Longitudinal database of rental housing market regulations: 100+ countries over 100+ years
Konstantin A. Kholodilin
DIW Berlinkkholodilin@diw.de
August 5, 2025
Abstract
This study presents a large longitudinal database of governmental rental market regulations. The intensity of these regulations is measured using binary variables based on a thorough analysis of the real-time country-specific legislation. Three major restrictive policies are examined — rent control, protection of tenants from eviction, and housing rationing. Currently, the database covers 150 countries and states between 1910 and 2025. These data allow comparisons of regulation intensity across both time and space. Moreover, a rich variety of analyses of the regulation effects on different aspects of the housing market and general economy becomes possible thanks to our data, as the already undertaken studies show.Introduction
In this study, we describe the methodology and the data used to construct rental housing market regulation indices. The database is thoroughly discussed in Konstantin A. Kholodilin (2020). Our aim here is to document the database by providing the list of legal acts and to present the individual binary indices reflecting specific aspects of governmental regulations of the rental housing market. In addition, given that the database is constantly evolving, we report here its most up-to-date version.
Everybody desiring to contribute to the further development of the database is welcome!
Methodology
In our approach, the quantification of legal acts is carried out in several steps. This section describes the whole algorithm. Its purpose is to make the approach used here as transparent and replicable as possible. The first step consists of exploring the literature that summarizes governmental housing market regulations in the country of interest. In a few select cases, a nice and systematic description of the evolution of such legislation exists. The main sources of such information are the Tenlaw project at the Universitaet Bremen1 for the 28 European Union member states plus Japan, Norway, Serbia, Switzerland, and Turkey; the “Tenancy Law and Procedure in the EU” project of the European University Institute in Florence2 for 13 EU member states plus Switzerland; International Labour Office (1924) for the origins of housing policies in 17 European countries (Austria, Belgium, Czechoslovakia, Denmark, Finland, France, Germany, Great Britain, Hungary, Italy, Netherlands, Norway, Poland, Russia, Sweden, Switzerland, and Yugoslavia); historical and legal studies; as well as preambles of legal acts or parliamentary discussions of law drafts that provide justification of regulations (e.g., Belgium, Portugal, and Romania). Also, the works of John W. Willis are extremely useful, who in the late 1940s made an excellent overview of rent control regulations in many countries across the world (Willis 1947, 1948a, 1949b, 1949a, 1950). In other cases, the country-specific studies are used in order to identify the relevant legal acts; see Table below.
| Country | Study and period under consideration |
|---|---|
| Argentina | Pellejero and Monaiser (2009) 1921–2009, Polotto (2012) 1901–1950, Turnaturi (2013) 1921–2013 |
| Australia | Schneller (2013) 1916-2013, Martin (2021) 2020 |
| Belgium | Henau (1991) 1914–1940, Bettendorf and Buyst (1997) 1929–1939 |
| Botswana | Frimpong (1989) 1977–1989 |
| Brazil | Bonduki (1994) 1930–1950, Rosenn (1969) 1944–1964 |
| Bulgaria | Miletić (2016) 1918–1928 |
| Canada | Thibodeau (2001) 1950–2000, Dillon (1982) 1940–1982, Schuss (2018) 1951–2018 |
| Chile | Hidalgo Dattwyler (2003) 1921–1930 |
| China | K. A. Холодилин (2022) 1921–2021 |
| Colombia | Soto Gil (2013) 1946–2013 |
| Costa Rica | Elizondo Calderón (1998) 1920–1928 |
| Cuba | de Peña Mulet (1992) 1902–1985 |
| Denmark | Hansen (2022) 1939–1945 |
