What you match does matter: the effects of data on DSGE estimation

This paper explores the effects of using alternative combinations of observables for the estimation of Dynamic Stochastic General Equilibrium (DSGE) models. I find that the estimation of structural parameters describing the Taylor rule and sticky contracts in prices and wages is particularly sensitive to the set of observables. In terms of the model's predictions, the exclusion of some observables may lead to estimated parameters with unexpected outcomes, such as recessions following a positive technology shock. More importantly, two ways to assess different sets of observables are proposed. These measures favor a dataset consisting of seven observables.