Does Rising Resources Income, Consumer Prices, Government Outlay, and Globalisation Hinder Africa's Sustainable Development?

This study examined the long-term effect of contemporary challenges such as growing resource income, rising consumer prices, inefficient public spending, and globalisation on Africa's quest for sustainable development. A robust measure of sustainable development that integrates resource productivity is adopted. The study period spanned from 1991 to 2021, and data sourced from 24 African countries. The empirical output for this study is derived using long-term methodologies, including feasible generalised least squares, Driscoll-Kraay, and panel dynamic ordinary least squares. The estimation of the long-term model was to capture the consequential effects of contemporary issues on sustainable development. Evidence from the model revealed that increases in resources income, consumer prices, public outlay, and globalisation are deterrents to sustainable development. The individual cross-sectional regression outputs also demonstrated similar effects. Given these contemporary challenges, the study proposed relevant policy measures to aid the attainment of sustainable development.


Introduction
With a few years to the 2030 sustainable development goals (SDGs) target, there have been different attempts to assess countries' accomplishment of these goals (Allen et al., 2018;Miola and Schiltz, 2019).The annual SDG index and dashboard (SDGI&D) proposed by Sachs et al. (2016) is prominent among such.Findings from the SDGI&D indicate that all signatory countries to the SDGs are reneging on efforts to fulfil the goals by 2030 (Sachs et al., 2020).Furthermore, the speed of world advancement fails to align with the ambitions of sustainable development (SD), indicating the urge for prompt and swift interventions by countries and stakeholders at all levels, particularly after the COVID-19 pandemic and its retarding impacts on specific SDGs and targets (UN, 2020).Recently, contemporary issues are exacerbating nations' challenges in actualising SD.Many economies have had their policymakers urgently "shopping" for measures to cushion the adverse effects of these phenomena.Specifically, African countries may end up worse hit due to the comparatively low investment inflows to the continent (Aladejare, 2022a).Aside its overwhelming agrarian wealth, its extractive sector accounts for about 30% of the global minerals deposits (UNEP, 2022).Furthermore, the continent houses 40% of the worldwide gold reserves and about 90% of the world's chromium and platinum (Aladejare, 2020;UNEP, 2022).Similarly, the continent is blessed with oil and natural gas deposits, making-up about 12% and 8% of the world's total reserves, respectively (UNEP, 2022).These resources have been significantly instrumental to economic growth in the continent (Aladejare and Nyiputen, 2022).However, their exhaustiveness and the prevailing inefficient extractive process in these economies can adversely deter SD (Aladejare, 2022c).For instance, the extraction of non-renewable resources, such as crude oil, minerals, natural gas, forestry and agricultural products, faster than their regeneration rate is known to deplete the quantum of these resources and degenerate SD (Majeed et al., 2021;Adekoya et al., 2022;Adebayo et al., 2022Ganda, 2022;Aladejare, 2022b;Aladejare, 2023a).Also, rising consumer prices experienced worldwide is a current challenge most countries are grappling with.As of 2022, the world's inflation rate had increased to 8.8% from 4.7% in 2021 (IMF, 2022).The situation has exacerbated the inflation problem in most countries and is swelling the population below the poverty line.In fact, in developing and emerging countries, the inflation rate was 9.9% for 2022 (IMF, 2022).Thus, the SDGs of no poverty, zero hunger, and good health and wellbeing may be unrealisable.In 2022 alone, at unprecedented levels, many countries have had to deal with related climate change issues such as flooding, drought, water shortage, extreme heat, etc.The implications of this could further worsen consumer prices, especially food prices, due to their needs and hinder SD.For instance, empirical evidence for Africa indicates that a significant amount of the yearly food crops produced and consumed lack quality from the perspective of critical vitamins and minerals (Aladejare et al., 2022).Also, in Africa, it is estimated that rising food prices exacerbated by climate change have created the worst food crisis in the past four decades, as about 146 million persons are battling extreme hunger (British Red Cross, 2022).Hence, rising consumer prices exert more pressure on inflation and worsen the quality of life since consumers are disincentivised to maintain/increase their consumption level.
Furthermore, there is an enormous finance gap in developing economies, handicapping them from effectively investing in SD.It is estimated that while their developed counterparts expend 3.5% of revenue on debt interest, 14% is used by developing countries (UN, 2022).Thus, debt repayment and deficit financing trajectory in developing countries have been upward while crowding-out investment for infrastructural development and outlay on socio-economic factors (such as education, income, security, unemployment, and social support).Many African countries are beginning to groan under the heavy burden of debt repayment, which is gulping an enormous share of public revenue and outlay (Aladejare, 2023b).African countries find themselves over-burden by their debt obligations because a vast portion of their expenditure is devoted to inefficiencies such as misappropriation, poor quality of government services, corruption, waste of resources, and the crowding-out of private spending (IMF, 2019;Cristobal et al., 2021).Thus, as public spending keeps rising, a significant amount of it gets crowded away by growing debt repayment obligations, thereby constraining outlay on projects needed to actualise SD (Van et al., 2020;Aladejare, 2023b).
In addition, the globalisation effect on developing countries is still being argued to have environmental repercussions, and hence, devastating effect on SD.From the neoliberal perspective, globalisation has been a blessing than a curse, especially from the lens of depreciating poverty and income inequality in developing nations (Aladejare and Nyiputen, 2022;Adjei and Adu-Gyamfi, 2022).However, globalisation is also believed to have aided developing countries' accelerated ecological deterioration through the transfer of "dirty technology" from the developed world (Le and Ozturk, 2020;Nathaniel, 2021;Hussain and Zhou, 2022;Aladejare, 2023c).
Thus, the question remains, can developing countries attain SD given the contemporary threats posed by growing resource income, rising consumer prices, inefficient public spending, and globalisation?Tackling this query forms the objective of this study.Notably, this study leads in the contemporaneous empirical examination of these contemporary issues on SD, particularly for African countries.Also, while there are challenges with SD indicators in African economies due to availability of data, SD studies for the continent have mainly dwelled on its responses to factors such as environmental change, information communication technology (ICT), and tourism (Siakwah et al., 2020;Tucho and Kumsa, 2020;Auriacombe and Van der Walt, 2021).Hence, this study extends the literature by broadening the challenges and measure of SD in developing countries.
The empirical findings of this study were derived through long-term estimation methodologies; they include the feasible generalised least squares (FGLS), Driscoll-Kraay (D-K), and panel dynamic ordinary least squares (PDOLS) techniques.Data was sourced from 24 African countries from 1991-2021.A long-term model was estimated to capture the consequential effects of contemporary issues on SD.Evidence from the model revealed that increases in resources income, consumer prices, public outlay, and globalisation are deterrents to SD in the continent.Hence, there is an urgent need for countries to take more ambitious actions if SD is to be realised.
The rest of the study follows this: Section 2 contains the reviewed literature; Section 3 captures the study's data and methodology; the study findings and discussion are in Section 4, and Section 5 are the conclusions and policy implications.

