Though Barrio Logan has been an artistic core of Chicano muralism since 1970, it is in a stage of artistic transformation as the neighborhood undergoes rapid gentrification. In this research, I focus on gentefication to analyze how redevelopment is being led and influenced by Latin@/Chican@ people. The word “gentefication” is a play on la gente (‘the people’ in Spanish) and suggests a grassroots, Spanish-speaking redevelopment of the community. While gentefiers may aim to maintain and protect the cultural expression of the community, this higher classed influx of new residents continues the process of displacement so often found in gentrification. By aestheticizing the neighborhood, which attracts higher classes, artists and so-called “creatives,” the cost of living rises in the neighborhood. In this research, I analyze the roots of this disparity by focusing on uneven development of the barrio. Using census data, I map demographic patterns in San Diego from 1970-2010. I also depend on participant observations and interviews with local residents, artists, business owners, developers, and a city planner to understand the consequences of displacement in redevelopment. I question the beneficial outcomes of gentefication/gentrification in Barrio Logan, focusing particularly on historical, cultural, and economic conflicts. I explore the way aesthetic improvements and cultural appropriation influence public opinion in both positive and negative ways. This thesis is a call to unite residents, artists, and business owners to find ways to protect the established community that has been historically marginalized.

In The Declining Significance of Race, William Julius Wilson (1987) raised key questions about the fate of urban black class structure and the social organization of black communities in the wake of civil rights era reforms. Unlike in previous decades, Wilson asserted that today’s black neighborhoods comprise almost exclusively of the most disadvantaged segments of the African American population, and therefore lack the basic opportunities, resources, and social controls necessary to reduce crime. In response, this study moves away from a focus on the “ghetto” poor to contextualize the neighborhood crime conditions of middle class blacks. Drawing on social disorganization and structural race theories, I examine the relationship between the black middle class and crime using data from the National Neighborhood Crime Study (NNCS). Results from the multi-level models demonstrate that black middle class family households do effectively reduce neighborhood property and violent crime rates. Subsequent cross-level interaction models suggest that neighborhood property and violent crime decreases as the number of black middle class families in the neighborhood increases, and that this relationship is most pronounced in less segregated cities. Implications and future research directions are discussed.

This dissertation focuses on topics related to public finance and explores the incidence of policies on residents and firms. Chapter 1 asks how school districts choose to allocate their limited funding across constituent schools. It finds that school account- ability policies can explain some of the variation in within-district funding, specifically finding that districts target schools that are relatively close to school accountability rating thresholds, which are based on the percent of students passing a standardized achievement test in the Texas sample analyzed. It predicts that a typical school receives 2.5 percent more per pupil funding for each percentage point closer it is to a rating threshold. This effectively redistributes funding away from schools who are not close to these rating thresholds, including very high- and very low-performing schools. Chapter 2 asks how local fiscal outcomes respond to changes in federal deductibility of state and local taxes. It finds that raising the tax price of state and locally provided goods and services by 1 percent through limiting the deduction lowers the use of local deductible taxes by 3.5 percent and lowers the total expenditures of local governments by over 2 percent. It further finds that completely cutting the deduction for state and local taxes would not disproportionately hurt resource-poor areas, making such limits potentially progressive policy options. Chapter 3 analyzes how taxes are passed through to consumers around state borders in the context of state motor fuels taxes. Using high frequency price data and precise location data for gas stations it compares how prices change in response to changes in tax rates both near state borders and on the interior of states. It finds that stations near a border pass through about 43 percentage points less of a tax than those on the interior of a state. Furthermore, it shows evidence of tax spillovers, with stations near a border passing through about 35 percent of tax changes from neighboring states. The results suggest that the incidence of a state motor fuels tax falls relatively more heavily on residents towards the interior of a state and on firms closer to state borders.