| Ecuador | Novillo Rodas (2006), Bravo Lozano (2015) 1938–2000 |
| Egypt | Attia (2016) 1924–1996, McCall (1988) 1924–1981 |
| El Salvador | Marmol Navas (2001) 1946–2001 |
| Finland | Malinen (2009) 1917–1922 |
| France | Croizé (2009) 1900–1980 |
| Germany (East) | Meggle (2004) 1945–1990 |
| Germany (West) | Kofner (1997) 1896–1945, Kofner (1999) 1946–1998, K. Kholodilin (2017) 1914–2016 |
| Ghana | Malpezzi, Tipple, and Willis (1990) and Tipple (1988) 1942–1989 |
| Guatemala | Villatoro Illescas (2009) 1932–1992 |
| Hong Kong | Cheung (1975) and Bradbrook (1977) 1921–1977, Choi (2017) 1921–2004, K. A. Холодилин (2022) 1921–2021 |
| Hungary | Antal (1997) 1946–1997 |
| Iceland | Jóhannsson and Sveinsson (1986) 1939–1986 |
| India | Dey and Dev (2006) 1918–2006 |
| Indonesia | Colombijn (2013) 1918–1966 |
| Iran | Mahmoudkalayeh (1991) 1977–1991 |
| Israel | Mark (2013) 1948–1954 |
| Italy | Carrara (1919) 1915–1919 |
| Japan | Suto (2015a), Suto (2015b), Suto (2016), Suto (2017) 1917–2015, Ono (2017) 1939–1950 |
| Kenya | Noormohamed (1975) and Bonna (1985) 1918–1985 |
| Lebanon | Marot (2018) 1940–2018 |
| Liechtenstein | Nägele (2014) 1812–2014 |
| Lithuania | Kuodys (2012) 1919–1937 |
| Macao | K. A. Холодилин (2022) 1921–2021 |
| Malaysia | Mohit and Sulaiman (2006) 1966–1997 |
| Malta | Mifsud-Bonnici (2003) 1473–1995, Vakili-Zad (2007) 1929–2007 |
| Mexico | Navarro González (1974) 1910–1970, Ramírez Navarro and Ramírez Navarro (2018) 1917–2015 |
| Netherlands | Priemus (1983) 1916–1983 |
| Nicaragua | Santos (1986) 1979–1985 |
| Nigeria | Oni, Ajibola, and Oloyede (2007) 1997 |
| Philippines | Ballesteros (2001) 1946–2001, Ballesteros, Ramos, and Magtibay (2016) 1971–2015 |
| Portugal | Reis (2022) 1910-2022 |
| Romania | Tabacu (2006) 1919–2006 |
| Russia | Konstantin A. Kholodilin (2017) and К. А. Холодилин (2019) 1917–1922, Konstantin A. Kholodilin and Meerovich (2018) 1916–1939 |
| Senegal | Diongue (2018) 1952–2018 |
| Singapore | Koh (1966) 1917–1966 |
| South Africa | Maass (2010) 1920–2010 |
| Spain | Aragoneses Alonso and Pascual Nieto (1956) and Madrid Cruz (2008) 1564–1842, Argelich Comelles (2017) 1610–2017, Arruñada (2022) 1842–2022, Ràfols Esteve (1979) 1920–1976 |
| Sri Lanka | Senaratne (2020) 1942–2002 |
| Sweden | Bengtsson (2006) 1907–2006 |
| Switzerland | Rohrbach (2014) 1911–2014 |
| Taiwan | K. A. Холодилин (2022) 1921–2021 |
| Tanzania | Chembo (2014) 1961–2015 |
| UK | Sabatino (1954) 1915–1954, Wilson (2017) 1915–1989 |
| USA | International Labour Office (1925) 1919–1925, McPherson (2003) 1920–2003, Willis (1948b) 1946–1947, Collins (2016) 1920–2016, Keating (1987) 1969–1985 |
| Venezuela | Lovera De Sola (2015) 1947–2014 |
| Vietnam | Herbelin (2009) 1920–1951 |
| Zambia | Nzonzo (2005) 1940–1994 |
In the second step, a list of relevant legal acts is compiled and the search for their original (not revised) texts is conducted. Since we are interested in the evolution of the housing legislation, we need the “real-time” texts, as formulated at the moment of their enactment. Most frequently, such texts are found in government, or official, gazettes. Fortunately, many of these gazettes are digitized and available as online archives. Hence, it is relatively easy to search for the necessary information. In other cases, laws can be obtained free of charge by contacting the national parliaments (e.g., as is the case for Denmark, Iceland, and Norway). Still other countries charge fees for providing the relevant laws (for example, Bulgaria, Singapore, and Sweden). As in some cases we were unable to locate laws as published in an official gazette, we use drafts of the laws from parliamentary proceedings (e.g., Belgium and Switzerland). In the worst case, answers to questions submitted remotely are not forthcoming (some African, Asian, as well as Latin American and the Caribbean countries) or one must visit a library in the country of interest.
