Panel Paper: Human Capital Flow: Industry Placement of Ph.D. Recipients

Saturday, November 9, 2019
Plaza Building: Concourse Level, Plaza Court 4 (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Gabi Xuan Jiang1 and Bruce Weinberg1,2, (1)The Ohio State University, (2)The National Bureau of Economic Research


An increasing share of PhD recipients are obtaining positions in industry, making it critical to assess the value of their training to their employers. Indeed a number of recent analyses have struggled to assess that value. We identify two ways in which PhD recipients may have value to business. First, PhD recipients may have substantive research knowledge that may be valuable (e.g. biochemists are likely to have specialized knowledge that is valuable to pharmaceutical companies). Additionally, people may have skills that are valuable as might be the case for physicists taking jobs at hedge funds or economists working as data scientists. In these cases, the research knowledge may have little direct application, but the skills and tools are valuable.

To quantify the importance of both channels and to measure how they are related to career outcomes, we link UMETRICS data on people employed on research projects at universities to restricted-use Census data. Specifically, we measure how closely related graduate students’ research is to the R&D conducted by businesses using the textual and semantic similarities between a doctoral dissertation and the US patents assigned to those businesses. We create a series of benchmark industries of Ph.D. placement by linking the ProQuest-US patent similarity to NAICS codes of the US patent assignee. We analyze the relationship between actual industry of placement and the benchmark industries across and within research field, which provides insights of field specific human capital flow. We also study how earnings vary with the quality of the match between research topics and patent portfolios. To identify businesses that use skills as opposed to knowledge, we identify large flows of researchers to businesses whose IP does not relate directly to the PhD’s research.