Factor Analysis of a Large DSGE Model
AbstractWe study the workings of the factor analysis of high-dimensional data using artificial series generated from a large, multi-sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allows us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical and finite sample properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of diffusion index forecasts, and assess the quality of the factor analysis of highly disaggregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model.
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Bibliographic InfoPaper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 2010-08.
Length: 61 pages
Date of creation: 2010
Date of revision:
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More information through EDIRC
Multisector economies; principal components; forecasting; pervasiveness; FAVAR.;
Other versions of this item:
- ONATSKI, Alexei & RUGE-MURCIA, Francisco J., 2010. "Factor Analysis of a Large DSGE Model," Cahiers de recherche 17-2010, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Alexei Onatski & Francisco J. Ruge-Murcia, 2010. "Factor Analysis of a Large DSGE Model," Working Paper Series 50_10, The Rimini Centre for Economic Analysis.
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005.
"A,B,C's (and D's)'s for Understanding VARS,"
172782000000000096, UCLA Department of Economics.
- Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent & Mark Watson, 2006. "A,B,C's (and D's)'s for Understanding VARS," Levine's Bibliography 321307000000000646, UCLA Department of Economics.
- Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005. "A, B, C’s (And D’s) For Understanding VARS," PIER Working Paper Archive 05-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Thomas Sargent, 2005. "A, B, C’s, (and D’s) for understanding VARs," Working Paper 2005-09, Federal Reserve Bank of Atlanta.
- Jesus Fernandez-Villaverde & Juan Rubio-Ramirez & Thomas J. Sargent, 2005. "A, B, C's (and D)'s for Understanding VARs," NBER Technical Working Papers 0308, National Bureau of Economic Research, Inc.
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