US study into preventing housing boom and bust

New research published by the Lincoln Institute of Land Policy shows how housing price bubbles grow and burst on a regional basis -- and how they might be prevented or limited in the future by targeting policies to specific metropolitan areas.

Preventing Housing Price Bubbles: Lessons from the 2006-2012 Bust, by James R. Follain and Seth H. Giertz, includes a comprehensive survey of the wide regional variation in the boom and bust in housing prices surrounding the 2008 crisis. Based on their analysis, the researchers suggest a pathway for more targeted intervention, rather than monetary policy implemented on a one-size-fits-all national level.

"Monetary policy is of limited use, given that price appreciation varies so widely across local markets," Follain and Giertz say. "Countercyclical capital buffers--which would raise capital requirements for financial institutions during the initial stages of the price bubble and reduce them during the period of decline--are much more promising because they could be designed to put the brakes on only in those markets where bubbles appear to be developing."

The growing availability of geographically detailed data makes this approach to bubble prevention much more viable than in the past, the researchers say.

The recent boom and bust in house prices generated widespread fallout, affecting metropolitan areas across the country. But the extent of the damage varied widely. In some metropolitan areas housing prices fell more than 50 percent while in others prices barely declined. These differences indicate that local market conditions played an important role in determining how the crisis played out. As a result, national aggregates were an unreliable guide to both housing market performance and the design of policies to mitigate the crisis.

In Preventing Housing Price Bubbles: Lessons from the 2006-2012 Bust, Follain and Giertz document how econometric models can be used to address some of the complex issues that have arisen since the house price bust. In particular, these models provide valuable insights into the interrelationships between house price patterns and their drivers--including new drivers that changed the fundamental dynamics of housing markets, such as the size of the distressed real estate inventory, the pace of price appreciation, and the amount of subprime lending.

These changes made policymaking in mid-crisis especially challenging. To illustrate the point, the authors analyze one of the major programs put in place to stem the spread of foreclosures. The Housing Affordable Modification Program (HAMP) was developed in 2007 just as the destructive fallout of the crisis began to appear. Traditional tools for measuring and managing the crisis were insufficient. The design of HAMP thus rested upon a number of critical judgments about borrower and lender behavior made without the benefit of strong empirical support.

While recognizing the challenges of responding to a bust once it has begun, the authors suggest that attempts to deal with any future crises of this type would benefit from a different approach, including an initial focus on hardest-hit markets to fine-tune program parameters; the development of longer-term forecasts of house prices for local markets; greater efforts to foster more cooperation among all levels of government; and fuller recognition of the inherent weaknesses of securitization.

The researchers recommend how econometric results can be used to identify and prevent, or at least limit, the formation of future house price bubbles -- with the emphasis on local countercyclical capital policies. These types of "buffers" have been deployed on a regional basis in Europe, but are less well recognized as part of the regulatory arsenal in the U.S.