This dissertation explores intergenerational mobility and inequality in the early twentieth century. The first chapter asks whether economic downturns increase or decrease mobility. I estimate the effect of the Great Depression on mobility, linking a sample of fathers before the Depression to their sons in 1940. I find that the Great Depression lowered intergenerational mobility for sons growing up in cities hit by large downturns. The effects are driven by differential, selective migration: the sons of richer fathers are able to move to better destinations. The second chapter compares historic rates of intergenerational mobility to today. Based on a sample matched from the Iowa 1915 State Census to the 1940 Federal Census, I argue that there was more mobility in the early twentieth century than is found in contemporary data, whether measured using intergenerational elasticities, rank-rank correlations, educational persistence, or occupational status measures. In the third chapter, I detail the machine learning method used to create the linked census samples used in chapters 1 and 2. I use a supervised learning approach to record linkage, training a matching algorithm on hand-linked historical data which is able to efficiently and accurately find links in noisy in historical data.