This dissertation consists of three chapters. In each chapter I attempt to answer a question that pertains to the development of the American economy and also appeals to a general interest audience. I answer these questions in as straightforward of a manner as I deem possible and, when appropriate, I eschew technical details in favor of intuition. The first chapter of this dissertation sets out to answer one of the most enduring and contentious questions in the social sciences: why is the American labor movement so weak relative to other countries? In the spirit of Olson (1965), I build and test a model of labor union formation and activity, and, in the process, put forth industrial structure (particularly firm size) as a new explanation for the relative weakness of the American labor movement. The second chapter of this dissertation (co-authored with Karen Clay and Werner Troesken) addresses another enduring question in economic history and development: does cash cropping, and the commercialization of agriculture more generally, adversely affect nutrition? We use pellagra, a disease caused by a niacin deficiency, to study the impact of cash cropping on nutrition. Our work shows that cash cropping can displace local food production and set inmotion nutritional deficits that have long-term consequences not only for health but also for socioeconomic status. The third chapter of this dissertation (co-authored with Allison Shertzer) addresses a controversial question in labor and education economics: do school resources improve educational and labor market outcomes? We exploit the first large expansion in school resources, which occurred between 1900 and 1930, when expenditures per student almost doubled, student teacher ratios decreased by 20% and teacher salaries increased by a third. We find that increasing per pupil spending did, indeed, increase wages later in life. However, we find little evidence that increases in per pupil spending increased educational attainment.

The Moving to Opportunity (MTO) experiment randomly assigned housing vouchers that could be used in low-poverty neighborhoods. Consistent with the literature, I find that receiving an MTO voucher had no effect on outcomes like earnings, employment, and test scores. However, after studying the assumptions identifying neighborhood effects with MTO data, this paper reaches a very different interpretation of these results than found in the literature. I first specify a model in which the absence of effects from the MTO program implies an absence of neighborhood effects. I present theory and evidence against two key assumptions of this model: that poverty is the only determinant of neighborhood quality and that outcomes only change across one threshold of neighborhood quality. I then show that in a more realistic model of neighborhood effects that relaxes these assumptions, the absence of effects from the MTO program is perfectly compatible with the presence of neighborhood effects. This analysis illustrates why the implicit identification strategies used in the literature on MTO can be misleading.

California is home to more than 10 million immigrantsabout one in four of the foreign-born population nationwide. In 2015, the most current year of data, 27% of Californias population was foreign born, about twice the US percentage. Foreign-born residents represented more than 30% of the population in eight California counties; in descending order, they are Santa Clara, San Mateo, Los Angeles, San Francisco, Alameda, Imperial, Orange, and Monterey. Half of California children had at least one immigrant parent.

This paper creates a new database that covers all banks in the United States in the census years between 1870 and 1900 to test the interaction between inequality and financial development when the banking system was starting over from scratch. A fixed-effects panel regression shows that the number of banks per thousand people in the South has a strong positive relationship with the size of farm operations. This suggests that large Southern farm operators welcomed new banks after the Civil War. When the analysis is extended into the 1900s, the relationship becomes more negative, as bankers may have tried to block entrants.

I estimate the impact of two large-scale interventions aimed at improving the quality of black schooling in the South between 1900 and 1930. The first, The Julius Rosenwald Fund, focused on physical infrastructure by building nearly 5,000 schoolhouses. The second, The Anna T. Jeanes Fund, built a corps of trained supervisors whose contributions ranged from teacher training to fundraising, hence their motto: "The next needed thing." Variation in the timing and placement of these programs allows me to evaluate impacts of each, and to compare per-dollar effects of investments in human resources (Jeanes) versus physical capital (Rosenwald) on educational inequality.

The marked increase in income inequality over recent decades has become something of a preoccupation in this country—and rightly so. High levels of income inequality may adversely impact social outcomes as diverse as political participation, crime, health, and economic growth. Such levels of inequality are even more concerning given low rates of socioeconomic mobility. Contemporary to observed increases in income inequality, the U.S. also saw the rise of metropolitan “brain hubs,” labor markets characterized by rapidly growing service and technology industries and by higher average wages. In this paper, we examine how the changing industry and occupation composition of metropolitan-area labor markets is associated with patterns of romantic partnering by occupation from 1970 to the present. We contend that the advent of the American brain hub led to increases in occupational homogamy among couples. We also evaluate whether occupational assortative mating has contributed to differences in household income between metropolitan labor markets. In doing so, we establish the extent to which brain hubs and other metropolitan labor markets contribute to increases over time in newlywed assortative mating by lower and higher paying occupations and thus to increases in household income differences.

Over the past 40 years, the share of non-wage benefits in employee compensation grew from 5% to 30%. Using disaggregated data from Glassdoor, we first document a series of stylized facts about the availability of non-wage benefits and how these benefits are correlated with firm characteristics. We subsequently test three non-mutually exclusive hypotheses explaining the cross-section of non-wage benefits: (i) tax advantages, (ii) attracting and retaining specific employee groups, and (iii) mitigating the disutility of work. We find empirical evidence in support of all three hypotheses. Moreover, firms with higher rated benefits exhibit larger ex-post equity returns, suggesting that differences in non-cash types of compensation are not fully priced by the market.

