UC Berkeley

This dissertation explores the relationship between finance and welfare, focusing on how the expansion of credit supply in the beginning of the 2000s, leading to the 2007 financial crisis, affected U.S. households. This dissertation helps advance the study of how financial policies affect households' well- being.

In the first chapter, I study the effect of access to credit on family structure. There is a large debate over the welfare effects of the early 2000s housing boom and bust. One potentially important welfare effect is the impact of mortgage credit expansion on family structure. Exploiting pre-housing boom variation on the distribution of old homeowners who live alone and are older than 65, I conduct within-county analysis with zip code level data to causally identify the effect of access to credit on fertility outcomes through a channel associated with a more efficient reallocation of the existing housing stock among households. I examine two other housing channels, house wealth gains and new construction, and show that the most relevant channel is the reallocation, which allows young households to access space by either moving to larger homes or achieving homeownership earlier in their life-cycle. A one standard deviation increase in reallocation leads to a 6.4% increase in fertility from 2000 to 2006. The same increase in house prices leads to only a 2.7% increase, and in new construction leads to a 1.5% decline in fertility from 2000 to 2006. I estimate that approximately 500,000 babies were born between 2000 and 2006 because of the reallocation channel.

In the second chapter, I study the effect of housing demand on house prices through an interest rate channel. In the last housing boom, strong house price growth only lasted until 2005. Why did house price growth slowed down in 2006? This chapter studies the effect of interest rate changes on housing demand at the end of a housing boom and the subsequent effect on house prices. I use three different proxies for housing demand, based on Google search data on search terms likely to be used during the process of purchasing a home, such as "remax", "construction", or "real estate". A one- standard deviation increase in the change in interest in purchasing a home from 2005 to 2006, measured by the Google search volume, leads to a 0.4 standard deviation increase in contemporaneous house price growth. To identify the interest rate channel, I first compute a household income threshold for each county, defined as the necessary income to afford an interest-rate-only mortgage on a county's average loan in 2005. I then exploit the slope of the county's income distribution around this affordability threshold to estimate the fraction of households that, after an increase in mortgage interest rates from 2005 to 2006, could no longer afford to pay an interest-rate-only mort- gage. I use this fraction as an instrumental variable for housing demand. The IV beta is remarkably close to the OLS beta, and confirms the large effect of housing demand on house prices in 2006 through an interest rate channel. This chapter sheds light on the transition process between the housing boom in the 2000s and the subsequent financial crisis, and contributes to a better understanding of the impact of monetary policy on housing demand and house prices at the end of a housing boom.