"Real Estate" search produced two articles in Journal of Forensic Economics and none in Journal of Legal Economics.
Not surprising: income producing assets may be treated as any business.
There is a large existing business losses literature.
Not surprising: trade associations exist in real estate and appraisal.
E.g. National Association of Real Estate Appraisers (NAREA)
Not surprising: large academic literature in real estate.
No need to reinvent the wheel.
There may be some room in NAFE.
NAFE covers the overlap between academic literature and practitioner.
Some real estate losses are in sale only.
No explicit stream of income.
Trade associations, in this case, tend to be light on academic grounding.
Some support is technolocially advanced in statistics, but not in economic theory, which imposses an interpretation problem.
Academic literature often requires some "translation" to put into practice.
Cutting-edge research cannot always be used out of the box.
Some Economic and Considerations
Real estate expert witnesses deal with various case types.
Traditional business losses, takings (eminent domain), land-use regulation, environmental and safety regulations, county mass appraisal, condemned property, etc.
\(V = R/i\) still holds and \(i\) estimates are still controversial.
Income Capitalization Approach
Potential gross income (PGI), effective gross income (EGI), and net operating income (NOI)
Direct Valuation Approach
Comparable sales (or mass appraisal)
Hedonic modeling
Some Legal Considerations
States may dictate how you make calculations in detail.
E.g. in many states appraisal boards effectivily determine appraisal proceedures.
States may require additional credentials.
E.g. appraiser's licence or certificate.
Direct Valuation Approach
Hedonic Approach
Rationale: real estate is like a bundle of homogeneous services
The hedonic model estimates the "shadow price" of each service in order to measure the overall change in housing series prices.
E.g. \(lnP_{th} = \sum_{c=1}^C \beta_{c}z_{cth}+ \sum_{t=1}^T \delta_{t}d_{th}+ \varepsilon_{th}\)
Comparable Approach
Rationale: real estate is idiosyncratic, so use a selected small sample.
Match \(n\) recent sales and make adjustment to the expected sales price.
Adjustments are based (normally) on statistical relationships
Case One: Poor County Assessment
One school district overlaps two counties with very different appraising techniques.
A party has two properties, one in each county but both within the school district.
The county within state compliance is sued for "over assessing" since the other county assesses at a lower rate.
State compliance is determined via state approved techniques.
Error estimation and stratification
Data "provided" by regional MLS
In this case the expert witness has very little discretion except in data verification.
Mass Assessment Comparable Approach
Implicit errors from the counties' mass appraisal models were correlated with existing housing data. (I.e. using data the counties used to conduct their mass assessment comparable apporach.)
Neither efficient or unbiased.
In this cases the board approved proceedures are not producing the expected results.
There is room for considerable crituque.
Case Two: Federal Redesigniation of Flood Zones
Update of federal flood zone designation in 2008 changed insurance rates and thus housing values of many homes in the Saint Louis area.
Comparable approach less useful in this case. A log-linear hedonic model was used to estimate potential losses using spatial econometric techniques to estimate the change of housing values at the edge of the existing boundaries.
About a 9 percent loss in value was estimated.
In this case the Federal Emergency Management Agency and the Army Corps of Engineers incorporated potential housing loss estimates into their consideration.