DOES SUB-SAHARAN AFRICA'S RAPID POPULATION GROWTH HAVE POSITIVE OR NEGATIVE EFFECTS ON AGGREGATE DOMESTIC INVESTMENT?

Abstract

Spanish

Chinese

This study examines the effect of population growth on aggregate domestic investments in 45 Sub-Saharan African (SSA) countries over the period 2000–2020. It applies the Quantile Method of Moments with fixed effects (i.e., MM-QR), which has the ability to identify both negative and positive effects while controlling for trade, HIV/AIDS prevalence, and economic growth. The findings show that SSA’s rapid population growth has a positive and statistically significant effect on aggregate domestic investments. Findings from this study show that an increase in population growth in the 10th to 60th quantiles is associated with an increase of domestic investment in SSA. This suggests that, as the population grows in SSA, it generates demand for domestic investments such as healthcare services, education, and other social services. Our findings also show that trade is positive and significant across all quantiles (10th to 90th). We find evidence that disease risks, such as the prevalence of HIV/AIDS, slowed the increase in domestic investment in the region across all quantiles (10th to 90th). We conclude by arguing that, since SSA's population growth will double in the near future, the region is bound to become world's next investment hub. In order to enable long-term domestic investments in the region, future policy options should take the challenges of population growth into account.

Keywords

Population Growth Domestic Investment Sustainable Development Panel Quantile Regression Sub-Saharan Africa HIV/AIDS Healthcare Investment Social Services

The relationship between population growth and economic development in general has been a subject of debate among scholars and policy makers for a long time (Bucci, Eraydin and Müller 2019)—indeed, since Thomas Malthus (1798) claimed that population growth would lower living standards in the long run. Currently, there is no clear consensus on this link and the literature is mixed on whether rapid population growth is good or bad for domestic investments, particularly in developing countries like Sub-Saharan Africa (SSA). It is possible to believe that high fertility rates and rapid population growth in poor countries within SSA would shift the available resources away from savings and investment, slowing down economic development. For instance, child family size can reduce investment through spending on education and healthcare (Bloom, Canning and Sevilla 2003). This reduces the available funds for saving and investing in economic activities that promote growth. In addition, rapid population growth can lead to slow economic growth and increases in poverty and unemployment, add to the burden of public pensions and healthcare systems, and to environmental degradation in Africa (Bloom and Freeman 1986; Ezeh, Bongaarts and Mberu 2012; Dimnwobi et al. 2021). To balance the negative consequences of population growth, Kelley and Schmidt (1995) claimed that population growth has both negative and positive effects.

The unfulfilled agenda of family planning, which began in 1960 for the majority of developing countries until the present, sought to slow the rate of population growth. Its main goals were to advance socioeconomic development, fight poverty, and safeguard environmental sustainability (Cleland et al. 2006). To make a long story short, from the 1950s to the present, rapid population growth in developing countries such as SSA has been viewed as a problem for development. This article seeks to examine the evidence available in the dataset from 2000 to 2020 to determine whether SSA’s rapid population growth has positive or negative effects on domestic investments.

In terms of population growth, SSA has a young and rapidly growing population when compared to the rest of the world (Feng and Groth 2020). The region currently has a total population of around 1.2 billion people (World Development Indicators 2021), which is expected to more than triple by 2100 (United Nations 2019). The region's population is growing at a rate of 2.6 percent per year, which is higher than the global average of 1.5 percent (United Nations 2019). According to a Brookings (2019) publication, if such a population works as an asset, SSA will stand to offer the most remarkable business opportunities in terms of market size and human resources by the year 2100, both of which are critical areas for investment growth.

