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Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR

Author

Listed:
  • Jonas Dovern

    (Alfred-Weber-Institute for Economics, Heidelberg University)

  • Martin Feldkircher

    (Oesterreichische Nationalbank, Foreign Research Division)

  • Florian Huber

    (Vienna University of Economics and Business (WU))

Abstract

We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing the dependence structure across countries. The GVAR outperforms forecasts based on country-specific models. This performance is solely driven by superior predictions for the dependence structure across countries, whereas the GVAR does not yield better predictive marginal densities. The relative performance gains of the GVAR model are particularly pronounced during volatile periods and for emerging economies.

Suggested Citation

  • Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    • Handle: RePEc:onb:oenbwp:200
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    Citations

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    Cited by:

    1. Georgios Georgiadis, 2015. "To bi, or not to bi? differences in spillover estimates from bilateral and multilateral multi-country models," Globalization Institute Working Papers 256, Federal Reserve Bank of Dallas.
    2. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    3. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.
    4. Dovern, Jonas & Huber, Florian, 2015. "Global prediction of recessions," Economics Letters, Elsevier, vol. 133(C), pages 81-84.
    5. Georgios Georgiadis, 2016. "To bi, or not to bi? Differences in Spillover Estimates from Bilateral and Multilateral Multi-country Models," EcoMod2016 9145, EcoMod.
    6. 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.
    7. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    8. Fadejeva, Ludmila & Feldkircher, Martin & Reininger, Thomas, 2017. "International spillovers from Euro area and US credit and demand shocks: A focus on emerging Europe," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 1-25.

    More about this item

    Keywords

    GVAR; global economy; forecast evaluation; log score; copula;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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