We employ U.S. Census Bureau data from cities of 10,000 or more to examine the impact of immigrants in American cities on self-employment and median income. The results show that self-employment has a statistically significant and positive impact on median income and immigrant population. When controlling for race populations, lagged immigrant population has a negative impact on self-employment, but removing the Hispanic control causes this relationship to become statistically insignificant. In other words, Hispanics, not other ethnici-ties, drive much of the self-employment in U.S. cities. An implication is that more attention to helping Hispanic business owners succeed and expand their businesses could benefit the general population of a city.

This paper documents and explores black-white differences in U.S. womens labor force participation, occupations, and wages from 1940 to 2014. It draws on closely related research on selection into the labor force, discrimination, and pre-labor market characteristics, such as test scores, that are strongly associated with subsequent labor market outcomes. Both black and white women significantly increased their labor force participation in this period, with white women catching up to black women by 1990. Black-white differences in occupational and wage distributions were large circa 1940. They narrowed significantly as black womens relative outcomes improved. Following a period of rapid convergence, the racial wage gap for women widened after 1980 in census data. Differences in human capital are an empirically important underpinning of the black-white wage gap throughout the period studied.

Race and Ethnicity in America examines patterns and trends in racial and ethnic inequality over recent decades. John Iceland shows how color lines have generally softened over time in the United States but deep-seated inequalities remain-generally, blacks, American Indians, and some Hispanics fare less well than others. Among these groups, the underlying causes of the disadvantages vary, ranging from the legacy of racism, current discrimination, differences of human capital, the unfolding process of immigrant incorporation, and cultural responses to structural conditions. Throughout the book, Iceland also demonstrates that the ways Americans define racial and ethnic groups, along with changing patterns of identification in the U.S. population, influence our understanding of patterns and trends in racial and ethnic inequality.

This work interrogates the role of the law as an “actor” in the spatial patterning of racial classification. Laws governing racial intermarriage represent key ways that rigid distinctions between groups were codified. Critically, there is a great deal of state variation in these laws. We draw on a unique data set that combines samples from the 1990 and 2000 Census (5 percent IPUMS) and the 2009–2011 estimates from the American Community Survey with information on state-specific legal bans against intermarriage. Results from multilevel logistic and multinomial analyses indicate that a past of legal regulation is associated with a lower likelihood of a “mixed” classification for the offspring of black-white interracial unions, particularly in the 2009–11 period. Our results provide evidence that place-specific institutional legacies are imprinted on the classification choices made even in the midst of expanding options.

We employ a discrete choice experiment in the employment process for a national call center to estimate the willingness to pay distribu- tion for alternative work arrangements relative to traditional office positions. Most workers are not willing to pay for scheduling flexibil- ity, though a tail of workers with high valuations allows for sizable compensating differentials. The average worker is willing to give up 20 percent of wages to avoid a schedule set by an employer on short notice, and 8 percent for the option to work from home. We also doc- ument that many job-seekers are inattentive, and we account for this in estimation.

This paper provides new evidence on the effect of unionization on the cost of bank loans. By using a regression discontinuity design, we establish a causal relation between new unionization and bank loan pricing. Relative to firms in which unions barely lose elections, firms in which unions barely win elections experience an increase in the spread of the newly originated loans. Further tests suggest that the effect of labor unions on the loan spread arises through the channel of reducing the recovery rate of banks in bankruptcy rather than increasing firms' default risk.

We document the intergenerational mobility of black and white American men from 1880 through 2000 by building new datasets to study the late 19th and early 20th century and combining them with modern data to cover the mid- to late 20th century. We find large disparities in intergenerational mobility, with white children having far better chances of escaping the bottom of the distribution than black children in every generation. This mobility gap was more important than the gap in parents status in proximately determining each new generations racial income gap. Evidence suggests that human capital disparities underpinned the mobility gap.

The geographic distribution of political preferences in the US is highly correlated with population density, at national, state, and metropolitan-area scales. Using new data from voter registration records, we assess the extent to which this pattern can be explained by geographic mobility. We find that the revealed preferences of voters who move from one residence to another correlate with partisanship, though voters appear to be sorting on nonpolitical neighborhood attributes that covary with partisan preferences rather than explicitly seeking politically congruent neighbors. However, a simulation study reveals that the estimated partisan bias in moving choices is far too small to sustain the current geographic distribution of preferences. We conclude that geography must have some influence on political preference, rather than the other way around, and provide evidence in support of this theory.

