Papers Containing Keywords(s): 'asian'
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Sonya R. Porter - 4
Timothy Bates - 4
Viewing papers 1 through 10 of 17
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Working PaperRevisiting Methods to Assign Responses when Race and Hispanic Origin Reporting are Discrepant Across Administrative Records and Third Party Sources
May 2024
Working Paper Number:
CES-24-26
The Best Race and Ethnicity Administrative Records Composite file ('Best Race file') is an composite file which combines Census, federal, and Third Party Data (TPD) sources and applies business rules to assign race and ethnicity values to person records. The first version of the Best Race administrative records composite was first constructed in 2015 and subsequently updated each year to include more recent vintages, when available, of the data sources originally included in the composite file. Where updates were available for data sources, the most recent information for persons was retained, and the business rules were reapplied to assign a single race and single Hispanic origin value to each person record. The majority of person records on the Best Race file have consistent race and ethnicity information across data sources. Where there are discrepancies in responses across data sources, we apply a series of business rules to assign a single race and ethnicity to each record. To improve the quality of the Best Race administrative records composite, we have begun revising the business rules which were developed several years ago. This paper discusses the original business rules as well as the implemented changes and their impact on the composite file.View Full Paper PDF
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Working PaperExamining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.View Full Paper PDF
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Working PaperAge, Sex, and Racial/Ethnic Disparities and Temporal-Spatial Variation in Excess All-Cause Mortality During the COVID-19 Pandemic: Evidence from Linked Administrative and Census Bureau Data
May 2022
Working Paper Number:
CES-22-18
Research on the impact of the COVID-19 pandemic in the United States has highlighted substantial racial/ethnic disparities in excess mortality, but reports often differ in the details with respect to the size of these disparities. We suggest that these inconsistencies stem from differences in the temporal scope and measurement of race/ethnicity in existing data. We address these issues using death records for 2010 through 2021 from the Social Security Administration, covering the universe of individuals ever issued a Social Security Number, linked to race/ethnicity responses from the decennial census and American Community Survey. We use these data to (1) estimate excess all-cause mortality at the national level and for age-, sex-, and race/ethnicity-specific subgroups, (2) examine racial/ethnic variation in excess mortality over the course of the pandemic, and (3) explore whether and how racial/ethnic mortality disparities vary across states.View Full Paper PDF
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Working PaperEarnings Inequality and Immobility for Hispanics and Asians: An Examination of Variation Across Subgroups
September 2021
Working Paper Number:
CES-21-30
Our analysis provides the rst disaggregated examination of earnings inequality and immobility within the Hispanic ethnic group and the Asian race group in the U.S. over the period of 2005-2015. Our analysis differentiates between long-term immigrant and native-born Hispanics and Asians relative to recent immigrants to the U.S. (post 2005) and new labor market entrants. Our results show that for the Asian and Hispanic population aged 18-45, earnings inequality is constant or slightly decreasing for the long-term immigrant and native-born populations. However, including new labor market entrants and recent immigrants to the U.S. contributes significantly to the earnings inequality for these groups at both the aggregate and disaggregated race or ethnic group levels. These findings have important implications for the measurement of inequality for racial and ethnic groups that have higher proportions of new immigrants and new labor market entrants in the U.S.View Full Paper PDF
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Working PaperWhose Job Is It Anyway? Co-Ethnic Hiring in New U.S. Ventures
March 2021
Working Paper Number:
CES-21-05
We explore co-ethnic hiring among new ventures using U.S. administrative data. Co-ethnic hiring is ubiquitous among immigrant groups, averaging about 22.5% and ranging from 2% to 40%. Co-ethnic hiring grows with the size of the local ethnic workforce, greater linguistic distance to English, lower cultural/genetic similarity to U.S. natives, and in harsher policy environments for immigrants. Co ethnic hiring is remarkably persistent for ventures and for individuals. Co-ethnic hiring is associated with greater venture survival and growth when thick local ethnic employment surrounds the business. Our results are consistent with a blend of hiring due to information advantages within ethnic groups with some taste-based hiring.View Full Paper PDF
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Working PaperRacial Disparity in an Era of Increasing Income Inequality
January 2017
Working Paper Number:
carra-2017-01
