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Factor Analysis of a Large DSGE Model

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  • Alexei Onatski

    ()
    (Faculty of Economics, University of Cambridge)

  • Francisco J. Ruge-Murcia

    ()
    (Department of Economics, University of Montréal; The Rimini Centre for Economic Analysis (RCEA))

Abstract

We study the workings of the factor analysis of high-dimensional data using arti cial 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 allow us to shed some light on the practical bene ts and limitations of using factor analysis techniques on economic data. We explain in what sense the arti cial data can be thought of having a factor structure, study the theoretical and fi nite 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 dissagregated 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 Info

Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 50_10.

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Date of creation: Jan 2010
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Handle: RePEc:rim:rimwps:50_10

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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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