MODELLING REGIONAL INTERDEPENDENCIES USING A GLOBAL ERROR CORRECTING MACROECONOMETRIC MODEL

M. Hashem PESARAN (Cambridge University)
Til SCHUERMANN (Federal Reserve Bank of New York)
Scott WEINER (University of Oxford and Wyman & Company)

A financial institution such as a bank is ultimately exposed to macroeconomic fluctuations in the countries to which it has exposure, the most acute example being commercial lending to companies whose fortunes fluctuate with aggregate demand. It was this risk management need for financial institutions which motivated us to build a compact global macroeconometric model capable of generating (point as well as density) forecasts for a core set of macroeconomic factors for a set of regions and countries which explicitly allows for interconnections and interdependencies that exist between national and international factors. This paper provides such a global modeling framework by making use of recent advances in the analysis of cointegrating systems. In an unrestricted VAR(p) model in k endogenous variables covering N countries, the number of unknown parameters will be unfeasibly large, of order p(kN-1), requiring a more parsimonious solution. We first estimate individual country/region specific vector error-correcting models, where the domestic macroeconomic variables are related to corresponding foreign variables constructed exclusively to match the international trade pattern of the country under consideration. The individual country models are then combined in a consistent and cohesive manner to generate forecasts for all the variables in the world economy simultaneously. We estimate the model using quarterly data from 1979Q1 to 1999Q1 and shed light on the degree of regional interdependencies by investigating the time profile of the transmission of shocks of one variable to the rest of the world.