4 research outputs found
Race, Religion, and Immigration: Experimental Evidence from the Labor Market
In this project, we examine employers’ response to Black immigrants compared to native-born Black Americans. Between July 2017 and December 2018, we applied to publicly advertised positions using fictitious resumes that are manipulated on perceived race and ethnicity (Somali American, African American, and white American). We examine the proportion of resumes that are contacted by employers. We find that male African American applicants are 5 percentage points less likely to be contacted than equivalent white American applicants. Somali American applicants are 11 percentage points less likely to be contacted by employers than equivalent white American applicants and 6 percentage points less likely to be contacted than equivalent African American applicants. For female applicants, the effects followed a similar pattern, but were muted. Signals of language ability, education, and religiosity showed little impact on the proportion contacted by an employer
The Effect of the 2016 United States Presidential Election on Employment Discrimination
We examine whether employment discrimination increased after the 2016 presidential election in the United States. We submitted fictitious applications to publicly advertised positions using resumes that are manipulated on perceived race and ethnicity (Somali American, African American, and white American). Prior to the 2016 election, employers contacted Somali American applicants slightly less than white applicants but more than African American applicants. After the election, the difference between white and Somali American applicants increased by 8 percentage points. The increased discrimination predominantly occurred in occupations involving interaction with customers. We continued data collection from July 2017 to March 2018 to test for seasonality in discrimination; there was no substantial increase in discrimination after the 2017 local election
Native American Age at Death in the USA
There are persistent disparities in mortality rates between Native Americans and other groups in the USA. Public-use mortality data severely limits the ability of researchers to examine contextual factors that might explain these disparities. Using restricted-use mortality microdata, we examine the relationship between geographic location, specific causes of death, and age at death. We show that Native American women, on average, die 13 years earlier than White women; Native American men, on average, die 12 years earlier than White men. These disparities are largest in the northern Great Plains and Rocky Mountain states. The disparity in age at death is in part due to Native Americans dying from diseases at younger ages than White Americans. Native American women and men die younger and more often from homicide in counties with persistently higher White male to female ratios. Native American men also die younger and more often from homicide when White male to female ratios increase within their county over time
Native American Age at Death in the USA
There are persistent disparities in mortality rates between Native Americans and other groups in the USA. Public-use mortality data severely limits the ability of researchers to examine contextual factors that might explain these disparities. Using restricted-use mortality microdata, we examine the relationship between geographic location, specific causes of death, and age at death. We show that Native American women, on average, die 13 years earlier than White women; Native American men, on average, die 12 years earlier than White men. These disparities are largest in the northern Great Plains and Rocky Mountain states. The disparity in age at death is in part due to Native Americans dying from diseases at younger ages than White Americans. Native American women and men die younger and more often from homicide in counties with persistently higher White male to female ratios. Native American men also die younger and more often from homicide when White male to female ratios increase within their county over time