Over the past few decades, the United States (U.S.) has experienced a massive influx of low-skilled immigrants. Between 1990 and 2018, the total immigrant population increased from 20 million (8% of the population) to 45 million (14% of the population).1 However, not all low-skilled sectors of the economy have consistently experienced positive immigrant labor supply shocks. For example, recent evidence suggests that the agricultural sector has experienced a decline in the supply of immigrant workers. Mexican and Central American immigrants are by far the largest group of lowskilled immigrants in the U.S., comprising half of the immigrant population with a high school education or less. About 80% of Mexican and Central American immigrants have at most a high school diploma, and they are typically employed in low-skilled sectors of the economy, such as agriculture and construction. Estimates suggest that 11 million unauthorized immigrants reside in the U.S., 8 million of whom are Mexican and Central American. The issue of unauthorized immigration has led to a contentious debate, driving a wedge between Americans. Opponents of immigration argue that these immigrants take American jobs, depress the wages of native-born workers (natives), and drain resources from the social welfare system. Proponents argue that these immigrants take low-paying, physically demanding jobs that Americans don’t want, which reduces the cost of goods and services, and that immigrants often contribute to the tax base even if they are unauthorized to work. Economists have failed to come to a consensus on the debate, partly because it is difficult to find empirical settings that lend themselves to producing exogenous variation in the supply of immigrants. It is plausible that elements on both sides of the debate are valid to some extent, depending on the outcome of interest and the economic sector under consideration. In this dissertation, I examine how changes in the supply of low-skilled immigrants affect various outcomes in the U.S. and the extent to which these immigrants have been able to achieve economic success. The first chapter examines how a decline in the supply of immigrant farm workers impacts labor-intensive crop production in the state of California. The second chapter investigates how increased immigration impacts native workers in non-farm sectors of the economy. The third chapter documents the extent to which Mexicans and Central Americans have been able to close the earnings and employment rate gap (relative to native workers) over time. As a whole, this dissertation sheds light on how low-skilled immigration creates winners and losers and documents the extent to which immigrants have been successful in assimilating into the U.S. labor market. Chapter 1 extends the existing farm labor literature, which has found evidence of a declining farm labor supply, by quantifying the impacts such changes have on laborintensive crop production. Specifically, I provide reduced-form estimates of the effects of shifts in the farm labor supply on the production of hand-harvested fruits and vegetables. Using crop production and employment data from California between 1990 and 2017, I estimate fixed-effects panel regressions linking farm employment (measured at the countyyear level) to crop production outcomes (measured at the crop-county-year level). Because I use variation in equilibrium employment, as opposed to exogenous variation in the labor supply, I use an equilibrium displacement model to identify plausible sources of bias that may affect my empirical estimates. This exercise reveals that my point estimates should be interpreted as upper bounds for the effects of interest. Empirically, these bounds indicate that a one percent decrease in the farm labor supply (in terms of the number of workers) causes at most a 0.37% reduction in production in the top 10 producing counties, which together produce 86% of the total value of hand-harvested crops in the state. Production effects are channeled primarily through a reduction in harvested acreage, although there are some effects on yield. I also find that a 1% decrease in the labor supply causes at most a 0.46% decrease in the total value of hand-harvested crop production in the top 5 producing counties (or $600 million). The results from this chapter indicate that a declining farm labor supply could generate economically meaningful consequences for farmers, but that it will likely not devastate the aggregate production of fruits and vegetables in the near future. Chapter 2 analyzes the impact of immigration on the labor market outcomes of native workers in the U.S.2 The analysis focuses on workers in U.S. metropolitan statistical areas using U.S. Census and American Community Survey data between 1990 and 2011. We use a set of imperfect instruments to derive new bounds on the short-run impacts of immigration on the earnings, employment rate, and full-time employment rate of natives. We focus on nine sectors with higher immigrant penetration and instrument for the sectoral immigrant share using the immigrant share in all other sectors. We find negative effects of immigration on native earnings in sectors where we would most expect to find them: low-skilled sectors that produce non-traded goods where immigrant penetration has been high in recent decades. We uncover negative effects on native earnings in the construction, food service, and personal service sectors, with upper bounds ranging from -2.9% to -6.6% for each 10 percentage point increase in the immigrant share. Earnings effects in other sectors are not statistically significant. In the six low-skilled sectors we consider, immigration reduces the native employment rate, with effects ranging from -0.6 to -2.0 percentage points for each 10 percentage point increase in the immigrant share. Our findings indicate that increases in the low-skilled immigrant labor supply lead to worse labor market outcomes for some low-skilled native workers in the short run. Chapter 3 investigates whether recently arrived low-skilled immigrants have been more successful than older cohorts at assimilating into the U.S. labor market.3 Specifically, we use U.S. Census and American Community Survey data between 1970 and 2017 to examine how different Mexican and Central American cohorts of arrival compare to similarly aged and educated natives in terms of their earnings and employment rate over time. We find that, on average, they started with an earnings gap of 40-45 percent and eliminated half of it within 20 years of arrival. Recent cohorts that arrived after 1995 did better than earlier cohorts in terms of the initial gap and the convergence rate. All cohorts achieved employment rates that surpassed that of natives within 20 years of arrival. The most recent cohorts arrived in the U.S. with no employment rate gap. We conclude that Mexican and Central American immigrants enter the U.S. with a strong proclivity toward being employed. However, despite their successful integration into the labor market in terms of achieving gainful employment, they have not reached parity with their native counterparts in terms of earnings.

