We are far from a complete understanding of the causal determinants of health and mortality in the United States. Explosion of new administrative data has opened up new opportunities to study mortality and health disparities. What is the association between homeownership and longevity? How does it vary by race? What is the causal impact of homeownership on longevity?

This paper investigates the empirical relationship between inclusion and state capacity , as theorized by Besley and Persson (2009). We examine the impact of racial discrimination on Black U.S. military enlistment during the onset of WWII. We find that discrimination had a large and negative effect on volunteer enlistment after the Pearl Harbor attack. The result is robust to a large number of controls that account for potential confounders. The negative effect of discrimination is moderated by geographical proximity to Pearl Harbor, and is larger for educated men. We provide consistent evidence for Japanese Americans.

During the Great Depression, the United States removed approximately 263,000 Mexicans, including some legal US citizens, from the country. This repatriation was an effort to protect the jobs and earnings of US citizens. Mexicans were singled out for removal because they were one of the largest non-white migrant or ethnic groups in the US and because of prevailing beliefs that they would never integrate into US culture. In this study, economists Gustavo S. Cortes and Vinicios P. Sant’Anna explore the effects of this repatriation event on local real estate markets. Specifically, they look at how the removal of Mexicans influenced the economic recovery of US cities during and after the Great Depression. The authors find that cities from which more people were removed recovered slower than cities from which fewer people were removed. Sending Mexicans and some US citizens of Mexican heritage out of the country reduced new construction rates in cities and slowed the growth of home values and rents across America. These are economic costs that could be weighed against the economic benefits to other groups, but the authors find no clear benefits to native, non-Mexican workers. In sum, this paper indicates that efforts to deport immigrants may have long-lasting and negative effects on communities that experience those losses. Importantly, this paper considers only the economic effects and ignores the ethical implications of such policies. Policymakers should consider both, but the economic case for immigration is clear. Removing immigrants and their children en masse from the country can harm rather than promote the welfare of natives.

The Great Plains drought of 1931–1939 was a prolonged socio-ecological disaster with widespread impacts on society, economy, and health. While its immediate impacts are well documented, we know much less about the disaster’s effects on distal human outcomes. In particular, the event’s effects on later life mortality remain almost entirely unexplored. Closing this gap would contribute to our understanding of the long-term effects of place-based stress. To help fill this gap, I use a new, massive, linked mortality dataset to investigate whether young men’s exposure to drought and dust storms in 341 Great Plains counties was linked to a higher risk of death in early-old age. Contrary to expectations, results suggest exposure to drought conditions had no obvious adverse effect among men aged 65 years or older at time of death—rather, the average age at death was slightly higher than for comparable men without exposure. This effect also appears to have been stronger among Plainsmen who stayed in place until the drought ended. A discussion of potential explanations for these counterintuitive results is provided.

Childhood malnutrition and its later life effects were important concerns in European and North American social policy in the early twentieth century. However, there have been few studies of the long-term socioeconomic consequences of malnutrition in childhood. We use a unique longitudinal dataset to provide credible causal estimates of the effects of childhood nutrition on early-adult educational and employment outcomes. Our dataset includes 2,499 children in Saint Paul, Minnesota who were weighed and measured in a national children’s health survey in 1918/1919 at 0–6 years of age. We observe those same people in the 1920, 1930 and 1940 U.S. censuses allowing us to measure childhood socioeconomic status, adolescent school attendance (1930) and early-adult wages, and employment and educational attainment (1940). Examining variation between biological siblings, we are able to obtain credibly causal estimates of the relationship between childhood stature and weight and later life outcomes, largely canceling out the bias otherwise resulting from their joint correlation with genes and socioeconomic background. Because the initial survey located children within households, we identify the effect of differences in early childhood nutrition from differences between male siblings. Consistent with contemporary evidence from developing countries, we find that being taller and heavier in early childhood is associated with better educational and labor market outcomes. Identifying all effects within families to control for socioeconomic background and family structure, we find a standard deviation increase in BMI in early childhood was associated with a 3% increase in weekly earnings and that boys who were heavier for their age at the initial survey were 10% less likely to be unemployed in 1940. Taken together, these results confirm the importance of investments in early-life health for later-life outcomes.