In the third step, the compiled legal acts are summarized. The relevant provisions are identified and recorded. In particular, the following fields are captured: area of application, rent control, tenant protection, housing rationing, and bodies responsible for conflict settling and regulation of the housing sphere. Language barrier is an important challenge at this stage. In many cases, knowledge of the foreign languages (English, French, German, Italian, and Spanish), Russian being his mother tongue, permits the author of the study to understand the legal texts. In other cases, native speakers help decipher these texts (e.g., those in Greek). Otherwise, the author takes advantage of machine translation (the internet service of Google Translator) in order to translate the texts written in the languages he or his colleagues do not speak. Although the quality of modern machine translations is relatively high, there is still a room for mistakes.
In the fourth step, the textual summaries of legal acts are mapped into numeric values. Here, we rely upon the approach of Weber (2017) to code rent laws and tenure security and K. Kholodilin (2017) to code housing rationing. Based on a set of questions contained in Table below, binary variables are constructed that equal one, if regulation is more stringent, and zero, otherwise: \[ I^k_{jt}= \begin{cases} 1,& \text{if restriction $j$ of type $k$ is present in period $t$}\\ 0, & \text{otherwise} \end{cases} \] where \(k\) is a regulation type (rent laws, tenure security, or housing rationing) and \(t\) is the date on which the law containing such provision is enacted. Thus, each binary variable represents an answer to a question characterizing a particular aspect of the corresponding regulation. If the answer is “yes”, then the binary variable takes value 1, if the answer is “no”, then the variable takes the value zero. Typically, the positive answer corresponds to more limitations from the standpoint of landlords. Below, the coding is described in more detail.
Rent control. In his dissertation, Weber (2017) defines six binary variables: Real rent freeze (the rents are not allowed to grow faster than inflation), Nominal rent freeze (the rents are frozen in nominal terms), Rent level control (some government body, arbitration council, or court fixes the rent level at the beginning of new contracts), Intertenancy decontrol (if the rent control ceases with a change of tenant), Other specific rent decontrol (certain types of dwellings or settlements are no longer subject to the rent control), and Specific rent recontrol (certain types of dwellings or settlements are subject to more stringent controls).
Tenure security. This protection is summarized using four binary variables (Weber 2017). The binary variables Eviction protection during term or period and Eviction protection at the end of term or period take the value one, if, in order to evict a tenant during the contract term or at the end of it, the landlord is required to present justified reasons. The Minimum duration variable equals one, if the contract duration must be at least two years, while the Short-term tenancies’ variable is 1, if letting dwellings for a period of less than one year is prohibited.
Housing rationing. This policy is approximated with eight binary variables. Registration of housing equals one, if landlords are obliged to register vacant, or all available, premises. The binary variable Protection of housing is one, if it is prohibited to use dwellings for non-residential purposes, merge or demolish them, or to convert rental dwellings into condominiums. The variable Creation of housing space equals one, if the state prescribes the use of all available space for housing purposes, e.g., through the reconstruction or conversion of non-residential premises or through the subdivision of big dwellings into smaller ones. The dummy variable Requisition equals one, if requisition with subsequent compulsory letting of the vacant dwellings is conducted. Restriction of freedom to move is one, if residential mobility is restricted: for example, if access to areas with an acute housing shortage is closed to all persons, who are neither “indispensable” for these areas nor residing there on a permanent basis. Conservation of social composition is one, if a balanced social composition of population in particular urban areas is protected through interdiction to upgrade the dwellings to a state considered being above the standard level. The variable Housing consumption norms equals one, if restrictions on the amount of housing that might be used by tenants are imposed. The dummy Nationalization of housing takes the value one, if the state nationalizes housing stock, and zero, if no nationalization or privatization occurs. Unlike requisition, nationalization means the loss of property rights for the owner and no compensation for property taken. Table below defines the individual indices (binary variable) making up the three regulation types.