A large body of research documents that the 2010 dependent coverage mandate of the Affordable Care Act was responsible for significantly increasing health insurance coverage among young adults. No prior research has examined whether sexual minority young adults also benefitted from the dependent coverage mandate, despite previous studies showing lower health insurance coverage among sexual minorities and the fact that their higher likelihood of strained relationships with their parents might predict a lower ability to use parental coverage. Our estimates from the American Community Surveys using difference-indifferences and event study models show that men in same-sex couples age 21-25 were significantly more likely to have any health insurance after 2010 compared to the associated change for slightly older 27 to 31-year-old men in same-sex couples. This increase is concentrated among employer-sponsored insurance, and it is robust to permutations of time periods and age groups. Effects for women in same-sex couples and men in different-sex couples are smaller than the associated effects for men in same-sex couples. These findings confirm the broad effects of expanded dependent coverage and suggest that eliminating the federal dependent mandate could reduce health insurance coverage among young adult sexual minorities in same-sex couples.

The characteristics of urban land surfaces contribute to the urban heat island, and, in turn, can exacerbate the severity of heat wave impacts. However, the mechanisms and complex interactions in urban areas underlying land surface temperature are still being understood. Understanding these mechanisms is necessary to design strategies that mitigate land temperatures in our cities. Using the recently available night-time moderate-resolution thermal satellite imagery and employing advanced nonlinear statistical models, we seek to answer the question “What is the influence and relative importance of urban characteristics on land surface temperature, during both the day and night?” To answer this question, we analyze urban land surface temperature in four cities across the United States. We devise techniques for training and validating nonlinear statistical models on geostatistical data and use these models to assess the interdependent effects of urban characteristics on urban surface temperature. Our results suggest that vegetation and impervious surfaces are the most important urban characteristics associated with land surface temperature. While this may be expected, this is the first study to quantify this relationship for Landsat-resolution nighttime temperature estimates. Our results also demonstrate the potential for using nonlinear statistical analysis to investigate land surface temperature and its relationships with urban characteristics. Improved understanding of these relationships influencing both night and day land surface temperature will assist planners undertaking climate change adaptation and heat wave mitigation.

We make only one point in this article. Every quantitative study must be able to answer the question: what is your estimand? The estimand is the target quantity—the purpose of the statistical analysis. Much attention is already placed on how to do estimation; a similar degree of care should be given to defining the thing we are estimating. We advocate that authors state the central quantity of each analysis—the theoretical estimand—in precise terms that exist outside of any statistical model. In our framework, researchers do three things: (1) set a theoretical estimand, clearly connecting this quantity to theory, (2) link to an empirical estimand, which is informative about the theoretical estimand under some identification assumptions, and (3) learn from data. Adding precise estimands to research practice expands the space of theoretical questions, unlocks new tools with which to answer them, and heightens clarity about the link between theory and evidence.

