Optimal Monetary Policy in a Medium Scale Model for Emerging Markets

To establish that our model is a reasonable description of the data we estimate the model using Bayesian methods and then evaluate its fit along a number of standard dimensions. The Bayesian approach to estimating the model parameters is especially important for providing discipline on the parameters in the financial friction and nominal rigidities. As a technical contribution, we estimate the model using non-linear likelihood methods based on the “particle” filter. Since the model itself is inherently nonlinear, it cannot be solved using a linear approximation, nor it is appropriate to use a linear approximation to the likelihood function. To our knowledge this paper is the first likelihood-based empirical assessment of sudden stop models.