Interconnections between governance and socioeconomic conditions: Understanding the challenges in sub-Saharan Africa

doi:10.1016/j.regsus.2022.01.004

Abstract

Abstract:

Given that challenges on the issue of socioeconomic development faced by countries in sub-Saharan Africa (SSA) have been identified as critical to strengthening the inherent link between governance and socioeconomic conditions, this study examines the interconnections between governance and socioeconomic conditions in SSA. With a focus on 25 countries in SSA between 2005 and 2019, we conduct the analysis based on the Panel-Corrected Standard Error and System Generalized Method of Moments estimations and panel causality tests. The results show that SSA does not seem to have the means of effective governance to spur improved socioeconomic conditions. Moreover, the pervasiveness of institutional problems in many countries of SSA has been responsible for the poor socioeconomic conditions in the region. Likewise, governance quality and socioeconomic conditions are found to influence each other. An improvement in socioeconomic conditions could result in better governance quality. On the other hand, governance quality is viewed as a vital ingredient in achieving needed socioeconomic development outcomes. Thus, it is suggested that there is a need for countries in SSA to streamline governing systems toward engendering improved well-being. The introduction and implementation of transformative policies through effective governance are also necessary for ensuring critical structural changes and increasing social service provision. Overall, there should be a proactive identification of ineffective policies and procedures by policymakers to enhance meaningful impacts in the region.

Key words: Governance quality, Socioeconomic conditions, Economic development, System Generalized Method of Moments, Sub-Saharan Africa

Fisayo FAGBEMI, Geraldine Ejiaka NZERIBE, Tolulope Temilola OSINUBI, Simplice ASONGU. Interconnections between governance and socioeconomic conditions: Understanding the challenges in sub-Saharan Africa[J]. Regional Sustainability, 2021, 2(4): 337-348.

Figures/Tables 8

Fig. 1.

Table 1

Description, measurement, and source of variables used in the study."

Variable	Code	Description and measurement	Source
Socioeconomic condition	SOCD	An assessment of the socioeconomic pressures that could constrain government action or fuel social dissatisfaction. The risk rating assigned is the sum of three subcomponents (unemployment, consumer confidence, and poverty), and each of them has a maximum score of four points and a minimum score of zero point. A score of four points equates to very low risk and a score of zero point to very high risk. A total of 12 points is possible.	International Country Risk Guide (ICRG, 2019)
Income per capita (USD)	INC	It is gross national income in purchasing power parity (PPP) divided by mid-year population.	World development indicator (The World Bank, 2020)
Political stability	POL	Measuring perceptions of the likelihood of political instability and/or politically motivated violence, including terrorism. It is rated on a scale, as appropriate, ranging between -2.5 and 2.5.	World Governance Indicators (Kaufmann et al., 2010)
Voice and accountability	ACC	Representing the extent to which a country’s citizens are able to participate in selecting their government, as well as the freedom of expression, freedom of association, and free media. It is rated on a scale, as appropriate, ranging between -2.5 and 2.5.	World Governance Indicators (Kaufmann et al., 2010)
GDP per capita (USD)	GDP	The sum of gross value added by all resident producers in the economy in addition to any product taxes and minus any subsidies not included in the value of the products. It is measured without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.	World development indicator (The World Bank, 2020)
Foreign direct investment, net inflows (% of GDP)	FDI	Representing net inflows—new investment inflows less disinvestment—in the reporting economy from external (foreign) investors.	World development indicator (The World Bank, 2020)
Domestic credit to the private sector (% of GDP)	DCP	Referring to financial resources provided to the private sector by financial corporations, such as through loans, purchases of nonequity securities, and trade credits, and other accounts receivable that establish a claim for repayment.	World development indicator (The World Bank, 2020)

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Statistic	SOCD	INC (USD)	ACC	POL	GDP per capita (USD)	FDI (% of GDP)	DCP (% of GDP)
Mean	3.15	3667.13	-0.78	-1.00	1853.79	5.91	20.25
Median	3.00	2083.49	-1.02	-1.43	784.04	2.72	13.48
Maximum	6.00	17,260.46	0.65	1.10	9675.43	103.34	160.13
Minimum	1.00	518.84	-1.47	-2.18	300.56	-6.06	1.20
Standard deviation	1.05	4071.12	0.52	1.08	2410.66	11.42	28.12
Skewness^#	0.49	1.95	1.00	0.42	2.08	5.40	3.95
Kurtosis^#	2.83	5.55	3.05	1.93	5.95	37.90	18.19
Jarque-Bera^#	12.47	275.78	50.79	23.64	330.22	16,965.92	3725.33
Significance	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Sum	960.84	1,118,473.00	-236.33	-305.04	565,406.90	1801.79	6176.23
Sum square deviation	334.86	5.04	83.24	352.39	1.77	39,629.94	240,362.50
Observations	305	305	305	305	305	305	305

