Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analy

In this paper, I review the literature on the formulation and estimation of dynamic stochastic general equilibrium (DSGE) models with a special emphasis on Bayesian methods. First, I discuss the evolution of DSGE models over the last couple of decades. Second, I explain why the profession has decided to estimate these models using Bayesian methods. Third, I briefly introduce some of the techniques required to compute and estimate these models. Fourth, I illustrate the techniques under consideration by estimating a benchmark DSGE model with real and nominal rigidities. I conclude by offering some pointers for future research.

This dissertation consists of two essays on maximum likelihood estimation of Dynamic Stochastic General Equilibrium (DSGE) models. The first essay focuses on a monetary DSGE model of term structure, while the second essay explores and compares three different versions of New Keynesian DSGE models. In Chapter 1, a general background is given for the DSGE models, and their estimation techniques along with a review of the term structure models and New Keynesian models. The first essay, which is a joint work with Hwagyun Kim, empirically evaluates the relationships between money, inflation, output growth, and the interest rates of different maturities using a monetary DSGE model of term structure, featuring inflation targeting behavior, asset market segmentation, and external habit extended for nominal economy. This model can generate liquidity effect, average upward sloping yield curve, and time-varying bond risk premia for bearing inflation and real shocks. By exploiting the term structure equations derived from the model, the deep parameters of the model describing risk preference, inflation targeting behavior, and market segmentation between bond traders and non-traders are estimated. The model is estimated under alternative specifications: latent factors; macroeconomic factors; and both latent and macroeconomic factors. The empirical findings show that all the methods give consistent estimates of the parameters, and conclude that asset market segmentation, inflation targeting, and time-varying risk aversion are significant to account for the term structure dynamics. They also suggest that monetary factors and monetary policy are important to understand both short-run and long-run behaviors of bond prices. In the second essay, three different versions of New Keynesian DSGE models are developed, and their structural parameters are estimated by maximum likelihood estimation. Specifically, the role of velocity of money on the dynamics of real variables is empirically examined by constructing a money in the utility model and two special cases of transactions cost model. Wealth effects, previously ignored in many transactions cost models, are taken into consideration in one of the cases examined here, and comparisons are made between the transactions cost model that includes the wealth effects and the transactions cost model that ignores the wealth effects entirely. The equivalence of money in the utility model and transactions cost model with wealth effects is also quantitatively examined. The results show that there is no evidence of quantitative equivalence between these two models. Although the magnitude of impulse responses are different among the models studied here, all three models give consistent estimates for the structural parameters. The empirical findings from the maximum likelihood estimates of all three models' parameters also suggest that the velocity of money is a very important part of the IS and Phillips curves of all three models developed here, and should be included in IS and Phillips curves when examining the inflation and output dynamics.

The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods--which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics. Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. Methods for Applied Macroeconomic Research offers the essential tools for the next generation of macroeconomists.

In this collection of 17 articles, top scholars synthesize and analyze scholarship on this widely used tool of policy analysis, setting forth its accomplishments, difficulties, and means of implementation. Though CGE modeling does not play a prominent role in top US graduate schools, it is employed universally in the development of economic policy. This collection is particularly important because it presents a history of modeling applications and examines competing points of view. - Presents coherent summaries of CGE theories that inform major model types - Covers the construction of CGE databases, model solving, and computer-assisted interpretation of results - Shows how CGE modeling has made a contribution to economic policy