All redistributive and social insurance programs trade off the potential benefits of transfers with the disincentives these programs generate. We investigate this trade-off using newly collected lifetime data for 16,000 women who applied to the Mothers' Pension Program, the first cash transfer program in the US. In the short-run cash transfers reduced geographic mobility and delayed marriage of recipients but did not affect who they married or where they moved to. In the long run transfers had no effect on work, marriage or fertility behaviors. They also did not improve the economic conditions of recipients or their longevity.

The shifting of a country’s age structure has far-reaching socioeconomic and policy implications. In the US, the changing age structure at the sub-national level has received little research attention. To address this gap, we examine age dependencies across states in the US between 1990 and 2010 using decennial census data. We find that dependency changes have been gradual with a distinct graying of states during this period. Within this overarching trend, the sources of states’ dependencies follow complicated trajectories without clear spatiotemporal patterns. Nevertheless, changes in states’ old-age dependency contributions to respective total dependencies are geographically clustered and the inverse link between old-age dependency and economic productivity across states may be waning. Additional research is justified to further unravel these trends in old-age dependencies. The analytic framework that we apply can be adopted to conduct sub-national age dependency studies for other countries, including some European nations with relatively large proportions of older adults and many developing nations with an increasing share of older adults.

In 2017, the State of California adopted landmark legislation to increase the funds available for transportation in the state: Senate Bill 1 (SB1), the Road Repair and Accountability Act of 2017. Through a combination of higher gas and diesel motor fuel taxes, SB1 raises revenue for four critical transportation needs in the state: road maintenance and rehabilitation, relief from congestion, improvements to trade corridors, and improving transit and rail services. To help state leaders identify the most important projects and programs to fund within those four topical areas, we conducted an online survey that asked a sample of 3,574 adult Californians their thoughts on how the state can achieve the SB1 objectives. The survey was administered from April to August 2019 with a survey platform and panel of respondents managed by Qualtrics. Quota sampling ensured that the final sample closely reflects California adults in terms of key socio-demographic characteristics and geographic distribution. Key findings included very strong support for improving all transportation modes, reducing air pollution and greenhouse gas emissions from transportation, and more convenient options to travel without driving. Respondents placed particular value on better maintenance for both local streets and roads, as well as highways. Finally, the majority of respondents assessed all types of transportation infrastructure in their communities as somewhat or very good.

The mid-20th century American decline in income inequality has been called “the greatest leveling of all time,” despite a similarly unmatched rate of economic growth. To establish this insight, pioneering research has tracked a century of top income shares. However, limitations in the historical data had meant that we still do not fully understand the dynamics of change within the bottom 90% of the income distribution (prior to the 1960s). This paper sheds light on changes within the middle class—to study early and midcentury trends in income and wage inequality, by applying a powerful statistical model to archival tax records and survey data. We find that: (i) pre-war economic growth (and reduction in inequality) reached the upper middle class sooner than it (and they) reached the poorest households; and (ii) wartime relative income gains for the poorest were short-lived, while they proved durable for the upper middle class. In short, the relative gains from the New Deal, World War II and postwar eras were both more pronounced and more durable for the upper middle class than for the poorest. However, postwar wage compression lasted 30 years, to the particular benefit of the working poor.

I use state-level banking deregulation in the U.S. to study the causal impact of credit expansion on unemployment through its effects on the average monthly job-finding and job-losing rates. State-level analysis shows that deregulation increased the average job-finding rate and decreased the job-losing rate, and thus led to a lower unemployment rate. I also find that deregulation decreased the average unemployment duration. Extending the analysis to industry-state level, I find that the impact of deregulation on the job-finding rate is positive, but does not show any pattern across industries with respect to their needs for external finance. However, deregulation reduced the average job-losing rate, and the reduction monotonically increases with industries’ dependence on external finance.

BACKGROUND During the 19th and early 20th centuries, large waves of international immigrants, often heterogeneous in terms of age and sex structure, arrived in the United States. Within a relatively short time, many of these immigrants were assimilated. While prior studies have identified an impact of the marriage squeeze on intermarriage, the role of gender is less known. METHODS We use data from the 1930 census to examine the role played by variation in the sex ratios of the six largest immigrant groups at the beginning of the 20th century on marital outcomes by sex. RESULTS Our analyses show that the probability of marrying outside one’s ethnic group in this period is strongly tied to local ethnic sex ratios. Marital outcomes are affected for both sexes, but sex ratios are found to be more influential on males marrying out of their ethnic group. While a surplus of one’s own sex increases the probability of exogamy for males, it is likely to increase the probability of being single for females. CONTRIBUTION Our findings highlight the importance of ethnic sex ratios in local marriage markets at a critical juncture of American immigration and its consequences. We focus on an understudied aspect of this process: gender differences in the association between sex ratios and marital assimilation. We show that marital decisions differed by sex and that the high levels of intermarriage in this period are more likely to be explained by unbalanced sex ratios for males than for females.

