Abstract

http://ssrn.com/abstract=2006847
 
 

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PC-VAR Estimation of Vector Autoregressive Models


Claudio Morana


Università di Milano Bicocca; Università degli Studi di Milano-Bicocca - Department of Economics, Quantitative Methods and Business Strategies (DEMS); Center for Economic Research on Pensions and Welfare Policies (CeRP)

February 11, 2012

Open Journal of Statistics, 2012, 2, 251-259

Abstract:     
In this paper PC-VAR estimation of vector autoregressive models (VAR) is proposed. The estimation strategy successfully lessen the curse of dimensionality affecting VAR models, when estimated using sample sizes typically available in quarterly studies. The procedure involves a dynamic regression using a subset of principal components extracted from a vector time series, and the recovery of the implied unrestricted VAR parameter estimates by solving a set of linear constraints. PC-VAR and OLS estimation of unrestricted VAR models show the same asymptotic properties. Monte Carlo results strongly support PC-VAR estimation, yielding gains, in terms of both lower bias and higher efficiency, relatively to OLS estimation of high dimensional unrestricted VAR models in small samples. Guidance for the selection of the number of components to be used in empirical studies is provided.

Keywords: vector autoregressive model, principal components analysis, statistical reduction techniques

JEL Classification: C22

Accepted Paper Series


Not Available For Download

Date posted: February 18, 2012 ; Last revised: June 9, 2013

Suggested Citation

Morana, Claudio, PC-VAR Estimation of Vector Autoregressive Models (February 11, 2012). Open Journal of Statistics, 2012, 2, 251-259. Available at SSRN: http://ssrn.com/abstract=2006847 or http://dx.doi.org/10.2139/ssrn.2006847

Contact Information

Claudio Morana (Contact Author)
Università di Milano Bicocca ( email )
Dip Economia Metodi Quantitativi Strategie Impresa
Piazza dell'Ateneno Nuovo 1
Milano, 20126
Italy
+39 0264483091 (Phone)
University of Milan, Bicocca - Department of Economics, Quantitative Methods and Business Strategies (DEMS) ( email )
Piazza dell'Ateneo Nuovo, 1
Milan, 20126
Italy

Center for Economic Research on Pensions and Welfare Policies (CeRP) ( email )
Moncalieri, Turin
Italy
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