Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/153956 
Authors: 
Year of Publication: 
2013
Series/Report no.: 
ECB Working Paper No. 1523
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
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.
Subjects: 
forecasting and simulation
Global macroeconometric modeling
models with panel data
JEL: 
C33
C53
C61
E17
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.