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Estimating GVAR weight matrices

  • Gross, Marco
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    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

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    Paper provided by European Central Bank in its series Working Paper Series with number 1523.

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    Date of creation: Mar 2013
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    Handle: RePEc:ecb:ecbwps:20131523
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    1. Dees, S. & di Mauro, F. & Pesaran, M.H. & Smith, L.V., 2005. "Exploring the International Linkages of the Euro Area: a Global VAR Analysis," Cambridge Working Papers in Economics 0518, Faculty of Economics, University of Cambridge.
    2. Pesaran, M.H. & Smith, R., 2006. "Macroeconometric Modelling with a Global Perspective," Cambridge Working Papers in Economics 0604, Faculty of Economics, University of Cambridge.
    3. Lane, Philip R. & Shambaugh, Jay C., 2008. "Financial exchange rates and international currency exposures," Discussion Paper Series 1: Economic Studies 2008,22, Deutsche Bundesbank, Research Centre.
    4. Pesaran, M.H. & Weiner, S.M., 2001. "Modelling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Cambridge Working Papers in Economics 0119, Faculty of Economics, University of Cambridge.
    5. Eickmeier, Sandra & Ng, Tim, 2011. "How Do Credit Supply Shocks Propagate Internationally? A GVAR approach," CEPR Discussion Papers 8720, C.E.P.R. Discussion Papers.
    6. Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
    7. Papa M'B. P. N'Diaye & Dale F. Gray & Natalia T. Tamirisa & Hiroko Oura & Qianying Chen, 2010. "International Transmission of Bank and Corporate Distress," IMF Working Papers 10/124, International Monetary Fund.
    8. Silvia Sgherri & Alessandro Galesi, 2009. "Regional Financial Spillovers Across Europe: A Global VAR Analysis," IMF Working Papers 09/23, International Monetary Fund.
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