Thesis (Ph.D. (Economics)) -- University of Limpopo, 2022 / This study investigated the relationship between economic complexity and the three mac-roeconomic variables in a comparative setting between selected Sub-Saharan African (SSA) and BRICS countries. Economic complexity as a development index reveals how sophisticated a country is as shown by its exports structure through the Product Com-plexity Index (PCI) and Economic Complexity Index (ECI). The three macroeconomic var-iables are gross domestic product per capita (GDP per capita), current account and fixed investment (gross fixed capita formation) for the period 1994 to 2018.The first three set study objectives were investigated on whether there exists a short and long-run relation-ship through a Panel Autoregressive Distributed Lag (PARDL). The the fourth objective was to test for causality through a standard Granger causality, and fifth, to forecast the macroeconomic variables for the foreseeable future utilising the Impulse Response Func-tion (IRF) and the variance decomposition techniques, these are complementary tech-niques. The last two objectives were to draw a comparative analysis upon the findings, and to relate on the product complexities and economic landscape in the selected SSA and BRICS. Reporting on the ECI-GDP per capita nexus, the PARDL estimates revealed a positive and significant association between ECI and GDP per capita in both the se-lected SSA and BRICS in the long-run. There was no Granger causal effect between ECI and GDP per capita for both set of countries. The concern was in relation to forecasting GDP per capita due to a shock in ECI. The selected SSA GDP per capita response to a shock in ECI was neutral when adopting the IRF technique, and the variance decompo-sition also revealed small estimates in both the short and long-run, below 1%. In the BRICS economies, there was a meaningful positive reaction from a shock in ECI when deploying the IRF technique, while the variance decomposition had a 3% response in the long run when seen through the variance decomposition. On the current account-ECI relationship, the PARDL estimates exposed that there was a positive and significant impact from ECI on the current account in both the groups in the long-run significant while short-run results were insignificant. Granger causality could not detect any causal effect between ECI and current account in the selected SSA, while in the BRICS countries there was a unidirectional causal effect from ECI to current account. When forecasting the current account, the selected SSA reacted negatively to a shock in v ECI seen through the IRF, and the variance decomposition also revealed a small reaction in any period. In the BRICS case, current account’s response was a positive and explo-sive reaction from a shock in ECI when applying the IRF technique. The VD revealed a higher change in current account was explained by a shock in ECI. On the ECI-Fixed Investment, the PARDL estimates showed that there was a long-run positive and signifi-cant effect between ECI and fixed investment in bothgroups. However, the Granger causal results revealed no presence of causality in the selected SSA, while there was causal unidirectional effect from ECI to fixed investment. The IRF technique revealed a negative fixed investment reaction from a shock in ECI, and the variance decomposition results revealed a small reaction in fixed investment in the selected SSA. In the BRICS case, there was a positive and explosive fixed investment emanating from a shock in ECI. Utilising the variance decomposition fixed investment in BRICS was explained by inno-vative shocks in ECI in the long run. On the last two objectives, comparatively the selected SSA countries are disadvantaged as they are concentrated in negative ECI as seen in the descriptive statistics, reflecting that they are still much less developed. This tells us that they are less industrialised as compared to the BRICS nations who are better off. These selected SSA economies are not developed enough as compared to the BRICS nations. The SSA region needs to learn from the leading BRICS countries by creating a conducive environment for a better de-velopment of innovation that improves the domestic value chain that produces knowledge-based products for the export market. The rest of the selected SSA region should form part of economic integrations with the more developed countries that offer mutual beneficiation like South Africa to fast track the developmental of their states. There is a need to modernise the agricultural and agro-industries. The region should harness the full potential of its agricultural sector. This will create a large global market share and perhaps increase the current account outlook through trade with more efficient agro-pro-cessed products. Africa needs to scale up investment in many fronts from government to private investment to improve infrastructure, more so that the scale of needs is so much in the continent.