This dissertation consists of two essays on immigrant entrepreneurship. In the first essay I examine the question "Are immigrants more entrepreneurial than natives?" While previous papers have equated self-employment with entrepreneurship, in this essay I make the important distinction between entrepreneurs and other self-employed individuals based on incorporation status. Similar to what has been found by Levine and Rubinstein (2017), I find that incorporated self-employed immigrants have much higher levels of education and higher earnings compared to unincorporated self-employed and wage earner immigrants. These patterns suggest that it is useful to distinguish between the two types of self-employed even among immigrants. Making this distinction, I find that immigrants are more likely than natives to be incorporated self-employed. I also find that it takes time for immigrants to catch-up and surpass natives, and there is an important process of entrepreneurial assimilation. Immigrants start below natives when they first arrive but catch up to natives in approximately 10 years. Finally, second generation immigrants are even more likely than first generation immigrants to be incorporated business owners. In the second chapter I investigate the role of shocks to collateral and access to capital in accounting for this assimilation process. Using panel data constructed from March CPS I examine entry into entrepreneurship from wage employment and find evidence that collateral constraints are more important for immigrants than natives. I estimate the effect of an exogenous increase to collateral on entry into incorporation using a difference-in-differences estimation strategy, comparing across home owners and renters in states which experienced larger and smaller increases in home prices. Exogenous shocks to collateral have a positive effect on entry into entrepreneurship for immigrants but not so much for natives. In summary, this dissertation explores the entrepreneurship of immigrants relative to natives then investigates possible methods to entry into entrepreneurship in the United States.

Previous research has consistently shown that racial bias can influence employers’ perceptions and evaluations of Black individuals in hiring and promotion decisions. However, within-race differences (e.g., skin tone, Afrocentric features) can lead to variation in these decisions. In addition to phenotypical variation, ethnicity cues (e.g., perceived country of origin, name) may be important within-race factors influencing the perception and evaluations of Black job applicants. Using a resume evaluation paradigm, participants evaluated one of three resumes in which the target applicant’s name provided cues about ethnicity (either Black American, Black African, or White American). Results suggest that Black Americans may experience more discrimination in hiring and are generally perceived less positively across several employment-related domains than both White and Black African applicants. Specifically, we find that Black Americans are less likely to be selected for an interview or offered a job and are evaluated more negatively overall relative to Black Africans.

Objectives Nurse–Family Partnership (NFP) is an evidence‐based home visitation program designed for low‐income, first‐time mothers to support pregnancy, child development, and maternal self‐sufficiency. This study examined educational and employment outcomes among NFP clients compared to a reference sample. Design Entropy balancing and a difference‐in‐difference design were used to compare the two samples of women from 2007 to 2016. Sample There were 127,427 women in the NFP sample, and 787 women in the reference cohort. Measurements Educational outcomes included high school completion and employment outcomes consisted of employment status. Results Across a one‐year interval, NFP mothers with less than a high school diploma or general education diploma (GED) at baseline showed a 9.5 percentage point increase in diploma or GED attainment compared to the reference mothers [95% CI: 0.015–0.180]. Similarly, mothers enrolled in NFP who were not employed at baseline showed a 7.8 percentage point increase in employment compared to the reference mothers [95% CI: 0.003–0.150]. Conclusions The findings in this study show positive results for NFP mothers attaining high school completion and employment compared to mothers in the reference group. Such findings are of importance with regard to progression toward economic self‐sufficiency and corresponding reduction of health disparities.

This dissertation consists of three studies of the relationship between neighborhoods, housing policy, and local public schools. In the first chapter I analyze mortgage loans and home values from 2000-2014 to study housing markets in neighborhoods near racially diverse schools. Using a national sample of over 3,600 middle schools, I construct a measure of school demographic diversity and estimate how home values and mortgage loan amounts change as diversity increases. For identification I isolate variation in school demographics associated with the quasi-random timing of rental housing development under the Low-Income Housing Tax Credit (LIHTC) program. I find that mortgage amounts rise by nearly 6.7%, holding median home values constant and controlling for changes in local income levels and home buyer socioeconomic characteristics. The magnitude of the effect is consistent for white, black, and Hispanic home buyers, and coincides with a decrease in home values of 2.5% near diversifying schools. The effect is reversed for white home buyers near diverse schools in low-income areas, who borrow less for housing holding home values constant. I present two explanations for these findings, both which shed light on neighborhood wealth, down payment ability, and the consequences of household sorting over local amenities. The second chapter is a joint work with Pat Bayer and Peter Blair. We estimate how much parents value school expenditure and their willingness to finance it through higher taxes. Exploiting plausibly exogenous variation in expenditures and taxes from school finance reforms, we find that a 1 percent increase in taxes to fund education increases house prices by an economically small and statistically insignificant 0.06 percent. We find larger price changes in regions with less elastic housing supply. Our results provide support the core prediction of Tiebout (1956) that decentralized jurisdictions can efficiently provide local public goods such as education. The third chapter is a descriptive study of a key provision of the Low-Income Housing Tax Credit Program that reserves certain rental units for families with children. I show that this type of development in particular has an effect on schools that is statistically distinguishable from other types of LIHTC development. I then test whether changes at the school level induced by this provision alter the way districts allocated resources for schooling. The preliminary results of this analysis open the door for future research using more sophisticated inference techniques.