On the other hand, Lakhanpal et al. (2021) viewed investment growth as crucial for the economic development of any country as it can lead to economic transformation given the significant role it plays in promoting technological progress, productivity, and employment. To achieve satisfactory results in investment growth, a combination of investment promotion and an appealing investment environment, along with other factors that influence producers' incentives and opportunities, must be taken into account (Morisset 2003; World Bank 2004). For example, a favorable investment climate helps in reducing costs and risks associated with investment projects while attracting new and more productive technologies (Morisset 2003; World Bank 2004). In SSA, for example, domestic investment (i.e., gross fixed capital formation, percentage of GDP) increased from 20 percent in 2000 to 23 percent in 2020 (World Development Indicators 2021). This suggests that SSA continues to lag behind other regions in terms of domestic investments. 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.

Over the last three decades, SSA has failed to achieve satisfactory investment results, with average investment returns less than 25 percent (World Development Indicators, 2021). Tanzania, Ethiopia, Zambia, Uganda, Niger, and the Democratic Republic of Congo have the highest investment ratios above 25 percent, with an average population growth rate of more than 2.5 percent, while Nigeria, Burundi, Somalia, and Cameroon have domestic investment to GDP ratios below 20 with the same average population growth rate (World Development Indicators, 2021). Indeed, Gillis et al. (1989) stated that, long-term growth can only be achieved if the domestic investment-to-GDP ratio is 25 or higher.

In regard to domestic investments, optimists think that rapid population growth is a good asset for the economy. For example, some studies (see Baker, de Long and Krugman 2005; Linden 2017; Myrdal 1940; Sweezy 1940) show that population dynamics and emerging economic opportunities are strongly linked. Bloom, Canning and Sevilla (2003) pointed out that a rapid increase in the population of many Asian countries, including China, Hong Kong, Singapore, and Latin American and Middle Eastern countries in the mid-1960s was due to rising fertility rates and declining mortality rates. They believe that technology advances and human capital accumulation enabled Asian countries to achieve higher economic growth (Bloom, Canning and Sevilla 2003).

It is in this context that this study examines whether the rapid population growth in SSA is beneficial in terms of investment growth or is rather a problem as Thomas Malthus once predicted. Put differently, the study seeks to assess whether the region's current rapid population growth is favorable to its state of domestic investment with the view to strengthening policy actions toward enhancing the region's achievement of the sustainable development goals by 2030.

Against this background, our study focuses on the effect of population growth on aggregate domestic investments in 45 SSA countries using a new dataset covering the period between 2000 and 2020. Apart from other related studies on population growth and development, the novel contribution of the study to the existing knowledge is the use of Quantile Method of Moments with fixed effects (MM-QR) as developed by Machado and Silva (2019). No previous studies on population growth and investments nexus have used MM-QR to examine whether population growth has nonlinear effects (i.e., both positive and negative) on domestic investments across the quantiles. Only Asongu (2013) used linear regression based on condition mean (i.e., the vector error correction model) to examine the effect of population growth on future investment in 47 SSA countries.

Moreover, quantile regression is useful in this study for several reasons: First, the sampled 45 countries differ in terms of their domestic investments and population growth. Second, this is the first study to examine the heterogeneous effects of population growth on domestic investment in the African context using quantile regression. Third, the method is robust to results and allows for nonlinearity within the same model in a set of panel data (see Byaro, Nkonoki and Mafwolo 2022; Arellano and Bonhomme 2016). Relatedly, Amegavi et al. (2021) argued that when the relationship between two variables is non-existent or weak, quantile regression is the best technique to use.

The article is organized as follows. We first review the theoretical and related literature on population growth and investments. We then discuss the methodology and data sources followed by a presentation of the empirical findings and discussion. The final section provides the conclusion as well as policy implications of the study.

Literature Review

Scholars and policy makers have been concerned about whether population growth is beneficial or not. Generally, there are two schools of thought on population growth, grounded on pessimistic and optimistic theories. The pessimistic theory is based on Malthus’ argument in his “Essay on the Principle of Population,” which was backed up by Ehrlich (1968), Kelley (1988), and Lele and Adu–Nyako (1991). According to this theory, unchecked population growth tends to grow geometrically, putting pressure on a fixed stock of resources, resulting in disasters such as diseases, starvation, and war which eventually lower growth through increased death rates (Malthus 1798). From these concerns, family planning campaigns grew in strength since the 19th century in the hope that rapid population growth would pose a threat because resources would be diverted from capital growth to accommodate the growing population—which is thought to be associated with unemployment, declining income, environmental pollution, deforestation, and disease risks (Asongu 2013; Asongu and Jingwa 2012; Bloom, Canning and Sevilla 2003; Byaro, Mafwolo and Mayaya 2022; Oyetunji et al. 2020; Preston 1996; Sweezy 1940; Byaro, Mayaya and Pelizzo 2022).

