Collaborative Excellence in Research: Skill Acquisition, Technical Change and Differential Employment and Income Trajectories

This research project will construct a unique historical data set to test how technological change interacts with group identity to affect employment and earning trajectories of groups differently. Testing economic models of differential labor market effects is difficult because of lack of appropriate data; a situation compounded by technological innovations.

The researchers have access to historical data on post-military careers and wage trajectories between 1910 and 1940 of two groups of men who were trained and worked in the same unit performing the same military tasks during World War I. This data will be merged with individual level data from decennial census to create a unique historical data set. The researchers will use this data set to identify whether the observed differential employment and wage trajectories of these groups is due to technical change or discrimination.

At the heart of this research is the careful merging of historical data from personal records, census records, and military records to answer this important question. Apart from the policy implication of this research, the project will involve undergraduate researchers from Historically Black Colleges and Universities, hence contribute to broadening participation in STEM education.

The results of this research will shed light on differential labor market outcomes as well as provide inputs into policies to reduce earnings inequality.

This proposed research project will merge personal, employment, earnings trajectories, and census data to test how technological innovation interacts with discrimination to determine differential labor outcomes of different groups. The PIs will merge the post-military employment, earnings, and census records of two groups of people who received the same training and did the same jobs in signals during World War I.

The data are for the period 1910 to 1940 and the project will use difference-in-difference estimation strategy to establish causal identification of how the interaction of technical change and group differences affect the dynamics and trajectories of employment and incomes of otherwise comparable workers. The major focus and importance of this project is the unique historical data set the PIs will create for this project that will also allow other researchers to study differential labor market dynamics in the presence of technical change.

Besides policy implication of this research, the project will involve undergraduate researchers from Historically Black Colleges and Universities, hence contribute to broadening participation in STEM education.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.