GVAR Toolbox

Derived from Dr. L.Vanessa Smith's project Exploring International Economic Linkages Using a Global Model, the GVAR Toolbox is a collection of MatLab procedures with an Excel-based interface, designed for the purpose of GVAR modelling. It is primarily tailored to policy analysis and forecasting, though can be easily customised for other purposes.

It is an accessible and easy-to-use package, with no background knowledge of MatLab or Excel required. In order to use it, both Microsoft Excel and MatLab have to be installed on the user's computer. No specific MatLab toolboxes are required for running the program.

The GVAR Toolbox was originally launched in December 2010 with the release of version 1.0, sponsored by the European Central Bank. Version 1.1 subsequently followed in July 2011. The GVAR Toolbox 2.0 was released in August 2014 and is available to download, free of charge, from sourceforge.net. To view the changelog for the current and previous releases of the GVAR Toolbox click here.

The main additions to the latest release include:

    • the ability to use different weights for different variables in constructing the foreign variables

    • the option to select the lag orders of the weak exogeneity regressions using the AIC or SBC information criterion

    • a new shrinkage estimator of the GVAR covariance matrix with the shrinkage parameter computed internally by the program

    • the option of performing the bootstrap without using the inverse of the covariance matrix

    • the option of including a dominant unit in the GVAR model (this relaxes the need for any global variables to necessarily enter as domestic in a single country as was the case in version 1.1)

    • the ability to perform Trend/Cycle decomposition of the GVAR model which exports data for use in Multi-Country New Keynesian (MCNK) modelling

    • ex-ante forecasts subject to lower bound restrictions as well as conditional forecasts.

The program itself can be used either with the existing GVAR structure based on Dees, di Mauro, Pesaran and Smith (2007) or variants of it, or as a very general modelling framework for any large system where components are driven by weighted averages of other components. It can be applied to countries, regions (e.g. regional housing markets), states or firms, to name a few possibilities. Many or few countries, for example, can be used, so long as the required weak exogeneity assumptions are satisfied. Read more about its features>

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