The optimistic theory is based on Kuznets (1960) ideas, which were later supported by other scholars (see, for example, Boserup 1965). Generally, this school of thought proposes that the population can be an asset in an economy. According to Kuznets (1960), an increase in the number of people creates the capacity to exploit economies of scale and expands knowledge and production technologies, resulting in a decrease in the price of resources as the amount of goods and services produced increases. This thinking is in line with Myrdal (1940) and Simon (2019) who argued that a progressive population is a necessary condition for private investment in the capitalist world. In other words, while a declining population raises investment risk and reduces demand for new investments, population growth can lower investment risk and increase demand for new investments. Furthermore, it is argued that as the population grows, entrepreneurs are more likely to believe that certain investments will be profitable, either due to increased commodity demand or a cheaper labor supply, resulting in positive population–investment correlations (Sweezy 1940; Simon 2019). Similarly, this view is also supported by the United Nations (2021) which contends that a growing population necessitates improvements in education, health, and gender equality because an economy's productive capacity improves significantly with the proportional increase of working-age people.

On the other hand, Ehrlich (1968) using experiences from different parts of the world contend that rapid population growth increases the demand for demographic investment that ultimately reduces investment and savings. Kelley (1988) argued that rapid population growth increases the dependency ratio which reduces household savings while diverting public spending away from investment-oriented sectors and toward social services.

Higgins and Williamson (1997) found in their study that population growth helped to raise savings and investments in both physical and human capital in Asia and Latin America. On the other hand, Golley and Tyers (2013) argued that the Chinese “one child policy” reduced fertility rate significantly allowing the proportion of the working population to increase which increased productivity of the economy as a whole around 1990s and 2000 to the extent of achieving great economic transformations. Despite significant efforts to reduce China's fertility rate and population growth rate through the one child policy, the economy continues to experience increased age dependency, which has acted as a disincentive to investment, thus forcing the government to reconsider its decision (United Nations 2008).

Meanwhile, Gagnon, Johannsen and Lopez-Salido (2021) found that among the causes of the economic crisis in America over the past few decades has been declining rate of population growth. Dyson (2010) also argued that population growth is linked to lower mortality rates, which in turn makes people care more about the future by taking the trouble to abstain from current consumption and invest for the future. Using examples from the United States, Baker, de Long and Krugman (2005) argued that slow population growth in high income countries is responsible for low investment growth in the region and that future economic growth will be lower than what occurred in the 20th century.

Similarly, using the experiences of developing countries, Bloom, Canning, and Sevilla (2001) claimed that declining mortality is an essential feature of a growing population that has a tendency to induce higher savings and educational attainment among people, a factor that leads to an increase in both human and physical capital. Hansen (1939) also stated that the discovery of new territory and new resources as well as population growth is responsible for the rapid growth of capital formation. This is also supported by Asongu (2013) who claimed that as a population grows demand for social services increases thereby making growth in public investment inevitable. It is also true that, over time, population growth has given rise to modern institutions such as competitive markets, flexible public policies, and well-run government programs that allow economies to adapt quickly to various investment opportunities and make better use of resources (see Cincotta and Engelman 1997).

Given the aforementioned theoretical perspectives, it is clear that the two schools of thought produce contradictory views about population growth. It is not surprising that previous empirical findings also produced mixed results. Indeed, while a huge volume of studies support a pessimistic view (see, for example, Higgins and Williamson 1997; Golley and Tyers 2013; Preston 1996; Oyentunji et al. 2020; Asongu and Jingwa 2012), there are also significant number of studies that support an optimistic view (see, for example, Rosen 1942; Cincotta and Engelman 1997; Dyson 2010; Baker et al. 2005; Bloom, Canning and Sevilla 2001; Hansen 1939; Asongu 2013).

