Research 

Presentations: NBER DAE SI (2025), SITE Gender Conference (2024), EHA Annual Conference (2024), Cliometric Conference (2024), Chicago Federal Reserve, Harvard Graduate Economic History Workshop, Yale Economic History Workshop

Abstract: Due to data limitations, long-run changes in women's economic mobility are not well understood. Using a set of marriage certificates from Massachusetts over the period of 1850-1920, we link women and men to their childhood and adult census records to obtain a measure of occupational standing across two generations. Intergenerational mobility was higher for women than for men in the earliest 1850-70 cohort. Men's mobility increases by the 1880-1900 cohort, whereas women's does not, leading to a convergence. During a period with low married women's labor force participation, the choice of a partner was crucial for women's economic status. We find evidence of strong and increasing assortative matching prior to 1880, followed by declines to the 1900-20 cohort. Absent the increase in marital sorting, married women would have experienced the same increases in intergenerational mobility as did men in the sample. Finally, both men and women in the youngest cohort experience an increase in mobility and decreases in marital sorting, consistent with the widespread expansion of educational attainment during the ``High School Movement."  

Abstract: We introduce a new rule-based linking algorithm for historical Census records. We augment earlier ABE algorithms based on name, age and place of birth (Abramitzky, Boustan, Eriksson, 2012), with five matching characteristics – middle initial, county of residence, and spouse and parents’ names. Relative to basic ABE, ABE-Extra Information (“ABE-EI”) greatly increases match rates, improves accuracy and is similarly representative of the population on most attributes, with geographic mobility being one important exception. Relative to machine learning algorithms, ABE-EI has somewhat lower match rates, similar accuracy, improved representativeness, and offers full replicability.