UCLA

Chapter 1 examines the relationship between marriage and the economy during the 1930s.The Great Depression provides an ideal setting to examine the impact of economic downturns and recoveries on marriage outcomes. Using microeconomic data, I find that during the Great Depression, a standard deviation decrease in retail sales per capita, my proxy for local GDP, lowered a woman's probability of marriage by 18 percent. During the first few years of the crisis, the effect of GDP on marriage rates operated largely through high male unemployment.

Chapter 2 explores the impact of housing on marriage in the postwar baby boom period. The U.S. experienced an unprecedented increase in fertility during the baby boom. The elevated birth rates from 1946 to 1964 were driven in part by a shift toward more universal marriage; marriage rates increased by 25 percent from 1930 to 1950 and the average age of marriage fell by two years. This chapter argues that growth in the supply of housing after World War II contributed to the expansion of marriage during this period. Specifically, the paper estimates the effect of additional building permits at the city level on individual marriage outcomes. An instrumental variable approach is used to address endogenous permit location. I find a standard deviation increase in permits to a city increased the probability of marriage in that city by 13 to 16 percent over a two-year period. The estimates suggest that the growth in housing supply in the late 1940s can explain about 33 percent of the difference in marriage rates between 1930 and 1950. Overall, the increase in housing supply can account for nearly ten percent of the baby boom.

Chapter 3 re-examines the Easterlin hypothesis with microeconomic data. Easterlin argues relative income was the primary driver of the post war baby boom. I test this hypothesis using state income data in conjunction with individual level data from the U.S. census. I find relative income did positively impact completed fertility. However, this effect largely operates through a cohort effect and relative income can explain at most fifty percent of the baby boom.