Methodology and Data Sources

This article employs Machado and Silva's (2019) novel MM-QR with fixed effects or endogenous variables. The MM-QR technique is especially useful when the panel data model contains both endogenous independent variables and individual fixed effects. The model is written as follows:

y_{i t} = α_{1} + β X {^{'}}_{i, t} + (δ_{i} + θ_{i, t}^{'} γ) + ε_{i, t}

(1)

where

β

= location effect that measures residuals for estimating scale model.

θ^{'}

= scale effect that measures condition mean and estimate OLS models.

X^{'}

is a vector of explanatory variables for each country i with time t,

ε_{i, t}

is the vector of residuals and y is the dependent variable (domestic investments) and α₁ = constant.

Combining both location effect and scale effect, we obtain an estimate for the conditional quantile coefficient as follows:

Q y_{i t} (\frac{τ}{{x^{'}}_{i t}}) = α_{1} + β X_{i, t}^{'} + (δ_{i} + θ_{i, t}^{'} γ) + ε_{i, t}

(2)

Equation (2) is implemented as follows:

Investmen t_{i t} (\frac{τ}{{x^{'}}_{i t}}) = β_{i t}^{τ} + β_{1}^{τ} populatio n_{i, t} + β_{2}^{τ} trad e_{i, t} + β_{3}^{τ} HI V_{i, t} + β_{4}^{τ} GD P_{i, t}

(3)

where

τ

indicates the

τ

th quantile range estimates for 10th to 90th.

β_{i t}^{τ}

is the non-addictive fixed effects.

β_{1}

……..

β_{4}

are the coefficients of explanatory variables. In equation (3), the model's control variables are trade, HIV prevalence, and economic growth (GDP).

Data Sources

The data are gathered from 45 selected countries in SSA countries over the period 2000–2020 (see Appendix 1). Each country was selected depending on data availability. Domestic investments were expressed in terms of gross capital formation (i.e., formerly gross domestic investment, percentage of GDP). Domestic investments are expressed in terms of gross capital formation (i.e., formerly gross domestic investment, percentage of GDP). Domestic investments include plant, machinery, and equipment purchases; construction of roads, railways, schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings. Trade was expressed in terms of percentage of GDP. Population growth, GDP growth, and HIV/AIDS were expressed in percentage rates. All data were sourced from the World Bank Development Indicator (2021) database. The use of stated variables is consistent with similar studies such as that by Asongu (2013).

Results and Discussion

Tables 1 and 2 show the summary of descriptive statistics of variables and quantile regression results, respectively.

Table 1

Descriptive Summaries

Variables	N	Mean	Median	Std Dev	Min	Max
Investment (gross capital formation, % of GDP)	843	22.37	21.19	10.00	1.09	79.40
HIV/AIDS (rates)	924	5.36	2.1	6.72	0.1	28.9
Population growth (annual %)	936	2.47	2.65	0.93	−2.62	5.60
Trade (% of GDP)	853	70.85	60.97	34.56	20.72	225.02
GDP growth (%)	935	4.06	4.34	5.48	−36.39	63.37

Source: Authors computation (2022).