Using unique linked data, we examine income inequality and mobility across racial and ethnic groups in the United States. Our data encompass the universe of tax filers in the U.S. for the period 2000 to 2014, matched with individual-level race and ethnicity information from multiple censuses and American Community Survey data. We document both income inequality and mobility trends over the period. We find significant stratification in terms of average incomes by race and ethnic group and distinct differences in within-group income inequality. The groups with the highest incomes - Whites and Asians - also have the highest levels of within-group inequality and the lowest levels of within-group mobility. The reverse is true for the lowest-income groups: Blacks, American Indians, and Hispanics have lower within-group inequality and immobility. On the other hand, our low-income groups are also highly immobile when looking at overall, rather than within-group, mobility. These same groups also have a higher probability of experiencing downward mobility compared with Whites and Asians. We also find that within-group income inequality increased for all groups between 2000 and 2014, and the increase was especially large for Whites. In regression analyses using individual-level panel data, we find persistent differences by race and ethnicity in incomes over time. We also examine young tax filers (ages 25-35) and investigate the long-term effects of local economic and racial residential segregation conditions at the start of their careers. We find persistent long-run effects of racial residential segregation at career entry on the incomes of certain groups. The picture that emerges from our analysis is of a rigid income structure, with mainly Whites and Asians confined to the top and Blacks, American Indians, and Hispanics confined to the bottom.View Full Paper PDF
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Working PaperTaking the Leap: The Determinants of Entrepreneurs Hiring their First Employee
January 2016
Working Paper Number:
CES-16-48
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.View Full Paper PDF
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Working PaperMore than a Million New American Indians in 2000: Who are They?
March 2013
Working Paper Number:
CES-13-02
Over a million people reported their race as American Indian in the 2000 U.S. Census but did not report that race in the 1990 Census. We investigate three questions related to this extraordinary population change: (1) Which subgroups of American Indians had the greatest numerical growth? (2) Which subgroups had the greatest proportional increase? And (3) is it plausible that all 'new' American Indians reported multiple races in 2000? We use full-count and high-density decennial U.S. census data; adjust for birth, death, and immigration; decompose on age, gender, Latino origin, education, and birth state; and compare the observed American Indian subgroup sizes in 2000 to the sizes expected based on 1990 counts. The largest numerical increases were among non-Latino youth (ages 10-19), non-Latino adult women, and adults with no college degree. Latinos, highly-educated adults, and women have the largest proportionate gains, perhaps indicating that 'American Indian' has special appeal in these groups. We also find evidence that a substantial number of new American Indians reported only American Indian race in 2000, rather than a multiple-race response. This research is relevant to social theorists, race scholars, community members, program evaluators, and the Census Bureau.View Full Paper PDF
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Working PaperPast Experience and Future Success: New Evidence on Owner Characteristics and Firm Performance
September 2010
Working Paper Number:
CES-10-24
Because the ability of entrepreneurs to start their own businesses is key to the success of the U.S. economy and to the economic mobility of many disadvantaged demographic groups, understanding why entrepreneurship activity varies across groups and geography is an increasingly important issue. As a step in this direction we employ a novel set of metrics of business success to the growing literature and find great variation across groups and metrics. For example, we find that black-owned firms grow slower than white or Asian-owned firms. However, once we condition on firm survival, the differences disappear. Interestingly, we also find differences across groups in their start-up histories. For example, Asian-owned firms are less likely than white-owned firms to have started-out as nonemployers but firms owned by all other minority groups, as well as women-owned firms, are more likely to start-out without employees.View Full Paper PDF
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Working PaperHow Does Geography Matter in Ethnic Labor Market Segmentation Process? A Case Study of Chinese Immigrants in the San Francisco CMSA
March 2007
Working Paper Number:
CES-07-09
In the context of continuing influxes of large numbers of immigrants to the United States, urban labor market segmentation along the lines of race/ethnicity, gender, and class has drawn considerable growing attention. Using a confidential dataset extracted from the United States Decennial Long Form Data 2000 and a multilevel regression modeling strategy, this paper presents a case study of Chinese immigrants in the San Francisco metropolitan area. Correspondent with the highly segregated nature of the labor market as between Chinese immigrant men and women, different socioeconomic characteristics at the census tract level are significantly related to their occupational segregation. This suggests the social process of labor market segmentation is contingent on the immigrant geography of residence and workplace. With different direction and magnitude of the spatial contingency between men and women in the labor market, residency in Chinese immigrant concentrated areas is perpetuating the gender occupational segregation by skill level. Whereas abundant ethnic resources may exist in ethnic neighborhoods and enclaves for certain types of employment opportunities, these resources do not necessarily help Chinese immigrant workers, especially women, to move upward along the labor market hierarchy.View Full Paper PDF
