Refinancing Cross-Subsidies in the Mortgage Market (with Alessandro Gavazza, Lu Liu, Tarun Ramadorai, Jagdish Tripathy), July 2022.
In household finance markets, inactive households can implicitly cross-subsidize active households who promptly respond to financial incentives. We assess the magnitude and distribution of cross-subsidies in the mortgage market. To do so, we build a model of household mortgage refinancing and structurally estimate it on rich administrative data on the stock of outstanding UK mortgages in June 2015. We estimate sizeable cross-subsidies during this sample period, from relatively poorer households and those located in less-wealthy areas towards richer households and those located in wealthier areas. Our work highlights how the design of household finance markets can contribute to wealth inequality. Estimated cross-subsidies may differ in more recent periods given changes in the UK mortgage market since 2015.
The Cost of Labor Supply Biases (draft available on request)
This paper investigates an important dimension of the typical flexibility versus security trade-off that is used to frame self-employment, namely, behavioral frictions in exploiting flexibility. I study the welfare cost of behavioral biases in intensive margin labor supply decisions for a group of self-employed workers who are free to pick their hours. In response to salient wage variation, workers’ behavior implies a large and positive daily Frisch elasticity of 0.80 (s.e. 0.10). But in response to more common wage fluctuations their labor supply function is downward sloping for a range of wages, which is incompatible with even the most unrestrictive models of labor supply. In the spirit of Chetty-Looney-Kroft (2009), I use the salient Frisch elasticity to characterize preferences, and contrast outcomes under observed and optimal labor supply. A new sufficient statistics formula translates these deviations into daily welfare losses, which are economically significant. Point estimates range from two to five percent of income. Annually this can imply welfare losses of over £1,000.