Abstract

Experience is a factor of production. Practice makes perfect. But when prior production enters the firm's current production function, standard dynamic models of firm production like the Olley and Pakes (1996) proxy model suffer from a simultaneity problem. Furthermore, flexible inputs are chosen dynamically and firms may even choose negative markups temporarily to increase their stock of experience. So identification approaches that are based on assuming zero or positive markups will not work (like Gandhi, Navarro, and Rivers 2019). I develop an identification approach that works for this problem. My approach only requires panel data on firm input and output choice so it can be broadly applied. I use this appoach to study the evolution of learning rates (the rate at which firms learn from experience over time) and how differences in learning rates help explain differences in the firm size distribution across industries.

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