A major unresolved issue in business cycle theory is the construction of an endogenous propagation mechanism capable of capturing the persistence displayed in the data. In this paper we explore the quantitative implications of one propagation mechanism: learning by doing. Estimation of the parameters characterizing learning by doing is based on aggregate, 2-digit and plant level observations in the US. The estimated learning by doing function is then integrated into a stochastic growth model in which fluctuations are driven by technology shocks. We conclude that learning by doing can be a powerful mechanism for generating endogenous persistence. Moreover learning by doing modifies the labor supply decision of the representative agent making it forward looking. This has a number of implications for the interpretation of labor supply shifts as “taste shocks” and the cyclical utilization of labor which we explore in the paper.
