Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We present a dynamic model of individuals' educational investments that allows us to explore alternative modeling strategies for forecasting future wage distributions. The key innovation we propose is an approach to forecasting that relies only on the information that would be available at the actual time decisions are made and which incorporates the role of parameter uncertainty into the decision-making process. We compare the performance of our method with alternative models of forecasting behavior, based on CPS data over the period 1964-2004. (c) 2010 by The University of Chicago. All rights reserved.