In rank-aware processing, user preferences are typically represented by a numeric weight per data attribute, collectively forming a weight vector. The score of an option (data record) is defined as the weighted sum of its individual attributes. The highest-scoring options across a set of alternatives (dataset) are shortlisted for the user as the recommended ones. In that setting, the user input is a vector (equivalently, a point) in a d-dimensional preference space, where d is the number of data attributes. In this paper we study the problem of determining in which regions of the preference space the weight vector should lie so that a given option (focal record) is among the top-k score-wise. In effect, these regions capture all possible user profiles for which the focal record is highly preferable, and are therefore essential in market impact analysis, potential customer identification, profile-based marketing, targeted advertising, etc. We refer to our problem as k-Shortlist Preference Region identification (kSPR), and exploit its computational geometric nature to develop a framework for its efficient (and exact) processing. Using real and synthetic benchmarks, we show that our most optimized algorithm outperforms by three orders of magnitude a competitor we constructed from previous work on a different problem.

Background: Since 1990, Vital Statistics reports show a dramatic decline in the total fertility rates (TFRs) of American Indian and Alaska Native (AI/AN) women in the United States. Objective: We study whether the decrease in TFRs is due to a real change in fertility for a stable population; a compositional change in who identifies as AI/AN; or a methodological issue stemming from differences in identifying race across the data systems used to calculate fertility rates. Methods: We use data from the decennial US Census to study change in AI/AN fertility from 19802010. Results: We find declining TFRs when fertility is calculated within a single data system. Additionally, although TFRs are relatively stable within the subgroups of married and unmarried AI/AN women, the proportion of AI/AN women who are married has declined across birth cohorts. Conclusions: The decrease in TFRs for AI/AN women is a real change in fertility patterns and is not due to differences in racial identification across data systems. Contribution: We update knowledge of AI/AN fertility to include the decline in TFRs between 1980 and 2010.

Are the gains from trade unequally distributed in society? This paper presents new evidence on the distributional effects of trade on education groups in the U.S. through both consumer prices (expenditure channel) and wages (earnings channel). Our analysis, guided by a simple quantitative trade model, leverages linked datasets that cover the entire U.S. economy and include detailed spending data on consumer packaged goods and automobiles. First, we show that the expenditure channel is distributionally neutral due to offsetting forces. College graduates spend more on services, which are largely non-traded; however, their spending on goods is skewed towards industries, firms, and brands with higher import content. Second, on the earnings side, we find that college graduates work in industries that (1) are less exposed to import competition, (2) export more, (3) are more incomeelastic, and (4) use fewer imported inputs. The first three forces cause trade liberalizations to favor college graduates; the fourth has the opposite effect. Finally, we combine and quantify the expenditure and earnings channels using the model. A 10% reduction of all import and export barriers generates a modest increase in inequality between education groups, primarily due to the earnings channel. Welfare gains are 20% higher for college graduates, whose real income increases by 2.03% compared to 1.69% for individuals without a college degree. Reductions of import barriers with China have qualitatively similar implications.

Este artículo se centra en la siguiente pregunta: ¿Cómo las tasas de matrimonios interraciales cambiarían al considerar la distribución racial del mercado matrimonial local? Se utilizan datos de los censos brasileros de 1991 y 2000 y se estiman modelos log-lineales. Los resultados muestran que las tasas de homogamia-heterogamia han sido tradicionalmente sobreestimadas, como lo demuestra un cambio entre el 15,3% al 43,16%, cuando se considera la distribución racial local de los cónyuges. La diferencia entre las diferencias porcentuales es menor en 2000 que en 1991. Al analizar las tasas de heterogamia y homogamia para cada mercado matrimonial, se observa que la interacción entre la raza de un cónyuge y el mercado matrimonial es importante, con muy pocas excepciones. Además, aunque la mayoría de las mesorregiones tienen tasas de homogamia-heterogamia iguales al nivel promedio, existen algunas diferencias regionales importantes, especialmente en el Sur, donde los niveles son más altos que el promedio.

