Using a newly digitized database encompassing the universe of tariff lines across five US trade policy regimes between 1900 and 1940, we show that price dynamics combine with industry reliance on specific tariffs to generate large swings in average tariff levels. Intra-policy variation in tariffs is strongly predictive of import growth throughout our sample. Using linked Census data, we quantify the effects of imports on structural change in this era. We find that import growth decreases labor force participation and inhibits the transition into the expanding manufacturing and service sectors, especially among the young.

This article examines the long-term, intergenerational effects of financial crises on rich versus poor households. I study the first "Great Depression" originating from the Panic of 1873 in the United States and find that the economic consequences of this crisis persisted for over a century, especially for poor households. Using spatial variation in severity of the crisis and linked census and administrative records from 1870 to 2000, I trace how affected families fared across generations. Poor households, who had no wealth were unable to withstand the crisis in cities, were forced to relocate to rural areas with lower living costs. However, these areas offered worse educational opportunities and primarily lower-skilled jobs, potentially limiting prospects for future generations. Descendants of poor families with higher exposure to the crisis therefore show significantly lower education, income, and wealth. Importantly, these effects persist for four generations-well into the 2000s-and are most pronounced for households in the bottom third of the wealth distribution. Overall, my results suggest that recoveries from financial crises have historically been two-pronged: while some recover quickly and fully, lives of others-and their future generations-can be damaged irreparably.

In early twentieth-century America, many Blacks in the south had poor access to schooling. Philanthropist Julius Rosenwald and educator Booker T. Washington collaborated to help build schools in the south for Blacks in the 1920s and 1930s. This paper analyzes the geographic patterns of the schools that were built using funds donated by Rosenwald in the state of South Carolina. Some 446 of the 500 Rosenwald schools were located and mapped using a multi-step process, and then data related to these schools were analyzed in four state subregions. Rosenwald schools were built around the state, with relatively more schools built in the northern part of the state compared with the south, where a larger Black population in the south potentially points to less access to schools for Blacks at that time. Rosenwald funds required contributions from other sources, and the state, Blacks, and Whites all contributed. Interestingly, in the south, where there was a higher percentage of Blacks, Whites contributed a larger share towards the building of these schools in comparison with other state regions. The paper thus shows both the process and value of mapping these Rosenwald schools and analyzing this important historical time in South Carolina within a spatial construct.

We merge the longitudinally linked historical U.S. Census records with data on lynchings of Hispanics in Texas to investigate the impacts of historical lynchings of ethnic Mexicans in Texas on U.S.-born Mexicans Americans. Using variation in lynching incidents across counties over time, we explore the impacts of local exposure to lynchings during childhood on long-run outcomes such as earnings, education, and home ownership of adults in 1940. Our findings are suggestive of small, negative impacts, but we caution that more research in this area is needed for a more robust interpretation of the results.

This article describes the development of IPUMS full count datasets of the censuses of slave inhabitants of the United States in 1850 and 1860. These data are a result of two collaborations. The 1850 slave dataset stems from a collaboration between the Church of Jesus Christ of Latter-day Saints, whose volunteers transcribed the original manuscript forms, and IPUMS, which enhanced the raw data with editing, standardized coding procedures, constructed variables, and documentation. The 1860 dataset was the result of a similar collaboration between the genealogical company Ancestry and IPUMS. The article discusses the features of these datasets, their limitations, and suggests possible research uses.

This paper combines personnel records of the U.S. federal government with census data to study how shocks to the gender composition of an organization can persistently shift the gender norms of its workers. We exploit city-by-department variation in the sudden expansion of female clerical employment driven by America's entrance into World War I, and find that daughters of civil servants exposed to female co-workers are more likely to work later in life, command higher income, and have fewer children. The effects are driven by exposed fathers and daughters in their teenage years at the time of exposure. We also show that cities exposed to a larger increase in female federal workers saw persistently higher female labor force participation in the public sector, as well as modest increases in private sector labor force participation. Collectively, the results are thus consistent with both the vertical and horizontal transmission of gender norms, and highlight how increasing gender representation within an organization can have broader labor market implications.

