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Estimating GVAR weight matrices

Author

Listed:
  • Gross, Marco
Abstract
This paper aims to illustrate how weight matrices that are needed to construct foreign variable vectors in Global Vector Autoregressive (GVAR) models can be estimated jointly with the GVAR's parameters. An application to real GDP and consumption expenditure price inflation as well as a controlled Monte Carlo simulation serve to highlight that 1) In the application at hand, the estimated weights differ for some countries significantly from trade-based ones that are traditionally employed in that context; 2) misspecified weights might bias the GVAR estimate and therefore distort its dynamics; 3) using estimated GVAR weights instead of trade-based ones (to the extent that they differ and the latter bias the global model estimates) shall enhance the out-of-sample forecast performance of the GVAR. Devising a method for estimating GVAR weights is particularly useful for contexts in which it is not obvious how weights could otherwise be constructed from data. JEL Classification: C33, C53, C61, E17

Suggested Citation

  • Gross, Marco, 2013. "Estimating GVAR weight matrices," Working Paper Series 1523, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20131523
    Note: 3098116
    as

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    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp1523.pdf
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    References listed on IDEAS

    as
    1. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    2. Philip R. Lane & Jay C. Shambaugh, 2010. "Financial Exchange Rates and International Currency Exposures," American Economic Review, American Economic Association, vol. 100(1), pages 518-540, March.
    3. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    4. Chudik, Alexander & Fratzscher, Marcel, 2011. "Identifying the global transmission of the 2007-2009 financial crisis in a GVAR model," European Economic Review, Elsevier, vol. 55(3), pages 325-339, April.
    5. Eickmeier, Sandra & Ng, Tim, 2015. "How do US credit supply shocks propagate internationally? A GVAR approach," European Economic Review, Elsevier, vol. 74(C), pages 128-145.
    6. Chudik, Alexander & Bussière, Matthieu & Mehl, Arnaud, 2011. "Does the euro make a difference? Spatio-temporal transmission of global shocks to real effective exchange rates in an infinite VAR," Working Paper Series 1292, European Central Bank.
    7. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    8. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    9. M. Hashem Pesaran & Ron Smith, 2006. "Macroeconometric Modelling With A Global Perspective," Manchester School, University of Manchester, vol. 74(s1), pages 24-49, September.
    10. Ms. Silvia Sgherri & Mr. Alessandro Galesi, 2009. "Regional Financial Spillovers Across Europe: A Global VAR Analysis," IMF Working Papers 2009/023, International Monetary Fund.
    11. Fratzscher, Marcel & Chudik, Alexander, 2010. "Identifying the Global Transmission of the 2007-09 Financial Crisis in a GVAR Model," CEPR Discussion Papers 8093, C.E.P.R. Discussion Papers.
    12. Mr. Dale F Gray, 2013. "Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR," IMF Working Papers 2013/218, International Monetary Fund.
    13. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    14. Gross, Marco & Binder, Michael, 2013. "Regime-switching global vector autoregressive models," Working Paper Series 1569, European Central Bank.
    15. Mr. Papa M N'Diaye & Mr. Dale F Gray & Ms. Natalia T. Tamirisa & Ms. Hiroko Oura & Qianying Chen, 2010. "International Transmission of Bank and Corporate Distress," IMF Working Papers 2010/124, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Georgios Georgiadis, 2016. "To bi, or not to bi? Differences in Spillover Estimates from Bilateral and Multilateral Multi-country Models," EcoMod2016 9145, EcoMod.
    2. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    3. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    4. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    5. Julián Ramajo & José Manuel Cordero & Miguel Ángel Márquez, 2017. "European regional efficiency and geographical externalities: a spatial nonparametric frontier analysis," Journal of Geographical Systems, Springer, vol. 19(4), pages 319-348, October.
    6. Moisa Altar & Adam-Nelu Altar-Samuel & Ioana Marcu, 2014. "Measuring Systemic Risk using Contingent Claims Analysis (CCA)," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 22-48, December.
    7. Behn, Markus & Gross, Marco & Peltonen, Tuomas A., 2016. "Assessing the costs and benefits of capital-based macroprudential policy," ESRB Working Paper Series 17, European Systemic Risk Board.
    8. Mr. Dale F Gray, 2013. "Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR," IMF Working Papers 2013/218, International Monetary Fund.
    9. 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.
    10. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.

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    More about this item

    Keywords

    forecasting and simulation; Global macroeconometric modeling; models with panel data;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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