Heterogeneity in the determinants of local self-employment growth by gender, age and selected industry, Regional Studies. This study explores the determinants of self-employment growth across US regions and by gender, age group and industry. It uses Public Use Micro Sample (PUMS) data for the 2000–2006 period and finds that self-employment growth was faster for women than for men; that growth in the 45–64-year age group outpaced growth in the age 20–44-year group; and that growth was much faster in professional and business services than in healthcare. The regression results suggest that there is significant heterogeneity in the impact of regional characteristics on self-employment growth by gender, age group and industry.

The increasing prominence of income inequality as a concern in American political discourse and in voting patterns leads some to conclude that income inequality has supplanted traditional race and class cleavages as the country’s main political fault-line. That conclusion, we argue, misses the importance of the “structure” of inequality; i.e., the extent to which it reflects disparities between racial groups or inequities among individuals who comprise the groups. Accordingly, we first decompose income inequality nationally and in each state between 1980 and 2010 into race and class components using the Theil Index (a measure seldom used in political science research). We show that racial and class inequality account for a greater share of total inequality in 2010 than they did in 1980. We then demonstrate that between-race inequality affects state welfare policy whereas total inequality, between-class inequality, and the racial composition of the population per se do not; furthermore, political variables often examined in state policy research also show no impact. These results re-affirm and clarify the nature as well as the persistent and fundamental importance of race and of class in U.S. society and its politics and policies In sum, while economic inequality is large and has grown, it apparently has negligible impact on states’ welfare policy decisions; on the other hand, enduring racial inequality clearly and consistently diminishes support for redistribution.

The seminal ruling of Tarasoff v. Board of Regents of the Universities of California enacted a duty that required mental health providers to warn potential victims of any real threat to life made by a patient. Many have theorized that this required breach of confidentiality may have adverse effects on effective psychological treatment-but the issue remains unaddressed empirically. Because of the presence of duty-to-warn laws, patients might forgo mental health treatment that would prevent violence. Using a fixed-effects model and exploiting the variation in the timing and style of duty-to-warn laws across states, I find that mandatory duty-to-warn laws cause an increase in the homicide rate of .4, or 5 percent. These results are robust to model specifications and falsification tests and help to clarify the true effect of state duty-to-warn laws.

In the beginning of the 1890s, counties located in the Cotton Belt of the American South were hit by an agricultural plague, the boll weevil, that adversely affected cotton production and hence the demand for labor. We use variation in the incidence of the boll weevil multiplied with counties’ initial cotton share to construct instrumental variables estimates of the labor supply curve. Controlling for county and state-by-time fixed effects, we find a significant positive response of labor supply to changes in labor income. The effect is particularly large for females, consistent with evidence that females had a comparative advantage in picking cotton.

Differences in the reporting units of data from diverse sources and changes in units over time are common obstacles to analysis of areal data. We compare common approaches to this problem in the context of changes over time in the boundaries of U.S. census tracts. In every decennial census, many tracts are split, consolidated, or changed in other ways from the previous boundaries to reflect population growth or decline. We examine two interpolation methods to create a bridge between years, one that relies only on areal weighting and another that also introduces population weights. Results demonstrate that these approaches produce substantially different estimates for variables that involve population counts, but they have a high degree of convergence for variables defined as rates or averages. Finally, the article describes the Longitudinal Tract Database (LTDB), through which we are making available public-use tools to implement these methods to create estimates within 2010 tract boundaries for any tract-level data (from the census or other sources) that are available for prior years as early as 1970.

Housing analysts have extensively studied homeownership attainment of immigrants and the native-born population. One major factor determining the homeownership rate gap between the two groups is immigrants length of residency in the United States. Immigrants who have arrived recently in the U.S. typically have low homeownership rates. That rate advances to higher levels as immigrants become more economically established and gain experience in U.S. housing markets, thereby narrowing the homeownership rate gap. However, one issue that has not been explored fully is how the homeownership rate gap has changed during the recent housing crisis, compared to previous years.

We investigate a new theoretical mechanism linking income levels and income distribution according to which both a high inequality and a low inequality equilibrium can be sustained, for any given level of aggregate income. This leads to a "twisted" Kuznets curve, an inverted U-shaped relationship between income (on the vertical axes) and inequality (on the horizontal axes) which resembles the original Kuznets curve, but with the axes swapped. Our results are generated by a dynamic signaling game of labor market competition where the signal is productive and wages feed back into endowments, which in turns a ffects the cost of providing the signal. We o er evidence for the U.S. on the existence of such twisted Kuznets curves and of the relevance of the signaling mechanism.

Asian Americans have long been popularly portrayed as a “model minority” that has achieved approximate labor market parity with whites. However, this characterization has been alternatively described as “a destructive myth,” especially for those who do not have high levels of education. Our analysis focuses on less educated Asian Americans who may be particularly neglected in the labor market because of their incongruence with the model minority image. Consistent with this focus, we specify quantile regression models that estimate net racial effects at both the lower and the higher ends of the distribution of earnings. The results indicate that Asian American men who drop out of high school earn substantially less than comparable whites at the low end of the earnings distribution. This pattern of racial differentials seems to be consistent with the “destructive myth” perspective and inconsistent with the alternative explanation of negative educational selectivity. In general, our findings illustrate the fruitfulness of Kevin Leicht’s (2008) proposed research agenda of studying racial disadvantage by disaggregated class-related groupings and across the entire distribution of earnings rather than focusing exclusively on one overall racial differential that is assessed as a conditional mean.

