This report examines equity among local option sales tax (LOST) measures for transportation in California between 1976 and 2016. Since the first was enacted in 1976 in Santa Clara County (Silicon Valley), 76 LOST measures have appeared on county ballots, 48 of which (63%) were approved by voters. These measures have proven to be popular methods to finance transportation system construction, operations, and maintenance over the past four decades, increasing in number even after a 1995 ruling in Santa Clara County Local Transportation Authority v. Guardino required that LOSTs secure two-thirds support to pass. LOSTs are currently in place in 24 of California’s 58 counties that are home to 88 percent of the state’s population. Sales tax revenues dedicated to transportation today produce over $4 billion per year for transportation construction and maintenance in these “self-help counties.” Sixteen counties have enacted more than one sales tax measure: Alameda, Los Angeles, and Santa Clara counties have three, four, and five passed measures, respectively. Despite their popularity with voters and the local public officials who craft them, LOSTs raise several important questions concerning equity and fairness:Sales taxes are regressive with respect to income, meaning that they collect larger shares of household income from poorer households, on average, than from richer ones. While fuel taxes are similarly income regressive, their incidence rises and falls in proportion to fuel consumed—and therefore in rough proportion to road system use.1 Transportation sales taxes, by contrast, are levied on nearly all consumer purchases, and their payment is not directly related to travel. This means that, unlike fuel taxes, light users of transportation systems pay more in transportation sales taxes per mile travelled than heavy users of transportation systems. In this way, transportation sales taxes might be “doubly regressive.” These issues concern income equity. Securing supermajority (two-thirds) support for a LOST measure entails persuading enough voters to support a tax increase that will pay for the proposed expenditure plan. These plans (and the limited resources available to fund them) can pit groups of voters against one another, raising additional equity issues. How should LOST expenditures be divided among roads, public transit, and other travel modes? Even within a given mode, should priority be given to an expensive closure of a gap in the freeway network in one part of the county, or on resurfacing existing roads across the entire county? Should public transit expenditures support building a single new rail line, or improving bus service across the county? Should expenditures go to already built-up, congested parts of the county, or to outlying, growing areas where new transportation infrastructure is needed? These questions concern both modal and geographic equity. LOST measures are almost always linked to itemized expenditure plans, which specify how much is to be spent on which projects or programs, often in order of priority. Since LOSTs are typically in place for 20 or more years, when a specific project is delivered is key to determining the benefits of the plan. That an expenditure plan may propose widening a rural highway a decade before commencing an urban public transit project thus raises fairness questions as well. Further, such detailed expenditure plans may usurp transportation planning processes designed to solicit input and adapt to new circumstances. Is it fair that such plans can be locked into place, leaving certain projects or programs out, or at the back of the line, even when expert and popular opinion regarding priorities might change over time? Such questions concern temporal equity. These several dimensions of equity—income, modal, geographic, and temporal—can be conflated into more general assertions about the benefits and fairness of these taxes and their associated expenditure plans. In this report, we use the term “general equity” to refer to this conflation of equity concerns. To understand how these dimensions of equity have played out in the crafting of LOST measure expenditure plans, debates over the merits and fairness of the measures put before the voters, and in the delivery of the expenditure plans for approved measures, our research uses a mixed methods approach in which we draw from quantitative analyses of measures, financial, voter, and demographic data, as well as qualitative analyses of theories of equity and the language used to debate them.

In The Tumbleweed Society, Pugh (2015) explores the relationship between commitments at work – between employers and employees – and those at home, between partners. She finds no simple relationship such that, for example, people who feel their employers owe them nothing also have low commitment to their spouses. Rather, there is a complex web of commitments, and views of what constitutes an honorable level of commitment in different arenas. This paper is inspired by that discussion, and explores one possible connection between work and couple stability, using a new combination of data from the Current Population Survey (CPS) and the American Community Survey (ACS). In a previous paper I analyzed predictors of divorce using data from the ACS, to see whether economic indicators associated with the Great Recession predicted the odds of divorce (Cohen 2014). Because of data limitations, I used state-level indicators of unemployment and foreclosure rates to test for economic associations. Because the ACS is cross-sectional, and divorce is often associated with job instability, I could not use individual-level unemployment to predict individual-divorce, as others have done (see review in Cohen 2014). Further, the ACS does not include any information about former spouses who are no longer living with divorced individuals, so spousal unemployment was not available either.

Big geospatial data have unique challenges not associated with the greater big data community, namely, that raster and vector analytical approaches have evolved along two separate paths. Terra Populus is a next-generation spatial database repository that focuses on the integration of heterogeneous big data. When accessing Terra Populus through a web interface, users are able to transform microdata, vector, and raster datasets into user-requested formats for analysis. By providing this framework, Terra Populus lowers the barriers for researchers examining human-environment interactions.