Variable		Im, Pesaran, and Shin test (W-statistic)	ADF Fisher test (Choi Z-statistic)	Phillips-Perron Fisher test (Choi Z-statistic)
SOCD	Level	-0.02	-0.04	-0.86
SOCD	First difference	-11.61^***	-11.26^***	-16.03^***
ICN	Level	6.44	6.10	5.03
ICN	First difference	-7.20^***	-6.92^***	-7.20^***
ACC	Level	-7.46^**	9.10^**	-10.57^**
ACC	First difference	-	-	-
POL	Level	-14.51^***	1.89	2.91
POL	First difference	-	-12.34^***	-13.92^***
GDP per capita	Level	-7.26^***	-6.49^***	-7.06^***
GDP per capita	First difference	-	-	-
FDI	Level	1.32	1.33	2.16
FDI	First difference	-11.96^***	-13.38^***	-12.05^***
DCP	Level	2.47	4.81	1.37
DCP	First difference	-16.11^**	-13.98^***	-14.19^***

Variable	PCSE				System GMM
Variable	Model 1	Model 2	Model 3	Model 4	Model 1	Model 2	Model 3	Model 4
SOCD (lag)	-	-	-	-	0.67^*** (10.79)	0.65^*** (11.08)	-	-
INC (lag)	-	-	-	-	-	-	0.54^*** (7.91)	0.61^*** (6.01)
ACC	0.03^*** (4.81)	-	0.11^** (3.14)	-	0.06^** (3.12)	-	0.21^** (3.22)	-
POL	-	0.01^*** (5.26)	-	0.13^** (3.11)	-	0.05^** (2.85)	-	0.41^*** (4.21)
GDP per capita	0.13^** (2.58)	0.05^* (1.69)	0.12^** (3.01)	0.22^*** (5.04)	0.01^*** (5.62)	0.05^** (2.87)	0.17^*** (4.11)	0.25^** (2.96)
FDI	0.01^* (2.34)	0.11^* (1.88)	0.13 (1.15)	0.21 (0.88)	1.02 (0.19)	0.06 (0.11)	0.01 (0.17)	0.10 (0.61)
DCP	0.21^** (2.15)	0.13^** (2.71)	0.41^* (1.55)	0.23^** (2.52)	0.04^** (3.27)	0.01^** (3.11)	0.19^* (1.56)	0.23^* (1.51)
Constant	0.04 (0.11)	0.22 (0.71)	0.12^* (1.66)	0.20^** (2.53)	0.37^** (3.22)	1.21^** (2.91)	0.13^* (1.58)	0.17^** (2.01)
R²	0.56	0.54	0.57	0.55	-	-	-	-
Observations	305	305	305	305	257	257	257	257
Number of countries	25	25	25	25	25	25	25	25

Variable	PCSE				System GMM
Variable	Model 1	Model 2	Model 3	Model 4	Model 1	Model 2	Model 3	Model 4
Pesaran cross-sectional dependence	0.29	0.42	0.13	0.25	-	-	-	-
Heteroskedasticity	0.21	0.35	0.42	0.33	-	-	-	-
A-Bond AR (1)	-	-	-	-	-5.21 (0.00)	-5.18 (0.00)	-4.97 (0.00)	-5.32 (0.00)
A-Bond AR (2)	-	-	-	-	-1.03 (0.13)	-1.05 (0.28)	-1.12 (0.31)	-1.22 (0.33)
Sargan test	-	-	-	-	46.21 (0.31)	49.17 (0.14)	47.02 (0.34)	49.01 (0.23)

Causality	Wald test	Inference of causality
SOCD→ACC	4.11^**	Yes
SOCD→POL	5.41^**	Yes
INC→ACC	4.32^**	Yes
INC→POL	5.78^**	Yes
ACC→SOCD	9.20^***	Yes
POL→SOCD	11.15^***	Yes
ACC→INC	8.01^***	Yes
POL→INC	6.57^**	Yes