Prior to 1965, only small numbers of Korean people lived in the United States, mostly in Hawaii and on the West Coast. That year, however, the immigration restriction for Asians was abolished and a mass movement of Koreans began. Soon, new ethnic communities were established in most major American cities and smaller groupings in military towns and near universities. Although the experiences of Korean immigrants to the U. S. generally have been similar to those of other recently arrived Asian groups, a strong desire to find locales for business has produced an especially wide distribution. In addition, Korean-Americans established a number of major trends for Asian-American society as a whole, including military-tied family chain migration, an emphasis on family-owned small businesses, and active student migration.

Quantitative social survey research struggles to reconcile the widespread collection of categorical measures, and the common desire to conduct analyses which are not well suited to categorical data (involving comparing standardized, relative positions). By describing approaches taken in the DAMES NCeSS research Node, which is developing facilities to assist in the management of categorical data on occupations, educational qualifications, and ethnicity, this paper argues that tools and practices associated with e-Social Science offer an opportunity to raise standards in the analysis of categorical data.

Este trabajo estudia las disparidades salariales por raza en Brasil durante el período 1980-2010. Utilizando microdatos de censos brasileros, se encuentra que la mayor parte de la brecha observada entre el ingreso de un blanco y un afrodescendiente se debe a diferencias en características productivas, siendo el nivel educativo el mayor determinante. A pesar de ello, entre 20 y 30 por ciento de la diferencia de ingresos promedio observada no es explicada por ningún atributo determinante de la productividad, y esta porción es creciente en el tiempo. Asimismo, el análisis de la brecha salarial para distintos cuantiles de la distribución del ingreso, revela que el componente no explicado tiende a desaparecer en la cola inferior de la distribución de ingresos, y se acrecienta en la cola superior, evidenciando un posible techo de cristal para los afrodescendientes.

A disparity in pay exists between workers with and without disabilities. This gap persists even in analyses that control for a variety of factors and incorporate compensation benefits other than wages and salaries. To better understand the underlying sources of these differences, occupation-level data on employee skill and task requirements are considered. Evaluating the earnings gap with this additional information provides insights regarding the economic returns to certain workplace tasks and skills that may contribute to the earnings gap that we observe for people with disabilities.

Since the 1990s, many rural communities in the Southern US have experienced an unprecedented influx of Latino migrants. Some research undertaken on such new Hispanic destinations suggests that the newcomers tend to assume low-status jobs shunned by non-Hispanic residents and thus form a segmented labor market, but other work indicates that they heavily compete with natives (particularly African Americans) for less-skilled positions. Drawing on data from the 2000 census and 20092011 American Community Survey, this paper examines patterns of occupational stratification between Latino, white, and black men in the rural South to identify whether Hispanic economic relations in the area are better characterized by segmentation or competition. Specifically, occupational dissimilarity indexes and status scores are calculated to map the groups relative economic positions in the rural portions of five Southeastern states home to fast-growing nonmetro Latino populations: Alabama, Arkansas, Georgia, North Carolina, and South Carolina. Consistent with the segmentation hypothesis, the results reveal that Latinos are highly occupationally dissimilar from non-Hispanic whites and blacks and rank significantly below both in mean occupational status. Standardization of the stratification measures shows that Hispanics labor market isolation and disadvantage can be substantially accounted for by their lower average levels of human capital and US citizenship.

Hierarchical clustering problem is a traditional topic in computer science, which aims to discover a consistent hierarchy of clusters with different granularities. One of the most important open questions on hierarchical clustering is the identification of the meaningful clustering levels in the hierarchical structure. In this paper, we answer this question from algorithmic point of view. In particular, we derive a quantitative analysis on the impact of the low-level clustering costs on high level clusters, when agglomerative algorithms are run to construct the hierarchy. This analysis enables us to find meaningful clustering levels, which are independent of the clusters hierarchically beneath it. We thus propose a general agglomerative hierarchical clustering framework, which automatically constructs meaningful clustering levels. This framework is proven to be generally applicable to any k-clustering problem in any α-relaxed metric space, in which strict triangle inequality is relaxed within some constant factor α. To fully utilize the hierarchical clustering framework, we conduct some case studies on k-median and k-means clustering problems, in both of which our framework achieves better approximation factor than the state-of-the-art methods. We also extend our framework to handle the data stream clustering problem, which allows only one scan on the whole data set. By incorporating our framework into Guha’s data stream clustering algorithm, the clustering quality is greatly enhanced with only small extra computation cost incurred. The extensive experiments show that our proposal is superior to the distance based agglomerative hierarchical clustering and data stream clustering algorithms on a variety of data sets.

This article describes two new databases related to the racing industry. Using census data extracted from the North Atlantic Population Project and recently collected license data on jockeys of all races, the authors examine the labor market for thoroughbred horse jockeys, focusing on the period from 1880 to 1930. The decline in the number of African American jockeys is documented and discussed. The authors also estimate total labor force figures and compare experience levels and career lengths for both black and white jockeys. An unexpected finding is the higher level of labor force participation among black jockeys in the twentieth century, relative to earlier sources.