Year: 2014
Type: dissertation
Abstract: Trade of South Africa with the rest of the world has changed substantially since the mid-1990s. \nThe United States (US), which used to be the main trading partner of South Africa, is now only \nthe third largest trading partner of the country. South African trade with Germany, Japan and \nthe United Kingdom (UK) are also lower. The key reason is the emergence of China in the \nworld economy. South Africa did not trade with China before 1993, but from 2009 China \nbecame the main trading partner of the country. Globalisation and China’s emergence have \ninfluenced the trade linkages of many other countries in the world. To incorporate the changes \nin global trade linkages, the foreign variables of all the models in the study are compiled with \ntrade-weighted three-year moving average data. \nThe foremost objective of the thesis is to determine how the changes in trade linkages affect the \ntransmission of economic shocks originating in the rest of the world on South Africa. The global \nvector autoregression (GVAR) approach is used since one of its advantages is the incorporation \nof global trade linkages, which facilitates the analysis of the transmission of shocks from one \ncountry to another. \nAs a GVAR model combines many individual country models, the study first estimates such a \ncountry-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 \nmodel (VECM) with domestic variables and weakly exogenous (X) foreign (*) variables, denoted \nby VECX*. The results from the VECX* for South Africa are in line with expectations, showing \nthe effective transmission of monetary policy. \nThe study then examines the impact of international shocks on the South African economy with \na GVAR model. The GVAR, which incorporates country-specific VECX* models for 33 \ncountries, is solved for all 33 countries using global trade weight matrices at different dates. The \nresults indicate that over time South Africa is much more vulnerable to GDP shocks to the \nChinese economy, and less vulnerable to GDP shocks to the US economy. These trends are \nhowever not confined to South Africa, and as such highlights the increased risk to the South \nAfrican economy and many other economies, should China experience slower GDP growth. \nFinally, the thesis determines whether the forecasting performance of GVAR models is superior \nto that of a country-specific VECX* model. The study compares the out-of-sample forecasts of \ntwo key South African variables (real GDP and inflation) for five types of models: a VECX*, a \ncustomised small GVAR for South Africa, the more general 33-country GVAR, simple \nautoregressive models and random walk models. Better forecasts of both the GVAR models \ncompared to the VECX* model at forecast horizons of more than four quarters show that, \ndespite the complicated nature of the GVAR model with the inclusion of many countries and \nglobal trade linkages, the additional information is useful for forecasting domestic variables
Author: Annari De Waal
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W339584072