Real Business Cycles in Emerging Countries : The Role of Nonlinearity

We investigate a real business cycle (RBC) model with financial frictions for a small open economy by estimating the model solved up to the second order. The higher-order approximation more closely approximates the original model than the linear approximation. In this paper, we evaluate the likelihood of the nonlinear model using the Gaussian mixture filter (GMF) and employ the GMF within the MCMC algorithm. From the estimation results of the quadratic approximation, we obtain the following implications for a small open economy: First, contrary to the linear model with financial frictions, the quadratic model accounts for Argentine economic fluctuations by assigning a dominant role to non-stationary productivity shocks. Second, the quadratic RBC model with financial frictions does a good job of identifying the parameters of the non-stationary productivity shock process. Third, the observed data favor the quadratic benchmark RBC and financial frictions models over the linear models. Fourth, the quadratic RBC model with financial frictions is relatively more successful in capturing serial correlations of the observed data than the linear model with financial frictions. Finally, we find that risk factors play an important role in capturing the economic downturn and the counter-cyclical trade balance