We review the current state of estimation dynamic stochastic general equilibrium (DSGE) models. After introducing a framework for dealing with DSGE models, state-space representation, we discuss how to evaluate moments or likelihood function implied by such structure. discuss, in varying degrees detail, recent advances field, as tempered particle filter, approximated Bayesian computation, Hamil...

 Libya experienced a substantial increase in oil revenue as a result of increased oil prices during the period of the late 1970s and early 1980s, and again after 2000. Recent increases in oil production and the price of oil, and their positive and negative macroeconomic impacts upon key macroeconomic variables, are of considerable contemporary importance to an oil dependent economy such as that...

Over the past 15 years there has been remarkable progress in the specification and estimation of dynamic stochastic general equilibrium (DSGE) models. Central banks in developed and emerging market economies have become increasingly interested in their usefulness for policy analysis and forecasting. This paper reviews some issues and challenges surrounding the use of these models at central ban...

Recent literature points out that key variables such as aggregate productivity and in‡ation display long memory dynamics. We study the implications of this high degree of persistence on the estimation of Dynamic Stochastic General Equilibrium (DSGE) models. We …rst show that long memory data can produce substantial bias in the deep parameter estimates when a standard Kalman Filter-MLE procedure...

This note documents a DSGE model of Climate Change. I extend the NK with geophysical variables, such as greenhouse gas emissions, carbon cycle, radiative forcing, and climate change. In this model, specify five different policy regimes: no policy, cap, intensive, tax, mandate.

Modern policy analysis makes extensive use of dynamic stochastic general equilibrium (DSGE) models. These models differ significantly from earlier generations of large-scale econometric models. I review what I see as major progress in the ability of economists to conduct model-based policy analysis. This progress has come through the evolution in the types of models being used and in a refineme...

Rational expectations are at the heart of the DSGE models maintained by central banks. A key equation which governs the evolution of prices in those models is the New Keynesian Phillips (NKPC) curve, in which today‟s rate of inflation is linked to expected future inflation. Expected future inflation is in turn modeled using rational expectations, which operationally means that forecast errors a...

This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and proposes a new algorithm that correctly applies the procedure proposed by Kim, Shephard, and Chib (1998) to the estimation of VAR or DSGE models with stochastic volatility. Relative to Primiceri (2005), the correct algorithm involves a different ordering of...

In this paper, it is argued that the observed high positive correlation between national savings and investment which is found in the data can in part be explained by shocks to monetary policy. This hypothesis, which is established by reviewing some empirical findings, is tested in a two-country DSGE-model framework in the tradition of the New Open Economy Macroeconomics. The simulation results...

Abstract The current financial crisis highlights the need to develop DSGE models with real-financial linkages and an active banking sector. This paper proposes a fully micro-founded framework that incorporates optimizing banks, the interbank market, and the credit market into a DSGE model, and evaluates the role of banks and financial shocks in the U.S. business cycles. We assume two types of h...