Finding relevant variables in sparse Bayesian factor models: Economic applications and simulation results
This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant variables from the informative ones, we choose a Bayesian framework for factor estimation with sparse priors on the loadings matrix. The choice of a sparse prior is an extension to the existing macroeconomic literature, which predominantly uses normal priors on the loadings. Simulations show that the sparse factor model can well detect various degrees of sparsity in the data, and how irrelevant variables can be identified. Empirical applications to a large multi-country GDP dataset and disaggregated CPI inflation data for the US reveal that sparsity matters a lot, as the majority of the variables in both datasets are irrelevant for factor estimation.
|Date of creation:||2012|
|Contact details of provider:|| Postal: Postfach 10 06 02, 60006 Frankfurt|
Phone: 0 69 / 95 66 - 0
Fax: 0 69 / 95 66 30 77
Web page: http://www.bundesbank.de/
More information through EDIRC
References listed on IDEAS
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.:
- Boivin, Jean & Ng, Serena, 2006.
"Are more data always better for factor analysis?,"
Journal of Econometrics,
Elsevier, vol. 132(1), pages 169-194, May.
- Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
- Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 338-357, July.
- Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
- Altissimo, Filippo & Cristadoro, Riccardo & Forni, Mario & Lippi, Marco & Veronese, Giovanni, 2006. "New EuroCOIN: Tracking Economic Growth in Real Time," CEPR Discussion Papers 5633, C.E.P.R. Discussion Papers.
- Mario Forni & Filippo Altissimo & Riccardo Cristadoro & Marco Lippi & Giovanni Veronese., 2008. "New Eurocoin: Tracking Economic Growth in Real Time," Center for Economic Research (RECent) 020, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
- Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2007. "New Eurocoin: Tracking Economic Growth in Real Time," Temi di discussione (Economic working papers) 631, Bank of Italy, Economic Research and International Relations Area.