The US Civil War ended in 1865 without the distribution of land or compensation to those formerly enslaved—a decision often seen as a cornerstone of racial inequality. We build a dataset to observe Black households’ landholdings in 1880, a key component of their wealth, alongside a sample of White households. We then link their sons to the 1900 census records to observe economic and human capital outcomes. We show that Black landowners (and skilled workers) were able to transmit substantial intergenerational advantages to their sons. But such advantages were small relative to the overall racial gaps in economic status.

We examine the socioeconomic consequences of discrimination against people of Southern origins during the US Great Migration of the first half of the twentieth century. We ask whether people living in the American North and Midwest in 1940 fared worse with respect to education, occupation, and income if they were perceived to be of Southern origins. We also assess variation in these effects across racial groups and across actual region of origin groups. Using linked data from the 1920 and 1940 US censuses, we compare the life outcomes of about half a million pairs of brothers who differed with respect to the regional origin implied by their first names. For both Whites and Blacks, we find statistically significant associations between outcomes and the regional origin implied by names; regardless of where they were born, men living in the North or Midwest in 1940 did worse if their names implied Southern origins. However, these associations are entirely confounded by family-specific cultural, socioeconomic, and other factors that shaped both family naming practices and life outcomes. This finding—that regional discrimination in the early-twentieth-century United States did not happen based on names—contrasts sharply with findings from research in more recent years that uses names as proxies for people’s risk of exposure to various forms of discrimination. Whereas names are a basis for discrimination in modern times, they were not a basis for regional discrimination in an era in which people had more immediate and direct evidence about regional origins.

This paper develops early estimates of how public pensions affect retirement timing by examining the Railroad Retirement Act of 1937, which replaced private railroad pensions with a national program similar to Social Security. Leveraging various samples of linked Decennial Census records between 1910-1940, the analysis compares male labor force nonparticipation by previous industry, year, and age. Higher benefits led to earlier retirement, largely driven by exit at age 65. Exploiting newly progressive benefits, the elasticity of nonparticipation at ages 65-69 is 0.55, which is large relative to findings in modern settings but consistent with contemporary elderly transfer programs.

In this paper I try to explain what happened to young black men's labor supply during the XX century. After 1930, there is a black/white divergence that has not been properly explained. I show that common explanations like the black migration to the North and the Great Depression are unlikely to have produced the labor supply divergence. However, the New Deal could be a far better explanation.

The US and other developed nations have experienced two concurrent phenomena over the previous two decades: Slow productivity growth and rapid workforce aging. In this paper I argue that both phenomena are linked through a demand channel. Following an instrumental variable strategy I provide evidence for a causal link between workforce aging and lower innovation.

