Implications of Governance, Natural Resources, and Security Threats on Economic Development: Evidence from Sub-Saharan Africa

Abstract

Sub-Saharan African countries are known to be bedeviled with some challenges hindering the economic development. Meanwhile, some of these issues have not been exhaustively investigated in the context of the region. Thus, this study aimed at investigating the implications of government effectiveness, availability of natural resources, and security threats on the regions’ economic development. Yearly data, spanning from 2007 to 2020, was converted from low frequency (yearly) to high frequency (quarterly) and utilized. Data analysis was conducted using Dynamic heterogeneous panel level estimators (PMG and CS-ARDL). Findings show that while PMG estimator confirms a long-run causal effect of governance, natural resources, and security threats on economic development, only natural resources show a short-run causal effect with economic development, while the CS-ARDL (model 2) confirms the significance of all the variables both in the long and short-run. Moreover, the ECT coefficients for both models were found to be statistically significant at less than 1% significance level, which indicates that the systems return back to equilibrium in case of a shock that causes disequilibrium, and in addition, reveals a stable long-run cointegration among the variables in the model. Finally, this study suggests that the policy makers in SSA countries should place more emphasis on improving governance, managing security challenges, and effectively utilizing rents from the natural resources, as all these have severe implications for the economic development of the region if not addressed.

The Effect of Resource Endowment and Governance on Human Capital Development of Sub-Saharan African Countries

“…Because system GMM use control variables as instrument. Mathematically the model can be written as: -hc = f(gov, nrs, CONVA) hcit = bO + b1hcit − 1 + b2xit + uit (5) Where; hc=human capita development, gov=governance indicator (government effectiveness, control of corruption, rule of law, voice and accountability, regulatory quality and Political Stability &Absence of Violence), HI=human capital (education and health), CONVA=other control variables such as labor participation rate and foreign direct investment. Econometrics estimation of dynamic panel System GMM model can be estimating as follows.…”

“…Furthermore, Governance involves different affairs that comprised creating conducive political, legal, economic, and human capital. Corruption has negative effect on the economic, social, and political development of countries and which manifested by amplified transaction costs, the diminution in the efficiency of public services, and the discouragement of social values [5]. On the other hand, Corruption is one indicator of bad governance but its effect depends on forms of institution.…”

Does Sub‐saharan Africa's Rapid Population Growth Have Positive or Negative Effects on Aggregate Domestic Investment?

“…For instance, East Asia and the Pacific had the highest average domestic investment (i.e., 35.7 percent of gross capital formation to GDP), followed by South Asia (31.6 percent), the Middle East and North Africa (26.6 percent), and SSA (22.37 percent) (see World Development Indicators 2021). Rjoub et al (2021) contend that SSA's low domestic investment has prevented its economies from taking full advantage of the potential of the region's natural resource endowments. This argument was also voiced by Venables (2016), who said that developing countries must continuously support the growth of domestic investment in order to sufficiently benefit from the stock of resources available.…”

Editorial Statement and Research Ideas on Using Behavioral Models in Environmental Research and Public Health with Applications

“…al. [ 4 ], Du et al [ 5 ], Lv et al [ 6 ], Pentrakan et al [ 7 ], Rjoub et al [ 8 ], Wang et al [ 9 ], Mumtaz et al [ 10 ], Wu et al [ 11 ], and Yao et al [ 12 ]. Among them, Attiq et al [ 3 ] used the partial least squares structural (PLS) model to examine the impacts of financial, cognitive, and emotional concerns of consumers on recycling behavior, reuse, and food waste reduction and among restaurant patrons.…”

“…Moreover, Rjoub et al [ 8 ] employed dynamic, heterogeneous panel-level estimators to investigate both the low and high frequency of the data to examine the relationship between natural resources, government effectiveness, and security threats on the regions’ economic development. Cázares-Manríquez et al [ 4 ] used the risk factors including heart rate, age, respiratory rate, gender, respiratory rate, body mass index, and blood pressure to develop quantitative models to predict cumulative trauma disorders and prevent injuries in manufacturing factory operators.…”