BACKGROUND: Total societal costs due to occupational injury and illness in the United States have been estimated to be in excess of $50 billion per year. Previous studies of selected worker populations have noted overweight and obese workers have higher levels of occupational injury and absenteeism. OBJECTIVES: The primary objective was to quantify, in the broader worker population, the relative prevalence of occupational injury among overweight and obese workers. The study also aimed to analyze the association of short-term absenteeism with the obesity level of workers. METHOD: The data source was the Integrated Health Interview Series (IHIS), based on a national survey of health behaviors in the United States. The study sample included 5,045 workers aged 18-65 years, across major industry sectors, during years 2005 to 2014. Logistic regression was used to estimate association of occupational injury prevalence and short-term absenteeism with worker body mass index, controlling for selected sociodemographic factors. RESULTS: Overweight and obese workers had significantly higher prevalence of occupational injury compared with normal weight workers. Injury prevalence was 23 percent higher among overweight persons, 32 percent higher among obese persons, and 55 percent higher among very obese persons. No association was found between short-term absenteeism and worker weight. CONCLUSIONS: Overweight and obese workers are at significantly increased risk of occupational injury. Targeted actions by private and public health providers may help mitigate underlying risk factors and reduce worker occupational injury and associated costs.

Previous water injustice research focuses predominantly on inequities and power relations in water use, management, governance, and rights. This article charts a new research direction with a case study of the unequal distribution of surface water toxic release hazard levels across census block groups in Californias Bay-Delta region in the year 2000. The article draws on secondary data and geographic information systems, as well as spatial regression analyses to test intersectional environmental inequality hypotheses regarding the determinants of surface water cumulative areal-weighted modeled hazard scores (CAWMHS) - a new environmental health hazard indicator derived in this study from the U.S. Environmental Protection Agency Risk-Screening Environmental Indicators database. Spatial error regression models demonstrate that black disadvantage and isolated Latino disadvantage are the strongest and positive demographic determinants of surface water CAWMHS, net of other factors. Findings have scholarly and practical implications for environmental inequality and water injustice research and policy.

urrent employment growth in the Fourth District appears to be above the level required to hold steady the Districts unemployment rate at todays historically low levels. But the unemployment rate, or the fraction of people in the labor force who do not have a job, will hold steady only if employment grows at the same rate as the labor force, or the number of people who either have a job or want one. How low can employment growth go before we would expect unemployment rates to rise, and, alternatively, what rate of employment growth would it take to hold the Districts unemployment rate steady?

We demystify and formalize the Bartik instrument. The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the Bartik instrument is equivalent to using local industry shares as instruments. Hence, the identifying assumption is best stated in terms of these shares, with the national industry growth rates only affecting instrument relevance. This insight applies to a variety of “Bartik-like” instruments. We consider three tests of this identifying assumption and implement them in the context of the canonical application of estimating the inverse elasticity of labor supply.

College affordability for students and taxpayers is a function of time-to-degree. Slow time to degree is costly, and student loan debt without a degree all too often is a financial disaster. For taxpayers, investments in college affordability yield little fiscally if they do not result in degree attainment. College degree completion depends primarily upon student academic preparation at the secondary school level, college selection, full-time enrollment, and the efforts of colleges themselves to support completion. Limited resources for college affordability should be leveraged against those influences and targeted where need is greatest.

We estimate a measure of long-run development in Mexico by calculating a Quasi- Human Development Index for the period 1895-2010. This index is calculated using urbanization rates, schooling measures and the number of doctors for each state in Mexico. This is the longest homogenous series to date in order to compare development at national and state level. Our findings suggest that there has been a significant increase of human development over the period studied here –however, divergence across Mexican states increased up to 1940 and then decreased substantially. Perhaps more significant, development patterns across states exhibited a strong persistence over time. The northern states turned out to be richer than the rest since the beginning of the period, while the southern states were the poorest. Moreover, the states surrounding Mexico City were as poor as the southern states at the beginning of the century, but they developed faster from 1940 to 1980.

I propose a new mechanism for sluggish wages based on workers’ noisy information about the state of the economy. Wages do not respond immediately to a positive aggregate shock because workers do not (yet) have enough information to demand higher wages. This increases firms’ incentives to post more vacancies, which makes unemployment volatile and sensitive to aggregate shocks. The model is robust to two major criticisms of existing theories of sluggish wages and volatile unemployment: flexibility of wages for new hires and pro-cyclicality of the opportunity cost of employment. Calibrated to U.S. data, the model explains 70% of unemployment volatility.