The estimated effects critically rely upon information on workers’ reallocation patterns, which is typically plagued with coding errors. I develop an econometric framework to collectively estimate misclassification probabilities, corrected mobility matrices, and structural parameters in a unified method. Under completely different model specifications, I examine how the estimated effects of a commerce shock differ on whether or not the analysis uses correct mobility measures and parameters. The outcomes show that estimated employment and welfare effects of a trade shock are substantially different, raising an essential warning for quantitative exercises utilizing mobility information with coding errors. We examine the determinants of lifetime earnings inequality in the us by focusing on job ladder dynamics and on-the-job learning as sources of wage progress.
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