Literature Review 2.2 Theoretical review
The theoretical perspective of SD was developed in three separate periods: embryonic (before 1972), moulding (1972-1987), and developing (after 1987).

The embryonic period (Before 1972)
The entire history of sustainability can be traced to the Western Zhou Dynasty (B.C. 1100-771).In the embryonic stage of SD, the main feature of the stage focuses on sustaining the natural resources and the environment.The rulers and scholars of the period believed that the natural vegetation, namely mountains, forests, and rivers, should be rationally used according to the laws of nature rather than overexploited (Mebratu, 1998).This idea of sustainability evolved across most of Europe and in ancient civilisations due to environmental degradation caused mainly by human activities.Hence, during ancient Egyptian, Mesopotamian, Greek, and Roman civilisations, different causes of environmental degradation, including farming, logging, and mining, were discussed (Shi et al., 2019).The dimension of sustainability in this era was geared towards environmental protection to ensure that natural resources are not depleted to create a scarcity of resources.

The moulding period (1972-1987)
In this theoretical formative stage of SD, the perspective of SD and its intended objectives were defined.The theory received severe consideration at the 1972 UN Conference on the human environment in Stockholm, Sweden.The summit's resolution urged all countries to improve their environmental policies while growing their economies.However, there was an opposite conclusion between the developed and the developing countries, centred on the trade-off between environmental protection and reduction in poverty.Based on the divergent view, in 1987, a report by the World Commission on Environment and Development (WCED) known as "Our Common Future" was drafted.This stage is critical in theorising SD and consists of managing the global population, food security, energy resource policies, and human habitation (Shi et al., 2019).The objective of this theorisation stage was to ensure that natural resources are not used up to jeopardise future development goals.However, developed countries believe these resources could be used and channelled into developmental programs that could overlap and meet the needs of future generations.