We examine the golden age of U.S. innovation by undertaking a major data collection exercise linking historical U.S. patents to state and county-level aggregates and matching inventors to Federal Censuses between 1880 and 1940. We identify a causal relationship between patented inventions and long-run economic growth and outline a basic framework for analyzing key macro and micro-level determinants. We find a positive relationship between innovation and drivers of regional performance including population density, financial development and geographic connectedness. We also explore the impact of social structure measured by slavery and religion. We then profile the characteristics of inventors and their life cycle finding that inventors were highly educated, positively selected through exit early in their careers, made time allocation decisions such as delayed marriage, and tended to migrate to places that were conducive to innovation. Father's income was positively correlated with becoming an inventor, though not when controlling for the child's education. We show there were strong financial returns to technological development. Finally, we document an inverted-U shaped relationship between inequality and innovation but also show that innovative places tended to be more socially mobile. Our new data help to address important questions related to innovation and long-run growth dynamics.

Women have increased their labor participation, which has inspired the approach of some theories and empirical studies that study wages, their determination and effects in terms of occupation, inequality for reasons of gender. The objective of this research is to review the theories and empirical studies that try to explain the unequal treatment women receive in the labor market. The main results indicate that women are victims of inequality in the labor market, even in the XXI century, which causes them to be relegated to lower- level occupations and less important than to be undervalued, these occupations are considered proper or "adequate" for that sex.

What was the state-level impact of bank branching deregulation on metrics such as profits, bank size, bank efficiency, and bank employee compensation? Did the timing of deregulation influence its effects? In this essay, I will use the American state-by-state deregulation of bank branching restrictions that occurred between the 1970s and 1990s to analyze the effects of branching regulations on the banking industry within each state. I will use a difference-indifference analysis of metrics including asset size, profits, income, and indicators of industry efficiency. I test my results with additional controls including state per capita GDP, if the state was a unit banking state, and others. I examine branching deregulation's effect on workers in the industry by race, gender, and state-level banking structure, as well as the effects of a state deregulating early vs. late. I confirm that branching deregulation lowered wages of workers in commercial banking and that wages of men fell further than those of women, but I counterintuitively find that the wages of Hispanics declined by more than those of whites. I also find that bank-level metrics like asset size rise overall, but that these changes are concentrated in non-unit banking states rather than unit banking states that experienced the greatest regulatory shifts over the time period analyzed. I also construct several measures of industry efficiency and find that, by those measures, deregulation did not make the banking industry more efficient.

This paper performs a subgroup analysis on the effect of receiving a Moving to Opportunity (MTO) housing voucher on test scores. I find evidence of heterogeneity by number of children in the household in Boston, gender in Chicago, and race/ethnicity in Los Angeles. To study the mechanisms driving voucher effect heterogeneity, I develop a generalized Rubin Causal Model and propose an estimator to identify transition-specific Local Average Treatment Effects (LATEs) of school and neighborhood quality. Although I cannot identify such LATEs with the MTO data, the analysis demonstrates that membership in a specific demographic group is more predictive of voucher effects than is the groups average change in school or neighborhood quality. I discuss some possible explanations.

How can cities improve neighborhood quality after years of decline? One prominent attempt is the Minneapolis Neighborhood Revitalization Program (NRP) established in 1991 that earmarked $400 million over 20 years for neighborhoods to engage residents and create plans to improve the community. Previous studies evaluated the NRP program, but were completed too soon for the program to have a noticeable impact. Additionally, reviews of the first decade of implementation completed by 35 of the 67 neighborhoods assessed the success of the program, but these documents mainly served marketing and accountability purposes. This study adds to the critical appraisal of the NRP program by using census data and indicators for neighborhood income, home value, rent, and vacancy rate to examine whether or not the City of Minneapolis increased neighborhood quality. Propensity score matching paired Minneapolis study site neighborhoods with similar neighborhoods in St. Paul and difference-in-differences and hot spot analysis determined any significant changes in Minneapolis and its neighborhoods from 1990-2014. Regression models explored the relationship between each indicator and variables for NRP participation, amount of NRP funding, number of days participated in the NRP, and neighbor funding levels, and spatial analysis explained why some neighborhoods were more successful than others. Results show that Minneapolis performed better than St. Paul during the study period, and that some neighborhoods in the city experienced statistically significantly greater improvements, most notably the neighborhoods in downtown. Based on this analysis, the study recommends solutions to improve future iterations of this program in other locales.

