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Lag Selection in Subset VAR Models with an Application to a U.S. Monetary System

Author

Listed:
  • Ralf Brueggemann

    (Humboldt Universitaet zu Berlin)

  • Helmut Leutkepohl

    (Humboldt Universitaet zu Berlin)

Abstract

In this paper we consider alternative modeling strategies for specification of subset VAR models. We present four strategies and show that under certain conditions a testing procedure based on t-ratios is equivalent to eliminating sequentially lags that lead to the largest improvement in a prespecified model selection criterion. One finding from our Monte Carlo study is that differences between alternative strategies are small. Moreover, all strategies often fail to discover the true model. We argue that finding the correct model is not always the final modeling objective and find that using subset strategies results in models with improved forecast precision. To illustrate how these subset strategies can improve results from impulse response analysis, we use a VAR model of monetary policy shocks for the U.S. economy. While the response patterns from full and subset VARs are qualitatively identical, confidence bands from the unrestricted model are considerably wider. We conclude that subset strategies can be useful modeling tools when forecasting or impulse response analysis is the main objective.

Suggested Citation

  • Ralf Brueggemann & Helmut Leutkepohl, 2000. "Lag Selection in Subset VAR Models with an Application to a U.S. Monetary System," Econometric Society World Congress 2000 Contributed Papers 0821, Econometric Society.
  • Handle: RePEc:ecm:wc2000:0821
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    References listed on IDEAS

    as
    1. Christiano, Lawrence J & Eichenbaum, Martin & Evans, Charles, 1996. "The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 16-34, February.
    2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    3. Benkwitz, Alexander & L tkepohl, Helmut & Wolters, J rgen, 2001. "Comparison Of Bootstrap Confidence Intervals For Impulse Responses Of German Monetary Systems," Macroeconomic Dynamics, Cambridge University Press, vol. 5(01), pages 81-100, February.
    4. Alexander Benkwitz & Michael Neumann & Helmut Lutekpohl, 2000. "Problems related to confidence intervals for impulse responses of autoregressive processes," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 69-103.
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    Cited by:

    1. repec:jns:jbstat:v:227:y:2007:i:1:p:87-101 is not listed on IDEAS
    2. Soo Khoon Goh, 2005. "New empirical evidence on the effects of capital controls on composition of capital flows in Malaysia," Applied Economics, Taylor & Francis Journals, vol. 37(13), pages 1491-1503.
    3. Ubilava, David & holt, Matt, 2013. "El Ni~no southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), June.
    4. Hulsewig, Oliver & Mayer, Eric & Wollmershauser, Timo, 2006. "Bank loan supply and monetary policy transmission in Germany: An assessment based on matching impulse responses," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2893-2910, October.
    5. Derek W. Bunn & Carlo Fezzi, 2007. "Interaction of European Carbon Trading and Energy Prices," Working Papers 2007.63, Fondazione Eni Enrico Mattei.
    6. Victor Bystrov, 2014. "A factor-augmented model of markup on mortgage loans in Poland," Bank i Kredyt, Narodowy Bank Polski, vol. 45(6), pages 491-512.
    7. Melisso Boschi & Alessandro Girardi, 2007. "Euro area inflation: long-run determinants and short-run dynamics," Applied Financial Economics, Taylor & Francis Journals, vol. 17(1), pages 9-24.
    8. Benner Joachim & Meier Carsten-Patrick, 2004. "Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 639-652, December.
    9. Martina Alexová, 2012. "What determines inflation?," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 5(4), pages 345-369.
    10. Boriss Siliverstovs & Olena Bilan, 2006. "Modeling Inflation Dynamics in Transition Economies: The Case of Ukraine," Eastern European Economics, Taylor & Francis Journals, vol. 43(6), pages 66-81, December.
    11. Markus Krätzig, 2005. "A Software Framework for Data Based Analysis," SFB 649 Discussion Papers SFB649DP2005-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Brüggemann, Ralf & Krolzig, Hans-Martin & Lütkepohl, Helmut, 2002. "Comparison of model reduction methods for VAR processes," SFB 373 Discussion Papers 2002,80, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    13. Holtemöller, Oliver, 2002. "Structural vector autoregressive models and monetary policy analysis," SFB 373 Discussion Papers 2002,7, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    14. Philip Rothman & Dick van Dijk & Philip Hans Franses, 1999. "A Multivariate STAR Analysis of the Relationship Between Money and Output," Working Papers 9913, East Carolina University, Department of Economics.
    15. Avner Offer, 2000. "Economic Welfare Measurements and Human Well-Being, [revised version, March 2000]," Economics Series Working Papers 2000-W34, University of Oxford, Department of Economics.
    16. Brüggemann, Ralf, 2002. "On the small sample properties of weak exogeneity tests in cointegrated VAR models," SFB 373 Discussion Papers 2002,2, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    17. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    18. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, EconWPA.
    19. Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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