We study the spatial and temporal variation of the human population in the United States (US) counties from 1790 to 2010, using an ecological scaling pattern called Taylor’s law (TL). TL states that the variance of population abundance is a power function of the mean population abundance. Despite extensive studies of TL for non-human populations, testing and interpreting TL using data on human populations are rare. Here we examine three types of TL that quantify the spatial and temporal variation of US county population abundance. Our results show that TL and its quadratic extension describe the mean-variance relationship of county population distribution well. The slope and statistics of TL reveal economic and demographic trends of the county populations. We propose TL as a useful statistical tool for analyzing human population variability. We suggest new ways of using TL to select and make population projections.

Who files for bankruptcy in the United States is not well understood. Previous research relied on small samples from surveys or a small number of states from administrative records. Using over ten million administrative bankruptcy records linked to the 2000 Decennial Census and the 2001–2009 American Community Surveys, I document who files for bankruptcy. Compared to the US population, bankruptcy filers are middle income, more likely to be divorced, more likely to be black, more likely to be veterans, less likely to be immigrants, and more likely to have a high school degree or some college. Filers are more likely to be employed. The bankruptcy population is aging faster than the US population as a whole. Lastly, using pseudo-panels I study what happens in the years around bankruptcy. Individuals are likely to get divorced in the years before bankruptcy and then remarry. Income falls before bankruptcy and rises after bankruptcy.

As the world recognizes that its growing reliance on private, fossil fuel-based vehicles is unsustainable, understanding how to avoid growth in car ownership and how to shift current users towards more efficient, environmentally-friendly, safe, and inclusive alternatives is a critical vision for meeting sustainable (transportation) development goals. Policy makers looking to shift consumer behavior away from cars need a more rigorous understanding of how different attitudes play a role in influencing car ownership and use and how this might vary by people and place. In this dissertation we provide deep insight into one of the many symbolic and affective motives behind car consumption: “car pride” or the attribution of social status and personal image to owning and using a car. Using data collected from individuals in two U.S. cities and in 51 countries around the world, we develop and demonstrate the reliability, validity, and invariance of polytomous (12, 7-point Likert-format statements) and dichotomous (9, dichotomous statements) sur- vey measures for car pride using confirmatory factor analysis (CFA). With these measures, we explore variations in car pride across individuals, cities, and countries using Structural Equation Modeling (SEM). Across individuals, we find that those who are younger, male, and have higher incomes generally have higher car pride. Controlling for individual charac- teristics, we find that car pride is influenced by context. Between U.S. cities, we find that Houston has higher car pride than New York City. Across countries, we find that less devel- oped countries exhibit higher car pride. We also disentangle the bidirectional causal relations between car pride and car consumption using instrumental variable (IV) techniques. We find that car pride strongly predicts car ownership, while no statistically significant relation ex- ists in the opposite direction. Car pride additionally predicts car use, but only through its relation with car ownership (mediator). In the reverse direction, car use strongly reinforces car pride. While the directions of these relations appear almost universal across contexts, their strengths differ by country, emphasizing the importance of taking national context into account when measuring and interpreting symbolic motivations for car consumption. This dissertation builds a systematic understanding of car pride and its relations with car consumption across individuals, cities, and countries. For researchers, it serves as an exam- ple of methodological good-practice for empirical studies of attitude-behavior relations in transportation. For policymakers, it builds awareness of how policies can target attitudi- nal, social, and cultural factors, such as car pride, that present additional obstacles to the adoption of more sustainable transportation alternatives at both the individual and national levels.

We study the effect of public insurance on smoking cessation medication prescriptions and financing. We leverage variation in insurance coverage generated by recent Affordable Care Act expansions to Medicaid. We estimate differences‐in‐differences models using administrative data on the universe of Medicaid‐financed prescriptions sold in retail and online pharmacies 2011–2017. Our findings suggest that these expansions increased Medicaid‐financed smoking cessation prescriptions by 34%. This increase reflects new medication use and a shift in payment from private insurers and self‐paying patients to Medicaid. Adjusting our estimate for changes in financing implies that Medicaid expansion led to a 24% increase in new medication use.

Labor market segmentation by race, ethnicity, and nativity has long been documented in the social science literature. However, relatively few studies have examined a variety of nativeand foreign-born groups under one comparative assessment. I address this research gap by concomitantly examining eight native- and foreign-born, racial and ethnic groups. I measure their occupational segregation in emerging and established immigrant gateways of the United States and their job attributes net of worker characteristics. Thus, this dissertation combines research about occupational segregation, job quality, and immigration for a multi-angle assessment of labor market outcomes in light of labor market segmentation and queue theories. I focus on the racial and ethnic composition of the labor market, the occupational segregation of native- and foreign-born groups in prominent immigrant destinations across the country, and the job attributes associated with each group net of theoretically-relevant worker characteristics.

A common approach to estimating the elasticity of income to taxation is to construct an instrumental variable using synthetic tax rates. Individual-level income dynamics threaten the validity of this instrument, but this problem can potentially be mitigated by group-averaging the instrument. In this article I show that rather than imposing an arbitrary minimum threshold for group sizes to avoid small-sample bias, researchers should use leave-one-out group averages. Using CPS data I show that this correction increases the estimate for broad income elasticity.