This article provides the theoretical foundation for the concept of "Underwaterwriting," which can be understood as various informational and institutional limitations related to environmental exposure and climate change impacts-specifically flooding and sea level rise inundation-shaping firm participation in mortgage markets. Underwaterwriting suggests that the unevenness of scientific knowledge and local soft information, as well as the institutional barriers for the utilization of that information, could result in determi-nations of risk that may not accurately reflect long-term asset performance or credit loss. These informational asymmetries may result in assignments of risk that reflect a degree of arbitrariness or inaccuracy that may operate to strand assets and shed or increase market share in ways that are inefficient and may otherwise lead to negative public externalities. Consistent with this theory, this article provides evidence that concentrated local lenders are transferring risk in high-risk coastal geographies in the Southeast Atlantic and Gulf Coasts (U.S.) through increased securitization of mortgages. These findings provide an impetus for supporting more robust analysis of climate-risk in light of forthcoming accounting rules that require an upfront accounting of forward-looking credit losses.

Using a 5% random sample of administrative IRS tax records covering households born from 1933 to 1952, we evaluate how three widely-used household surveys-the Health and Retirement Study, the Survey of Income and Program Participation, and the Current Population Survey-capture the level of and trends in late-life income and assets. First, relative to the tax data, survey data underestimate total income levels and overestimate declines in income at the median during the initial transition from working life to retirement. Survey estimates of median income at age 73 are lower than tax data estimates by an average of 4.5% in the HRS, 14.2% in the SIPP, and 25.1% in the CPS. Median total income declined from 58 to 68 by an average of only 11.7% in the tax data, compared with 24.4% in HRS, 16.8% in SIPP, and 29.0% in CPS. Second, survey sources overestimate income growth across birth cohorts at older ages but do a better job of capturing these trends at younger ages. Third, lower-income households have not experienced income growth across birth cohorts outside of the Social Security system. Averaging across ages 68 to 74, the 25th percentile income excluding Social Security fell by 16.5% from the 1933 birth cohort to the 1943 birth cohort in the tax data. These declines are larger in the HRS (26.9%) and SIPP (45.5%) and smaller in the CPS (11.1%). The fraction of households in the tax data with no non-Social Security income and no assets at age 72 rose from 18.9% to 20.5% from cohorts born in 1933 to 1945. The fraction of such households is captured well by the HRS and SIPP, but overstated by the CPS.

Objectives Ethnoracial disparities in sleep health across the lifecourse, may underlie other disparities in health and well-being among adults in the United States (U.S.). We evaluated if socioenvironmental stressors, which likely differ by the race/ethnicity of college students, may contribute to sleep disparities in this demographic group. Design/Measurements National Health Interview Survey data pooled from 2004 to 2017 were used to test the hypothesis that ethnoracial disparities in sleep exist among college students residing in dormitories in the U.S. Setting Nationally representative survey data. Participants A total of 2,119 college students residing in dormitories (71% White, 16% Black/African-American, 7% Hispanic/Latino, and 6% Asian) participated in the study. Results The prevalence of short sleep duration was higher among Black/African-Americans than among White students, but not among Hispanics/Latinos and Asians, after adjusting for age, gender, and region of residence. In fully adjusted models, Black/African-Americans, although no longer statistically significant after adjustments, were more likely to report short sleep duration compared with White students (adjusted prevalence ratio; [aPR] = 1.30, 95% confidence interval [CI]: 0.98-1.71). The prevalence of separate insomnia symptoms did not differ by ethnoracial group in adjusted models. Only Asian students had a higher prevalence (aPR = 1.40, 95% CI: 1.12-1.75) of nonrestorative sleep than White students. Conclusion Black/African-American but not Hispanic/Latino or Asian college students were more likely to report short sleep duration than Whites. Insomnia symptoms did not differ between groups, while Asians experienced more nonrestorative sleep. Future studies should investigate the socioenvironmental causes of disparities using longitudinal designs, larger sample sizes, better socioeconomic status (SES) indicators, and objective sleep measures.