How do banks respond to asset booms? This paper examines (i) how U.S. banks responded to the World War I farmland boom; (ii) the impact of regulation; and (iii) how bank closures exacerbated the postwar bust. The boom encouraged new bank formation and balance sheet expansion (especially by new banks). Deposit insurance amplified the impact of rising crop prices on bank portfolios, while higher minimum capital requirements dampened the effects. Banks that responded most aggressively to the asset boom had a higher probability of closing in the bust, and counties with more bank closures experienced larger declines in land prices.

Religion has always been a vital part of American identity, with entire libraries written about Americans’ distinctively religious behaviors. But basic facts about American religious history, and implications for American religion today, remain widely unknown. This report will present a wide range of new data on the history of religion and religiosity in America, discuss causes of changes over time, and explain what it all implies for American society today and in the future. By any measure, religiosity in America is declining. As this report will show, since peaking in 1960, the share of American adults attending any religious service in a typical week has fallen from 50 percent to about 35 percent, while the share claimed as members by any religious body has fallen from over 75 percent to about 62 percent. Finally, the share of Americans who self-identify or report being affiliated with any religion has fallen from over 95 percent to about 75 percent. All these statistics, and where they come from, will be explained in detail in this report. The present decline is striking in its speed and uniformity across different measures of religiosity. But a longer historical perspective suggests some caution in making overbold statements about what such a decline might portend. At the dawn of the American republic in the 1780s, probably just a third of Americans were members in any religious body, and just a fifth could be found at church on a given Sunday. This was a historic low ebb in American religiosity. Thus, in some important ways, America today is more religious than it was two centuries ago—and indeed at any point between 1750 and 1930. But the perception of an increasingly secular society is not wrong. Even in past periods when religious attendance and membership were low, other forms of religious attachment were still robust: More than 85 or 90 percent of Americans most likely perceived themselves as religious in some form or fashion in all periods before 1960. They were hard-drinking, sometimes murderous, rapscallions, gamblers, and slavers, who did not go to church and were not part of any religious body. But, if you asked, the vast majority of Americans would most likely say they at least believed in God and quite likely would identify themselves as Christians. More than two-thirds of baby boys received religious names, and before 1800, virtually all babies born in America had church baptisms, dedications, or christenings. Furthermore, early America was dominated by formal, official religion. Most of the 13 colonies had established religions, and legal favoritism for some religious groups continued in various forms and places until at least the 1950s. Today, all this has changed. More Americans have no religious identity at all. A quarter do not identify with any religion, less than a third are given names connected to any religion, and America’s legal environment is increasingly secular, explicitly limiting support for religion. Indeed, that changing legal and policy environment may be the cause of declining religiosity. Research on determinants of religiosity has found two contrasting results. First, explicitly sectarian governance, such as having a state religion, tends to reduce religiosity, because it reduces the competitiveness and diversity of the religious marketplace. Second, expansions in government service provision and especially increasingly secularized government control of education significantly drive secularization and can account for virtually the entire increase in secularization around the developed world. The decline in religiosity in America is not the product of a natural change in preferences, but an engineered outcome of clearly identifiable policy choices in the past.

Using a novel database of 159 million online job postings, we examine changes in employer skill requirements for education and specific skillsets between 2007 and 2017. We find that upskilling-in terms of increasing demands for bachelor's degrees as well as software skills-was a persistent trend among high-skill occupations, but either a temporary or non-existent phenomenon among middle-skill and low-skill occupations. We also find evidence that persistent upskilling in the high-skill sector contributed to greater occupational mismatch that remained elevated during the recovery from the Great Recession. In contrast, labor market mismatch had largely dissipated within the low-skill and middle-skill sectors by 2017.

