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

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  • Dovern, Jonas
  • Feldkircher, Martin
  • Huber , Florian

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.

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  • Dovern, Jonas & Feldkircher, Martin & Huber , Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 0590, University of Heidelberg, Department of Economics.
    • Handle: RePEc:awi:wpaper:0590
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    Cited by:

    1. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.
    2. Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
    3. Martin Feldkircher & Thomas Gruber & Florian Huber, 2017. "Spreading the word or reducing the term spread? Assessing spillovers from euro area monetary policy," Department of Economics Working Papers wuwp248, Vienna University of Economics and Business, Department of Economics.
    4. Peter McAdam & Kostas Mouratidis & Theodore Panagiotidis & Georgios Papapanagiotou, 2023. "European Trade & Growth Imbalances: An Analysis using a Sign-Restriction Bayesian-GVAR with Stochastic Volatility," Working Paper series 23-12, Rimini Centre for Economic Analysis.
    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. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    7. Beckmann, Joscha & Czudaj, Robert L., 2020. "Fundamental determinants of exchange rate expectations," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224617, Verein für Socialpolitik / German Economic Association.
    8. 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.
    9. Dovern, Jonas & Huber, Florian, 2015. "Global prediction of recessions," Economics Letters, Elsevier, vol. 133(C), pages 81-84.
    10. 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.
    11. Carlos Cañon & Eddie Gerba & Alberto Pambira & Evarist Stoja, 2023. "An Unconventional FX Tail Risk Story," CESifo Working Paper Series 10629, CESifo.
    12. 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.
    13. Martin Feldkircher & Gabriele Tondl, 2020. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(3), pages 225-247, August.
    14. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    15. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    16. Georgiadis, Georgios, 2015. "To bi, or not to bi? Differences in spillover estimates from bilateral and multilateral multi-country models," Working Paper Series 1868, European Central Bank.
    17. Deniz Sevinc & Edgar Mata Flores, 2021. "Macroeconomic and financial implications of multi‐dimensional interdependencies between OECD countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 741-776, January.
    18. George N. Apostolakis & Nikolaos Giannellis & Athanasios P. Papadopoulos, 2023. "Macro‐financial effects of monetary policy easing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 715-738, April.
    19. Georgiadis, Georgios, 2017. "To bi, or not to bi? Differences between spillover estimates from bilateral and multilateral multi-country models," Journal of International Economics, Elsevier, vol. 107(C), pages 1-18.
    20. Markus Eller & Martin Feldkircher & Florian Huber, 2017. "How would a fiscal shock in Germany affect other European countries? Evidence from a Bayesian GVAR model with sign restrictions," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 54-77.
    21. Cañon, Carlos & Gerba, Eddie & Pambira, Alberto & Stoja, Evarist, 2023. "An unconventional FX tail risk story," LSE Research Online Documents on Economics 120052, London School of Economics and Political Science, LSE Library.
    22. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    23. Maximilian Böck & Martin Feldkircher & Florian Huber, 2020. "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R," Globalization Institute Working Papers 395, Federal Reserve Bank of Dallas.

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    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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