Minority-owned banks (MOBs) are small banks, which often serve disadvantaged communities of color, and failed at high rates after the financial collapse. The U.S. Census and FDIC data are used to analyse bank failures for 20092014, with predictors from 2008, using logistic regression for estimation. Failure rates were high among Black and Asian Americanowned banks; these are related to bank failures in African American communities and concentration in commercial real estate lending; policy responses to the collapse were generally ineffective for small banks. We conclude that policy support for MOBs operating in disadvantaged communities of color is warranted.

Population aging is being experienced by many rural communities in the United States, as evidenced by increases in the median age and the high incidence of natural population decrease. The implications of these changes in population structure for the daily lives of the residents in such communities have received little attention. We address this issue in this study by examining the relationship between population aging and the availability of service-providing establishments in the rural United States between 1990 and 2010. Using data mainly from the U.S. Census Bureau and the Bureau of Labor Statistics, we estimate a series of fixed-effects regression models to identify the relationship between median age and establishment counts net of changes in overall population and other factors. We find a significant but nonlinear relationship between county median age and the total number of service-providing establishments, and counts of most specific types of services. We find a positive effect of total population size across all of our models. This total population effect is consistent with that found in other research, but the independent effect of age structure that we observe represents a novel finding and suggests that age structure is a salient factor in local rural development and community well-being.

This paper aims to explain the high intergenerational persistence of inequality between groups of different ancestries in the US. Initial inequality between immigrant groups is interpreted as largely due to differently strong self-selection on unobservable skill endowments. These endowments are in turn assumed to be more persistent than observable outcomes across generations. If skill endowments are responsible for a larger share of total inequality between immigrant groups than between individuals generally, the former inequality will be more persistent. This explanation implies the additional testable hypothesis that the correlation between home country characteristics that influence the self-selection pattern – in particular the distance to the US - and migrants’ or their descendants’ outcomes will increase with every new generation of descendants. This prediction receives strong empirical support: The migration distance of those who moved to the US around the turn of the 20th century has risen from explaining only 14% of inequality between ancestry groups in the immigrant generation itself, to a full 49% in the generation of their great-grandchildren today.

This exercise reproduces and assesses the historical time series on the top shares of the wealth distribution for the United States presented by Thomas Piketty in Capital in the Twenty-First Century. Piketty’s best-selling book has gained as much attention for its extensive presentation of detailed historical statistics on inequality as for its bold and provocative predictions about a continuing rise in inequality in the twenty-first century. Here I examine Piketty’s US data for the period 1810 to 2010 for the top 10 percent and the top 1 percent of the wealth distribution. I conclude that Piketty’s data for the wealth share of the top 10 percent for the period 1870 to 1970 are unreliable. The values he reported are manufactured from the observations for the top 1 percent inflated by a constant 36 percentage points. Piketty’s data for the top 1 percent of the distribution for the nineteenth century (1810–1910) are also unreliable. They are based on a single mid-century observation that provides no guidance about the antebellum trend and only tenuous information about the trend in inequality during the Gilded Age. The values Piketty reported for the twentieth century (1910–2010) are based on more solid ground, but have the disadvantage of muting the marked rise of inequality during the Roaring Twenties and the decline associated with the Great Depression. This article offers an alternative picture of the trend in inequality based on newly available data and a reanalysis of the 1870 Census of Wealth. This article does not question Piketty’s integrity.

Despite the large number of papers that investigate the linkage between income inequality and physical health, research on the linkage between income inequality and mental health has been sparse. Furthermore, the mental health and income inequality literature focuses primarily on national- and state-level income inequality, generally ignoring the sub-state level. I attempt to fill this gap in the literature by combining mental health and demographic data from the 1997 cohort of the National Longitudinal Survey of Youth with state and county income data samples from the U.S. Census Bureau in order to investigate the effect of county-level income inequality on individual mental health. Results indicate that county-level income inequality has modest non-linear effects on individual mental health, with more equal counties being affected more by increases in inequality and increases in income inequality in unequal counties may even improve individual mental health. However, after controlling for unobservable individual characteristics, income inequality has no effect on mental health suggesting that previous models in the literature are inadequate.