Table 2

Method of Moment Quantile Regression Estimates for Domestic Investments in SSA

Quantiles	Population	Trade	GDP growth	HIV/AIDS
$τ$ = 0.10	1.67*(0.984)	0.13***(0.032)	0.11 (0.101)	−0.87*** (0.320)
$τ$ = 0.20	1.58**(0.788)	0.15*** (0.025)	0.10 (0.081)	−0.86***(0.257)
$τ$ = 0.30	1.52**(0.672)	0.16***(0.022)	0.09 (0.069)	−0.84***(0.219)
$τ$ = 0.40	1.45**(0.593)	0.17***(0.019)	0.08 (0.061)	−0.83***(0.193)
$τ$ = 0.50	1.40 **(0.583)	0.18***(0.019)	0.07 (0.060)	−0.81***(0.190)
$τ$ = 0.60	1.33**(0.643)	0.20***(0.021)	0.06 (0.066)	−0.80 ***(0.209)
$τ$ = 0.70	1.25 (0.776)	0.21***(0.025)	0.05 (0.079)	−0.78***(0.253)
$τ$ = 0.80	1.19 (0.924)	0.22***(0.030)	0.04 (0.095)	−0.77**(0.301)
$τ$ = 0.90	1.09 (1.19)	0.24***(0.039)	0.03 (0.122)	−0.75**(0.388)
Observations	813	813	813	813

Source: Authors estimates (2022).

Notes: Standard errors in parentheses ().

*** p < .01, **p < .05, and * p < .1 show significance at 1%, 5%, and 10%, respectively.

The mean for domestic investment accounts for 22.37 percent of GDP while the median accounts for 21.19 percent of GDP in SSA. The highest domestic investments are found in the Democratic Republic of Congo (79.40 percent), Cabo Verde (50.79 percent), Mozambique (45.84 percent), and Tanzania (41.01 percent). Countries with the lowest domestic investments include Sierra Leone (1.09 percent), Zimbabwe (7.45 percent), and Eswatini (12.81 percent). The mean and median for annual population growth in SSA are 2.47 percent and 2.65 percent, respectively. Countries with the highest population growth include Niger (3.77 percent), Equatorial Guinea (3.40 percent), and Uganda (3.26 percent), while those with the lowest population growth include Lesotho (0.79 percent), Mauritius (0.03 percent), and Eswatini (1.04 percent).

Table 2 shows the results of quantile regression with fixed effects via method of moment estimator in a sample of 45 SSA countries over the period 2000–2020 at selected quantiles of 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, and 0.90. The median is 50th quantile.

Table 2 shows that an increase in population growth in the 10th to 60th quantiles associates with an increase of domestic investments in SSA. This means, as population grows, it creates demand for new domestic investments such as healthcare services and medicines, education, and other social services in SSA. However, at the 70th to the 90th quantiles, the effects of population growth on domestic investments are insignificant. The impact of population growth on domestic investment is at its greatest in the lower quantiles (10th to 60th) and weakest in the upper quantiles (70th to 90th). This implies that countries with higher population growth such as Uganda (3.26 percent), Niger (3.77 percent), Equatorial Guinea (3.40 percent), Burundi (3.07 percent), and Democratic Republic of Congo (3.14 percent) have opportunities to create more domestic investments in the region. In turn, countries with the lowest population growth rates, such as Eswatini (1.04 percent), Lesotho (0.79 percent), Mauritius (0.03 percent), and Seychelles (0.85 percent) are among the weakest upper quantiles (70th to 90th). Similarly, trade is positive and significant across all quantiles (10th to 90th). This means that the growth of trade also associates with an increase of population in SSA.

The findings also revealed that disease risks, such as the prevalence of HIV/AIDS, slowed the increase in domestic investment in the region across all quantiles (10th to 90th). This means, HIV/AIDS reduces labor productivity, income, and savings, resulting in a drop in domestic investment. Thus, HIV/AIDS continues to deter investors to invest in SSA countries.

In general, the findings show that the majority of quantiles have a positive and significant effect on population growth and trade on domestic investments in SSA countries. The upshot here is that, if SSA countries want to accelerate regional trade to their economies, they must increase domestic investments, which in turn is the function of region's population growth. Our results finally suggest that population growth rate and trade are key strong determinants of domestic investment in SSA countries.