Pediatric surgeons are collectively passionate about prioritizing the healthcare needs of children. We contend that this passion is deeply ingrained in how we drive clinical care and influence scientific discovery. Thus, the future of clinical research in our field will be deeply embedded in our history as a “patient-centric” profession. Service to pediatric patients requires an understanding of their needs and expectations, and designing research that acknowledges both. In this article we detail how future pragmatic clinical research will look in the evolving and learning health system.

In this paper we examine the education and occupation mismatch for Hispanics in the US using a novel objective continuous mismatch index and explore the role of immigrants’ social networks on this mismatch. We explore whether having a larger social network helps Hispanics in finding jobs that better match with their skill and education levels or whether living in areas with larger concentration of Hispanics leads to more competition for the same jobs in the labor market. Given that the legal status of immigrants influence how the social networks are leveraged and their impact on labor market outcomes, we focus on the citizenship status for Hispanics. The quality of match between Hispanic’s college degree major and occupation is measured using one of the continuous indices proposed in Rios-Avila and Saavedra-Caballero (2019) and calculated using pooled data for all college graduates in the US from 2010 to 2017. The Hispanic networks measures are constructed as the share of Hispanic population who are 25 years or older with respect to the total population of the same age and the second measure only includes Hispanics with at least a bachelor’s degree using the weighted pooled data from 2010 to 2015. We find that networks have a positive impact on the job-match quality, but mostly for Hispanic citizens and this effect is stronger when the networks constitutes of at least a college degree. This shows that Hispanic citizens living in higher concentration of Hispanic college graduates are better able to leverage their networks or their networks are better able to match them with jobs closer to their field of specialization and skill set.

While policymakers often promote further education for displaced workers, evidence on its effectiveness in the U.S. context primarily comes from evaluations of specific government sponsored training programs, which only represent one narrow avenue for skill acquisition. This paper studies the returns to retraining among unemployed workers, where retraining is broadly defined as enrollment in community colleges, four-year institutions, and technical centers. We link together high quality administrative records from the state of Ohio and estimate the returns using a matching design in which we compare the labor market outcomes of similar workers who do and do not enroll. Our matching specification is informed by a separate validation exercise in the spirit of LaLonde (1986), which evaluates a wide array of estimators using a combination of experimental and non-experimental data in a setting similar to ours. We graphically present the average quarterly earnings trajectories of the enrollees and matched non-enrollees over a nine-year period and show that there is little difference in earnings pre-enrollment, followed by temporarily depressed earnings among enrollees during the first two years after enrolling, and sustained positive returns thereafter. We find that enrollees experience an average earnings gain of seven percent three to four years after enrolling, and that the returns are driven by those who switch industries, particularly to healthcare.

The present study conducts a nationwide study of the association of toxic industrial pollution and the facilities that produce it on trust and civic engagement. Data on pollution exposure come from the Risk-Screening Environmental Indicators Geographic Microdata (RSEI-GM) and Toxic Release Inventory (TRI) datasets for the years 1995 to 1999. Data on trust and civic engagement come from the 2000 restricted-access Social Capital Community Benchmark Survey (SCCBS). Statistical analyses indicate that exposures to more toxic air pollution associate negatively with various measures of trust and that increased numbers of TRI facilities associate negatively with various measures of civic engagement. The implication is that exposures to toxic industrial air pollution and the facilities that produce it not only adversely affect the physical health of nearby communities but also their social wellbeing, including underlying capacities for collective action.

The coronavirus disease 2019 (COVID-19) pandemic and the policies to curb its spread brought parts of the U.S. economy to a virtual halt in March 2020. Payroll jobs declined by 0.7 million in March 2020 and 20.5 million in April 2020, pushing the seasonally adjusted official unemployment rate (U-3) to a peak of 14.7% in April 2020 (U.S. Bureau of Labor Statistics, 2020a, 2020b). This rate far surpasses the peak rates during the Great Recession of 2007 to 2009 (10.6%, January 2010) and the early 1980s recession (11.4%, January 1983; U.S. Bureau of Labor Statistics, 2020c), and yet the unemployment rate during COVID-19 has likely been underestimated (Montenovo et al., 2020). Analyses of how the COVID-19 pandemic and resulting recession impact older workers has been limited. In this report, we discuss how older workers fared in prior recessions in the United States, estimate some early effects of the COVID-19 pandemic and recession on employment and unemployment rates by age group and sex, discuss how COVID-19 and this recession differ from prior recessions, and conclude with a brief discussion of important topics for future research.

