English, Article, Journal or magazine article edition: Housing market spillovers : evidence from an estimated DSGE model Matteo Iacoviello; Stefano Neri

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Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Housing market spillovers: Evidence from an estimated DSGE model
Author
  • Matteo Iacoviello
  • Stefano Neri
Physical Description
  • preprint
Notes
  • We study sources and consequences of fluctuations in the housing market. The upward trend in real housing prices of the last 40 years can be explained by slow technological progress in the housing sector. Over the business cycle, housing demand and housing technology shocks explain one-quarter each of the volatility of housing investment and housing prices. Monetary factors explain 20 percent, but they played a bigger role in the housing cycle at the turn of the century. We show that the housing market spillovers are non-negligible, concentrated on consumption rather than business investment, and have become more important over time.
  • Housing, Wealth E¤ects, Bayesian Estimation, Two-sector Models
  • RePEc:nbb:reswpp:200810-20
  • Using U.S. data and Bayesian methods, we quantify the contribution of the housing market to business fluctuations. The estimated model, which contains nominal and real rigidities and collateral constraints, is used to address two questions. First, what shocks drive the housing market? We find that the upward trend in real housing prices of the last 40 years can be explained by slow technological progress in the housing sector. Over the business cycle instead, housing demand and housing technology shocks account for roughly one-quarter each of the volatility of housing investment and housing prices. Monetary factors account for about 20 percent, but they played a major role in the housing market cycle at the turn of the century. Second, do fluctuations in the housing market propagate to other forms of expenditure? We find that the spillovers from the housing market to the broader economy are non-negligible, concentrated on consumption rather than business investment, and they have become more important over time, to the extent that financial innovation has increased the marginal availability of funds for credit-constrained agents.
  • Housing, Collateral Constraints, Bayesian Estimation, Two-sector Models
  • RePEc:boc:bocoec:659
  • The ability of a two-sector model to quantify the contribution of the housing market to business fluctuations is investigated using U.S. data and Bayesian methods. The estimated model, which contains nominal and real rigidities and collateral constraints, displays the following features: first, a large fraction of the upward trend in real housing prices over the last 40 years can be accounted for by slow technological progress in the housing sector; second, residential investment and housing prices are very sensitive to monetary policy and housing demand shocks; third, the wealth effects from housing on consumption are positive and significant, and have become more important over time. The structural nature of the model allows identifying and quantifying the sources of fluctuations in house prices and residential investment and measuring the contribution of housing booms and busts to business cycles.
  • House prices, Collateral Constraints, Bayesian methods, Two-sector Models
  • RePEc:bdi:wptemi:td_659_08
Language
  • English
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