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Lag length selection in vector autoregressive models: symmetric and asymmetric lags

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  • Omer Ozcicek
  • W. DOUGLAS McMILLIN

Abstract

This study used Monte Carlo simulations to study the performance of alternative lag selection criterion for symmetric lag and asymmetric lag vector autoregressive models. Lag models with short lags and with long lags were considered. The alternative criteria considered were the AIC, SIC, Phillips' Posterior Information Criterion, and Keating's modification of the AIC and SIC. The alternative criteria were evaluated by computing the frequency distribution of lags selected, by computing the out-of-sample forecasting performance of models with lags selected using each criterion, and by comparing the ability of models with lags selected using each criterion to mimic the 'true' impulse response functions for the lag model.

Suggested Citation

  • Omer Ozcicek & W. DOUGLAS McMILLIN, 1999. "Lag length selection in vector autoregressive models: symmetric and asymmetric lags," Applied Economics, Taylor & Francis Journals, vol. 31(4), pages 517-524.
  • Handle: RePEc:taf:applec:v:31:y:1999:i:4:p:517-524
    DOI: 10.1080/000368499324237
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    1. Peter C.B. Phillips, 1994. "Model Determination and Macroeconomic Activity," Cowles Foundation Discussion Papers 1083, Cowles Foundation for Research in Economics, Yale University.
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    12. Gupta, Abhay, 2004. "Comparing Bank Lending Channel in India and Pakistan," MPRA Paper 9281, University Library of Munich, Germany.
    13. Albis, Manuel Leonard F. & Mapa, Dennis S., 2014. "Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models," MPRA Paper 55902, University Library of Munich, Germany.
    14. George Vamvoukas, 2002. "Budget Deficits and Interest Rates in a Small Open," International Economic Journal, Taylor & Francis Journals, vol. 16(2), pages 31-36.
    15. Chen, Yiqi & Ibhagui, Oyakhilome W., 2019. "R&D-firm performance nexus: New evidence from NASDAQ listed firms," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
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    17. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, September.
    18. Vale, Sergio Rodrigo, 2005. "Inflation, Growth and Real and Nominal Uncertainty: Some Bivariate Garch-in-Mean Evidence for Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 59(1), January.
    19. Keating, John W., 2000. "Macroeconomic Modeling with Asymmetric Vector Autoregressions," Journal of Macroeconomics, Elsevier, vol. 22(1), pages 1-28, January.

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