Markus Schneider

Currently I am involved in two distinct projects. The first uses restricted-access Census data via the Rocky Mountain Research Data Center (RMRDC) in Boulder, CO, to investigate the evidence for labor market segmentation and specifically to use distributional features to better characterize the observed segmentation. My co-author, Ellis Scharfenaker at the University of Utah, and I use Maximum Likelihood and Bayesian methods to distinguish between different distributional models that fit the observed distribution of earnings. Our focus is specifically on finite mixture models as these intuitively capture the possibility of discrete labor market segments with potentially qualitatively different generating mechanisms. Our initial results have been presented in a number of conferences and a working paper is forthcoming. This 5-year project has many different strands and will result in a new body of work providing an empirical characterization of labor market segmentation.

The second project I am involved in was started by Christine Ngo (now at Bucknell University), Yavuz Yasar, and myself, and generously supported by a PROF grant. Using novel UNU-WIDER data on manufacturing in Vietnam, we investigate gender differences in firm management practices across manufacturing sub-sectors. The results of this work have been presented at conference and are being prepared for submission to a suitable outlet.