Supplementary appendix: Careers in firms: estimating a model of learning, job assignment, and human capital aquisition
AbstractIn this appendix I present details of the model and of the empirical analysis and results of counterfactual experiments omitted from the paper. In Section 1 I describe a simple example that illustrates how, even in the absence of (technological) human capital acquisition, productivity shocks, or separation shocks, the learning component of the model can naturally generate mobility between jobs within a firm and turnover between firms. I also present omitted details of the proofs of Propositions 1, 2, and 3 in the paper. In Section 2 I provide an overview of the numerical solution of the model. In Section 3 I discuss in detail model identification. In Section 4 I briefly describe the original U.S. firm dataset of Baker, Gibbs, and Holmström (1994a), on which my work is based. In Section 5 I derive the likelihood function of the model. In Section 6 I present results from a Monte Carlo exercise to show the identifiability of the model’s parameters in practice. In Section 7 I derive bounds on the informativeness of jobs at competitors of the firm in my data, based on the estimates of the parameters reported in the paper. Finally, in Section 8 I present estimation results based on a sample that includes entrants into the firm at levels higher than Level 1. Results of counterfactual experiments omitted from the paper are contained in Tables A.12–A.14.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 470.
Date of creation: 2012
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- Erik Meijer & Jelmer Ypma, 2008. "A Simple Identification Proof for a Mixture of Two Univariate Normal Distributions," Journal of Classification, Springer, vol. 25(1), pages 113-123, June.
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