The impact of global economic shocks on South Africa amid time-varying trade linkages

Abstract

Trade of South Africa with the rest of the world has changed substantially since the mid-1990s. The United States (US), which used to be the main trading partner of South Africa, is now only the third largest trading partner of the country. South African trade with Germany, Japan and the United Kingdom (UK) are also lower. The key reason is the emergence of China in the world economy. South Africa did not trade with China before 1993, but from 2009 China became the main trading partner of the country. Globalisation and China’s emergence have influenced the trade linkages of many other countries in the world. To incorporate the changes in global trade linkages, the foreign variables of all the models in the study are compiled with trade-weighted three-year moving average data. The foremost objective of the thesis is to determine how the changes in trade linkages affect the transmission of economic shocks originating in the rest of the world on South Africa. The global vector autoregression (GVAR) approach is used since one of its advantages is the incorporation of global trade linkages, which facilitates the analysis of the transmission of shocks from one country to another. As a GVAR model combines many individual country models, the study first estimates such a country-specific model for South Africa to determine whether it displays the expected impact of domestic shocks on the economy. This type of model is known as a vector error correction model (VECM) with domestic variables and weakly exogenous (X) foreign (*) variables, denoted by VECX*. The results from the VECX* for South Africa are in line with expectations, showing the effective transmission of monetary policy. The study then examines the impact of international shocks on the South African economy with a GVAR model. The GVAR, which incorporates country-specific VECX* models for 33 countries, is solved for all 33 countries using global trade weight matrices at different dates. The results indicate that over time South Africa is much more vulnerable to GDP shocks to the Chinese economy, and less vulnerable to GDP shocks to the US economy. These trends are however not confined to South Africa, and as such highlights the increased risk to the South African economy and many other economies, should China experience slower GDP growth. Finally, the thesis determines whether the forecasting performance of GVAR models is superior to that of a country-specific VECX* model. The study compares the out-of-sample forecasts of two key South African variables (real GDP and inflation) for five types of models: a VECX*, a customised small GVAR for South Africa, the more general 33-country GVAR, simple autoregressive models and random walk models. Better forecasts of both the GVAR models compared to the VECX* model at forecast horizons of more than four quarters show that, despite the complicated nature of the GVAR model with the inclusion of many countries and global trade linkages, the additional information is useful for forecasting domestic variables