Discussion

Our quantile regression results suggest that both population growth and trade have a positive and significant effect on domestic investments in SSA countries. This shows that the pattern of population growth in the region corresponds to the hypothesis of modern theories that support a positive contribution of population growth on domestic investment (see Headey and Hodge 2009). Note that the population of SSA is the fastest growing population among regions of the world at the rate of 2.66 percent, followed by the Middle East (World's Population Prospect 2019). By 2100, it is estimated that several regions of the world will experience a decrease in population size, while the most growing populations will be centered in SSA (World's Population Prospect 2019). For example, the United Nations forecasted that, from 2019 to 2050, 2.0 billion people will be added to the global population, out of which 52 percent (equivalent to 1.05 billion people) will be in SSA. This suggests that by the end of this millennium, SSA countries could become the worlds’ investment hub.

Furthermore, a rise in population growth in SSA is bound to create demand for education, health, and transportation infrastructures, which can be sourced from the expansion of tax revenues, increased market sizes and labor force, which in turn stimulates investment and generates jobs and new technology. In addition, as the population grows, societies tend to innovate (i.e., increase food production to accommodate population growth). Therefore, a massive increase in population growth can create economic benefits and lower mortality rates in general (i.e., infants and children) and eventually increases life expectancy in SSA (Byaro, Mafwolo and Mayaya 2022; Byaro, Mayaya and Pelizzo 2022).

In view of this reality, a rapidly growing population stimulates investments in various ways including creating a market for produced goods with an abundant labor supply, which lowers investment risks and costs with a bright prospect for future profits (see Myrdal 1940; Sweezy 1940). Moreover, the SSA population structure reveals that the size of the working ages (i.e., aged between 15 and 64 years) are growing faster than the size of other age groups (World's Population Prospect 2019). This reflects a good opportunity for investors to use the available human resources (i.e., labor) to establish various investments at affordable prices. Of course, this implies that governments in SSA must upgrade their workforce in order to turn human resources into human capital.

Similarly, the facts that trade increases domestic investments in all quantiles implies the contribution of trade to domestic investment cannot be ignored. This result is in line with Smith's (2013) argument that trade is instrumental in absorbing surplus products from the market. Likewise, the region has been involved in trade movements for decades, establishing regional trade agreements, reforming policies, and developing and improving infrastructure (see Byaro, Nkonoki and Mayaya 2021). It is also important to note that the fast growing economies of SSA (i.e., Ethiopia, Rwanda, Ghana, Côte d’Ivoire, Senegal, Kenya, Uganda, Burkina Faso, and Tanzania) achieved the status through an improvement of their trade environment that led to growth in trade (IMF 2019).

China and the Netherlands are other solid examples of countries where population growth contributed to their economy and investments. For instance, China has experienced a massive population growth and remains the second leading economy in the world today due to improved trade structures and exports. The Netherlands, with its limited land area, adapted and changed to accommodate its high-density population through reclaimed land from the sea with properly designed waste management systems and other significant infrastructure. It has proven that as their populations rise, countries can improve trade activities and transport infrastructures, health services, and medicine to accommodate changes in population growth (Asongu 2013). This suggests that population growth challenges can be addressed since human beings have the ability to develop solutions to their problems.

To this end, our findings support optimistic theory and are consistent with other similar recent studies (see, for example, Asongu 2013; Bloom, Canning and Sevilla 2001; Chaisrisawatsuk and Chaisrisawatsuk 2007; Cincotta and Engelman 1997; Duval 2008; Hansen 1939; Headey and Hodge 2009; Musila and Yiheyis 2015; Were 2015). Therefore, we conclude the notion that population growth dynamic and trade are fundamental in stimulating investments and the economy as whole.

Conclusion

This study examined the effect of population growth on domestic investments in SSA in a sample of 45 selected countries using a novel method of moment's quantiles with fixed effects from 2000 to 2020. We controlled for GDP growth, trade, and disease prevalence in the model. The key findings from the study revealed that population growth is statistically significant and increases domestic investments (i.e., gross capital formation) at lower quantiles (10th to 60th) in SSA countries. This implies that, as population grows, it generates modern demand for domestic investments like healthcare services and medicines, infrastructures, education, and other social services. The results further show that trade increases domestic investments across all quantiles (10th to 90th). This implies the growth of trade activities attracts more firms to invest in the region. Significantly, our findings revealed that HIV/AIDS incidence/prevalence exhibits a negative sign as expected in affecting domestic investments in SSA, meaning that HIV/AIDS reduces labor productivity, income, and savings, resulting in a drop in domestic investments.

