Author: Mario Forni
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 38
Book Description
We urge the use of Structural Dynamic Factor Models (DFM) to validate and to guide the construction of Dynamic Stochastic General Equilibrium (DSGE) models. The main reason is that the log-linear solution of a DSGE model has a factor structure which ensures consistency between the representations of the two models. We assess, by means of a few simulations, the validity of SDFM as an empirical tool to complement DSGE analysis. Using a DSGE model as data generating process, the factor model provides very accurate estimates of the true impulse response functions. As an application, we validate a theory of TFP news and surprise shocks.
Validating DSGE Models Through Dynamic Factor Models
Author: Mario Forni
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 38
Book Description
We urge the use of Structural Dynamic Factor Models (DFM) to validate and to guide the construction of Dynamic Stochastic General Equilibrium (DSGE) models. The main reason is that the log-linear solution of a DSGE model has a factor structure which ensures consistency between the representations of the two models. We assess, by means of a few simulations, the validity of SDFM as an empirical tool to complement DSGE analysis. Using a DSGE model as data generating process, the factor model provides very accurate estimates of the true impulse response functions. As an application, we validate a theory of TFP news and surprise shocks.
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 38
Book Description
We urge the use of Structural Dynamic Factor Models (DFM) to validate and to guide the construction of Dynamic Stochastic General Equilibrium (DSGE) models. The main reason is that the log-linear solution of a DSGE model has a factor structure which ensures consistency between the representations of the two models. We assess, by means of a few simulations, the validity of SDFM as an empirical tool to complement DSGE analysis. Using a DSGE model as data generating process, the factor model provides very accurate estimates of the true impulse response functions. As an application, we validate a theory of TFP news and surprise shocks.
Dynamic Factor Models
Author: Jörg Breitung
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description
Factor models can cope with many variables without running into scarce degrees of freedom.
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
Book Description
Factor models can cope with many variables without running into scarce degrees of freedom.
Deep Dynamic Factor Models
Identification and Estimation of Dynamic Factor Models
Validating Monetary DSGE Models Through VARs
Author: Fabio Canova
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 52
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 52
Book Description
Bayesian Estimation of DSGE Models
Author: Edward P. Herbst
Publisher: Princeton University Press
ISBN: 0691161089
Category : Business & Economics
Languages : en
Pages : 295
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.
Publisher: Princeton University Press
ISBN: 0691161089
Category : Business & Economics
Languages : en
Pages : 295
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.
Dynamic Factor Models in Estimation and Forecasting
Author: Victor Bystrov
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 95
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 95
Book Description
Empirical Bayes Methods for Dynamic Factor Models
Author: Siem Jan Koopman
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
Book Description
We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates have lower quadratic loss compared to the standard maximum likelihood estimates. We investigate the methods in a Monte Carlo study where we document the finite sample properties. Finally, we present and discuss the results of an empirical study concerning the forecasting of U.S. macroeconomic time series using our empirical Bayes methods.
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
Book Description
We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates have lower quadratic loss compared to the standard maximum likelihood estimates. We investigate the methods in a Monte Carlo study where we document the finite sample properties. Finally, we present and discuss the results of an empirical study concerning the forecasting of U.S. macroeconomic time series using our empirical Bayes methods.
Large-Dimensional Dynamic Factor Models in Real-Time
Author: Matteo Luciani
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
In this paper I review the literature on Large-Dimensional Dynamic Factor Models for real-time applications. I first present the Dynamic Factor model, the implications of using large-dimensional databases, and the challenges of real-time applications. Then, I discuss how the literature has solved these problems, and I present numerous empirical applications that show the usefulness of these models in both constructing business cycle indicators, and predicting economic activity. Finally, I present two recent extensions of the Dynamic Factor model, one in a Bayesian and one in a non-stationary setting.
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
In this paper I review the literature on Large-Dimensional Dynamic Factor Models for real-time applications. I first present the Dynamic Factor model, the implications of using large-dimensional databases, and the challenges of real-time applications. Then, I discuss how the literature has solved these problems, and I present numerous empirical applications that show the usefulness of these models in both constructing business cycle indicators, and predicting economic activity. Finally, I present two recent extensions of the Dynamic Factor model, one in a Bayesian and one in a non-stationary setting.
Financial Crises in DSGE Models
Author: Mr.Jaromir Benes
Publisher: International Monetary Fund
ISBN: 1475524986
Category : Business & Economics
Languages : en
Pages : 59
Book Description
This paper presents the theoretical structure of MAPMOD, a new IMF model designed to study vulnerabilities associated with excessive credit expansions, and to support macroprudential policy analysis. In MAPMOD, bank loans create purchasing power that facilitates adjustments in the real economy. But excessively large and risky loans can impair balance sheets and sow the seeds of a financial crisis. Banks respond to losses through higher spreads and rapid credit cutbacks, with adverse effects for the real economy. These features allow the model to capture the basic facts of financial cycles. A companion paper studies the simulation properties of MAPMOD.
Publisher: International Monetary Fund
ISBN: 1475524986
Category : Business & Economics
Languages : en
Pages : 59
Book Description
This paper presents the theoretical structure of MAPMOD, a new IMF model designed to study vulnerabilities associated with excessive credit expansions, and to support macroprudential policy analysis. In MAPMOD, bank loans create purchasing power that facilitates adjustments in the real economy. But excessively large and risky loans can impair balance sheets and sow the seeds of a financial crisis. Banks respond to losses through higher spreads and rapid credit cutbacks, with adverse effects for the real economy. These features allow the model to capture the basic facts of financial cycles. A companion paper studies the simulation properties of MAPMOD.