This special issue, Differential Privacy for the 2020 U.S. Census: Can We Make Data Both Private and Useful?, provides an entry point to help data scientists across many disciplines adjust to a big change in a key component of our national data infrastructure. The United States Census Bureau is adopting formal differential privacy protections for public products from the 2020 U.S. Decennial Census. This is the first time that a country has released most of its subpopulation counts with formal privacy protections, although certainly not the first time that other official counts have been perturbed for the purpose of disclosure avoidance. Population censuses are important. Indeed, they may be the oldest statistical products of communal societies. They are mentioned in the Bible (the book of Numbers) and required by Article I, Section 2 of the U.S. Constitution for allocating seats in Congress. After all, as Lord Kelvin noted in 1883: [W]hen you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind. (William Thomson, Lord Kelvin, Electrical Units of Measurement [1883]) [Lord Kelvin’s observation is often paraphrased to more zippy aphorisms such as, ‘You cannot manage what you cannot measure.’] These days, each U.S. decennial census plays a role far beyond simply determining how many seats each state holds in Congress. Statistical frames based on Census Bureau counts underlie nearly all the demographic descriptions and many decisions made by government, business, or other organizations in the United States. Massive federal expenditures are distributed according to population estimates based on census data. Furthermore, a number of active and influential research communities depend upon decennial census data products. Privacy protection for respondents is also important and getting more difficult to achieve. Such protection has long been required by law, in order to prevent harm and to encourage full and honest responses. Recently, though, growing uses of the decennial census, availability of other data sources, and increased computational firepower make protecting the privacy of census respondents more difficult. Fortunately, newly developed formal privacy protection systems can both measure the degree of privacy protection and allow adequate transparency to inform statistical inference on protected data. Previous statistical methods used to protect privacy (such as suppression and swapping observations) lack both of these desirable properties. Nevertheless, adopting a new form of privacy protection for such important data is far from easy. Some of the key challenges include implementation issues confronted by the Census Bureau, understanding analytical implications for data scientists, and managing communication so that all stakeholders can engage effectively with each other and inform the public about the implications of the change.

Background: Emergency employment programmes during the 1930s and 1940s invested income, infrastructure and social services into communities affected by the Great Depression. We estimate the long-term associations of growing up in an area exposed to New Deal emergency employment in 1940 with cognitive functioning in later life. Methods: Members of the Health and Retirement Study cohort (N=5095; mean age 66.3 at baseline) who were age 0–17 in 1940 were linked to their census record from that year, providing prospective information about childhood contextual and family circumstances. We estimated the association between subcounty-level emergency employment participation in 1940 and baseline cognition and rate of cognitive decline between 1998 and 2016. Results: Compared with those living in the lowest emergency employment quintile in 1940, those who were exposed to moderate levels of emergency employment (third quintile) had better cognitive functioning in 1998 (b=0.092 SD, 95% CI 0.011 to 0.173), conditional on sociodemographic factors. This effect was modestly attenuated after adjusting for respondents’ adult education, finances and health factors. There were no significant effects of area-level emergency employment on rate of cognitive decline. Conclusions: Exposure to New Deal employment policies during childhood is associated with long-term cognitive health benefits. This is partially explained by increases in educational attainment among those with greater levels of emergency employment activity in the place where they were raised. Future research should investigate which types of New Deal investments may most be related to long-term cognitive health, or if the associations we observe are due to co-occurring programmes.

One of the largest population displacement episodes in the U.S. took place in 1942, when over 110,000 persons of Japanese origin living in the West Coast were forcibly sent to ten internment camps throughout the country. Those affected lost jobs and assets and lived in camps between one and three years. After internment they had to reassess labor market and location choices. Using Census data, camp records, and survey data I study the long-run career consequences of this episode for those affected. Combining information from these three data sources I develop a predictor of a person’s future or past internment based on Census observables. Using a differencein-differences framework I find a positive average effect of internment on earnings in the long run, robust to different control group choices. I consider exposure to socioeconomically diverse peers followed by increased occupational and geographic mobility as likely mechanisms, finding support in the data for both. I do not find evidence of other potential drivers such as increased labor supply or changes in cultural preferences. These findings provide evidence of labor market frictions preventing people from accessing their most productive occupations and locations, how exposure to socioeconomically diverse peers can lower these barriers, and the possibility of overcoming adverse shocks.

We examine the relationship between board diversity and a firm's corporate social responsibility (CSR) performance in a novel way. The relation between visible forms of board diversity (gender, ethnic, age diversity) and CSR may arise endogenously due to visible diversity management. In contrast, we focus on cultural diversity (based on directors' ancestry), which is less visible. We demonstrate that cultural diversity, unlike visible diversity, is not considered in director replacements, consistent with cultural diversity not being affected by firms signaling their CSR commitment by ‘looking’ diverse. We show that board cultural diversity is positively related to CSR performance. This result holds when we control for visible board diversity, directors' foreignness and diversity in nationalities, and endogeneity. We also show that CSR performance decreases when a firm increases its visible board diversity at the cost of cultural diversity.

