Zoning and Housing Affordability

Vanessa Brown Calder has posted Zoning, Land-Use Planning, and Housing Affordability to SSRN. It opens,

Local zoning and land-use regulations have increased substantially over the decades. These constraints on land development within cities and suburbs aim to achieve various safety, environmental, and aesthetic goals. But the regulations have also tended to reduce the supply of housing, including multifamily and low-income housing. With reduced supply, many U.S. cities suffer from housing affordability problems.

This study uses regression analysis to examine the link between housing prices and zoning and land-use controls. State and local governments across the country impose substantially different amounts of regulation on land development. The study uses a data set of court decisions on land use and zoning that captures the growth in regulation over time and the large variability between the states.

The statistical results show that rising land-use regulation is associated with rising real average home prices in 44 states and that rising zoning regulation is associated with rising real average home prices in 36 states. In general, the states that have increased the amount of rules and restrictions on land use the most have higher housing prices.

The federal government spent almost $200 billion to subsidize renting and buying homes in 2015. These subsidies treat a symptom of the underlying problem. But the results of this study indicate that state and local governments can tackle housing affordability problems directly by overhauling their development rules. For example, housing is much more expensive in the Northeast than in the Southeast, and that difference is partly explained by more regulation in the former region.

Interestingly, the data show that relatively more federal housing aid flows to states with more restrictive zoning and land-use rules, perhaps because those states have higher housing costs. Federal aid thus creates a disincentive for the states to solve their own housing affordability problems by reducing regulation. (1)

This paper provides additional evidence for an argument that Edward Glaeser and others have been making for some time now.

Local governments won’t make these changes on their own. Nonetheless, local land-use decisions have a large negative impact on many households and businesses who are not currently located within the borders of the local jurisdictions (as well as some who are). As a result, the federal government could and should take restrictive land use regulation into account when it allocates federal aid for affordable housing.

The Obama Administration found that restrictive local land-use regulations stifled GDP growth in the aggregate. Perhaps reforming land-use regulation is something that could garner bipartisan support as it is a market-driven approach to the housing crisis, a cause dear to the hearts of many Democrats (and not a few Republicans).

Regression Aggression: Statistics and Disparate Impact

The Third Circuit affirmed, in Rodriguez et al. v. National City Bank et al., No. 11-8079 (Aug. 12, 2013), the denial of final approval “of the parties’ proposed settlement and certification of the settlement class” in a mortgage loan discrimination case brought by minority borrowers who claimed a disparate impact resulting from how the defendants charged borrowers. (4)

The part of the opinion that I found most interesting (but not compelling) was where it discussed the statistical work that the plaintiffs had done to support their case.  The Court states that

Even if Plaintiffs had succeeded in controlling for every  objective  credit-related variable – something no court could have reviewed because the analyses are not of record – the regression analyses  do not even purport to control for individual, subjective considerations.  A loan officer may have set an individual borrower’s interest rate and fees based on any number of non-discriminatory reasons, such as whether the mortgage loans were intended to benefit other family members who were not borrowers, whether borrowers misrepresented their income or assets, whether borrowers were seeking or had previously been given  favorable loan-to value terms not warranted by their credit status, whether the loans were part of a beneficial debt consolidation, or even concerns the loan officer  may have  had  at the time  for the financial institution irrespective of the borrower. While those possibilities do not necessarily rebut the argument that the Discretionary Pricing Policy opened the door to biases that individual loan officers could have harbored,  they  do undermine the assertion that there was a common and unlawful mode by which the officers exercised their discretion. (26-27)

I have not read the plaintiffs’ study, but the Court’s logic seems suspect to me. I can’t imagine how a statistician would “control for individual, subjective considerations,” particularly as that appears to be an infinite set of variables. Indeed, the Court gives little meaningful guidance as to what a comprehensive regression analysis would look like. What “individual, subjective considerations” would they include?  Where would that data exist to be studied?

The court does note some serious problems with the plaintiffs’ case, including the fact that they did not introduce their data or regression analyses into the record.  But those failings are not sufficient to explain the Court’s reasoning in the selection quoted above.

This case might be ripe for reconsideration or an en banc review, even if just to clarify what the Court wants from plaintiffs in future disparate impact cases.