With an ever-increasing globalising world, trade is of most importance for developing countries to not fall behind and be outcompeted. Export-led growth theory states that one of the key determinants for economic growth is exports. This thesis aims to analyse the causal effects of exports on economic growth in the case of Brazil. Annual data from the World Bank’s database for the years 1990-2018 has been used. The variables included are GDP, exports, gross capital formation, FDI and labour force. This study puts the export-led growth theory in a Vector Error Correction – Granger Causality framework. As opposed to previous scholars’ findings, neither export-led growth nor growth-led export could be determined for Brazil.

Magister Commercii - MCom / The objective of this study is to investigate the empirical relationship between exports and economic growth in order to ascertain whether the hypothesis of export-led growth is valid in the case of South Africa. This study has not only focused on sectoral exports for the period 1990-2011; but it has also examined total exports for the period extending from 1970 to 2011. Using quarterly data and time series econometric techniques of co-integration and Granger-causality tests over the two set of periods, the key findings of the study are as follows: (i) At the aggregate level (using total exports): the technique of co-integration suggests that total exports and GDP moved together in the long-run, though deviations from the steady state might happen in the short-run. Furthermore, Granger causality tests inferred from the Vector Error Correction model reveal that the direction of causality between export and GDP growth is bidirectional. (ii) At the sectoral level (using the main component of exports): export-growth link emerges as a long-run behavioural relationship since a co-integrating relation was found among output and agricultural, manufactured and mining exports. This relationship demonstrates that manufactured exports have the greatest positive impact on output growth. (iii) Sectoral level Granger-causality tests based on ECM reveal the existence of a long run causality running from manufactured exports to GDP; whereas the short-run causality runs from manufactured and mining exports to GDP. However, the Toda-Yamamoto Granger test confirms only short-run causality from manufactured exports to GDP. In both cases, there is evidence of a uni-directional causality from exports to GDP.The above results show that the hypothesis of export-led growth is valid for South Africa. This implies that exports, particularly manufactured and mining exports play a key role in driving economic growth. Hence, the key policy implication of these results is that, measures which aim at stimulating production for exports and shifting the content of exports will meaningfully contribute to the improvement of GDP growth and employment prospects in South Africa.

Doctor of Philosophy / Department of Economics / Wayne Nafziger / This dissertation constructs three empirical essays. The first essay illustrates the causality on the relationship between output (GDP) growth and exports. By using the Modified Wald (MWald) test we observe unidirectional causality from exports to GDP. More specifically, for the robustness we use a Vector Error Correction Model (VECM) model and the Generalized Impulse Response Function Analysis (GIRA). The VECM and the GIRA yield bidirectional causality between exports and GDP, which weakly supports the unidirectional result of the to MWald test. Meanwhile, we confirm that there is structure break by using the structural break test. These results are plausible and consistent with the expectations of our study for the Export Led Growth Hypothesis (ELGH). However, compared with previous studies on the ELGH for Korea, our results are different. Other studies show a bidirectional causality relationship but this study only has unidirectional causality. These differences may be caused from different observation data, various variables, and use of different econometric methodologies. Also, model selection and omitting variables can also significantly change the results of causality testing. The second essay investigates a degree of competition between Korea's and China's exports in the U.S. market by using the substitute elasticity on a simple demand model. The market share of Korean exports has been decreasing while that of China's has been increasing. The results of this study are as follows. First, we find that Korea has a dominant market share of only goods group code 27 in commodity groups over that of China, otherwise having China's dominant market shares over those of Korea for other export sections by using historical trade data. Second, most estimates of substitute elasticity between both countries' exports in the U.S. market are small (inelastic). However, 61 (apparel articles and accessories, knit or crochet), 62 (apparel articles and accessories, not knit etc) and 85 (electric machinery etc, sound equipments, TV equipment, parts) commodity groups' substitute elasticities are large (elastic) and are competitive in the U.S. market compared with those of China. A small value of the elasticity of substitution may be due to an identification problem for a simple standard model as well as measurement errors in prices as a unit value in this study. So, in order to avoid problems such as these, we may need to use appropriate instrumental or proxy variables in the simple standard model, which highly correlate with the independent (unit price) variables and are uncorrelated with measurement error terms. In practice, it is not easy to find good instrumental variables. The final essay evaluates the roles of price and income as important factors that affect Korea's exports by using the most recent monthly data. By using the Autoregressive Distributed Lag (ARDL) bounds testing approach we find the long-run relationship of variables and estimate the long-run price and income elasticities. However, the estimates of these long-run elasticities are statistically insignificant. This may be due to some misspecifications or measurement errors in our model. Meanwhile, due to the existence of the long-run relationship between variables, we construct the Error Correction Model (ECM) in order to observe the short-run dynamics of the elasticities. Specifically, we add a dummy variable into our export demand model to achieve more efficient estimations since the dummy variable reflects a shock in Korea's export; Korea's economic crisis in 1997. In contrast to the long-run elasticity, we find that the short-run elasticities' estimates are more statistically significant. When we use the structure break test to check the structural stability of Korea's export demand, we find that there is no structural break point of 1997. Therefore, a shock of Korea's economic crisis in 1997 might not significantly affect Korea's export demand in a given sample. However, the Information Technology (IT) bubble of the world economy in 2001 and the entry of Korea into the OECD had triggered an increase in Korea's export demand due to existing structural break points of both events. In addition, we find that income elasticities are larger than price elasticities in the short run. This implies that income has more of an impact than that of price for the export demand model in the short run. This also implies that the change of Korea's exports in the short run is more sensitive to changes in foreign income (industrial production) compared with that of price (exchange rate). An interesting result, thus, is that Korea's exports in the short run may have higher export performance on income than that of price (exchange rate). This might be a consequence of the dependence of an increase in foreign income in recent years. In recent years, developing countries have greatly increased their economic growth compared with that of developed countries and Korea's exports have increased into these developing countries. Thus, we confirm that an increase in Korea's exports is mainly affected by income compared with price, specifically in the short run by using recent data.