Browsing by Author "Howell, Junia"

Now showing 1 - 5 of 5
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    As Disaster Costs Rise, So Does Inequality
    (Sage, 2018) Howell, Junia; Elliott, James R.
    Across the United States, communities are experiencing increases in the frequency and severity of natural hazards. The pervasiveness and upward trajectory of these damages are worrisome enough, but equally disconcerting are the social inequalities they can leave in their wake. To examine these inequalities, the authors linked county-level damage data to a random sample of American households. The authors visualize the pervasiveness of natural hazards as well as their influence on racial wealth gaps over time. The results show that natural hazard damages and how relief is provided afterward exacerbate the growing gap between white and black wealth.
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    Disparate City: Understanding Rising Levels of Concentrated Poverty and Affluence in Greater Houston
    (Kinder Institute for Urban Research, 2016) O'Connell, Heather; Howell, Junia
    The poverty rate of Harris County, which surrounds Houston, rose from 10 percent in 1980 to 17 percent in 2014. That alone is a troubling trend, but equally concerning is the increasing tendency in the Houston area for that poverty to be highly concentrated. Economic segregation appears to be tightening its grip on Harris County and the area’s neighborhoods are increasingly economically polarized. There is a declining number of middle-class neighborhoods in the region, and Greater Houston is experiencing an increasingly stark division between the “haves” and “have nots.”
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    Houston Region Grows More Ethnically Diverse, With Small Declines in Segregation. A Joint Report Analyzing Census Data from 1990, 2000, and 2010
    (Kinder Institute for Urban Research, 2012) Emerson, Michael O.; Bratter, Jenifer; Howell, Junia; Jeanty, Wilner
    Houston’s population grew substantially between 1990 and 2010. Between 2000 and 2010, the Houston metropolitan area added more people (over 1.2 million) than any other metropolitan area in the United States. That growth has brought important changes to the region. This report focuses on two such changes—the changes in racial/ethnic diversity and in residential segregation between the four major racial/ethnic groups.
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    Investigating the United States’ Racial Structure through the Evaluation of Residential Distribution
    (2013-04-22) Howell, Junia; Emerson, Michael O.; Lopez Turley, Ruth N.; Denney, Justin T.
    Diversification of the United States population over the past 45 years has sparked a debate about the contemporary racial structure. Some theorize Latino and Asian immigrants will eventually integrate into the White community, like the European immigrants before them. Others suggest their classification as “people of color” means they will integrate into the Black community. Still others theorize the United States is moving towards a three-tiered racial hierarchy. Racial residential segregation has been demonstrated to be an influential factor in reproducing racial classifications. Yet the use of residential distribution data to test hypotheses of racial structure has been limited because, I argue, segregation indexes are based on particular racial structures, none of which effectively capture multiple tiered hierarchies. Thus, this paper investigates the contemporary racial structure manifested through residential distribution by comparing computer simulations of hypothesized distributions to the observed distributions of Asians, Blacks, Latinos, and Whites in all census tracts in the United States in 1980, 1990, 2000, and 2010. Finding that residential segregation contributes to the mounting support for Bonilla-Silva’s theory of a three-tiered racial hierarchy, this paper argues that future research on residential segregation needs to utilize an index that effectively measures segregation in multigroup populations. Through an evaluation of the most widely utilized indexes and conceptions of segregation, this paper introduces the Summary Index of Multigroup Segregation (SIMS), which builds off the Segregation Index to give an overall measure of segregation similar to Theil’s Information Index but that can be compared across populations with different group compositions. The SIMS calculates the proportion of the total population that would need to move for the area to be completely integrated. If commonly adopted, the SIMS can enable researchers to compile studies to further investigate the factors contributing to multigroup segregation and the implications of multigroup segregation.
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    Measuring Neighborhood Effects: Re-examining the Conceptualization and Operationalization of Neighborhood Effects
    (2017-04-17) Howell, Junia; Elliott, James R
    Urban sociologists have long studied neighborhood inequality and its implications for residents’ life chances. Focusing on marginalized communities, qualitative scholars have illuminated how low educational expectations, destructive social norms and a lack of formal resources limit residents’ socioeconomic outcomes. Quantitative scholars then employ these observations to explain the correlations they find between neighborhoods and residents’ wellbeing. Yet, the most common measurements of neighborhood effects do not operationalize the multifaceted and nonlinear relationship between residential communities and residents’ socioeconomic outcomes. This dissertation is an in depth investigation into how neighborhood effects are measured and the theoretical and policy implications of these measurements. Organizationally, this dissertation is divided into three empirical studies. The first combines longitudinal geo-coded surveys from both the United States and Germany—the U.S. Panel Study of Income Dynamics and the German Socio-Economic Panel—with national censuses, governmental reports and information on local businesses and finds neighborhood socioeconomic status and institutional resources are not always correlated and operate differently across national contexts. Building off these findings, the second study examines the nonlinear relationship between neighborhood socioeconomic status and residents’ outcomes. Findings suggest neighborhood effects are strongest in advantaged communities. Finally, the third empirical piece in this dissertation examines the tipping points used to classify concentrated poverty. Results indicate the void of poverty—not its excess—drives the relationship between residential context and socioeconomic status. The dissertation concludes with a discussion about the theoretical and policy implications of these findings.