Tag Archives: regression analysis

Zoning and Housing Affordability

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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).

Kroll on Mortgage Performance

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The Kroll Bond Rating Agency has issued an update of its residential mortgage-backed securities model methodology, Residential Mortgage Default and Loss Model. Before the financial crisis, ratings models seemed to be very reliable, data-driven models of probity and caution. We have since learned that different mortgage vintages (the year of origination) can behave very differently and ratings models could be based on simplistic assumptions. Hopefully, the updated Kroll model does not suffer from those flaws, although their key takeaways seem pretty basic to me:

  • Underwriting standards are the fundamental determinant of mortgage quality.
  • Negative home equity creates a major incentive for borrower default, resulting in substantial credit loss.
  • Credit scores continue to have value as a relative indicator of risk.
  • Inflation of real home prices above the long-term mean is unsustainable and represents increased credit risk. (4-5)

Kroll’s update does include some interesting revisions, including,

Reduced default expectations for purchase loans. It has long been observed that purchase loans generally have lower default risk than refinancings, all else being equal. This is attributed to the fact that a purchase represents an actual arms-length transaction which yields a more accurate view of a home’s value than an equivalent refinancing transaction. However the pre-crisis mortgage vintages showed high levels of default associated with purchase mortgages. This was largely due to the practice of extending credit to first time homebuyers, often on very favorable terms despite these borrowers having little credit history or poor credit history. This poor performance by purchase loans was reflected in the historical data regression analysis used to develop the RMBS model.

Based on analysis focused on both jumbo and conforming prime mortgages, KBRA has found that, for these loans, the traditional benefits of purchase loans remain well established, and we have adjusted the model ‘s treatment of purchase loans to reflect lower default expectations relative to equivalent refinancing mortgages. This revision is effective with the publication of this report.

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Penalty for high debt-to-income (DTI) loans. While the KBRA RMBS model does not contain a specific risk parameter based on DTI, it is our opinion that very high DTI loans can bear significant incremental risk. When we began to encounter newly originated loans with back-end DTIs in excess of 45%, we assigned an additional default penalty to such loans. This has been documented in presale reports for those rated RMBS backed by loans with high DTIs. (3)

Time will tell if Kroll got it right . . ..