IPUMS has finalized databases for each of the United States population censuses from 1850 to 1880. These data are the result of collaborations between FamilySearch and Ancestry.com, which provided the raw data, and IPUMS, which enhanced the data with editing, standardized coding, inter-census harmonization, and documentation. We discuss the data capture process conducted by the nineteenth-century United States Census Office, construction of the modern datasets, and variable availability. We conclude by briefly discussing the potential and limitations of these data for social science research. The public data are distributed by IPUMS and available for researchers to use free of charge.

In my first chapter, I study the effect of the expansion of the streetcar network on suburbanization and socioeconomic dynamics of neighborhoods. My novel data work involves georeferencing historical streetcar maps of Chicago for three decadal years- 1900,1910 and 1920. To study the streetcar impact on changes in a neighborhood over time, I divide the city into consistent hexagons and study the changes within each hexagon. Using different empirical methodologies such as two-way fixed effects and first differences including an instrumental variable, I find that streetcars played a significant role in shaping suburbanization. I find that streetcars played a significant role in city expansion, with population increasing in the suburbs particularly near streetcar lines, away from the city center. Results indicate that due to streetcar expansion, the rich moved away from the city center but settled near streetcars, while the poor clustered in the city center and near the public transit network.

This dissertation studies the social determinants of health and economic wellbeing in the United States and how they contribute to observed outcome disparities. Chapter 1 investigates the Great Migration of millions of Black Americans out of the South during the mid-20th century and how it impacted Southern racial inequality. The results provide novel empirical evidence for how this seminal event in U.S. history impacted the South, finding improvements for Black workers and reductions in the racial wage gap. Chapter 2 turns to a modern context and explores how social connections can help overcome barriers to public program take-up, which tends to be well below full enrollment. When states expanded eligibility rules for Medicaid—the low-income public health insurance program— many previously eligible individuals became enrolled. I find this effect was partially driven by learning from friends. Focusing on Medicaid-eligible people living in non-expansion states, those with more friends in states expanding Medicaid became more likely to enroll after the expansions, even though eligibility had not changed for themselves. The results show program experiences among one’s friends can improve their own program participation and highlight how policy changes can have indirect, geographically distant impacts propagated through social networks. Finally, Chapter 3 looks forward to project how current socioeconomic disparities in health and economic wellbeing will translate to disparities in future outcomes. Using a dynamic microsimulation model to forecast healthy life expectancy and expected economic resources among Americans nearing retirement age, we find significant disparities between economic status groups in expected future outcomes. These gradients have widened over time; inequality within the middle of the economic distribution grew between 1994 and 2018, in addition to expanding differences between the most and least advantaged.

The quality of historical US census data is critical to the performance of linking algorithms. We use genealogical profiles to correct measurement error in census names and ages. Our findings suggest that one in every two records has an error in name or age, and human capital is correlated with lower error rates. While errors in age decline across subsequent census rounds from 1850 to 1930, errors in names do not exhibit such trends. Fixing all transcription errors, hence leaving only those errors made at the time of enumeration, would reduce error rates in names by 41 percent. Correcting all names and ages using genealogical profiles leads to 20%–36% more links and fewer false positives. Reassuringly, we find that reducing such errors has a negligible effect on estimates of intergenerational mobility.

The Civil War was the deadliest conflict in US history. However, incomplete records have made it difficult to estimate the exact death toll both nationally, and especially, at the state level. In this article, we leverage the recently released full count of individual census returns and a sample of linked records across multiple censuses to provide i) the most precise national estimate of excess mortality to date and ii) reliable state-level estimates of excess mortality among native-born white males. Our national estimate is 698,000 Civil War deaths. This is substantially higher than the conventional historical estimate of 618,000 but lower than the most recent estimate of around 750,000 deaths based on a 1% census sample. Leveraging a novel migration-adjusted census comparison method, we document the extent to which the war’s toll was much greater in the Confederate states than in the Union.