The developed stage (After 1987)
The current stage of SD theorisation is the developing stage, and it is characterised by four major UN resolutions on SD.The first was the UN Rio de Janeiro resolution to address ecological and developmental challenges.At this stage, the principle of building a global partnership to jointly formulate, solve and design action plans for global environmental challenges was born to realise SD (Singh, 2020;Shi et al., 2019).The second was the UN millennium summit in 2000, birthed the MDGs targeted at economic development and eliminating extreme poverty.The third aspect focused on science and technology.The primary goal was to link natural science and social science in enhancing the ability to merge into a sustainable trajectory.The fourth aspect is modifying the theory to incorporate poverty eradication, economic growth pursuit, and social and ecological development.Hence, the concept of SD transformed into a global action and gained theoretical significance.Furthermore, SD cemented its reputation as a core concept for resolving the apparent contradiction between economic development and environmental protection.It was also viewed from the lens of societal polarisation and equity value (Shi et al., 2019).It is on this premise of SD that integrates economic, environmental, and social dimensions that this study is anchored.Ulucak and Khan (2020) conducted a study for BRICS countries using the FMOLS and DOLS estimation approaches.The analysis expressed that well-managed natural resource wealth will enhance SD through ecological sustainability.However, by applying the Bayer and Hack and bootstrap causality methodologies, Ahmed et al. (2020) showed that natural resource wealth denigrates environmental sustainability in China.In a related study, Sarkodie et al. (2020) demonstrated with a battery of techniques that natural resource consumption is a conducive trigger for ecological atrophy in China.Ologunde et al. (2020) applied the pool mean group (PMG) technique.They found no association between crude oil revenue and SD proxied by the human development index (HDI) for a selected number of oil-producing African countries.Hassan et al. (2021) used the autoregressive distributed lag (ARDL) and vector error correction model (VECM) techniques and concluded that natural resources degenerate environmental sustainability in Pakistan.Another study by Xiaoman et al. (2021) adopted the continuously updated, fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) approaches.The study found natural resource abundance adversely related to MENA economies' ecological sustainability.Zhang et al. (2022) also demonstrated through the application of cross-sectional ARDL (CS-ARDL) that resource rents degenerate ecological sustainability in 48 developing countries.

Empirical Review 2.3.1 Resources income and SD nexus
Similarly, Azam et al. (2022) applied fully modified OLS (FMOLS), generalised linear model (GLM), and generalised method of moments (GMM) and expressed that natural resources degrade environmental sustainability in France.Gyamfi et al. (2022) also employed the quantile regression, AMG, DOLS, and FMOLS techniques and concluded that natural resource rents exacerbated climate change and did not promote ecological sustainability for G7 countries.Similarly, Aladejare (2022b) demonstrated with the fixed and random effect, feasible generalised least squares (FGLS) and AMG methodologies; and found that natural resource rents worsened ecological sustainability for the five wealthiest African countries.In a related study, Aladejare (2023c) applied the CS-ARDL approach and revealed that natural resource wealth promotes ecological atrophy in 29 African economies.Alola et al. (2019) demonstrated with the ARDL technique that high inflation episodes in coastline Mediterranean countries enhance ecological sustainability.The study by Koirala and Pradhan (2020) revealed through a random and fixed-effect process that the inflation rate adversely impacts SD in 12 Asian countries.Also, Ullah et al. (2020) adopted the asymmetric ARDL technique to study Pakistan.Empirically, the study confirmed that while negative inflationary shock positively impacted environmental sustainability, positive inflationary shock exacted insignificant effects.Furthermore, by applying FMOLS, CCE, and ARDL methodologies, Odugbesan et al. (2021) showed that inflation significantly impacted the sustainable green economy of Turkey.Likewise, Ahmad et al. (2021) employed the FMOLS procedure to demonstrate that inflation instability enhances ecological sustainability.However, Rakshit and Neog (2021) used the generalised autoregressive conditional heteroscedasticity (GARCH) to show that inflation instability reduces environmental sustainability in India.In a study for the USA, Tahir et al. (2022) applied the non-linear ARDL (NARDL), and ARDL approaches to show that adverse inflation shocks positively and significantly affect environmental sustainability.