Composition and definition of regulation indices
For each regulation type \(k\), a composite index is computed as a simple average of binary variables: \[I^k_{t}= \frac{1}{N_k}\sum_{j=1}^{N_k} I^k_{jt} \] where \(k=\{\mbox{Rent laws},\mbox{Tenure security}, \mbox{Housing rationing}\}\) and \(N_k\) is the number of binary indices. For example, for rent laws the composite index is based on six binary indices. When all of them are equal zero, their simple average is equal to zero too implying that no limitations on rent setting are present. The more such limitations the closer the index to 1. The composite index equal to 1 means the highest intensity of regulations of type \(k\).
The binary and composite indices are constructed for a large balanced panel of 150 countries or subnational regions (113 nations) covering the period 1910–2024, see Table and Figure below. The choice of countries is dictated by the availability of legal acts. The best coverage exists for Europe, Asia, and Latin America. In Africa, mainly former French and Portuguese colonies are covered, since it was relatively easy to locate the historical legal acts for them. For North American countries, coding is complicated by the fact that housing regulations there are created at the regional level, including not only states or provinces, but also cities. All in all, our data set covers the majority of the world population, given that the population of countries for which rental market regulation indices are constructed makes up 81.2% of the total world population as of 2010.
List of countries, for which regulation indices are constructed
List of relevant legal acts
Table below reports the relevant laws for each country, which are used in the study to construct regulation indices. The first column contains the name of the country and an ISO 3166-1 alpha-2 code. The second and the third columns report the date, when the law was passed/assented, and the date on which it was enacted, correspondingly. Finally, in column four, the title of the law both in original and in angle brackets the English translation. Not all titles are translated yet.
Graphical representation of regulation intensities
The continent-wide averages of the three rental regulation indices are shown in Figure below. The high values of indices correspond to a more intense tenant protection.
Rental regulation intensity by continents
Figure below shows in form of animation the variation of the intensity of rent control across space and time. The darker shades of gray correspond to stronger rent restrictions. The yellow color denotes countries, for which no rent control indices are yet available.
Change of rent control intensity over the space and time
The next three figures allow examining each regulation index for each country. You just need to select the options you are interested in.
Choice of rent control by country/region
Choice of tenure security by country/region
Choice of housing rationing by country/region
Download regulation indices
Use the table below to download rental housing market regulation indices.
Use of the regulation indices
The rental housing market regulation indices have been already used in several studies. Konstantin A. Kholodilin and Kohl (2023a) investigate whether rental regulations affect the homeownership formation. The effects of rental regulations on new construction are considered in Konstantin A. Kholodilin and Kohl (2023b). Jacobo and Kholodilin (2020) examine the impact of rental housing market regulations on rents in Argentina. Cournède, Sakha, and Ziemann (2019) find that a tighter rental regulation tends to exacerbate the risk of severe economic downturns. The results of Cavalleri, Cournède, and Özsöğüt (2019) suggest that restrictive rental market regulations can decrease the price elasticity of housing supply “by reducing the expected net present value of housing investment”. According to Eichholtz, Korevaar, and Lindenthal (2019), in the short run, the nominal rent control appears to improve the rental housing affordability (measured as the ratio between wages and rent prices) in urban areas. The researchers from the IMF Elfayoumi et al. (2021) investigate the link between rental market regulations and affordability of rental housing. Nelson et al. (2023) use our rent control index in their analysis of political determinants of housing benefits. Rubaszek, Stenvall, and Uddin (2025) using interacted panel VAR and data on 9 OECD member states find that rent control has no effect on the volatility of housing prices.
