Estimation of dynamic stochastic general equilibrium models (in Russian)

This essay is a survey of the main econometric approaches to estimation of the dynamic stochastic general equilibrium (DSGE) models widely used by central banks and federal reserves. The paper discusses in detail the main econometric problems arising in inferences about the parameters of the log-linearized DSGE models. We examine three main estimation approaches: the minimum distance method, the maximum likelihood method and the Bayesian approach. We focus on the problems of weak identification that are due to scarcity of macro data. The issues of economic modelling and methods of solving dynamic models are beyond the scope of the current essay.