This chapter analyzes the determinants of bilingualism at home (i.e. speaking a language other than or in addition to English) among children born in the United States or who immigrated as children. It does this through an analysis of a large data set (American Community Survey [ACS]) using the tools and methodology of economics. Little attention has been devoted to the determinants of bilingualism among children in the United States in the economics literature. This is largely due to the lack of suitable microeconomic data. However, the origin of bilingualism among native-born American children is a topic of particular interest. Usua11y, considerable conscious investment of time and out-of-pocket expenses in learning a second language (a form of human capital) are required for an adult; however, children do not usually make such an investment consciously and may obtain their knowledge through another path, such as interacting with a parent, or other caregiver, who speaks a language other than English. It is also important to consider foreign-born children who immigrated at a very young age, for example, prior to the age of 14, the so-called 1.5 generation. These children may have already developed competence in the language(s) of their country of origin, even if they no longer practice it/them at home in the host country.

Over the early twentieth century, urban centers across the United States adopted full-time public health departments. Using an event-study design, we show that opening full-time administration had no impact on mortality (all-cause, infant, by-cause). Then, we use city financial records to explain why health departments were ineffective. First, cities with and without health departments had comparable spending on public health. Second, per capita expenditures (and per capita expenditures interacted with a health department) correlate with infant mortality reductions. While urban public health administration as a bureaucratic apparatus appears unnecessary, public health system funding may be more meaningful for local health.

This dissertation analyses how the geographical sorting of individuals and households affects labour markets as well as gender and spatial inequality. In the first chapter, I show that labour force participation increases with city size for all demographic groups except for women with children, for whom it decreases, a phenomenon that I label Big City Child Penalty (BCCP). Both by means of empirical evidence and a quantitative spatial model of households, I show that the BCCP can be explained by commuting times, wages, and childcare price differentials between small and big cities as well as for unobserved heterogeneity in preferences for a stay-home parent. The second chapter of this dissertation highlights the role of delayed childbearing as an important driver of gentrification. While downtowns provide shorter commuting times and more consumption amenities, limited housing space and schools’ worse quality reduce the value of this location choice when children are born. We exploit exogenous variation in the cost of postponing childbearing to obtain causal estimates of the impact of delayed maternity on gentrification. We find that enhanced access to assisted reproductive technologies in the state increases income downtown by 5.4% relative to the suburbs. The third chapter studies the relationship between trade and migration. Coinciding with a period of increasing trade integration, the educational composition of migrants within the European Union changed towards high-skilled workers. We build a two-country, two-sector general equilibrium model in which countries only differ in the productivity of high-tech workers. While price equalization, induced by trade integration, equalizes the real wages of non-educated workers, differences in the real wages of educated workers remain, since the latter are more productive in the most advanced country. As a consequence, factor mobility is needed to exhaust differences in real wages, leading to high-skilled emigration towards the most advanced country.

The Current Population Survey (CPS) classifies the jobs of respondents into hundreds of detailed industry and occupation categories. The classification systems change periodically, creating breaks in time series. Standard concordances bridge the periods, but often leave empty cells or inaccurate sharp changes in time series. Standard concordances also usually hold the assumption that a certain period of time can be representative, on more aggregate levels, of various historical periods. For each employed CPS respondent classified under a previous classification method we apply prediction algorithms, principally random forests, to impute standardized industry, occupation, and related variables. The imputations use micro data about each individual and large training data sets about the population. In some of the training data sets, industry and occupation have been classified by specialists into two industry and occupation category systems-that is, they are dual-coded. We train a random forests classifier to handle the changes in classification between the 1990s and 2000s largely on the dual-coded data set and apply it to the full CPS and IPUMS-CPS to impute several variables including industry and occupation. For changes in classification when an industry or occupation splits, we train the algorithms on the observations with the newly classified industry or occupation split, to predict how the historical observations would have been classified. We generate an augmented CPS, with additional columns of standardized industry and occupation. Augmented data sets of this kind can serve research on many topics.

This thesis analyzes the association between MSA-level segregation and labour market and educational outcomes in the US for individuals belonging to the three largest racial minorities in the US, namely blacks, Hispanics, and Asians. Five different measurements of segregation are included in the analysis and the results are compared across outcomes and minority groups. Data is collected from the IPUMS USA database and the sample consists of cross-sectional microdata from the US censuses of 1980, 1990 and 2000. The thesis finds that the average level of segregation in an urban area is indeed associated with individual labour market and educational performance but that results differ from minority group to minority group and is dependent on the way segregation is measured.

