In 1935, the United States passed Social Security Act (SSA) providing financial security to American families. I use the individual census data for 1940 and 1960 to show that women from states that allowed for more social spending under the SSA had substantially more children than women from states that allowed for lower social benefits. I also use a new panel of state-level fertility by parity between 1935 and 1959 to show that family allowances were connected to first, second and third parities, but that there was a differential effect according to the different social programs and race.

While the effect of credit on having a financial crisis is well-studied, its impact on recovering from the crisis is unresolved. This paper establishes the causal effect of loan supply shocks on the real economy using newly-collected archival data and a novel empirical strategy. The Bank of America was only bank large and geographically diversified enough to weather the Great Depression without shutting lending down completely did not select into better performing cities before the Depression. I find that cities with access to more stable lending from 1929 to 1933 had smaller contractions in economic activity in the same period. While cities with relatively little credit access during the 1930's did not recover to 1929 levels until 1940, Bank of America branched-cities grew during the Depression. Confirming the city-level results, there is a credit availability wage premium in individual-level data, even when controlling for workers' pre-crisis characteristics. These increases in wages are driven by a reallocation towards nontradable employment at the expense of the agricultural sector.

We provide the first nationally representative long-run series (1870–2020) of incarceration rates for immigrants and the US-born. As a group, immigrants have had lower incarceration rates than the US-born for 150 years. Moreover, relative to the US-born, immigrants’ incarceration rates have declined since 1960: immigrants today are 60% less likely to be incarcerated (30% relative to US-born whites). This relative decline occurred among immigrants from all regions and cannot be explained by changes in immigrants’ observable characteristics or immigration policy. Instead, the decline is part of a broader divergence of outcomes between less-educated immigrants and their US-born counterparts.

From 1999 to 2019, IPUMS collaborated with genealogical organizations to develop massive individual-level census datasets spanning the 1790 through 1940 period, and we are currently working on the 1950 census. This research note describes how our genealogical collaborations came about. We focus on our collaborations with the Church of Jesus Christ of Latter-Day Saints Family and Church History Department (later known as FamilySearch) and the private genealogical companies HeritageQuest and Ancestry.com.

What role did the use of convict labor play in the establishment of early labor unions? This paper introduces a model where certain firms employ convict labor, reproducing the empirical patterns observed in the data. Workers face reduced wages and migrate to other firms, while firms see heightened profits, exacerbating income inequality. In response, workers organize, form unions, and initiate strikes. The calibrated model highlights the role of unions in narrowing income disparities. Empirically, I use an instrumental variable approach to demonstrate that, at the turn of the 20 th century, convict labor significantly boosted union growth, strikes, and membership. This influence has persisted as regions with a history of heavy dependence on convict labor continue to display higher rates of union membership in the present day. These findings provide the first evidence of the role of coerced labor in the formation and persistence of labor unions.

This paper shows that immigration positively affected the development of organized labor in the United States at the beginning of the 20th century. I digitize archival data to construct the first county-level dataset on historical union membership in the U.S. and use a shift-share instrument to exploit plausibly exogenous variation in immigration between 1900 and 1920. Ifind that counties that received more immigration experienced an increase in the probability ofhaving any labor union, the share of unionized workers, the number of local union branches,and the average branch size. Exploring the mechanisms driving the effect, I find that theincrease occurred only among unions representing skilled workers, particularly in countiesmore exposed to the immigrants’ labor competition, and in places harboring less favorable attitudes towards immigration. Taken together, these results indicate that existing workersformed and joined labor unions due to both economic and social motivations. The findings shed light on a novel driver of unionization in the early 20th-century United States: in the absence of immigration, the average union density of this period would have been 17% lower.They also identify an unexplored consequence of immigration: the development of institutions that aim to protect workers’ status in the labor market.

