Factor Analysis of a Large DSGE Model
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.
|Date of creation:||2010|
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- Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent & Mark Watson, 2006.
"A,B,C's (and D's)'s for Understanding VARS,"
321307000000000646, UCLA Department of Economics.
- 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.
- 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.
- 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.
- 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.
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