The study focuses on the temporal differences (30 years on average) between ethnic groups migrating from the Austro-Hungarian Empire to the U.S. between 1850 and 1910. In our study, we argue that the main factor that led to differences in the timing of emigration was the differences in regional economic development of different ethnic groups living in different regions of the Empire. Migration costs: before the 1864 introduction of steam engine technology in transatlantic maritime transport, emigration costs were not affordable for Hungarians and Slovaks due to the sea and land voyage high ticket prices. Therefore, with more resources, Austrians and Czechs could afford to migrate earlier. However, after the introduction of steamship technology and the technological change in ship engines, travel became more affordable due to reduced ticket prices, faster voyages, and increased capacity. This allowed Hungarians and Slovaks from poorer regions to begin migrating in larger numbers as migration became economically feasible. In this study, we utilise a complete count of the U.S. Census records from 1900 and 1910 (Helgertz et al., 2023; Ruggles et al., 2021), which Integrated Public Use Microdata Series (IPUMS). On the other hand, we utilise economic indicators, which are regional daily wage, GDP per capita income and living standard data for the Austria-Hungary Empire from Cvrcek (2013) and Schulze (2000).

This paper presents new estimates of wage inequality in the United States from 1918 to 1949. Building upon a new top-income methodology, we provide various definitions of top wage groups that account for the sharp fluctuations in the employed population during this period. The results confirm the decline in wage inequality during the Second World War, primarily due to the relative stagnation of the top 1% group and a sharp increase at the bottom. However, the underperformance of top wage earners was driven by a significant compositional shift that resulted from an unprecedented rise in the corporate tax. This change prompted a shift in business preferences regarding their legal status, fostering a surge in partnerships during the 1940s. Consequently, a significant number of workers transitioned from salaried positions to self-employment, which amplified the compression observed in the wage distribution.

This study investigates three distinct examples of technological innovation during the 19th century United States. I first examine the long-run impacts of a deskilling technology on workers and their children. The McKay stitcher dramatically changed shoe production in the late 19th century by replacing skilled artisans with machines and less-skilled workers. It was licensed in only a few counties and impacted workers across counties unevenly through the transportation network. More-exposed shoemakers and their children faced long-run losses in the face of this displacement. During the same era, the railroad network of the US expanded rapidly, changing the organization of firms in manufacturing. Expanding market access pushed establishments to specialize production on fewer products. Manufacturing plants specialized on specific steps in the production process, shortening the production chain within establishments. Together these imply that the ingredients for Smithian growth arose in response to technologically driven market integration. Towards the end of the century, a new method of market integration began to take hold

We compile, transcribe, and standardize historical records for 2.5 million students at 65 elite (private and public) U.S. colleges. By combining these data with more recent survey and administrative data, we assemble the largest dataset on the socioeconomic backgrounds of students at American colleges spanning the last 100 years. We document the following: First, despite a large increase in the share of lower-income students in the overall college-going population, the representation of these students at elite private or public colleges has remained at similarly low levels throughout the last century. Second, the representation of upper-income students at elite colleges decreased after World War II, but this group has regained its high representation since the 1980s. Third, while there has been no increase in the economic diversity of elite private and public colleges, these colleges have become more racially and geographically diverse. Fourth, two major policy changes in the history of American higher education, namely the G.I. Bill after World War II and the introduction of standardized tests for admissions, had little success in increasing the representation of lower- and middle-income students at elite colleges.

IPUMS has finalized databases for each of the United States population censuses from 1850 to 1880. These data are the result of collaborations between FamilySearch and Ancestry.com, which provided the raw data, and IPUMS, which enhanced the data with editing, standardized coding, inter-census harmonization, and documentation. We discuss the data capture process conducted by the nineteenth-century United States Census Office, construction of the modern datasets, and variable availability. We conclude by briefly discussing the potential and limitations of these data for social science research. The public data are distributed by IPUMS and available for researchers to use free of charge.