Between the late 19th and early 20th centuries, millions of immigrants arrived in the United States seeking a better life. These newcomers brought with them diverse cultures, traditions, and languages, and contributed to the growth and development of the American economy. At the same time, migrants’ pathways were influenced by the transportation and housing infrastructure they encountered along the way. This dissertation considers migrants’ economic contributions and outcomes from the perspective of housing and transportation. The first chapter investigates the impact of housing regulation on the health and economic outcomes of mostly immigrant residents. I exploit variation arising from the Tenement House Act of 1901, which imposed minimum housing standards on new construction in New York City, to show that legislation improved children’s health and changed neighborhood composition. Although lower income households in treated neighborhoods were more often displaced relative to their higher income counterparts, tenement legislation is nonetheless responsible for two additional years of life in treated children who stayed. The second chapter examines the impact of the transition to steamships on immigrant destination choices and the resulting effects on innovative activity in the United States. Since sea surface winds between origin and destination were a determining factor in travel time by sail, the reduction in travel time when transitioning from sail to steam depends on exogenous wind patterns (Pascali 2017). Using newly transcribed data on international migrations from 1830 to 1880, I exploit the disproportionate decrease in between-country travel times to show that a one percent decrease in travel time increases the number of migrants by two percent. I find evidence that steamship induced migrants increased county-level innovation such that a one percentile increase in immigrant share among counties led to 0.49 more patents. This dissertation sheds new light on the experiences of immigrants during this pivotal period in American history, offering insights into the ways in which regulation and technology influenced the lives of those who sought a better future in the United States.

New hand-collected school administrative data from 1870s Virginia, alongside linked individual US Census records, reveals that temporary school closures had lasting effects on literacy and income in adulthood. Those affected by the closures had lower intergenerational economic mobility, particularly those from low-income backgrounds. The age at which the closures occurred also played a role with younger cohorts more affected by early developmental disruptions and older cohorts more affected by prolonged closures.

This paper examines how immigration affects native children’s economic opportunities leveraging linked U.S. censuses in the early twentieth century. Using the shift-share instrument for county-level immigration exposure, I find that childhood exposure to immigrants enhances native-borns’ adulthood economic performance. However, children of high-skilled fathers enjoy a higher positive impact than their peers, given the same exposure level. I investigate two potential channels and show that immigration-induced into-city migration explains only around 10% of the exposure effect. In addition, immigration encourages native children to advance on the occupational ladder and to specialize in less immigrant-intensive jobs.

Historians have taken as a defining characteristic of Chinese experience in the United States their inability to naturalize until the repeal of Chinese Exclusion in 1943. It is certainly true that treaty agreements, court rulings, and discrimina-tory legislation conspired to prevent the existence of Chinese American citizens. But scholars may have taken for granted Chinese migrants’ alien status and disen-franchisement more than they themselves did. In 1900, the US census recorded that 6.7 percent of the Chinese population had naturalized. These naturalized Chinese accomplished a seemingly impossible task and in so doing they exposed broader truths about the uncertain nature of citizenship in the postbellum era.

Leveraging the capabilities of the Historical Spatial Data Infrastructure (HSDI) and composite indices we explore the importance of children's built and social environments on health. We apply contemporary GIS methods to a set of 2000 historical school records contextualized within an existing HSDI to establish seven variables measuring the relative quality of each child's built and social environments. We then combined these variables to create a composite index that assesses acute (short-term) health risks generated by their environments. Our results show that higher acute index values significantly correlated with higher presence of disease in the home. Further, higher income significantly correlated with lower acute index values, indicating that the relative quality of children's environments in our study area were constrained by familial wealth. This work demonstrates the importance of analyzing multiple activity spaces when assessing built and social environments, as well as the importance of spatial microdata.

