Advancing sustainable development with green financial technology and natural resources rents
Nomazwe Sibanda et al.
What the paper says
Purpose This study aims to investigate the combined impact of technological innovation, natural resource rents (NRR) and green finance (GF) on sustainable human development in Sub-Saharan Africa (SSA). SSA is associated with poor quality of life because of low-level standards of living, poor health facilities, weak technological systems and low-level human capital. There is a dearth in the literature on how the advancement of human development could be achieved SSA, and this research provides empirical evidence that is crucial for policy implications. Design/methodology/approach Through adopting the human development index (HDI) the methods of moments quantile regression is used in this analysis. The annual data of the 43 SSA nations for the period are used. Robustness is ensured through feasible generalized least squares and panel-corrected standard errors with pretests confirming cross-sectional dependency heterogeneity and cointegration. Findings The outcomes of the research depict the importance of technological innovations, government effectiveness, NRR, financial development and GF in supporting human development. However, in as much as GF improves human development, its effect becomes insignificant in the upper quantiles. This research also depicts that renewable energy reduces human development, hence a great cause on concern in policymaking. Originality/value The novelty of the study is in employing the HDI of the United Nations Development Programme that constitutes three key dimensions – being knowledgeable, a health life and high standards of living – to cover the gap existing in the literature and present key policies for sustainable human development in SSA.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.