[Standard theory predicts a positive relationship between risk and return, yet recent data show that housing returns vary positively with risk in some markets but negatively in others. This paper rationalizes these cross-market differences in the risk-return relationship for housing, and in so doing, explains the puzzling negative relationship. The paper shows that when the current house provides a hedge against the risk associated with the future housing consumption, households are willing to accept a lower return to compensate for risk, thus weakening the positive risk-return relationship. Further, in markets with less elastic housing supply and a growing population, hedging incentives can be sufficiently strong to make the relationship negative. The empirical analysis confirms these predictions, suggesting that hedging incentives, housing supply, and urban growth are indeed central to understanding the risk-return relationship for housing.]

Standard theory predicts a positive relationship between risk and return, yet recent data show that housing returns vary positively with risk in some markets but negatively in others. This paper rationalizes these cross-market differences in the risk-return relationship for housing, and in so doing, explains the puzzling negative relationship. The paper shows that when the current house provides a hedge against the risk associated with the future housing consumption, households are willing to accept a lower return to compensate for risk, thus weakening the positive risk-return relationship. Further, in markets with less elastic housing supply and a growing population, hedging incentives can be sufficiently strong to make the relationship negative. The empirical analysis confirms these predictions, suggesting that hedging incentives, housing supply, and urban growth are indeed central to understanding the risk-return relationship for housing.

[This article examines how price risk affects housing demand. It identifies two relevant channels: a financial risk effect that reduces demand, and a hedging effect that increases demand since current homes may hedge future housing costs. The latter dominates when hedging incentives are strong, namely when the likelihood of moving up the housing ladder is high and the tendency to move across markets is low. For households with weak hedging incentives, the article finds negative effects of price risk on the timing and size of home purchases, but positive effects for households with strong hedging incentives.]

This article examines how price risk affects housing demand. It identifies two relevant channels: a financial risk effect that reduces demand, and a hedging effect that increases demand since current homes may hedge future housing costs. The latter dominates when hedging incentives are strong, namely when the likelihood of moving up the housing ladder is high and the tendency to move across markets is low. For households with weak hedging incentives, the article finds negative effects of price risk on the timing and size of home purchases, but positive effects for households with strong hedging incentives. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

Abstract In Los Angeles, all-cash home purchases quintupled during the last decade. Compared with an else-equal mortgage offer, a cash offer is associated with 29 percent shorter time-to-close and a 2–3.9 percent price discount, indicating a substantial amount of financing risk—the risk to a seller that a transaction may not close on time and may fail to occur again because a mortgage contingency fails. The estimated cash discount aligns well with a canonical model calibrated to the sample market. Our findings reveal that closing risk alone is insufficient to explain the cash discount. Rather, it turns on the possibility that a property back on the market may fail to sell, requiring a substantial risk compensation. The estimated cash discount is smaller during booms and in larger markets, highlighting the inseparability of financial frictions in the mortgage market and search frictions in the housing market.

We perform a comprehensive neighborhood-level analysis of housing supply. Predictions of floor space and housing unit supply elasticities using our estimates average 0.5 and 0.3 across all urban neighborhoods in the United States, exhibiting greater variation within than between metro regions. New construction accounts for about 50% of unit supply responses, with important additional roles for teardowns and renovations. Supply responses grow with central business district distance mostly from the increasing availability of undeveloped land, flatter land, and less regulation. Identification comes from variation in labor demand shocks to commuting destinations, as aggregated using insights from a quantitative spatial equilibrium model.

Abstract We examine how team allocation shapes mutual fund managers’ compensation as well as their future productivity and careers. Assignment to a high-quality team lowers immediate compensation but accelerates career development—sharpening investment skill, boosting media visibility, deepening industry and style specialization, and raising future revenue. Team quality also raises promotion odds and explains the steep, tenure-based earnings profile common in asset management. Team allocation therefore acts as a career-steering mechanism embedded in fund-family compensation contracts.

Abstract Using sales and leasing data, this paper finds three novel effects of a higher property transaction tax: higher buy-to-rent transactions alongside lower buy-to-own transactions despite both being taxed, a lower sales-to-leases ratio, and a lower price-to-rent ratio. This paper explains these facts by developing a search model with entry of investors and households, households choosing to own or rent in the presence of credit frictions, and homeowners deciding when to move house. A higher transaction tax reduces homeowners’ mobility and increases demand for rental properties, which explains the empirical facts and leads to a lower homeownership rate. The deadweight loss is large at 111% of tax revenue, with more than half of this due to distorting decisions to own or rent.

Abstract We study how financial constraints affect the housing market by exploiting a regulatory change that increases the down payment requirement for homes selling for $$$1M or more. Using Toronto data, we find that the policy causes excess bunching of homes listed at $$$1M and heightened bidding intensity for these homes, but only a muted response in sales. While difficult to reconcile in a frictionless market, these findings are consistent with the implications derived from an equilibrium search model with auctions and financial constraints. Our analysis points to the importance of designing macroprudential policies that recognize the strategic responses of market participants.