Our findings suggest that countries in SSA should accelerate regional trade integration and channel their rapidly growing populations into productive activities and other investment opportunities. Besides, the region should continue to fight the HIV/AIDS pandemic to increase future domestic investments. To allow for sustainable domestic investments in the region, future policy options should consider all challenges posed by population growth.

Footnotes

Appendix 1: List of countries included in the analysis

S/N	Name of country	S/N	Name of country
1	Angola	29	Mauritania
2	Benin	30	Mauritius
3	Botswana	31	Mozambique
4	Burundi	32	Namibia
5	Cameroon	33	Niger
6	Burkina Faso	34	Nigeria
7	Cabo Verde	35	Rwanda
8	Central African Republic	36	Papua New Guinea
9	Chad	37	Senegal
10	Comoros	38	Seychelles
11	Congo, Rep.	39	Sierra Leone
12	Congo, Dem. Rep.	40	South Africa
13	Cote d'Ivoire	41	Tanzania
14	Equatorial Guinea	42	Togo
15	Eritrea	43	Zambia
16	Eswatini	44	Uganda
17	Ethiopia	45	Zimbabwe
18	Gabon
19	Ghana
20	Gambia, The
21	Guinea
22	Guinea-Bissau
23	Kenya
24	Lesotho
25	Liberia
26	Madagascar
27	Malawi
28	Mali

Data Availability Statement

This article utilizes the data, which is available at World Bank Development Indicators Database (2021). . The data is public and it can be shared.

ORCID iD

Mwoya Byaro

About the Authors

Dr. Mwoya Byaro is a Lecturer at the Institute of Rural Development Planning, in Tanzania. He has a large number of publications in reputable journals such as Health Economics Review (Springer), Poverty and Public Policy (Wiley Library), Health Policy Open (Elsevier), Environmental Science and Pollution Research (Springer), African Journal of Economics Review (AJOL), Research in Globalization (Elsevier), Scientific African (Elsevier), European Journal of Internal Medicine (Elsevier), and World Affairs (SAGE). He has over ten years working experiences in sub-Saharan Africa. His areas of interest include quantitative research and scholarly research on socioeconomic and inter-related issues aligned with the achievement of sustainable development goals. He can be contacted at mwoyabyaro2018@gmail.com.

Dr. Abel Alfred Kinyondo is at the University of Dar es Salaam (DUCE), in Tanzania and is currently a Visiting Scholar at York University in Canada. Previously, he worked as a Director of Strategic Research at REPOA and Head of Economics and Geography Department at DUCE. He has also worked for the United Nations Development Programme as NUNV Specialist. He holds a Ph.D. from Monash University (Australia); a distinction in Master of Art (Economics) Degree from the University of Botswana, and a first-class Economics Degree from the University of Namibia. Dr. Kinyondo has over ten years of research experience and has published over 70 articles, books and book chapters in internationally reputable journals such as in the Oxford Development Studies, Politics & Policy, Extractive Industries and Society, World Affairs, African Development Review, and Parliamentary Affairs. He has also led several teams of experts in formulating various socioeconomic policies, regulations, and codes of ethics in Tanzania and beyond. He can be contacted at kinyondoabel@yahoo.com.

Deusdedit A. Lemnge is a Tanzanian economist and research fellow with a wide range of knowledge in areas of institutional economics, development economics, economic statistics and Project Planning and Management. He has conducted research and project evaluation in Counter Violent Extremism (CVE), agriculture, finance, and community health in various parts of Tanzania and has over ten years of experience in working with both national and international organizations. Currently he is a full-time assistant lecturer at the Mwalimu Nyerere Memorial Academy in the field of economics. He can be contacted at lemnged@gmail.com.

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