Labor productivity growth powers economic growth. Yet growth in productivity has generally slowed over the past half century, except for a brief burst during the mid-1990s and early 2000s. Since 2004 output per hour worked has grown at a pace of just 1.4 percent—which is half its pace in the three decades after World War II. This slowdown in productivity growth is not unique to the United States: all of the major advanced economies have experienced similar declines in productivity growth. In this paper we consider explanations for the slowdown in productivity growth as well as the public policies that can help restore it.

Unconventional extraction techniques including hydraulic fracturing or "fracking"have led to a boom in oil and gas production in the Eagle Ford shale play, Texas, one of the most productive regions in the United States. Nearly 400000 people live within 5 km of an unconventional oil or gas well in this largely rural area. Flaring is associated primarily with unconventional oil wells and is an increasingly common practice in the Eagle Ford to dispose of excess gas through combustion. Flares can operate continuously for months and release hazardous air pollutants such as particulate matter and volatile organic compounds in addition to causing light and noise pollution and noxious odors. We estimated ethnic disparities in exposure to flaring using satellite observations from the Visible Infrared Imaging Spectroradiometer between March 2012-December 2016. Census blocks with majority Hispanic (>60%) populations were exposed to twice as many nightly flare events within 5 km as those with <20% Hispanics. We found that Hispanics were exposed to more flares despite being less likely than non-Hispanic White residents to live near unconventional oil and gas wells. Our findings suggest Hispanics are disproportionately exposed to flares in the Eagle Ford shale, a pattern known as environmental injustice, which could contribute to disparities in air pollution and other nuisance exposures.

Digital map processing has been an interest in the computer science and geographic information science communities since the early 1980s. With the increase of available map scans, a variety of researchers in the natural and social sciences developed a growing interest in using historical maps in their studies. The lack of an understanding of how historical maps can be used in research and the capabilities of map processing technologies creates a significant gap between the wide range of communities that could benefit from the advances in digital map processing technologies and the disciplines in which the technologies are developed. As a result, researchers who intend to use historical maps in their studies still need a significant amount of resources to digitize their maps, while the existing digital map processing technologies are difficult to apply and understand and thus do not look promising. In many cases, existing digital map processing technologies could help facilitate the digitization process, and it just requires additional knowledge to select an appropriate technology given the problem scope (e.g., the number of maps for processing, map conditions, and style varieties). The result is that researchers waste time and resources building and testing various systems that partially duplicate prior work and cannot fully use the potential of existing technology. This chapter presents real-world applications of historical maps and case studies of both semi-automatic and fully automatic approaches for geographic feature extraction from historical maps. These real-world applications illustrate and exemplify various needs and scopes of using historical maps in scientific studies (e.g., processing thousands of historical maps from a map series vs. a few historical maps from various publishers and with different cartographic styles). The two example map processing technologies described help understand current strengths and weaknesses. These examples also illustrate tremendous collaboration opportunities between and beyond the computer science and geographic information science communities to build advanced map processing technologies that are more effective in transforming the scientific studies that use historical maps.

Research suggests that increases in a nation’s ethnic polarization will diminish its prospects for inclusive economic growth. We study the extent to which this depends on i) whether citizenship rules are based on ethnic versus civic criterion, and ii) a nation’s economic reliance on government enterprise. We do so using a novel empirical setting, comparing the growth-inequality relationships on Native American reservations (sometimes called Tribal Nations) from 1945 to 2010. We find that ethnically homogenous reservations have had relatively inclusive growth whereas ethnically polarized reservations have followed the same trend of exclusive growth – i.e., rising inequality - found elsewhere in the United States. The effect of polarization appears to be driven by uneven distribution of returns from collective tribal enterprise (e.g., casino gaming) along ethnic divisions. The findings suggest that government enterprise and ethnic nationalism are barriers to inclusive growth in ethnically polarized societies.