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Model uncertainty in panel vector autoregressive models

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  • Gary Koop
  • Dimitris Korobilis

Abstract

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsi- monious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

Suggested Citation

  • Gary Koop & Dimitris Korobilis, 2014. "Model uncertainty in panel vector autoregressive models," Working Papers 2014_10, Business School - Economics, University of Glasgow.
  • Handle: RePEc:gla:glaewp:2014_10
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    Cited by:

    1. Christou, Christina & Cunado, Juncal & Gupta, Rangan & Hassapis, Christis, 2017. "Economic policy uncertainty and stock market returns in PacificRim countries: Evidence based on a Bayesian panel VAR model," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 92-102.
    2. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 90110, University Library of Munich, Germany, revised 16 Nov 2018.
    3. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
    4. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    5. Korobilis, Dimitris, 2016. "Prior selection for panel vector autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 110-120.
    6. Annalisa Marini & Steve McCorriston, 2017. "Propagation of Commodity Market Shocks," Discussion Papers 1708, University of Exeter, Department of Economics.
    7. Annalisa Marini & Steve McCorriston, 2019. "Weather, Prices and Spillovers," Discussion Papers 1905, University of Exeter, Department of Economics.
    8. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    9. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2016. "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1371-1391, November.
    10. Ters, Kristyna & Urban, Jörg, 2018. "Intraday dynamics of credit risk contagion before and during the euro area sovereign debt crisis: Evidence from central Europe," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 123-142.
    11. Wang, Shengquan & Chen, Langnan & Xiong, Xiong, 2019. "Asset bubbles, banking stability and economic growth," Economic Modelling, Elsevier, vol. 78(C), pages 108-117.
    12. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    14. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Korobilis, Dimitris, 2015. "Prior selection for panel vector autoregressions," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-73, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Annika Schnücker, 2016. "Restrictions Search for Panel VARs," Discussion Papers of DIW Berlin 1612, DIW Berlin, German Institute for Economic Research.
    17. Florian Huber & Michael Pfarrhofer, 2018. "Dealing with cross-country heterogeneity in panel VARs using finite mixture models," Papers 1804.01554, arXiv.org, revised Mar 2019.
    18. Annalisa Marini, 2019. "The Impact of Weather on Commodity Prices: A Warning for the Future," Discussion Papers 1902, University of Exeter, Department of Economics.
    19. Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
    20. Lubos Komarek & Kristyna Ters & Jorg Urban, 2016. "Intraday Dynamics of Euro Area Sovereign Credit Risk Contagion," Working Papers 2016/04, Czech National Bank.
    21. Schnücker, A.M., 2019. "Penalized Estimation of Panel Vector Autoregressive Models," Econometric Institute Research Papers EI-2019-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Georgios Magkonis & Simon Rudkin, 2019. "Does Trilemma Speak Chinese?," Working Papers in Economics & Finance 2019-01, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    23. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
    24. Schnücker, Annika, 2016. "Restrictions Search for Panel VARs," Annual Conference 2016 (Augsburg): Demographic Change 145566, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

    Bayesian model averaging; stochastic search variable selection; financial contagion; sovereign debt crisis;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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