Scottsville, and Virginia Beach (Virginia), ? micro: resident behavior data from own survey linear regression; simulation model energy consumption, energy expenditure -1, -1 –, – green building standards, green building standards
X. Zheng, Chen, and Yuan (2021) CHN 195 Chinese cities, 2007–2014 micro: parcel-level land transaction data from China Land Market website difference-in-differences uncontrolled property price 1 – home purchase restriction
H. Zheng and Zhang (2013) CHN Chongqing, Shanghai and other 33 Chinese cities, 2009–2012 macro: monthly residential housing price from China Real Estate Index System; land space purchased, investment of real estate development on residential buildings and total funding (domestic loans, foreign investment, self-raising funds and other sources of funds) synthetic control method property price -1 – property tax
Zhu, Betzinger, and Sebastian (2017) AUT, BEL, FIN, FRA, DEU, GRC, IRL, ITA, NLD, ESP, PRT 11 Euro Area countries, 1992–2012 macro: house prices from BIS and Oxford Economics, real GDP, credit from domestic banks to the private non-financial sector as a share of GDP, CPI, total population, unemployment rate, disposable personal income, housing permits, mortgage rate from BIS, Oxford Economics, and Datastream interacted panel VAR property price 1 – monetary policy
Zorn, Hansen, and Schwartz (1986) USA Davis (California), 1971–1979 micro: house sales prices from Society of Real Estates Appraisers hedonic regression property price, property price 1, -1 –, – land use, housing rationing
Y. Zou, Zhao, and Zhong (2017) CHN China, 2014 micro: data on all green buildings certified by the 3-Star rating system from Energy Saving and Building Science Division of MOHURD; macro: GDP per capita, real estate price, energy efficiency from China’s Statistical Yearbook OLS green construction, green construction 0, 1 –, – green building standards, green subsidy
Z. Zou et al. (2025) AUS New South Wales, 2019–2023 micro: property-level STR monthly booking activities with operational and dwelling characteristics from AirDNA; property-level LTR records from Australian Property Monitor dynamic difference-in-differences number of listings, reservation days, revenue per listing, rent -1, 0, 0, 0 –, –, –, – housing rationing, housing rationing, housing rationing, housing rationing

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  1. For different variants of the term of “housing allowances” see Table PH3.2.1: Characteristics of housing allowances: details on eligibility: https://www.oecd.org/els/family/PH3-2-Key-characteristics-of-housing-allowances.pdf.↩︎