Modelling the Impact of FDI on Growth in a Global Vector Autoregressive Framework

Austrian National Bank

This project uses a global vector autoregressive (GVAR) model to analyze the relationship between FDI inflows and output dynamics in a multi-country context.The GVAR model enables us to make two important contributions: First, to model international linkages among a large number of countries, which is a key asset given the diversity of countries involved, and second, to model foreign direct investment and output dynamics jointly. The country-specific small-dimensional vector autoregressive submodels are estimated utilizing a Bayesian version of the model coupled with stochastic search variable selection priors to account for model uncertainty. Using a sample of 15 emerging and advanced economies over the period 1998:Q1 to 2012:Q4, we find that US outbound FDI exerts a positive long-term effect on output. Asian and Latin American economies tend to react faster and also stronger than Western European countries. Forecast error variance decompositions indicate that FDI plays a prominent role in explaining GDP fluctuations, especially in emerging market economies.