Innovation is a crucial determinant of long-run economic growth in advanced economies. This dissertation explores the economic and social determinants of the production and diffusion of innovation in the context of Europe and the United States in the late nineteenth and early twentieth century.The first chapter (jointly authored with Gaia Dossi) documents how out-migration impacts innovation in the country of origin of migrants. During the Age of Mass Migration, nearly fourmillion English migrants settled in the US. We construct a novel individual-level dataset link-ing English immigrants in the US to the UK census and complement it with the newly digitizeduniverse of UK patents. Using a new shift-share instrument for bilateral migration flows and atriple-differences design, we document a positive, significant, and persistent effect of exposureto US technology through migrant ties on the direction of innovation in Britain in 1870–1940.The individual-level analysis suggests that physical return migration is not the main factor un-derlying this “return innovation” effect. Instead, we find that migration ties generate infor-mation flows that facilitate the cross-border diffusion of novel knowledge. Furthermore, ourfindings suggest that market integration fostered by migration linkages is a crucial driver ofinformation flows.The second chapter (jointly authored with Lorenzo Spadavecchia) interprets out-migrationthrough the lenses of directed technical change and adoption theory. We study the impact ofimmigration restriction policies on technology adoption in countries sending migrants. Be-tween 1920 and 1921, the number of Italian immigrants to the United States dropped by 85%after Congress passed the Emergency Quota Act, a severely restrictive immigration law. In adifference-in-differences setting, we exploit variation in exposure across Italian districts to thismassive restriction against human mobility. Using novel individual-level data on Italian immi-grants to the US and newly digitized historical censuses, we show that this policy substantially hampered technology adoption and capital investment. We interpret this as evidence of di-rected technical adoption: an increase in the labor supply dampens the incentive for firms toadopt labor-saving technologies. To validate this mechanism, we show that more exposed dis-tricts display a sizable increase in overall population and employment in manufacturing. Weiii provide evidence that “missing migrants,” whose migration was inhibited by the Act, drive thisresult.The third chapter (jointly authored with Enrico Berkes, Gaia Dossi, and Mara P. Squiccia-rini) investigates how societies respond to adversity. After a negative shock, separate strandsof research document either an increase in religiosity or a boost in innovation efforts. In thispaper, we show that both reactions can occur at the same time, driven by different individuals within the society. The setting of our study is 1918–1919 influenza pandemic in the United States.To measure religiosity, we construct a novel indicator based on the naming patterns of new-borns. We measure innovation through the universe of granted patents. Exploiting plausibly exogenous county-level variation in exposure to the pandemic, we provide evidence that more-affected counties become both more religious and more innovative. Looking within counties,we uncover heterogeneous responses: individuals from more religious backgrounds further embrace religion, while those from less religious backgrounds become more likely to choose a scientific occupation. Facing adversity widens the distance in religiosity between science-oriented individuals and the rest of the population, and it increases the polarization of religious beliefs.

We present a new series on the trend of occupational task content between 1900 and 2020. We find that Black workers were concentrated in tasks that declined in demand over the last 120 years, while white workers were concentrated in tasks that increased in demand. We then use longitudinal data to show that transitions across occupational task content were racially biased, where Black workers ended up in occupations with lower-rewarded task content than their white counterparts. This bias also existed across generations in pre-World War II data, but not for post-World War II years. These results suggest that a given task-displacing technological shock will impact Black-white inequality within one generation, but not across generations.

French-Canadian child mortality in an early twentieth-century North American industrial city. The analysis is based on the exploitation of an original dataset constructed by linking the 1910 census data (IPUMS-Full Count) for Manchester, New Hampshire to Quebec Catholic marriage records (BALSAC) and geocoding census data at the household level (Sanborn Fire Insurance Maps). Our results suggest that the presence of maternal and paternal grandmothers in the city living in different households were associated with reduced child mortality and that French-Canadian women who arrived in the United States as children or young adults experienced higher child mortality compared to second-generation French Canadians and those who migrated at a later age.

How accurately can age of death be predicted using basic sociodemographic characteristics? We test this question using a large-scale administrative dataset combining the complete count 1940 Census with Social Security death records. We fit eight machine learning algorithms using 35 sociodemographic predictors to generate individual-level predictions of age of death for birth cohorts born at the beginning of the 20th century. We find that none of these algorithms are able to explain more than 1.5% of the variation in age of death. Our results suggest mortality is inherently unpredictable and underscore the challenges of using algorithms to predict major life outcomes.

In the first half of the twentieth century, deaths from infectious disease, especially among the very young, fell dramatically in American cities. However, as infant mortality fell and life expectancy rose, racial inequality in urban infectious disease mortality grew. In this paper, we show that the fall in mortality and the rise in racial inequality in mortality reflected two countervailing processes. The dramatic decline in infant mortality from waterborne diseases drastically reduced the total urban infectious disease mortality rate of both Black and white Americans while having a comparatively small effect on the total racial disparity in urban infectious disease mortality. In contrast, the unequal fall in tuberculosis mortality, particularly in the prime of life, widened racial inequality in infectious disease mortality in US cities.

BACKGROUND: Smoking is a leading cause of premature death across contemporary developed nations, but few longitudinal individual-level studies have examined the long-term health consequences of exposure to smoking. OBJECTIVE: We examine the effect of fetal and infant exposure to exogenous variation in smoking, brought about by state-level cigarette taxation, on adulthood and old-age mortality (ages 55‒73) among cohorts of boys born in the United States during the 1920s and 1930s. METHODS: We use state-of-the-art methods of record linkage to match 1930 and 1940 US full-count census records to death records, identifying early life exposure to the implementation of state-level cigarette taxes through contemporary sources. We examine a population of 2.4 million boys, estimating age at death by means of OLS regression, with post-stratification weights to account for linking selectivity. RESULTS: Fetal or infant exposure to the implementation of state cigarette taxation delayed mortality by about two months. Analyses further indicate heterogeneous effects that are consistent with theoretical expectations; the largest benefits are enjoyed by individuals with parents who would have been affected most by the tax implementation. CONCLUSIONS: Despite living in an era of continuously increasing cigarette consumption, cohorts exposed to a reduction in cigarette smoking during early life enjoyed a later age at death. While it is not possible to comprehensively assess the treatment effect on the treated, the magnitude of the effect should not be underestimated, as it is larger than the difference between having parents belonging to the highest and lowest socioeconomic groups. CONTRIBUTION: The study provides the first estimates of long-run health effects from early life exposure to cigarette smoking.

