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Category Archives: J61

Immigrant Workers in a Changing Labor Environment: A study on how technology is reshaping immigrant earnings

By Grace Peterson

This research determines how automation affects immigrant wages in the US and how closely this impact follows the skills-biased technical change (SBTC) hypothesis. The present study addresses this question using American Community Survey (ACS) data from 2012 to 2016 and a job automation probability index to explain technological change. This research leverages OLS regressions to evaluate real wage drivers, grouping data by year, immigration status, and education level. According to the SBTC hypothesis, high skill immigrant wages should be less negatively affected by technological change than low skill immigrant wages. Univariate analysis suggests that the SBTC hypothesis is even stronger for US = immigrants than native-borns, as high skill immigrants have a lower average probability than low skill immigrants of having their jobs automated, and the difference in effect on high versus low skilled workers is larger for immigrant than native-borns. However, multivariate analysis asserts that technological change affects low skill immigrants’ wages less than high skilled individuals’ wages, which counters the SBTC hypothesis.

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Advisors: Professor Grace Kim | JEL Codes: J15, J24, J31, J61, E24

Endogeneity in the Decision to Migrate: Changes in the Self-Selection of Puerto Rican Migrants before, during, and after the Great Recession

By Aasha Reddy 

Migrants self-select on characteristics such as income. We use the U.S. Census’ ACS and PRCS to study changes in selection patterns of Puerto Rican migrants to the to the U.S. mainland (50 states) before, during, and after the Great Recession (2005 to 2016). We construct counterfactual income densities to compare incomes of Puerto Rican migrants to the mainland versus incomes of island residents under equivalent returns to skill. We examine where Puerto Rican migrants to the mainland tend to fall in the island’s income distribution and find that Puerto Rican migrants tend to come from the top 20% of the island’s income distribution. This pattern remained stable with little to no effect of the Great Recession on selectivity patterns.

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Advisors: William Darity and Michelle Connolly | JEL Codes: J15, J61, O15

The Impact of Suburbanization on Poverty Concentration: Using Transportation Networks to Predict the Spatial Distribution of Poverty

By Winston Riddick

The purpose of this paper is to investigate the determinants of concentrated poverty, a phenomenon where socioeconomically deprived groups are heavily concentrated in particular neighborhoods in a metropolitan area. Drawing on Land Use Theory and the Spatial Mismatch Hypothesis, I develop a theory that identifies suburbanization as a principal cause of poverty concentration. Using interstate highway expansion as a source of exogenous variation in suburbanization rates, I evaluate this relationship in 240 U.S. Metropolitan Statistical Areas (MSAs) from 1960-1990, with concentrated poverty measured at the tract level. Panel regressions with MSA Fixed Effects find a positive and significant relationship between highway expansion and increased poverty concentration under a variety of specifications, including alternative measures of highways and an instrumented measure of urban population decline.

Honors Thesis

Advisor: Charles Becker, Michelle Connolly | JEL Codes: I30, J61, R13, R40 | Tagged: Highways, Poverty Concentration, Spatial Mismatch, Suburbanization, Transportation Networks

Questions?

Undergraduate Program Assistant
Jennifer Becker
dus_asst@econ.duke.edu

Director of the Honors Program
Michelle P. Connolly
michelle.connolly@duke.edu