Estimating DSGE Models with Long Memory Dynamics

Estimating DSGE Models with Long Memory Dynamics PDF Author: Gianluca Moretti
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
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.

Estimating DSGE Models with Long Memory Dynamics

Estimating DSGE Models with Long Memory Dynamics PDF Author: Gianluca Moretti
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
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.

DSGE Models in Macroeconomics

DSGE Models in Macroeconomics PDF Author: Nathan Balke
Publisher: Emerald Group Publishing
ISBN: 1781903050
Category : Business & Economics
Languages : en
Pages : 480

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Book Description
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

The Econometrics of DSGE Models

The Econometrics of DSGE Models PDF Author: Jesús Fernández-Villaverde
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 56

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Book Description
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.

Solving and Estimating Indeterminate DSGE Models

Solving and Estimating Indeterminate DSGE Models PDF Author: Mr.Roger Farmer
Publisher: International Monetary Fund
ISBN: 1484342658
Category : Business & Economics
Languages : en
Pages : 31

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Book Description
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.

Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model

Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model PDF Author: Mr.Maxym Kryshko
Publisher: International Monetary Fund
ISBN: 1463904215
Category : Business & Economics
Languages : en
Pages : 62

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Book Description
When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent.

Data-Rich DSGE and Dynamic Factor Models

Data-Rich DSGE and Dynamic Factor Models PDF Author: Mr.Maxym Kryshko
Publisher: International Monetary Fund
ISBN: 1463903499
Category : Business & Economics
Languages : en
Pages : 51

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Book Description
Dynamic factor models 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 unobserved factors. Similarly, the dynamics in DSGE models are often governed by a handful of state variables and exogenous processes such as preference and/or technology shocks. Boivin and Giannoni(2006) combine a DSGE and a factor model into a data-rich DSGE model, in which DSGE states are factors and factor dynamics are subject to DSGE model implied restrictions. We compare a data-richDSGE model with a standard New Keynesian core to an empirical dynamic factor model by estimating both on a rich panel of U.S. macroeconomic and financial data compiled by Stock and Watson (2008).We find that the spaces spanned by the empirical factors and by the data-rich DSGE model states are very close. This proximity allows us to propagate monetary policy and technology innovations in an otherwise non-structural dynamic factor model to obtain predictions for many more series than just a handful of traditional macro variables, including measures of real activity, price indices, labor market indicators, interest rate spreads, money and credit stocks, and exchange rates.

Evaluating and Estimating a DSGE Model for the United Kingdom

Evaluating and Estimating a DSGE Model for the United Kingdom PDF Author: Richard Harrison
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Estimation and evaluation of DSGE models : progress and challenges

Estimation and evaluation of DSGE models : progress and challenges PDF Author: Frank Schorfheide
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 50

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Book Description
Abstract: Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models, discusses current challenges, and provides avenues for future research

DSGE Models in a Data-rich Environment

DSGE Models in a Data-rich Environment PDF Author: Jean Boivin
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 0

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Book Description
Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However, recent empirical research on factor models has shown that information contained in large data sets is relevant for the evolution of important macroeconomic series. This suggests that conventional model estimates and inference based on estimated DSGE models might be distorted. In this paper, we propose an empirical framework for the estimation of DSGE models that exploits the relevant information from a data-rich environment. This framework provides an interpretation of all information contained in a large data set, and in particular of the latent factors, through the lenses of a DSGE model. The estimation involves Markov-Chain Monte-Carlo (MCMC) methods. We apply this estimation approach to a state-of-the-art DSGE monetary model. We find evidence of imperfect measurement of the model's theoretical concepts, in particular for inflation. We show that exploiting more information is important for accurate estimation of the model's concepts and shocks, and that it implies different conclusions about key structural parameters and the sources of economic fluctuations.

Learning in an Estimated Medium-scale DSGE Model

Learning in an Estimated Medium-scale DSGE Model PDF Author: Sergey Slobodyan
Publisher:
ISBN: 9788073441876
Category :
Languages : en
Pages : 65

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Book Description