Work often entails up-front effort costs in exchange for delayed benefits, and mounting evidence documents present bias over effort in the face of such delays. This paper studies the implications for the optimal income tax. Optimal tax rates are computed for present-biased workers who choose multiple dimensions of labor effort, some of which occur prior to compensation. Present bias reduces optimal tax rates, with a larger effect when the elasticity of taxable income is high. Optimal marginal tax rates may be negative at low incomes, providing an alternative, corrective rationale for work subsidies like the Earned Income Tax Credit.

Rural communities in the U.S. High Plains rely on groundwater from the declining Ogallala aquifer. I apply the sociological concepts of social structure, culture, and agency to understand the relationships between farmers/producers and groundwater management. My mixed methods approach includes quantitative modeling of secondary data, a survey of producers across the Ogallala Aquifer region, interviews with producers in Western Kansas, and a case study of sustained civic engagement among the producers who formed the Wichita County Water Conservation Area (WCA). My model of secondary data shows no association between groundwater extraction and human development at the county level. This suggests that the benefits of groundwater extraction are not being reinvested into local human and financial capitals. My interviews with producers provide support for a treadmill of production and for reinvestment into local cultural and social capitals. Consistent with a treadmill of production, producers described how investments in irrigation infrastructure make it costly for them to conserve groundwater. They described how irrigation increases cultural and social capital through higher populations, increased community cohesion, and maintaining their way of life. My survey of producers indicates that an overwhelming majority (92%) agree that groundwater should be conserved, primarily to benefit future generations (86%), support local jobs and businesses (66%), provide insurance against drought (63%), and continue the economic viability of irrigated agriculture (60%). Most producers (72%) believe they are already doing all they can individually to conserve groundwater on their operations. Interviews with producers indicate that those who become involved voluntary group conservation efforts find additional ways to conserve. Most producers (84%) are open to the possibility that voluntary group conservation may be effective and that they might have something personally to contribute to such efforts, but few (7%) are currently involved. My interviews show that values, beliefs, and norms are important to their individual and collective groundwater management decisions. However, my model of survey data suggests that differences in producers’ values, beliefs, and norms do not explain which producers are civically engaged in voluntary group conservation efforts. I argue that civic engagement is contingent, in that structural and cultural factors must align in a particular community to enable producers to choose to pursue voluntary group conservation. My interviews with producers and case study of the Wichita County WCA support this explanation. Wichita County was primed for voluntary group conservation through structural and cultural factors, including a quantity of groundwater that made conservation efforts both urgent and promising, a single town that producers value and which economically relies on groundwater, and previous efforts that raised local awareness about groundwater conservation. The Wichita County WCA team sustained civic engagement through solidarity, developing a shared sense of meaning and purpose, and taking a diffuse and relational approach to leadership. They managed emotions such as fear, grief, despair, and frustration in a manner consistent with the Public Narrative model of social action. Key factors in their success included an early focus on teambuilding, diverse stakeholder representation, bringing in an outside facilitator, frequent and respectful community outreach, and partnering with state and local government. Voluntary group efforts are effective at conserving groundwater and merit support.

This paper examines the coalitional stability of apportionment rules considered as part of the Fourteenth Amendment, assuming Congress limited itself to the eleven rules proposed by its members. Using each state's vote share as a measure of preference for various apportionment schemes, we find that the stability of legislative apportionment depended upon which states were seated in Congress as well as the voting threshold-majority, two-thirds, or three-fourths. Among all states, all eleven apportionment rules were in a top cycle under majority rule. A population-based apportionment, initially proposed by Representative James Blaine, made it out of committee and through both chambers of Congress largely because it was not voted upon against other proposals. Many of these rules provided greater vote shares for a majority of members than Blaine's and could have defeated that status quo just as easily. Our analysis raises questions about majority support for a portion of the Fourteenth Amendment in 1866.

In this document we describe a project to link records from the 1940 U.S. Census to records for respondents to the Health and Retirement Survey (HRS). The project is part of a larger effort to conduct parallel linkages to the 1940 Census for respondents to the HRS, the Panel Study of Income Dynamics (PSID), the Wisconsin Longitudinal Study (WLS), the National Social Life, Health, and Aging Project (NSHAP), and the National Health and Aging Trends Study (NHATS). In each cohort study, many sample members were alive at the time of the 1940 federal census and were thus enumerated (along with their families and household members). These five ongoing longitudinal studies are central components of America’s data infrastructure for interdisciplinary research on aging and the life course; physical and mental health, disability, and well-being; later-life work, economic well-being, and retirement; end-of-life issues, and many other topics. Adding information about sample members from the 1940 Census will expand the utility of all five projects and will enable important research on the effects of early life social, economic, environmental, contextual, and other factors on subsequent life outcomes. Broadly, the project described in this document involved (1) preparing and formatting data files containing respondents’ identifying information; (2) deploying machine learning algorithms to mechanically link project records to the 1940 U.S. Census; (3) hand linking records that could not be machine linked and hand-verifying a portion of those that could; and (4) documenting the new measures and making them available as part of the HRS’s restricted access dissemination systems in a manner consistent with HRS respondents’ privacy rights. In this document we describe the linking procedures, explain the structure of the resulting linked files and how they can be accessed, and provide information about linkage rates and the reliability and validity of the links.