Government outlay and SD nexus
In the study by Cristobal et al. (2021), an assessment of government outlay efficiency for SDGs achievement was conducted for 156 countries.Using the data envelopment analysis (DEA) procedure, the research demonstrated that most countries' public spending growth will fail to enhance SDGs realisation by 2030.Similarly, Azam et al. (2022) applied FMOLS, GLM, and GMM and expressed that government final consumption spending debases environmental sustainability in France.However, Ullah et al. (2021) demonstrated using the two-step system GMM that public health spending per capita improves SD (Adjusted net savings) in 64 Belt and Road Initiative countries.Similarly, Shao et al. (2022) applied the CS-ARDL procedure and found that government budgetary spending on the entertainment and cultural industry and socio-economic status aided ecological sustainability in OECD countries.
Conversely, Guerrero and Castañeda (2022) used simulations and descriptive analysis and showed that public spending could not guarantee SD in 140 developing and emerging countries.Similarly, Guerrero et al. (2022) also employed simulations and descriptive analysis and concluded that SDGs are not viable given Mexico's prevailing subnational budgetary spending.In contrast, a mixed result was reported by Guariso et al. (2022) in the public spending-SD relationship for Mexico.With machine learning, agent computing, and regression analysis, the study demonstrated that no link existed between both variables in the regression and machine learning results.However, the agent computing outcome revealed a positive effect of government outlay on development indicators.However, Donkor et al. (2022) employed the panel quantile regression and panel VAR techniques in submitting that government spending has a positive and substantial impact on ecological sustainability in northern and southern African countries Yameogo et al. (2021) expressed with the GMM estimator that no significant effect existed between globalisation and ecological sustainability for 20 sub-Saharan Africa (SSA) countries.A mixed impact of globalisation on environmental sustainability was found by Leal and Marques (2021).The study employed the D-K methodology in submitting that while economic globalisation (de facto) reduces ecological sustainability, economic and political globalisation (de jure) enhances it in 23 African countries.Similarly, by employing the GMM estimator, Radmehr et al. (2022) found an insignificant effect of economic and social globalisation but adverse and significant financial globalisation on ecological sustainability in G7 economies.

Globalisation and SD nexus
In contrast, the study by Sart (2022) demonstrated with the common correlated effect (CCE) estimator that globalisation positively impacted SD in 11 new EU member countries.Likewise, Gasimli et al. (2022) adopted the FMOLS technique and concluded that globalisation is a blessing for SD in the commonwealth of independent states.Similarly, Miao et al. (2022) used the moments quantile regression (MMQR) approach and concluded that financial globalisation aids environmental sustainability in newly industrialised countries.Likewise, Kihombo et al. (2022) used the CUP-FM and CUP-BC methods to show that financial globalisation promotes ecological sustainability in West Asian and Middle East countries.Also, Zhang et al. (2022) demonstrated using the MMQR technique that financial globalisation dissuades ecological sustainability in BRICS countries.In a related study for the United Kingdom, Ramzan et al. (2022) found, with the aid of a time-varying rolling window method, that financial globalisation aids environmental sustainability.
However, an adverse effect of globalisation was reported by Hussain and Zhou (2022), who applied the system GMM and D-K procedures.They submitted that globalisation deterred ecological sustainability in 92 Belt and Road Initiative countries.Similarly, Xu et al. ( 2022) affirmed the degrading effect of globalisation on environmental sustainability in the big five economies (USA, UK, China, Germany, and Japan) by adopting the FMOLS and DOLS procedures.Likewise, Adjei and Adu-Gyamfi (2022) studied the ten largest African economies using FMOLS, DOLS, and FE methodologies.The study revealed that globalisation diminishes ecological sustainability.

Literature gap
Since eradicating poverty and improving the standard of living of every citizen forms the crux of every responsible government's policy, research on SD is increasingly gaining the required attention.However, overwhelmingly, SD literature, as reviewed above, has focused more on factors that impacted the environmental dimension and less on the economic and social components.Consequently, this literature gap is being exploited and filled by this study.

