Chunmian Ge

Engineer/Scientist Careers: Patents, Online Profiles, and Misclassification Bias

Through an inventor survey, we find substantial error in tracking mobility of engineers and scientists by patents. These errors cause misclassification of mobility -- false positives (wrongly recording change of employer), and false negatives (failing to record change of employer). Errors are higher among inventors with shorter patent careers. Econometric theory shows that misclassification of the dependent variable causes systematic bias in regression estimates (not merely attenuation). We introduce LinkedIn as a more accurate source of career data. Taking LinkedIn as a benchmark, the rate of false positives in patent measures of mobility is 12 percent, while the rate of false negatives is 83 percent. Measuring mobility by LinkedIn, we investigate the effect of aspects of human capital previously found to affect mobility. One previous finding is robust: that mobility is higher among Silicon Valley inventors than those elsewhere. Other findings are sensitive to sample or misclassification. We interpret our results as the outcome of targeted retention of human capital.

Do economic recession and gender influence the likelihood of entry job in IT for IT graduates

Attracting and retaining women is a major concern in the IT profession. Existing literature has noted that female students are less likely to choose IT as an undergraduate major, while female IT professionals are more likely to leave the IT workforce. There is little study of an intermediate step i.e., if gender affects whether IT graduates take up their first job in IT. At the same time, the recession in developed economies has prompted research interest on its effects on IT jobs. This paper examines the intersection of these two phenomena i.e., it seeks to understand the influence of both gender and the recent recession on the likelihood of IT graduates taking up their first jobs in IT. It hypothesizes direct and interaction effects of gender and recession on the dependent variable. The hypotheses are tested through analyzing data from annual surveys of undergraduate students majoring in IT at a large public university over a 5-year period from 2007-2011 that includes the recent recession. As hypothesized, female IT graduates were found to be 7.5% less likely to enter IT jobs over this period than their male counterparts. We also found that the economic recession of 2009 has significant interaction with gender i.e., female IT students were 20.9% less likely to enter an IT job in 2009 than male IT students. We contribute to the literature by demonstrating that economic downturn and gender could significantly affect likelihood of entry job in IT, while most of the previous research considers the effects of individual characteristics. Our findings provide implications for IT students, IT employers, and government policy makers.