Analysing the Complexities of Export and Heterogeneity of BRICS Economies
Description
This study examines BRICS export competitiveness, focusing on economic sophistication and competitive strength. While previous research relied heavily on GDP, this study incorporates per capita income (PCI) and the GINI coefficient to capture income distribution disparities. Using quantitative methods such as the EGARCH Model, VECM, ARDL, and Cochran’s Q test, the study explores export dynamics at the product level. Data were collected using a longitudinal survey research design covering the period from 1989 to 2022. The study relied on economic fundamentals such as Gross Domestic Product (GDP), GINI coefficient (a measure of income inequality), and Per Capita Income (PCI), alongside trade indicators (Exports and Imports). Data sources included international trade databases, national statistical agencies, and economic reports. Data were collected from publicly available sources such as the World Bank, IMF, and UNCTAD, with storage and analysis conducted at Landmark University, Nigeria. Statistical models like EGARCH, VECM, ARDL, and Cochran’s Q test were used to analyze export competitiveness and economic heterogeneity among BRICS nations. The study highlights the significance of economic role demand management, including skill discretion, meaningfulness, challenging tasks, management support, and time management, in shaping trade competitiveness. These factors significantly influence economic performance, just as eustress enhances productivity among academic staff. Findings reveal that China leads in economic complexity and competitiveness, followed by Russia, Brazil, India, and South Africa. Economic homogeneity among BRICS nations is supported by F-test results for GDP, PCI, and GINI coefficient homogeneity, aligning with shared developmental goals. By integrating income distribution measures, this study provides a comprehensive perspective on trade competitiveness. Grounded in Yerkes-Dodson’s Theory. The data underscore the potential for economic strategies that enhance trade competitiveness, with broader implications for quality research, teaching, and economic policy frameworks aimed at fostering sustainable global development.
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This study analyses the export competitiveness and the heterogeneity of BRICS economies. The paper uses two pioneering model to analyse the export competitiveness of the five BRICS countries (Brazil, Russia, India, China and South Africa) and the heterogeneity of their economies. Consequently, the economic fundamentals of the BRICS countries and their trade statistics (Exports and Imports) served as the population of the study. The study used a longitudinal survey research design of some economic fundamentals like the Gross Domestic Product (GDP), GINI (a measure if the income inequality and Per Capita Income (PCI) as well as the Trade indicators (Exports and Imports). The period covered is 1989-2022. 3.1 Measurement of Variables and Model Specifications This section presents the measurement of the research variables and the mathematical specifications of the study’s models 3.1.1 Export Competitiveness Equation (i) presents the Measurement of trade competitiveness (TC) index 〖TC〗_ij = ((X_(ij -) M_ij ))/(X_ij+M_ij ) … (i) Where 〖TC〗_ijklm = trade competitiveness of country i relative to countries j, k, l and m x_ijklm = the monetary value of exports from country i to countries j, k, l and m m_ijklm = the monetary value of imports from countries j, k, l and m to country i. Table 1 Trade competitiveness (TC) index level of the export competitiveness of agricultural Index Range Export competitiveness level of agricultural products TC < - 1.000 Imports but does not export—no export competitiveness -1.000 < TC < -0.500 Very poor export competitiveness -0.500 < TC < 0.000 Poor export competitiveness 0.000 < TC < 0.500 Strong export competitiveness 0.500 < TC < 1.000 Very strong export competitiveness TC = 1000 Exports but does not import—strongest export competitiveness Source: Long (2021 3.1.2 Test for Heterogeneity of the of Brics Economies The study used the Gross Domestic Product (GDP), Per capita income and GINI Coefficient (a measure of the income inequality of the citizen) to measure the economies of the BRICS countries and employed the Cochran’s Q statistic to test for the heterogeneity of the data on the GDP. Per capita income and GINI of the BRICS economies. The study also used the F statistic (ANOVA) to test for homogeneity of the data on GDP to ascertain the degree of heterogeneity of the economic fundamental of the BRICS economies. Following the results of the ANOVA test of significant and the resultant differences in the average economic fundamentals, the study tested for homogeneity of heterogeneous subgroups or heterogeneity of homogeneous subgroups using the Waller Duncan Post-Hoc technique. 4. Results Table 1 presents the Export competitiveness of the BRICS economies. The results show that 15 (44%) of Brazil’s Exports between the period 1989 and 2022 resulted in strong Export Competitiveness while the remaining 19 (56%) resulted in very strong export and sustainable competitiveness globally.
Institutions
- Landmark University