Author: Pieter Wieger Otter
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
On Information in Static and Dynamic Factor Models
The Oxford Handbook of Economic Forecasting
Author: Michael P. Clements
Publisher: OUP USA
ISBN: 0195398645
Category : Business & Economics
Languages : en
Pages : 732
Book Description
Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Publisher: OUP USA
ISBN: 0195398645
Category : Business & Economics
Languages : en
Pages : 732
Book Description
Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Dynamic Factor Models
Author: Jörg Breitung
Publisher:
ISBN: 9783865580979
Category :
Languages : en
Pages : 29
Book Description
Publisher:
ISBN: 9783865580979
Category :
Languages : en
Pages : 29
Book Description
Identification of Static and Dynamic Factor Models
Author: Marcelle Chauvet
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 33
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 33
Book Description
Large Dimensional Factor Analysis
Author: Jushan Bai
Publisher: Now Publishers Inc
ISBN: 1601981449
Category : Business & Economics
Languages : en
Pages : 90
Book Description
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Publisher: Now Publishers Inc
ISBN: 1601981449
Category : Business & Economics
Languages : en
Pages : 90
Book Description
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Model Identification in Bayesian Analysis of Static and Dynamic Factor Models
Dynamic Factor Models
Author: Siem Jan Koopman
Publisher: Emerald Group Publishing
ISBN: 1785603523
Category : Business & Economics
Languages : en
Pages : 685
Book Description
This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Publisher: Emerald Group Publishing
ISBN: 1785603523
Category : Business & Economics
Languages : en
Pages : 685
Book Description
This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
A Forecasting Performance Comparison of Dynamic Factor Models Based on Static and Dynamic Methods
Author: Fabio Della Marra
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
Book Description
We present a comparison of the forecasting performances of three Dynamic Factor Models on a large monthly data panel of macroeconomic and financial time series for the UE economy. The first model relies on static principal-component and was introduced by Stock and Watson. The second is based on generalized principal components and it was introduced by Forni, Hallin, Lippi and Reichlin. The last model has been recently proposed by Forni, Hallin, Lippi and Zaffaroni. The data panel is split into two parts: the calibration sample, from February 1986 to December 2000, is used to select the most performing specification for each class of models in a in-sample environment, and the proper sample, from January 2001 to November 2015, is used to compare the performances of the selected models in an out-of-sample environment. The metholodogical approach is analogous to, but also the size of the rolling window is empirically estimated in the calibration process to achieve more robustness. We find that, on the proper sample, the last model is the most performing for the Inflation. However, mixed evidencies appear over the proper sample for the Industrial Production.
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
Book Description
We present a comparison of the forecasting performances of three Dynamic Factor Models on a large monthly data panel of macroeconomic and financial time series for the UE economy. The first model relies on static principal-component and was introduced by Stock and Watson. The second is based on generalized principal components and it was introduced by Forni, Hallin, Lippi and Reichlin. The last model has been recently proposed by Forni, Hallin, Lippi and Zaffaroni. The data panel is split into two parts: the calibration sample, from February 1986 to December 2000, is used to select the most performing specification for each class of models in a in-sample environment, and the proper sample, from January 2001 to November 2015, is used to compare the performances of the selected models in an out-of-sample environment. The metholodogical approach is analogous to, but also the size of the rolling window is empirically estimated in the calibration process to achieve more robustness. We find that, on the proper sample, the last model is the most performing for the Inflation. However, mixed evidencies appear over the proper sample for the Industrial Production.
Modern Econometric Analysis
Author: Olaf Hübler
Publisher: Springer Science & Business Media
ISBN: 3540326936
Category : Business & Economics
Languages : en
Pages : 236
Book Description
In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.
Publisher: Springer Science & Business Media
ISBN: 3540326936
Category : Business & Economics
Languages : en
Pages : 236
Book Description
In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.
Macroeconomic Forecasting in the Era of Big Data
Author: Peter Fuleky
Publisher: Springer Nature
ISBN: 3030311503
Category : Business & Economics
Languages : en
Pages : 716
Book Description
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Publisher: Springer Nature
ISBN: 3030311503
Category : Business & Economics
Languages : en
Pages : 716
Book Description
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.