Hydrologic budgets to determine groundwater availability are important tools for water-resource managers. One challenging component for developing hydrologic budgets is quantifying water use through time because historical and site-specific water-use data can be sparse or poorly documented. This research developed a groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010 that related county-level aggregated water-use data to site-specific well locations and aquifer units. A simple population-based linear model, constrained to 0 million liters per day in 1900, provided the best means to extrapolate groundwater-withdrawal rates pre-1950s when there was a paucity of water-use data. To disaggregate county-level data to individual wells across a regional aquifer system, a programmatic hierarchical process was developed, based on the level of confidence that a well pumped groundwater for a specific use during a specific year. Statistical models tested on a subset of the best-available site-specific water-use data provided a mechanism to bracket historic groundwater use, such that groundwater-withdrawal rates ranged, on average, plus or minus 38% from modeled values. Groundwater withdrawn for public supply and domestic use accounted for between 48 and 74% of total groundwater use since 1901, highlighting that groundwater provides an important drinking-water resource. The compilation, analysis, and spatial and temporal extrapolation of water-use data remain a challenging task for water scientists, but is of paramount importance to better quantify groundwater use and availability.

We often consider the toll the ticking biological clock takes on women, but not the economic loss it causes via its impact on marriage market prospects. I document two new facts in Census data demonstrating the potential importance of fertility in marriage market outcomes. First, women who are older at first marriage are matched with poorer husbands, whereas men who marry when older marry richer spouses. Second, the returns to education on the marriage market have historically been non-monotonic, with graduate educated women marrying poorer spouses than college educated women. To study the economic effects of time-limited fertility, I provide a matching model of the marriage market where women’s human capital investments impact a second dimension, “reproductive capital.” The model predicts precisely the non-monotonic matching equilibrium observed in the data when the fertility loss from investment is large relative to the income gains. Moreover, the model predicts the more recent movement toward assortative matching as family sizes have fallen and the return to women’s human capital has risen. To test the model’s central mechanism, I use an incentive-compatible experiment to show that age has a causal negative impact on women’s marriage market value. For every year a woman ages beyond 30, she must earn an extra $7,000 a year to remain equally attractive to potential partners.

The idiosyncratic availability and survival of historical records often forces quantitative social science historians to rely on sources describing only a subset of the population that they wish to study. Whether and how such sources can be used to study this population is a key concern. In this paper, I illustrate the intuition of an approach that enables researchers to recognize the presence of sample-selection bias—a systematic difference between the sample and the population of interest that can render conclusions drawn from the sample uninformative about the population of interest—and to draw conclusions about the broader population without ignoring this potential pitfall. A key part of this discussion concerns the role of a variable that affects whether an individual is observed but not the outcome of interest. I focus specifically on differences in average stature between the Northeast and the Midwest in the antebellum United States as observed in historical military data. Using voting patterns in the Presidential Election of 1860 as this variable, I show what simple patterns in the military data can indicate the presence of sample-selection bias, and outline how the variable enables the researcher to understand the potential impact of this bias.

This chapter describes where rural America is and how the population of rural America is changing. Rural America is large and diverse. Some rural areas are growing rapidly, whereas other rural communities house far fewer people today than they did a century ago. Rural concerns are often overlooked in a nation dominated by urban interests. Yet a vibrant rural America contributes to the nation's intellectual and cultural diversity and provides most of the nation's food, minerals, clean air, and clean water. The demographic change in rural America has implications for poverty and family well-being. This chapter considers the unfolding demographic story of rural America, setting the stage for the remainder of the book. It examines how poverty influences the viability of rural communities, the lives of rural residents, and the contributions rural America makes to the nation's material, environmental, and social well-being.

The growing economic resemblance of spouses has contributed to rising inequality by increasing the number of couples in which there are two high- or two low-earning partners. The dominant explanation for this trend is increased assortative mating. Previous research has primarily relied on cross-sectional data and thus has been unable to disentangle changes in assortative mating from changes in the division of spouses’ paid labor—a potentially key mechanism given the dramatic rise in wives’ labor supply. We use data from the Panel Study of Income Dynamics (PSID) to decompose the increase in the correlation between spouses’ earnings and its contribution to inequality between 1970 and 2013 into parts due to (a) changes in assortative mating, and (b) changes in the division of paid labor. Contrary to what has often been assumed, the rise of economic homogamy and its contribution to inequality is largely attributable to changes in the division of paid labor rather than changes in sorting on earnings or earnings potential. Our findings indicate that the rise of economic homogamy cannot be explained by hypotheses centered on meeting and matching opportunities, and they show where in this process inequality is generated and where it is not.