In addition, the rental housing market regulation indices presented here are cited and used for illustrative purposes in Alves et al. (2023), Barker (2019), Barker and Korczak-Krzeczowski (2023), Causa, Woloszko, and Leite (2020), Causa and Woloszko (2020), Cavalleri, Cournède, and Ziemann (2019), Claveres et al. (2020), Cohen (2021), Cournède, Ziemann, and De Pace (2020), Hill, Steurer, and Waltl (2020), Huesmann (2020), Jalil and Maidin (2021), Kettunen (2021), López Rodrı́guez and Marı́a de los Llanos (2020), Marsh et al. (2023), Mendes (2022), Micallef (2021), Naidin, Waltl, and Ziegelmeyer (2022), Nelson et al. (2023), Pastrana (2022), Reusens and Warisse (2018), Soaita (2022), Spencer, Nguyen, and Momen (2023), UNECE (2021), Vidal, Gil, and Martínez (2024), as well as Weber and Lee (2020). The regulation indices are also used in the McKinsey Report 2020 (Manyika et al. 2020).
Acknowledgments
Last but not least, I would like to thank all the people who contributed —either by data collection or by coding effort— to the creation of this database: Nabil AbuDayyeh (Jordan), Rehman Abdur (Pakistan), Haymanot Baheru (Sweden / Ethiopia), Nadine Bekdache (Lebanon), Debjani Bhattacharyya (India), Andrés Blanco Blanco (USA / Colombia), Viktor Burakov (Belorussia), Vanessa Caru (France), María Elena Cobas Cobiella (Spain), Hjalte Christiansen (Denmark), Youssouph Diémé (Senegal), Vedat Dicleli (Turkey), Angelique Diongue (Senegal), Emily Dix (Canada), Thomas David DuBois (China / USA), Pavel Dudin (Russia), Ece Ergün (Turkey), Markus Forster (Germany), Timofey Gerasimov (Ukraine), Zahra Gharibreza (Iran), Hildur Gróa Gunnarsdóttir (Iceland), Kari Gyllander (Norway), Mária Györgyi (Hungary), Alejandro Jacobo Ostapchuk (Argentina), Jakob Juul-Sandberg (Denmark), Nino Iarajuli (Georgia), Fidel Kalenga (Democratic Republic of the Congo), Dennis Keating (USA), Annika Klintefelt (Denmark), Sebastian Kohl (Germany), Julija Kolomijceva (Latvia), Matthijs Korevaar (Netherlands), Irene Kull (Estonia), Jussi Lahtinen (Finland), Andrei Lankov (Korea), Kwangun Lee (Korea), Julien Licheron (Luxembourg), Mette Lindbjerg Jørgensen (Denmark), Irma Lovera (Spain / Venezuela), Antii Malinen (Finland), Silvia Mastrantonio (Italy), Khulan Mendbayar (Mongolia), Valentinas Mikelėnas (Lithuania), Sonya Mirzoyan (Armenia), Dimitrios Moschos (Greece), Nir Mualam (Israel), Nenad Mušić (Croatia), George Mwaisondola (Tanzania), Sergio Nasarre Aznar (Spain), Peter Nägele (Lichtenstein), Mounira Nouri (Tunisia), Aleksei Netšunajev (Estonia), Are Oust (Norway), Sane Pashane Zuka (Malawi), Linus Pfeiffer (Germany), Maja Pindstrup (Greenland), Nikos Potamianos (Greece), Rajvi Prajapati (India), Yulia Prozorova (Russia), Andrei Quintiá Pastrana (Spain), Victor Reis (Portugal), Maridalia Rodriguez (Spain / Dominican Republic), Carles Sala Roca (Spain), Dale Schuss (Canada), Perakotuwe W. Senaratne (Sri Lanka), Kua Hui Shan (China), Dmitriy Shevyakov (Russia), Boriss Siliverstovs (Latvia), Derck Stabler (Netherlands), Tamara Starič Petrović (Slovenia), Toshikazu Suto (Japan), Jón Rúnar Sveinsson (Iceland), Irina Veinberga (Latvia), Alberto Javier Villar Calvo (Mexico), Sofie Waltl (Austria), Kurt Xerri (Malta), Rima Zenevskienė (Lithuania).