NBER Publications by Alok Johri

A major unresolved issue in business cycle theory is the construction of an endogenous propagation mechanism capable of capturing the amount of 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 both on aggregate 2-digit data 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.

This paper considers the importance of dynamic complementarities as an endogenous source of propagation in a dynamic stochastic economy. Dynamic complementarities link the stocks of human and organizational capital, which are influenced by past levels of economic activity, to current levels of productivity. We supplement an otherwise standard dynamic business cycle model with both contemporaneous and dynamic complementarities. The model is calibrated using estimates of these effects. Our quantitative analysis identifies empirically relevant dynamic complementarities as a source of propagation for both technology and taste shocks.