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Selection of Optimal Lag Length in Cointegrated VAR Models with Weak Form of Common Cyclical Features

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Author Info
Carlos Enrique Carrasco Gutiérrez
Reinaldo Castro Souza
Osmani Teixeira de Carvalho Guillén

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Abstract

An important aspect of empirical research based on the vector autoregressive (VAR) model is the choice of the lag order, since all inference in the VAR model depends on the correct model specification. Literature has shown important studies of how to select the lag order of a nonstationary VAR model subject to cointegration restrictions. In this work, we consider an additional weak form (WF) restriction of common cyclical features in the model in order to analyze the appropriate way to select the correct lag order. Two methodologies have been used: the traditional information criteria (AIC, HQ and SC) and an alternative criterion (IC(p,s)) which select simultaneously the lag order p and the rank structure s due to the WF restriction. A Monte-Carlo simulation is used in the analysis. The results indicate that the cost of ignoring additional WF restrictions in vector autoregressive modeling can be high, especially when SC criterion is used.

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Paper provided by Central Bank of Brazil, Research Department in its series Working Papers Series with number 139.

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Date of creation: Jun 2007
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Handle: RePEc:bcb:wpaper:139

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  1. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-80, October.
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  2. Gianluca Cubadda, 1999. "Common serial correlation and common business cycles: A cautious note," Empirical Economics, Springer, vol. 24(3), pages 529-535. [Downloadable!] (restricted)
  3. Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-60, Oct.-Dec.. [Downloadable!] (restricted)
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  4. Caporale, Guglielmo Maria, 1997. "Common features and output fluctuations in the United Kingdom," Economic Modelling, Elsevier, vol. 14(1), pages 1-9, January. [Downloadable!] (restricted)
  5. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-79, April.
  6. Engle, Robert F. & Issler, Joao Victor, 1995. "Estimating common sectoral cycles," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 83-113, February. [Downloadable!] (restricted)
  7. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-95, October.
  8. Alain Hecq & Franz Palm & Jean-Pierre Urbain, 2001. "Testing for Common Cyclical Features in Var Models with Cointegration," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
  9. Vahid, Farshid & Issler, Joao Victor, 2002. "The importance of common cyclical features in VAR analysis: a Monte-Carlo study," Journal of Econometrics, Elsevier, vol. 109(2), pages 341-363, August. [Downloadable!] (restricted)
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  10. Braun, Phillip A. & Mittnik, Stefan, 1993. "Misspecifications in vector autoregressions and their effects on impulse responses and variance decompositions," Journal of Econometrics, Elsevier, vol. 59(3), pages 319-341, October. [Downloadable!] (restricted)
  11. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254. [Downloadable!] (restricted)
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