This article discusses the evolution of dynamic macroeconomic models from calibrated Real Business Cycle models to estimated dynamic stochastic general equilibrium models. The purpose is to suggest the usefulness of these models as a tool for policy analysis, with a particular emphasis on aspects

This paper employs the one-sector Real Business Cycle model as a testing ground for four di®erent procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1) Maximum Likelihood (with and without measurement errors and incorporating priors), 2) Generalized

We take as a starting point the existence of a joint distribution implied by different dynamic sto-chastic general equilibrium (DSGE) models, all of which are potentially misspecified. Our objective is to compare “true ” joint distributions with ones generated by given DSGEs. This is accomplished

This paper presents the first version of an open economy Dynamic Stochastic General Equilibrium (EP DSGE) model for Estonia. The model is designed to highlight the main driving forces behind Estonian business cycle and to understand how the euro area economic shocks and monetary policy transmit

Dynamic factor models (DFM) and dynamic stochastic general equilibrium (DSGE) models are widely used for empirical research in macroeconomics. The empirical factor literature argues that the co-movement of large panels of macroeconomic and financial data can be captured by relatively few common

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This paper evaluates monetary policy trade-offs in low-income countries using a dynamic stochastic general equilibrium model estimated on data for Mozambique, taking into account the sources of major exogenous shocks and the level of financial development. The simulations suggest that an exchange

In this paper I propose an alternative to calibration of linearized singular dynamic stochastic general equilibrium models. Given an a-theoretical econometric model as a representative of the data generating process, I will construct an information measure which compares the conditional

We compare two methods of motivating money in New Keynesian dynamic stochastic general equilibrium models—money-in-the-utility function and the cash-in-advance (CIA) constraint—as well as two ways of modelling monetary policy: the interest rate feedback rule and money growth rules. As an aid

We use a structural dynamic stochastic general equilibrium model to investigate how initial data releases of key macroeconomic aggregates are related to final revised versions and how identified aggregate shocks influence data revisions. The analysis sheds light on how well preliminary data