Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective

In a model with housing collateral, the ratio of housing wealth to human wealth shifts the conditional distribution of asset prices and consumption growth. A decrease in house prices reduces the collateral value of housing, increases household exposure to idiosyncratic risk, and increases the conditional market price of risk. Using aggregate data for the United States, we find that a decrease in the ratio of housing wealth to human wealth predicts higher returns on stocks. Conditional on this ratio, the covariance of returns with aggregate risk factors explains 80% of the cross-sectional variation in annual size and book-to-market portfolio returns. HOUSE PRICE FLUCTUATIONS PLAY AN IMPORTANT ROLE in explaining the time-series and the cross-sectional variation in asset returns. Given the magnitude of the housing market, this is unsurprising. This paper shows that the way in which housing affects asset returns is through the role of housing as a collateral asset. We identify a novel collateral channel that transmits shocks in the housing market to risk premia. In a model with collateralized borrowing and lending, the ratio of housing wealth to human wealth, the housing collateral ratio, changes the conditional distribution of consumption growth across households. When the collateral ratio is low, the dispersion of consumption growth across households is more sensitive to aggregate consumption growth shocks, and this raises the market price of aggregate risk. ∗Hanno N. Lustig is from the University of Chicago and NBER; and Van Nieuwerburgh is from the New York University Stern School of Business. The authors thank Thomas Sargent, Andrew Abel, Fernando Alvarez, Andrew Atkeson, John Cochrane, Timothey Cogley, Steven Grenadier, Robert Hall, Lars Peter Hansen, John Heaton, Narayana Kocherlakota, Dirk Krueger, Sydney Ludvigson, Monika Piazzesi, the editor, Robert Stambaugh, Laura Veldkamp, Pierre-Olivier Weill, Amir Yaron, and an anonymous referee. We also benefited from comments from seminar participants at Duke University, Stanford GSB, University of Iowa, Université de Montreal, New York University, University of Wisconsin, University of California at San Diego, London Business School, London School of Economics, University College London, University of North Carolina, Federal Reserve Bank of Richmond, Yale University, University of Minnesota, University of Maryland, Federal Reserve Bank of New York, Boston University, University of Pennsylvania, University of Pittsburgh, Carnegie Mellon University GSIA, Northwestern University, University of Texas at Austin, Federal Reserve Board of Governors, University of Gent, UCLA, University of Chicago, Stanford University, the 2003 NBER Asset Pricing Meeting in Cambridge, the Society for Economic Dynamics Meeting in New York, and the North American Meeting of the Econometric Society in Los Angeles. For help with the data, we thank Kenneth French, Chris Lundblad, and Savina Rizova. Stijn Van Nieuwerburgh acknowledges financial support from the Stanford Institute for Economic Policy research and the Flanders Fund for Scientific Research.