This study examines the impact of diaspora income on the ecological footprint of 22 countries African countries. Methodologically, we used the Driscoll-Kraay (1998) fixed-effect model, fixed effect instrumental variable regression, Machado and Silva (2019) panel quantile regression, and Dumitrescu and Hurlin (2012) causality test. There are four main important findings from this empirical study: (1) diaspora income has a negative and statistical impact on ecological degradation, (2) financial development plays a crucial role in mitigating the environmental impact of diaspora income, and African countries must achieve an annual estimated threshold of financial development before they could reap the environmental quality impact of diaspora income, (3) the role of financial development in reducing the environmental degradation impact of diaspora income is less for higher polluting countries in Africa, (4) unidirectional causality from diaspora income to ecological footprint. In ensuring a sustainable environment, we recommend that African governments provide a tax credit to the recipient of the diaspora income who invests in environment-friendly technologies.
This study examines the spatial impact of FDI on the poverty of 44 African countries. In achieving this, the study uses the Driscoll–Kraay fixed effect instrumental variable regression, the instrumental variable generalized method of moments estimator (IV-GMM), and the spatial Durbin model. The empirical investigation of this study yielded four significant findings: (1) neighboring countries’ FDIs have a positive and significant impact on the incidence and intensity of the host country’s poverty, (2) improved institutional quality in neighboring countries has a significant impact on the FDI–poverty reduction nexus of the host country, (3) the empirical results lend support for a significant spatial spillover of poverty in the region, (4) the marginal effect results indicate that countries within the region are no longer in isolation or independent, i.e., the level of poverty in a particular country is influenced by its determinants in the neighboring country. This result is robust to the alternative proximity matrix, which is the inverse distance. Since there is spatial interdependence among African countries, we recommend that African governments, through the African Union (AU), should not only champion the institutional reform in the region, but also establish a binding mechanism to ensure reform implementation.
Different regions are linked through different factors such as climate, and border sharing. Apart from this, African countries have developed significant links as a result of globalization, economic integration, and trade liberalization. Since any country's economic growth is influenced by the performance of its neighbours, these ties have resulted in spatial dependence among these countries.On this basis, the significance of spatial interactions between countries cannot be overemphasised. It is for this reason that the study investigated spatial dependence between African countries. The study employed non-spatial (FE, GMM) and spatial (SDM, SAM, and SEM) econometrics techniques and data ranging from 1996 to 2019 to examine the impact of ODA on Economic growth in Africa and its spillover effects. Based on the graphs and the Moran I test, the findings reveal that i) there is spatial dependence among African countries ii) The GMM results indicate that the ODA impact was positive and statistically significant but smaller in magnitude compared to the magnitude of the spatial models' coefficients. This suggests that not controlling for space heterogeneity will possibly underestimate the real impact of ODA on GDP. Secondly, the study found that the weighted GDP was positive and statistically significant, which indicates that an increase in the GDP of a certain country has a positive and statistically significant impact on their neighbour's economic growth. Based on the findings of the study, it is suggested that countries should improve their relationships and partnerships if they want ODA to provide the desired benefits across Africa.
This study examines the spatial impact of FDI on the poverty of 44 African countries. In achieving this, the study uses the Driscoll-Kraay fixed effect instrumental variable regression, instrumental variable generalised method of moments estimator (IV-GMM), and the spatial durbin model. The empirical investigation of this study yielded four significant findings: (1) neighbouring countries’ FDI has a positive and significant impact on the incidence and intensity of host country’s poverty. (2) Improved institutional quality in neighbouring countries has a significant impact on FDI-poverty reduction nexus of the host country. (3) the empirical results lend support for a significant spatial spillover of poverty in the region. (4) the marginal effect results indicate that countries within the region are no longer in isolation or independent, i.e., the level of poverty in a particular country is influenced by its determinants in the neighbouring country. This result is robust to the alternative proximity matrix, which is the inverse distance. Since there is spatial interdependence among African countries, we recommend that African governments through the African Union (AU) should not only champion the institutional reform in the region, but also establish a binding mechanism to ensure reform implementation.
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