Are heterogeneous labor market outcomes a product of markets efficiently allocating resources or the result of structural market failures which should be corrected through well-crafted policy? In order to address this fundamental question in modern economics, we must first understand the forces which shape individuals’ earnings, employment, and occupational choices. This collection of essays provides new evidence to support several novel channels which influence labor markets. First, I evaluate the connection between technological change and labor market outcomes by bringing new data and methods to study the mechanization of American agriculture in the early 20th century. Using an instrumental variables estimation strategy, I find that exogenous increases in exposure to technological change generated occupational displacement for incumbent laborers, increased income inequality, and had important impacts on intergenerational mobility for the children of affected workers. Additionally, I investigate the connection between low-opportunity neighborhoods and public housing residents’ labor market outcomes. Leveraging quasi-random variation in neighborhood quality due to a public housing demolition, I find that residents’ wages increased after moving to higher-opportunity neighborhoods and that more intense supportive services improved post-move employment. Taken together, these essays provide new evidence that both large-scale factors like new technologies and local factors like neighborhood quality contribute to heterogeneity in labor market outcomes both historically and up to the present day.

In the aftermath of World War I, U.S. discourse was animated by the concern that demobilized soldiers, having experienced the world outside of their hometowns, would resist returning to farms and to their preinduction occupations. Did military service really encourage an occupational shift? Were rural individuals especially susceptible to and was emplacement in foreign locales especially culpable for this change, as popular culture suggested? Focusing on North Dakota, a state with unusually detailed World War I records, this article uses a novel linked census–military data set and statistical analysis to examine how individuals’ place-based military experience might have inflected their postwar occupational mobility. Whereas univariate models support the contemporary perception that farm boys with overseas service were less likely to remain in agriculture, increasingly complex models suggest more nuanced interpretations, with civilian individual and contextual characteristics and their interaction being significantly predictive of farm leaving. Addressing substantive gaps in World War I historiography by contextualizing neglected subpopulations, this research also shows the value of using quantitative methods to engage with critical military geographies. Operationalizing theories of place–individual co-constitution through the analysis of longitudinal, individual data demonstrates how interest in soldiers’ experiences and in the spatiotemporally distant effects of war can be productively intertwined.

The U.S. Census Bureau plans to use a new disclosure avoidance technique based on differential privacy to protect respondent confidentiality for the 2020 Decennial Census of Population and Housing. Their new technique injects noise based on a number of parameters into published statistics. While the noise injection does protect respondent confidentiality, it achieves the protection at the cost of less accurate data. To better understand the impact that differential privacy has on accuracy, we compare data from the complete-count 1940 Census with multiple differentially private versions of the same data set. We examine the absolute and relative accuracy of population counts in total and by race for multiple geographic levels, and we compare commonly used measures of residential segregation computed from these data sets. We find that accuracy varies by the global privacy-loss budget and the allocation of the privacy-loss budget to geographic levels (e.g., states, counties, enumeration district) and queries. For measures of segregation, we observe situations where the differentially private data indicate less segregation than the original data and situations where the differentially private data indicate more segregation than the original data. The sensitivity of accuracy to the overall global privacy-loss budget and its allocation highlight the fundamental importance of these policy decisions. Data producers like the U.S. Census Bureau must collaborate with users not only to determine the most useful set of parameters to receive allocations of the privacy-loss budget, but also to provide documentation and tools for users to gauge the reliability and validity of statistics from publicly released data products. If they do not, producers may create statistics that are unusable or misleading for the wide variety of use cases that rely on those statistics.

