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Factor Analysis of a Large DSGE Model

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  • ONATSKI, Alexei
  • RUGE-MURCIA, Francisco J.

Abstract

We 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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File URL: https://papyrus.bib.umontreal.ca/jspui/handle/1866/4231
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Bibliographic Info

Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 2010-08.

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Length: 61 pages
Date of creation: 2010
Date of revision:
Handle: RePEc:mtl:montde:2010-08

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Keywords: Multisector economies; principal components; forecasting; pervasiveness; FAVAR.;

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  1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005. "A,B,C's (and D's)'s for Understanding VARS," Levine's Bibliography 172782000000000096, UCLA Department of Economics.
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