Estimating DSGE-Model-Consistent Trends for Use in Forecasting. December 2009 PDF Download
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Author: Bank of Canada
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
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Author: Bank of Canada
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
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Author: Jean-Philippe Cayen
Publisher:
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Category : Economic forecasting
Languages : en
Pages :
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Author: Nathan Balke
Publisher: Emerald Group Publishing
ISBN: 1781903050
Category : Business & Economics
Languages : en
Pages : 480
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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
Author: Rochelle M. Edge
Publisher:
ISBN:
Category :
Languages : en
Pages : 67
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Author:
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Category :
Languages : en
Pages :
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Author: Michal Andrle
Publisher: International Monetary Fund
ISBN: 1484341619
Category : Business & Economics
Languages : en
Pages : 23
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This paper introduces methods that allow analysts to (i) decompose the estimates of unobserved quantities into observed data, (ii) to better understand revision properties of the model, and (iii) to impose subjective prior constraints on path estimates of unobserved shocks in structural economic models. For instance, a decomposition of the flexible-price output gap, or a technology shock, into contributions of output, inflation, interest rates, and other observed variables' contribution is feasible. The intuitive nature and analytical clarity of the suggested procedures are appealing for policy-related and forecasting models.
Author: Mr.Roger Farmer
Publisher: International Monetary Fund
ISBN: 1484342658
Category : Business & Economics
Languages : en
Pages : 31
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We propose a method for solving and estimating linear rational expectations models that exhibit indeterminacy and we provide step-by-step guidelines for implementing this method in the Matlab-based packages Dynare and Gensys. Our method redefines a subset of expectational errors as new fundamentals. This redefinition allows us to treat indeterminate models as determinate and to apply standard solution algorithms. We provide a selection method, based on Bayesian model comparison, to decide which errors to pick as fundamental and we present simulation results to show how our procedure works in practice.
Author: Gianluca Moretti
Publisher:
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Category :
Languages : en
Pages : 0
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Recent literature claims that key variables such as aggregate productivity and inflation 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 show that long memory data produce substantial bias in the deep parameter estimates when a standard Kalman Filter-MLE procedure is used. We propose a modification of the Kalman Filter to effectively deal with this problem. The augmented Kalman Filter can consistently estimate the model parameters as well as produce more accurate out-of-sample forecasts compared to the standard Kalman filter.
Author: Edward P. Herbst
Publisher: Princeton University Press
ISBN: 0691161089
Category : Business & Economics
Languages : en
Pages : 295
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Book Description
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.
Author: Alexander Meyer-Gohde
Publisher:
ISBN:
Category :
Languages : de
Pages : 0
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In this paper, we propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting (see Giannone, Monti and Reichlin (2016)). The second method transforms a quarterly state space into a monthly frequency and applies, e.g., the Kalman filter when faced missing observations (see Foroni and Marcellino (2014)). Our algorithm combines the advantages of these two existing approaches, using the information from monthly auxiliary variables to inform in-between quarter DSGE estimates and forecasts. We compare our new method with the existing methods using simulated data from the textbook 3-equation New Keynesian model (see, e.g., Galí (2008)) and real-world data with the Smets and Wouters (2007) model. With the simulated data, our new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in our method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