Under the federal Affordable Care Act (ACA), California expanded eligibility for Medi-Cal, the state’s Medicaid program, to most non-elderly, non-disabled low-income adults. Although this change focused directly on improving the health and well-being of adults, it is likely that Medi-Cal expansion has had a dramatic effect on households with children. In recent years, as the federal government has attempted to dismantle the ACA, California policymakers have continued to push forward with efforts to protect and expand coverage gains. A better understanding of the impact of adult Medi-Cal on child well-being can help inform state efforts to expand health care coverage and improve outcomes for low-income children and families.

Large black-white fertility differences are a key feature of US demography, and are closely related to the broader dynamics of US racial inequality. To better understand the origins and determinants of racial fertility differentials, this paper examines fertility patterns in the period surrounding passage and implementation of the 1964 Civil Rights Act, which precipitated a period of rapid socioeconomic and political progress among African Americans, with these gains strongly concentrated in the South. I first show that the relative fertility of southern black women precipitously declined immediately after 1964. Specifically, as of 1964 the general fertility rate of southern black women was 53 births greater than the general fertility rate of southern white women, but by 1969 this gap had fallen to 33 births, a decline of approximately 40% in five years. The black-white fertility gap outside of the South was unchanged over this period. Measures of completed childbearing similarly show rapid black-white fertility convergence in the South but not in the North. An analysis of potential mechanisms finds that a substantial share of the observed fertility convergence can be explained by relative improvements in the earnings of southern blacks, and that the historical intensity of slavery and lynching activity are the strongest spacial correlates of fertility convergence

Our analysis uses data on firms and labor markets, both national and local, from several sources. We provide additional details on these sources and the methodology to replicate the estimates in the paper. Throughout the paper, we use data on firms from the restricted-access U.S. Census Bureau Longitudinal Business Database (LBD) and its public-use tabulations, the Business Dynamics Statistics (BDS).1 We combine these data with measures of labor supply growth from the Census Bureau and Bureau of Labor Statistics. Finally we use tabulations from Census Bureau’s County Business Patterns (CBP) for an independent historical estimate of an establishment startup rate.

Economists generally consider intergenerational economic mobility to be an important feature of market economies, as it allows people born into poverty to achieve a measure of prosperity in the presence of minimal government intervention or redistribution. The empirical literature on mobility in the U.S. has, however, found evidence that mobility is lower than previously thought, and scholars have responded by developing expansive literatures on many aspects of intergenerational mobility, including studies of its origins. In this dissertation, I contribute to this strand of the literature by reviewing recent trends in the literature, with a particular emphasis on studies aimed at explaining the sources of mobility, and then discussing three empirical studies into specific sources of mobility, using data organized at different geographic and temporal scales. These empirical chapters focus on the role of different aspects of childhood poverty in determining income rank in adulthood, modeling variation in racial mobility gaps across different kinds of communities and local economies, and measuring the relationship between trends in intergenerational mobility and the structural transformation of agriculture in the 20th century U.S..

This dissertation is a collection of three independent chapters on topics in applied microeconomic analysis, focusing on issues in urban and education economics. The first chapter examines local housing values in Dallas after the repeal of the Wright Amendment, legislation that limited activity at the neighborhood airport Love Field. I find that, on average, the repeal of the Wright Amendment led to a 11% increase in rents and a 10% increase in housing values for units less than 6 miles of the Love Field Airport. The second chapter examines interest in the education industry following Act 10, a Wisconsin legislative act that limited the collective bargaining power of teachers’ unions in the state. Comparing the share of postsecondary students enrolled in a teacher preparation program in Wisconsin before and after Act 10 and relative to similar states, we find that on average Act 10 lead to a 12% increase in teacher preparation enrollment. Finally, the third chapter examines spatial crime activity in cities when hosting large events, such as college football games. Using geo-located daily level crime data from college towns, I estimate that crime increases in census tracts closer to the event by approximately 44% relative to tracts farther away on days with a football game, and is spatially concentrated in areas near the stadium.

Racial economic divides seem a fixed feature of American society. Yet the past 75 years have witnessed important shifts in this dimension of inequality. This dissertation studies two key episodes in American economic history that have shaped current patterns of racial disparities. The first chapter examines the role of the Great Migration in the changing geography of upward mobility for black families. I show that northern cities responded endogenously to black population increases during the Great Migration, lowering the gains from growing up in destination cities and widening the racial gap in upward mobility in the region. The second chapter explores mechanisms of the Migration’s effect on upward mobility. Starting in the 1960s, destination commuting zones exhibited higher white private school enrollment rates, greater investment in police services, higher urban murder rates,and increased incarceration, suggesting rising segregation and urban decline as plausible channels. The third chapter of the dissertation uncovers the role of federal minimum wage policy in the sharp decline of racial earnings gaps during the Civil Rights Era. The 1966 Fair Labor Standards Act extended federal minimum wage coverage to retail, services, agriculture, and other sectors where black workers were overrepresented. The reform increased wages for workers in newly covered industries, with twice as large an effecton black workers as on white, and with no detectable effects on employment. The 1966 extension can explain 20% of the reduction in the racial earnings gap in the late 1960s and early 1970s.