IPUMS recently released final versions of full count census data for the United States 1900-1930. The information contained in these files is the product of three broad work stages: historical census enumeration, digitization, and IPUMS processing. The data were produced within an evolving institutional context and subjected to subsequent processes that had important ramifications on the final product. This paper documents these histories and processes and their implications for research. Because of the datasets' sheer size and scale, the development of these files necessitated applying different methods and approaches to assess data quality and correct the data. We document cases where data quality was affected not only by choices made by the Census historically, but also by data transcription errors in the modern day. Finally, we describe our approaches to processing the data, and we note some of the implications for research these various decisions have. As with any dataset, researchers should use this resource critically for their particular research questions and consider the data creation process from respondent to digital dataset. Despite some limitations and liabilities, the IPUMS full count data provide a powerful and valuable resource to study demographic effects on a variety of health and socioeconomic questions.

The migration of large populations has had significant importance on historical and contemporary societies. Since mass migration is a multifaceted phenomenon that significantly impacts both places of origin and destination, shaping the lives of those directly and indirectly involved, it has drawn extensive research attention. Much of the economic history literature has focused on the Age of Mass Migration, particularly European emigration to the New World. Early studies primarily used aggregate data to explore migration dynamics concerning, the determinants of migration and the assimilation of immigrants in the receiving society. However, aggregate data many times can fall short of explaining migration dynamics because it does not show the differences between groups of migrants. However, recent research utilizing micro-level data s enabled new research questions to be asked. This dissertation contributes to the existing literature by exploring the migration of Swedish immigrants to the US during the peak years of emigration. It utilizes newly digitized micro-level data and recordlinking techniques to trace individuals from their parental households in Sweden to adulthood, whether they remained in Sweden or emigrated to the US. By comparing Swedish migrants with stayers of similar backgrounds, the research offers insights into the potential outcomes that male and female immigrants might have experienced had they remained in Sweden. Sweden, one of the countries with the highest sending country to the US, underwent significant transformation during this period, offering a valuable context for study. The dissertation specifically focuses on how family migration patterns affect the risks of emigration, as well as how was economic assimilation of immigrants. In four papers, this dissertation provides a view of key aspects of the Swedish emigration experience. Although the importance of family and friends encouraging migration was known, this dissertation shows evidence of how siblings, and even extended kin, who emigrated, increased the likelihood of relatives migrating. In addition, this study shows that both men and women benefitted greatly from the migration decision, with potentially even higher gains for women who worked in domestic service. Finally, it shows how migrant networks could have positive effects on the economic assimilation of recently arrived immigrants.

This paper studies how the racial and ethnic demographic composition of U.S. municipalities is priced in the municipal bonds market. It leverages highfrequency financial data on the universe of municipal bonds issued between 2004 and 2019. More diverse cities pay higher costs on their debt: up to +10 basis points of yield-spread (+6%) per standard deviation increase of Black and Latino population shares, equivalent to +3.8% in total interest costs for the average bond. This holds controlling for maturity structure and credit ratings. Causal estimates of this diversity premium are based on a novel implementation of shift-share instruments for Black and Latino population shares. The effect is not driven by income, population trends, municipal revenues, amount of outstanding debt, or tax capacity of the issuers. The results are consistent with the discrimination of racial and ethnic minorities in the primary market for municipal bonds. Discrimination is not present in credit ratings and does not occur because of the underwriters involved in the issuance process. This evidence carries important implications for our understanding of public investments and the provision of public goods in local governments

In this paper, I examine the intergenerational occupational mobility of Native American men who entered the labor market toward the end of the Assimilation Era (1887- 1934). I use historical census data to construct transition matrices that comparatively represent the occupational mobility dynamics of Native Americans based on a series of historical policy variables. I find that Native American men during this period ex- perienced high levels of downward mobility and correspondingly low levels of upward mobility. I also find that those living in counties with reservations had worse mobility outcomes compared to those not living on reservations, and that individuals who lived in Oklahoma, which had unique political economic dynamics, had the highest relative rates of upward mobility and the lowest relative rates of downward mobility. These findings provide quantitative insight into the often neglected economic lives of Native Americans in the early twentieth century and raise further questions regarding the persistence of mobility and how to alter mobility processes.