Data
Data observations between 1991 and 2021 were utilised to quantitatively evaluate the impact of growing resources income, rising consumer prices, inefficient public spending, and globalisation on SD in 24 African countries.Data availability, timeliness, and completeness informed the choice of the 24 countries, and their list is contained in Table 10.
Over time, two SD measures namely the sustainable society index (SSI) and adjusted savings index (ASI) have been employed by researchers due to the perception of being the most comprehensive SD indicators (Ullah et al., 2021).However, while data for SSI and ASI are only available from 2000 and 1990, respectively, they are also lacking or incomplete for most African countries.Therefore, these studies used the GDP deflated by the EF approach as an indicator for SD.The technique is considered idle as it shows output efficiency from productive activities and natural resources since it involves the ratio of GDP (the welfare index) and EF (the natural resource usage).Aside from the EF being regarded as a good indicator of natural resource consumption, it also defines human's impact on (arable, built-up, energy, grazing, forest) land and fishing grounds.Furthermore, Rees (2000) noted that EF is closely equivalent to Ehrlich and Holdren's (1971) popular explanation of human ecological impact expressed as  = ; given that  is impact,  denotes population,  represents affluence, and  is technology.Thus, EF also incorporates the effect of population and technology on the environment.Consequently, EF can also be regarded as a socioenvironmental indicator of sustainability.
Another justification for this measure is that utilising ecological and resource factors is not often represented in the production function; hence, these resources end up abused by overexploitation without being replenished.In other words, it is evident that as countries expand economically (i.e., in GDP), the availability of resources supporting such growth also becomes increasingly constrained (i.e., in EF).Thus, this research widens the application of the GDP and EF to produce a reliable indicator of SD.
Natural resource rent denotes resource income in this study.A contemporary challenge most African countries face is increasing their resource income.It is represented in this study by total natural resource rents, which include aggregated rents derived from oil, minerals, natural gas, coal, and forest products.African countries are well-endowed in these resources.Hence, they are pivotal to the continent's development.However, poor extraction and over-exploitation of these resources can inhibit SD in the continent.
Another militating threat to SD is rising consumer prices of goods and services, exacerbating the continent's inflationary problems.Consumer prices indicate movement in prices of goods and services from the household or consumer's viewpoint.Hence, this research used changes in the consumer price index, which tracks the mean change in prices of a weighted basket of goods and services households consume over time.Rising consumer prices diminish household purchasing power and can worsen the quality of life, thereby constraining SD-furthermore, the general government final consumption expenditure proxy for government outlay.Public spending on critical services to the public is growing on the continent.Public outlays on national defence and security, the rule of law, housing, education, health care, etc., are critical for Africa's SD.Every responsible government expends resources on these public and market goods for general welfare enhancement, which can also impact SD.
Similarly, globalisation is critical to the continent's SD drive, as it can fast-track its development process through rapid industrialisation.Globalisation aids the interaction between people of various backgrounds, exchanging ideas and information.It is a broader concept beyond trade, and capital flows, including technology transfer between economies, particularly between advanced and developing nations (Gygli et al., 2019;Aladejare and Nyiputen, 2022).However, globalisation can support the accumulation of less-efficient technologies, hindering SD.Thus, globalisation can either be an enhancer or an inhibiter of SD through its effect on ecological quality.This study employed the aggregated KOF's globalisation index, which evaluates globalisation from economic, political, and social viewpoints.
A moderating indicator in the study is the GDP per capita used to proxy income growth, which extant studies have proved may impact the level of development in a country (Masud et al., 2018;Iftikhar et al., 2020;Baloch et al., 2020;Khan et al., 2021).

FGLS technique
For panel study long-run output devoid of CSD, autocorrelation, and heteroscedasticity, Beck and Katz (1995) and Reed and Ye (2011) proposed the FGLS technique.The form of the FGLS estimator is: given that Ω � symbolises an innovation covariance output; hence, the computed coefficient covariance matrix is: where The FGLS technique is known to produce efficient long-term parameter estimates, especially in studies where T>N (Usman et al., 2020;Awan et al., 2020;Khan et al., 2022, Aladejare, 2022b).

D-K Approach
Similar to the FGLS approach, the D-K technique developed by Driscoll and Kraay (1998) is known to produce robust outcomes irrespective of serial and spatial dependence, heteroscedasticity, and CSD in panel datasets.It is also adequate for handling small and large panels and balanced and unbalanced panels (Aladejare, 2023b).The form of the D-K technique is presented in Equation 5: , =  , ,  +  , ,  = 1, … , ,  = 1, … ,  .5

PDOLS method
To further ensure the robustness of the study's long-run estimates, the PDOLS technique advanced by Phillips and Moon (1999) and Kao and Chiang (1999) was adopted.Estimates derived from PDOLS are robust to traditional panel OLS due to the latter's tendency to respond to second-order asymptotic bias and serial correlation issues, which the DOLS corrects.Also, the flexibility of PDOLS enables the framework to accommodate series of a different orders of integration.DOLS is a parametric technique that employs lag and leads of differenced explanatory variables to treat estimation problems of endogeneity and serial correlation.The PDOLS equation is expressed as: where ∝  and   are constants representing individual fixed effects and time effects, respectively.ℎ  denotes a vector of regressors,   is the estimated long-term impact, and   is the parameter of a lead or lag of the first differenced regressors.