Attending high school can alter students’ life trajectories by affecting labor market prospects and through exposureto ideas and networks. However, schooling’s influence competes with early socialization forces and may be confounded byselection biases. Consequently, little is known about whether or how high school education shapes downstream politicalpreferences and voting behavior. Using a generalized difference-in-differences design leveraging variation in U.S. statedropout laws across cohorts, I find that raising the school dropout age decreases Democratic partisan identification andvoting later in life. Instrumental variables estimates suggest that an additional completed grade of high school decreasesDemocratic support by around 15 percentage points among students induced to remain in school by higher dropout ages.High school’s effects principally operate by increasing income and support for conservative economic policies, especially atan individual’s midlife earnings peak. In contrast, such schooling does not affect conservative attitudes on noneconomicissues or political engagement.

Between 2013 and 2016, following the implementation of the major coverage provisions of the Affordable Care Act (ACA) in 2014, insurance coverage and participation in Medicaid and the Children’s Health Insurance Program (CHIP) rose and the number of Medicaid/CHIP-eligible uninsured children and parents fell (Haley et al. 2018a, 2018b; Kenney et al. 2016a, 2016b, 2017). New analysis of data from 2017 indicates that these trends may be stalling or reversing. Key findings are as follows: Between 2013 and 2016, the uninsurance rate fell from 7.0 percent to 4.3 percent among children and from 17.6 percent to 11.0 . . .

The U.S. 1850, 1860, and 1870 Decennial Censuses did not include a question about relationship to head of household which is a major limitation for the study of historical family structures. The IPUMS project overcomes this lack of data by exploiting the 1880 census microdata as a donor pool for relationship status in these earlier years, making IPUMS USA the only source of family interrelationship data for the time period. Although the imputed data have been available since 1995, there has been little documentation on the procedure. In this paper we have three main goals. First, we outline the methods used to impute relationship status for the microdata samples from 1850 through 1870. We then highlight specific complications of working with these early datasets. Lastly, we document the reliability of these imputed relationships and introduce new ways of testing their reliability.

In this article, the authors examine how it is possible to construct records that track 1.4 million households that experience foreclosure from their pre-foreclosure to post-foreclosure residences. These records were created by merging two powerful sets of data: county registrar of deeds records (licensed from CoreLogic, Inc.) and consumer mail marketing data (licensed from RefUSA). The article starts with a description of the county registrar of deeds data and how it can be used to create a dataset of mortgages and outcomes (including foreclosure). The authors proceed to describe the nature of the consumer marketing data from RefUSA, how it can be used to track households as they move locations, and then how that data can be merged with the mortgage records constructed from registrar of deeds data. The article also includes discussions of how those combined records can be merged with the Home Mortgage Disclosure Act (HMDA) database, using GIS software, to learn additional demographic information (income, race, and so on) about individuals with mortgages and foreclosures.

Inversions—in which the popular vote winner loses the election—have occurred in 4 US Presidential elections. We show that rather than being statistical flukes, inversions have been ex ante likely since the 1800s. In elections yielding a popular vote margin within one percentage point (which has happened in one-eighth of Presidential elections), 40% will be inversions in expectation. Inversion probabilities are asymmetric, in various periods favoring Whigs, Democrats, or Republicans. Feasible policy changes—including awarding each state’s Electoral College ballots proportionally between parties rather than awarding all to the state winner—could substantially reduce inversion probabilities, though not in close elections.

More young people today have recently moved into their current home than those in previous decades - The share of 25- to 34-year-olds who have lived in their current home for less than two years rose from 33.8% in 1960 to 45.3% in 2017. - Among large metros, the biggest increases in the share of young people with short home tenures were seen in Boston, Pittsburgh, Detroit and Philadelphia. - The majority of young adults who move do so within the same metro area, and an increasing share are moving to a different metro in the same state.

We analyze the conditions in which ignoring spatial correlation is problematic for inference in differences-indifferences (DID) models. Assuming that the spatial correlation structure follows a linear factor model, we show that inference ignoring such correlation remains reliable when either (i) the second moment of the difference between the pre-and post-treatment averages of common factors is low, or (ii) the distribution of factor loadings has the same expected values for treated and control groups, and do not exhibit significant spatial correlation. We present simulation results with real datasets that corroborate these conclusions. Our results provide important guidelines on how to minimize inference problems due to spatial correlation in DID applications.

This paper presents a new approach to recoding industry and occupation in the Current Population Survey (CPS) from 1976 to 2019. This recode uses the three- and four-digit Census codes present in the CPS to create consistent aggregate categories that closely align with the detailed and major industry and occupation categories used in the 2019 CPS. This approach yields more consistent aggregate categories than previous recoding schemes. This approach can also successfully be applied to recoding industry and occupation in all panels of the Survey of Income and Program Participation (SIPP).