Housing Market Spillovers: Evidence from an Estimated DSGE Model

70 Pages Posted: 16 Mar 2008

See all articles by Stefano Neri

Stefano Neri

Bank of Italy

Matteo M. Iacoviello

Federal Reserve Board - Trade and Financial Studies

Multiple version iconThere are 2 versions of this paper

Date Written: January 2008

Abstract

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.

Keywords: House prices, Collateral Constraints, Bayesian methods, Two-sector Models

JEL Classification: E32, E44, E47, R21, R31

Suggested Citation

Neri, Stefano and Iacoviello, Matteo M., Housing Market Spillovers: Evidence from an Estimated DSGE Model (January 2008). Bank of Italy Temi di Discussione (Working Paper) No. 659. Available at SSRN: https://ssrn.com/abstract=1105750 or http://dx.doi.org/10.2139/ssrn.1105750

Stefano Neri (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy
+39 06 4792 2821 (Phone)

Matteo M. Iacoviello

Federal Reserve Board - Trade and Financial Studies ( email )

20th St. and Constitution Ave.
Washington, DC 20551
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
515
rank
23,415
Abstract Views
2,374
PlumX Metrics