Likelihood Estimation of DSGE Models with Epstein-Zin Preferences

This paper illustrates how to perform likelihood-based inference in dynamic stochastic general equilibrium (DSGE) models with Epstein-Zin preferences. This class of preferences has recently become a popular device to account for asset pricing observations and other phenomena that are challenging to address within the traditional state-separable utility framework. However, there has been little econometric work in the area, particularly from a likelihood perspective, because of the difficulty in computing an equilibrium solution to the model and in deriving the likelihood function. To fill this gap, we build a real business cycle model with Epstein-Zin preferences and long run growth, solve it with perturbation techniques, and evaluate its likelihood with the particle filter. We estimate the model using U.S. macro and yield curve data. We discuss the ability of the model to explain the business cycle, asset prices, the comovements between these two, and the implications of our point estimates for the welfare cost of the business cycle.