Using data on over 10,000 person-spells of non-employment lasting 2 months or longer in the NLSY79, my dissertation examines how women’s reasons for job exit, motherhood status, and education affect 1) the probability and timing of their return to work, 2) whether they change occupation and industry of employment between the jobs they left and the jobs they return to, and 3) whether and how women change work hours and wages between the jobs they left and the jobs they return to. Women’s exits have been studied widely, yet little is known about who returns to work. But, returning to work likely has important consequences for the well-being of women and their families. As would be expected given the high overall labor force participation rates of women in the 1980s to 2010s, nearly all women who spend two months or more not employed eventually return to work, although the timing of their reentry and the duration of their exit from employment vary greatly. Women who leave for family reasons tend to postpone re-employment for around a year longer than women who leave for other reasons; this difference is largest for women who have a bachelor’s degree. In addition, most women (51-76%, depending on classification scheme) who leave jobs and are observed returning to work change both occupation and industry upon returning to work, although change is less likely when leaving a job in occupations/industries with greater training and/or licensing requirements. On average, women who leave jobs and are observed returning to work do not experience a change in hourly wage, while they tend to return to jobs with about two fewer weekly work hours. Women who leave for family reasons and/or have children while away from employment tend to return to fewer work hours. Wages upon return are also predicted to be lower when women have children while away from employment. Results for changes in occupation/industry and job conditions upon return to work largely reflect a story of accumulated advantage, where women . . .

We study the impact of marriages resulting from bride kidnapping on infant birth weight. Bride kidnapping—a form of forced marriage—implies that women are abducted by men and have little choice other than to marry their kidnappers. Given this lack of choice over the spouse, we expect adverse consequences for women in such marriages. Remarkable survey data from the Central Asian nation of Kyrgyzstan enable exploration of differential birth outcomes for women in kidnap-based and other types of marriage using both OLS and IV estimation. We find that children born to mothers in kidnap-based marriages have lower birth weight compared with children born to other mothers. The largest difference is between kidnap-based and arranged marriages: the magnitude of the birth weight loss is in the range of 2 % to 6 % of average birth weight. Our finding is one of the first statistically sound estimates of the impact of forced marriage and implies not only adverse consequences for the women involved but potentially also for their children.

While black-white segregation has been consistently linked to detrimental health outcomes for blacks, whether segregation is necessarily a zero-sum arrangement in which some groups accrue health advantages at the expense of other groups and whether metropolitan segregation impacts the health of racial groups uniformly within the metropolitan area, remains unclear. Using nationally representative data from the 2008–2013 National Health Interview Survey linked to Census data, we investigate whether the association between metropolitan segregation and health is invariant within the metropolitan area or whether it is modified by neighborhood poverty for black and white Americans. In doing so, we assess the extent to which segregation involves direct health tradeoffs between blacks and whites. We conduct race-stratified multinomial and logistic regression models to assess the relationship between 1) segregation and level of neighborhood poverty and 2) segregation, neighborhood poverty, and poor health, respectively. We find that, for blacks, segregation was associated with a higher likelihood of residing in high poverty neighborhoods, net of individual-level socioeconomic characteristics. Segregation was positively associated with poor health for blacks in high poverty neighborhoods, but not for those in lower poverty neighborhoods. Hence, the self-rated health of blacks clearly suffers as a result of black-white segregation – both directly, and indirectly through exposure to high poverty neighborhoods. We do not find consistent evidence for a direct relationship between segregation and poor health for whites. However, we find some suggestive evidence that segregation may indirectly benefit whites through decreasing their exposure to high poverty environments. These findings underscore the critical role of concentrated disadvantage in the complex interconnection between metropolitan segregation and health. Weakening the link between racial segregation and concentrated poverty via local policy and planning has the potential for broad population-based health improvements and significant reductions in black-white health disparities.

There is substantial interest in measuring not just the quantity of new jobs but the quality as well. Existing surveys by the Bureau of Labor Statistics describe the number of new jobs created each month, as well as wages of incumbent workers, but not wages (or other characteristics) of newly created jobs. This paper aims to fill that gap by describing the creation of a new job quality metric for newly hired workers. Drawing on publicly accessible data from the Current Population Survey and Occupational Employment Statistics, I construct a job quality index of new hires based on occupation, which is more closely tied to skill demand and wages than measures based on industry. The New Hires Quality Index accounts for changing demographics of hires, can be consistently constructed from 2001 forward overall and for subgroups, does not rely on selfreported wages, and can be updated monthly. It also permits decompositions to illustrate which groups are affecting changes in the index. It should serve as a valuable new tool in gauging realized labor demand.

