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α: calibrated so average coauthorship-adjusted count equals average raw count
This paper studies the role of worker learning in a labor market where workers have incomplete information about the quality of their employment match. The amount of information about the quality of a new match depends on a worker's past job experience. Allowing workers to learn from experience generates a decline in job finding probabilities with age that is consistent with patterns found in the data. Moreover, workers with more past experience will on average have less wage volatility on new jobs, which is also consistent with the data. In contrast to the fact that the cross‐sectional wage distribution fans out with experience, this second result implies that individual wage changes become more predictable.