Among children under age nine, there is wide variation in rates of deep poverty across the states, ranging from 4 percent to 17 percent. Large racial disparities exist nationally and within most states. In the U.S., 5 percent of young white children and 3 percent of Asian American children live in deep poverty, while these percentages are more than double for other racial/ethnic groups of young children: 18 percent of Black children, 15 percent of American Indian and Native Alaskan children, and 11 percent of Hispanic/Latino children under age 9 are in families with incomes below 50 percent of the federal poverty line. For all but a few of the indicators we compared across income groups, children in deep poverty were the most likely to experience early conditions and circumstances that make them vulnerable to future health, development, and learning problems. These indicators include low birth weight, a physical condition or health problem that limits activities, an intellectual disability or developmental delay, participation in early intervention or special education, and less positive behavior. (As mentioned earlier, participation in early intervention and special education may also reduce risks posed by conditions that make children eligible for these programs.) The parents of young children in deep poverty were the most likely to have a mental health condition, to be a single parent, to lack a high school diploma, and to be unemployed. These parents were also the least likely to report that they can count on people in their neighborhood for help when they need it. For some indicators, families in income groups other than deep poverty showed the greatest disadvantage. Young children in poverty were the most likely to be obese. Low-income children were the most likely to lack health insurance, and they also had the highest prevalence of elevated blood lead levels, although percentages did not differ significantly across income groups. Among parents, those in poverty were the most likely to lack health insurance. Although the results suggest less optimal outcomes and family circumstances for poor and low-income children, the recommendations that follow focus on families with young children in deep poverty since indicators for this group suggest exceptional risks to children’s development and life opportunities. These recommendations incorporate income support policies targeting families in deep poverty into a two-generation approach that include investments in direct support for parents’ health and mental health, child birth outcomes, and children’s development. A body of theory and research suggests that policies aimed at promoting work and higher family income alongside the provision of other supports for parent well-being and children’s development can offer benefits for children that are larger than policies that focus solely on adult workforce development or children’s development.26 In addition, the recommendations call for policies that directly promote the integration of these supports so that they provide maximum opportunities for families to thrive.

Data in public health often contain a spatial component relevant to understanding underlying relationships of interest. Accounting for different manifestations of spatial components in statistical analyses is frequently challenged by a dearth of developed methodology or high computational costs. First, we consider the problem of estimating treatment effects from observational data with propensity score matching allowing for the presence of spatial and multi-level confounding. We build on recently developed distance-adjusted propensity score matching (DAPSm) and propose a two stage approach that first matches within clusters (WC), and then uses the DAPSm approach to match remaining subjects (WC+DAPsm). We demonstrate the benefits and robustness of our approach through an extensive simulation study. We apply our method to a population of patients in Georgia who have recently started dialysis, where both the treatment (informed of transplant options) and outcome (1-year referral for transplant) may be plausibly affected by individual, facility, and area-level factors. Next, we consider the task of using satellite-derived aerosol optical depth (AOD) as a predictor for particulate matter (PM2.5) concentrations, allowing broader coverage than the network of air pollution monitors. However, AOD contains large contiguous areas of missing data due to cloud cover. We propose imputing missing AOD data using lattice kriging, a large-scale spatial statistical method, and random forest, a regression tree-based machine learning method, as well as a distance-based ensemble for combining the two methods. Throughout our application, we construct cross-validation folds and testing data based on spatially clustered holdouts more closely mimicking observed data patterns than traditional random holdouts. Our results show that the proposed distance-based ensemble outperforms individual methods. For the third topic, we discuss on-going work assessing the equity of COVID-19 testing site access in the Atlanta area. We adapt methods from the environmental justice literature using empirical cumulative distribution functions to compare demographic subgroup access to testing sites. We consider different measures of access, and we conduct Monte Carlo simulations of test site placements under different sampling schemes to assess factors associated with site placement.