PC-VAR Estimation of Vector Autoregressive Models

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

Posted: 18 Feb 2012 Last revised: 9 Jun 2013

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); University of Bologna - Rimini Center for Economic Analysis (RCEA)

Date Written: February 11, 2012

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

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: https://ssrn.com/abstract=2006847 or http://dx.doi.org/10.2139/ssrn.2006847

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)

Università degli Studi di Milano-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

University of Bologna - Rimini Center for Economic Analysis (RCEA) ( email )

Via Patara, 3
Rimini (RN), RN 47900
Italy

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