City Equilibrium With Borrowing Constraints: Structural Estimation and General Equilibrium Effects

Abstract

This article develops a general equilibrium model of location choice where mortgage approval rates determine household-specific choice sets. Estimation of the model using San Francisco Bay area data reveals that the price sensitivity of borrowing constraints explains about two-thirds of the price elasticity of neighborhood demand. General equilibrium analysis of the 2000-2006 relaxation of lending standards predicts the following impacts on prices and neighborhood demographics: (i) an increase in house prices accompanied by a compression of the price distribution and (ii) a reduction in the isolation of Whites reflecting gentrification. Both predictions are supported by empirical observation. * Manuscript

Mortgage Finance and Climate Change: Securitization Dynamics in the Aftermath of Natural Disasters

“…Hence shifts in the amount of securitized debt may be due to shifts in house prices at constant lending standards and constant LTV. In addition, housing prices may respond to the supply of credit (Favara & Imbs 2015, Ouazad & Rancière 2019. Lenders may also aid in rebuilding by providing credit (Cortés 2014).…”

Financial Development, Growth, and Crisis: Is There a Trade-Off?

“…Thus, changes in the distribution of housing prices may be greater than what would be predicted using standard metro-level estimates. Ouazad and Rancière's (2016a) estimates of supply elasticities using 30m by 30m satellite data also display a positive correlation between supply elasticities and the distance to the central business district, a potential evidence of the importance of within-city distribution of elasticities in driving changes in wealth inequalities. Elasticities of the provision of higher education services are also likely far from the perfectly elastic benchmark.…”

“…Recent developments in the use of micro data now enable a microeconomic analysis of such general equilibrium effects. Overall, as in Ouazad and Rancière (2016a), financial deepening and the rise of credit are unlikely to yield uniformly positive welfare impacts, even before the onset of a credit downturn.…”

“…Ouazad and Rancière (2016a) plots the coefficients of a regression of census tractlevel white population changes as a fraction of initial population, on a set of dummies for quantiles of the initial fraction of Black population in 2000. The red line is the regression for metropolitan areas with high increase in approval rates as predicted by the instrument described above and the blue dotted line is for metropolitan areas with a low predicted increase in approval rate.…”