The first essay, “Pricing Housing Market Returns,” finds the housing premium to be smaller than the equity premium. Using state-level data that spans the 1983 to 2006 period, I estimate the asset pricing Euler equations from the intertemporal consumption problem faced by a representative consumer with Epstein-Zin (EZ) preferences. The EZ Capital Asset Pricing Model captures a large proportion of the variation in housing returns over the sample period, and I find there to be heterogeneity in the structural parameter estimates across geographies. Controlling for the risk priced by the model and the consumption value of housing, I find that the housing premium is smaller than the equity premium. This result is surprising given that frictions, such as high transaction costs and borrowing constraints, affect the investor in housing more than the investor in equities. I examine institutional differences between the asset classes and find that some of the difference between the two premia may be related to differences in the tax treatment between the two asset classes.
The second essay, “Non-durable Consumption Volatility and Illiquid Assets,” finds that factors beyond the volatility of asset payoffs may significantly affect the volatility of the agent’s consumption stream. The empirical failure of consumption-based asset pricing models is often attributed to the lack of volatility in aggregate measures of consumption. However, I illustrate in this paper that frictions faced by agents may lead to much higher levels of volatility in individual consumption than we observe in the aggregate data. I develop a life-cycle model of in which the consumer derives utility from non-durable consumption and stock in a risky asset: housing. Non-convex adjustment costs generate lumpy changes in the stock of the risky asset over the life-cycle. The model predicts that non-durable consumption volatility is increasing in both the ability to borrow against the assets held in the consumer’s portfolio and in the illiquidity of the portfolio.
The third essay, “Local and Global Risks in U.S. Housing Markets,” finds that variation in the cross section of expected housing market returns is better explained by a local CAPM model than by a global CAPM model. Housing is unlike many other assets in that it is primarily traded in local markets. The 2000 U.S. Census indicates that over 66% of housing units are owner occupied. For mean-variance optimizing investors, relatively small investment costs (less than 3.5% annually) will prevent the investor from optimally investing in housing markets in which the investor doesn’t reside. I propose two possible models for U.S. housing markets. The local CAPM assumes that only investors residing in the geographic region that constitutes market i invest in housing market i. The global CAPM assumes that investors who don’t reside in the geographic region that constitutes market i have costless access to the assets in that market. I test the ability of these models to explain the cross section of expected real housing returns and find that smaller mean pricing errors are associated with the local model.