Spatial income disparities have increased in the United States since 1980. Growth in this form of inequality is linked to major social, economic and political challenges. Yet, contemporary patterns, and how they relate to those of the past, remain insufficiently well understood. Building on population survey microdata spanning 1940-2019, this paper uses group-based trajectory modelling techniques to identify distinct sets of local labor markets based on the evolution of their income levels. We find that the increase in spatial inequality since 1980 is almost entirely driven by a small number of populous, economically-important, and resiliently high-performing ‘superstar’ city-regions. Meanwhile, since 1940, much of the rest of the urban system has continued to converge toward the mean. We examine the demographic, economic and social characteristics of these different trajectories, identifying catch-up regions, declining regions, long-term winners, and possible future superstars. There is considerable turbulence within the convergence process, consisting of regions that are moving both upward and downward in the system. We conclude by exploring implications for the American urban-regional system in the mid-21st century, considering the challenges in overcoming the growing split between superstar locations and the rest of the country.

Occupational regulation affects many people across many aspects of life. Most anyone knows someone affected or themselves are affected by some form of occupational regulation. This dissertation research investigates the consequences of occupational regulation across three different areas of study: economic history, urban and regional economics, and health policy. The first chapter investigates the historic licensing of emigrant agents. In the period following the US Civil War, firms wished to capitalize on the availability of African American labor. To do so they hired emigrant agents, also known as labor agents, to hire and help with the migration of individuals from the South. Faced with out-migration at the hands of the labor force, some southern states licensed the profession as a substantial barrier to practice. I use linked full-count US Censuses to determine the effect that licensing emigrant agents had on the individual probability of migration both out of state, and out of the South. A difference-in-differences analysis on the border counties of North and South Carolina suggests that the licensing of emigrant agents reduced the probability of migration out of the South by more than 1 percentage point. The second chapter deals with cross-border competition and the effects of licensing massage therapists. Occupational licensing has been shown to have many pervasive economic effects. Licensing restricts competition, which causes wage premiums, potentially induces rent seeking, and ultimately results in consumers having to pay high prices through both channels of reduced supply and producers passing on increased cost of doing business. Licensing laws are passed at the state level; and thus, there can be considerable variation across states. Should there be much economic activity at state borders, this would be inconsequential. Yet, the existence of metropolitan areas spanning state borders begs the question of what effects can restricting competition be when competitive substitutes are easily available. This theory is tested using major MSAs that cross state borders and data from the American Community Survey to show how the differing licensing schemes affect the incomes of practicing massage therapists. Ultimately, it appears that the effect of easily available substitutes of massage therapists in the border state mutes the effect of the wage premium that would be caused by a more restrictive licensure scheme. Not only do wage premiums not appear in geographically adjacent states, it is especially missing in border MSAs. The third chapter is joint work with Dr. Bobby W. Chung of St. Bonaventure University and presents an analysis of the effect of expanding scope of practice for nurse practitioners. As a response to the Covid-19 Pandemic many states choose to expand nurse practitioner scope of practice. We analyze the effects of the expansion of scope of practice on daily Covid related mortality using a synthetic control design. Our results suggest that expanding scope of practice for NPs reduced daily Covid related mortality and was most effective in non-rural areas. The total effect of expanding scope of practice is a reduction of hundreds of deaths over a 30 day period compared to the synthetic control.

Does personal and family history influence legislative behavior in democracies? Linking members of Congress to the census, we observe countries of birth for members, their parents, and their grandparents, allowing us to measure ancestry for the politicians in office when American immigration policy changed dramatically, from closing the border in the 1920s to reshaping admittance criteria in the 1960s. We find that legislators more proximate to the immigrant experience support more permissive immigration legislation. A regression discontinuity design analyzing close elections, which addresses selection bias and holds district composition constant, confirms our results. We then explore mechanisms, finding support for in-group identity in connecting family history with policymaking. Holding fixed family history, legislators with more visible indicators of immigration based on surnames are even more supportive of permissive immigration legislation. However, a common immigrant identity can break down along narrower ethnic lines when restrictive legislation targets specific countries. Our findings illustrate the important role of personal background in legislative behavior in democratic societies even on major and controversial topics like immigration and suggest lawmakers' views are informed by experiences transmitted from previous generations.