Estimating GVAR weight matrices

Marco Gross

No 1523, Working Paper Series from European Central Bank

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

Keywords: forecasting and simulation; Global macroeconometric modeling; models with panel data (search for similar items in EconPapers)
Date: 2013-03
New Economics Papers: this item is included in nep-ecm and nep-for
Note: 3098116
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Citations: View citations in EconPapers (15)

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