This paper analyzes the dynamics of prices and wages using a limited information approach to estimation. I estimate a two-equation model for the determination of prices and wages derived from an optimization-based dynamic model in which both goods and labor markets are monopolistically competitive; prices and wages can be reoptimized only at random intervals; and, when prices and wages are not reoptimized, they can be partially adjusted to previous-period aggregate inflation. The estimation procedure is a two-step minimum distance estimation that exploits the restrictions imposed by the model on a time-series representation of the data. In the first step, I estimate an unrestricted autoregressive representation of the variables of interest. In the second, I express the model solution as a constrained autoregressive representation of the data and define the distance between unconstrained and constrained representations as a function of the structural parameters that characterize the joint dynamics of inflation and labor share. This function summarizes the cross-equation restrictions between the model and the time-series representations of the data. I then estimate the parameters of interest by minimizing a quadratic function of that distance. I find that the estimated dynamics of prices and wages track actual dynamics quite well and that the estimated parameters are consistent with the observed length of nominal contracts.
wage and price dynamics, nominal rigidities, minimum distance estimation