I study the impact on health, as measured by average stature, of the development of the transportation network in the rural antebellum United States. Within-county panel analysis and a straight-line instrument, which links major watersheds to one another and to major cities, address endogeneity concerns. I find that market access in a cohort’s birth year had a negative and large impact on its average stature. A 10 percent rise in market access is associated with a decline in average height of 0.15 to 0.35 inches, and the observed increase in market access between 1820 and 1850 explains 26 to 77 percent (depending on the identification strategy) of the antebellum decline in average stature in the rural United States. Evidence also suggests that increases in population density in response to rising market access were a channel for the negative impact of market access on average stature.

Although a considerable amount of quantities environmental justice research exists, most studies have focused on the current distribution of environmental hazards, leaving out discussion on how and why such injustices occur. Further, of the handful of studies that have examined the processes by which racial and socioeconomic disparities have emerged, the majority have focused exclusively on the siting of hazardous waste Treatment, Storage, and Disposal Facilities (TSDFs), only a subset of all polluting facilities. This study is the first national-level longitudinal study using distance-based methods to examine the disparate siting hypothesis concerning coal-fired power plants (CFPPs). The purpose of this study is to determine if there are current (2010) racial and socioeconomic disparities around U.S. CFPPs and if so, whether such disparities were present at the time of siting. In particular, this study assesses whether there were differences in the patterns of disparate siting across decades prior to, during, and after the emergence of the modern environmental and environmental justice movements. Results show present-day (2010) racial and socioeconomic disparities for existing CFPPs, and lend support for hypotheses that increased environmental awareness in the 1960’s and 1970’s, as well as increased environmental justice awareness and activism in the late 1980’s onwards, influenced CFPP siting in communities of color. However, race disparities independent of socioeconomic factors were found to be significant predictors of CFPP siting from 1965 to 1974 only, a smaller window than found by prior studies for TDSFs. Socioeconomic variables were significant independent predictors of facility siting in time periods between 1945 and 1954, 1965 and 1974, and 1984 and 1995.

This paper analyzes how changes to the deductibility o f state and local taxes under the federal personal income tax affect local fiscal outcomes. This paper is the first to study the impact o f changing tax prices on local fiscal outcomes while allowing for local heterogeneity in tax incentives at the county level. Exploiting variation at the county level yields a more elastic relationship between tax price and local spending than using coarser units o f observation. Simulations suggest that limiting the deduction fo r state and local taxes would not disproportionately hurt resourcepoor areas, making such limits potentially progressive policy options.

Local Differential Privacy (LDP) protects user privacy from the data collector. LDP protocols have been increasingly deployed in the industry. A basic building block is frequency oracle (FO) protocols, which estimate frequencies of values. While several FO protocols have been proposed, their resulting estimations, however, do not satisfy the natural consistency requirement that estimations are non-negative and sum up to 1. In this paper, we study how to add post-processing steps to FO protocols to make them consistent while achieving high accuracy for a wide range of tasks, including frequencies of individual values, frequencies of the most frequent values, and frequencies of subsets of values. We consider 10 different methods, some of them explicitly proposed before in the literature, and others introduced in this paper. We establish theoretical relationships between some of them and conducted extensive experimental evaluations. Among them, we propose to use Norm-Hyb, which keeps estimations above a certain threshold unchanged, and then converts negative estimations to 0 while adding a value (typically negative) to all other estimations to ensure a sum of 1.

Younger men, ages 21 to 30, exhibited a larger decline in work hours over the last fifteen years than older men or women. Since 2004, time-use data show that younger men distinctly shifted their leisure to video gaming and other recreational computer activities. We propose a framework to answer whether improved leisure technology played a role in reducing younger men's labor supply. The starting point is a leisure demand system that parallels that often estimated for consumption expenditures. We show that total leisure demand is especially sensitive to innovations in leisure luxuries, that is, activities that display a disproportionate response to changes in total leisure time. We estimate that gaming/recreational computer use is distinctly a leisure luxury for younger men. Moreover, we calculate that innovations to gaming/recreational computing since 2004 explain on the order of half the increase in leisure for younger men, and predict a decline in market hours of 1.5 to 3.0 percent, which is 38 and 79 percent of the differential decline relative to older men.

We examine the association between employee quality and financial reporting outcomes. Using the average workforce education level in MSA(s) where the firm operates as a proxy for employee quality, we find that firms with a high-quality workforce exhibit higher accruals quality, fewer internal control violations, and fewer restatements. These firms also issue superior management forecasts, in terms of frequency, timeliness, accuracy, precision, and bias. Employees located at the firm's headquarters primarily drive our findings. Our evidence suggests employee quality, particularly at a firm's headquarters, is associated with both mandatory and voluntary disclosure quality.