The estimation of racial disparities in health care, financial services, voting, and other contexts is often hampered by the lack of individual-level racial information in administrative records. In many cases, the law prohibits the collection of such information to prevent direct racial discrimination. As a result, many analysts have adopted Bayesian Improved Surname Geocoding (BISG), which combines individual names and addresses with the Census data to predict race. Although BISG tends to produce well-calibrated racial predictions, its resid-uals are often correlated with the outcomes of interest, yielding biased estimates of racial disparities. We propose an alternative identification strategy that corrects this bias. The proposed strategy is applicable whenever one's surname is conditionally independent of the outcome given their (unobserved) race, residence location, and other observed characteristics. Leveraging this identification strategy, we introduce a new class of models, Bayesian Instrumental Regression for Disparity Estimation (BIRDiE), that estimate racial disparities by using surnames as a high-dimensional instrumental variable for race. Our estimation method is scalable, making it possible to analyze large-scale administrative data. We also show how to address potential violations of the key identification assumptions. A validation study based on the North Carolina voter file shows that BIRDiE reduces error by up to 84% in comparison to the standard approaches for estimating racial differences in party registration. Open-source software is available which implements the proposed methodology.

The Great Depression is one of the worst social, financial, economic, and environmental disasters in modern American history. Economic and climate distress provoked a large internal migration of people. This thesis attempted to glean predictions about the migratory decisions in the 1930s using decision trees utilizing linked full count US census data from 1930 and 1940. Five different models were employed to assess the 52 million linked records. Using variables from one census year alone provided poor classification rates for the migrants but near perfect rates for the non-migrants. Using a combination of all variables across both years provided the highest success in classifying both migrants and non-migrants. However, this was achieved by successive splitting on the basis of a location identifier that combines county and state across the two years. Excluding the location identifier for 1940 alone did produce better success than single years but still misclassified a large proportion of the migrants. The analysis conclusively pointed to the excessive reliance on geographic variables for the decision tree to make splitting decisions, contrary to the expected demographic and occupation details. The reliance potentially hints at spatial relationships or local shocks, that are not captured in the census data. In conclusion, it appears that the census data is missing some attribute(s) that makes people arrive at the difficult decision of migrating.

This dissertation examines the philosophy, behaviors, and consequences of the educational investments of Asian American families in critical historical times from the Asian Exclusion Period (1882±1943) to the COVID-19 pandemic. Chapter 1 uses historical censuses to examine the social mobility of Asian Americans in the early 20th century. It reveals a contrasting pattern of high intergenerational educational mobility but low occupational mobility among U.S.-born Asians who came of age during the Exclusion. This chapter complements existing theories of immigrant assimilation that have overlooked the mobility experiences of Asian Americans despite explicit exclusionary laws and the disconnection between educational and occupational mobility. Chapter 2 examines the K±12 educational expenses of contemporary Asian American families using the nationally representative Consumer Expenditure Surveys (2009±2022). . Analyses suggest that Asians outspend Whites on K±12 education in general but most substantially on housing to improve their children's access to better public education. These results highlight housing expenditures as one of the most expensive forms of educational investments today. Chapter 3 uses interviews with middle-class Chinese and Indian parents in New Jersey (N = 44) between December 2020 and January 2022 to study childrearing philosophies and cautions against a simplistic description of Asian American parenting as academics-centered. I argue that middle-class Asian parenting can be better understood as an "inclusive assimilation" process: Asian parents aim for a well-rounded education that resembles the aim of White parenting, but similarly to other minority parents, they enrich the concept with racial socialization tasks in the face of rising anti-Asian violence. This pattern contests the unidirectional assimilation process that presumes White middle-class families as the default destination. Together, this dissertation shows how the American public tends to use parenting behaviors to measure Asian Americans' foreignness despite drastic changes in the group's demography.