Estimated Results and Discussions 4.1 Descriptive statistic test outcome
Table 2 captures the study's descriptive statistics, and evidence from the output shows that the mean GDP per EF for the African countries is $88638.79,which exceeds the world average of $4036.5 (WDI, 2023;GFN, 2022).Deducible reasoning from this output is that African countries are not optimising their resource potentials as the rest of the world.Also, the average natural resource rent for the studied countries was 9.3%, exceeding the world's mean of 2.6% (WDI, 2023).Thus, suggesting a greater reliance on and exploitation of natural resources by African countries.The average consumer price growth rate was 6.9%, exceeding the world's mean of 3.42% (WDI, 2023).The mean public spending per GDP is 14.9%.The estimate is still lower than the world average of 16.8% of GDP for the study period (WDI, 2023), implying that despite the rise in public outlay in the continent, it still falls short of the world's average public commitment.
The mean globalisation index for the studied countries is 48.2%, against the world's 54.6% (Gygli et al., 2019).Therefore, poor growth of globalisation policies and terms can impact economic, political, and social interactions within and beyond the continent.Table 2 further shows that the average income growth for African countries is 1.6%; and marginally falls short of the world's mean of 1.7% for the study period (WDI, 2023).Therefore, indicating that there may be a convergence between the continent's income growth and other parts of the world.

Correlation matrix and cross-sectional dependency results
Table 3 presents the correlation test result with evidence of weak multi-collinearity between the explanatory variables.The variance inflation factor (VIF) was further used to validate the weak multi-collinearity between the variables, and its output captured in the lower panel of Table 3.The mean VIF value of 1.05 shows less collinearity between the explanatory variables in the study model.

Slope heterogeneity and unit root outcomes
Contained in Table 5 is the slope heterogeneity test output.Inference derived from the result upheld the rejection of the null hypothesis, which states homogenous slope coefficients.Instead, the alternative hypothesis was accepted, validating the presence of slope heterogeneity in the coefficients of the study variables.As previously noted, the validation of CSD and slope heterogeneity in the panel dataset necessitated conducting unit root tests embedded with the capabilities to treat both panel data issues.Therefore, Table 6 reveals the result for first and second-generation panel unit root tests developed for handling CSD and heterogeneity challenges.Table 6 shows that all other study variables exhibited integration or stationary at the first difference with exceptions to the consumer prices and income growth that are level series.

Westerlund panel cointegration output
After determining the variables' stationarity condition, their long-term association was probed using the Westerlund cointegration technique.The approach, as prior noted, is efficient in handling CSD and heterogeneity in the panel dataset, and its result displayed in Table 7.The test output invalidated the null hypothesis of no cointegration.While instead, the alternative view upheld that there exists long-term nexus between the study covariates.

Long-term estimated results
Presented in Table 8 are the long-term estimates for the FGLS, D-K, and PDOLS.All the variables exhibited significant long-term effects on the SD measure.Also, the results of the regressors on the SD indicator were the same in the three models, indicating the robustness of the study findings.Resource rents, consumer prices, government spending, and globalisation had significant negative long-term coefficients.Income was the only variable with a significant positive long-term coefficient.Presented in Table 9 are the individual PDOLS estimates for the studied countries.Similar to the output in Table 8, the regressors had the same direction of effect on SD in most countries.

Discussion of findings
As evident from the estimated output, resource rents showed an adverse long-term effect on SD, demonstrating that higher income from natural resources does not promote the actualisation of SD.This finding contradicts Ulucak and Khan (2020), who reported a positive association in BRICS countries, and Ologunde et al. (2020), who found no link for some African countries.When natural resources are excessively demanded because of the wealth they create, they also get increasingly exhausted.Thus, it becomes increasingly difficult to sustain the economic prosperity they generate in the long-term.Economic growth may become stunted and even begin to decelerate due to the increasingly depleted natural wealth, and consequently, SD is adversely affected.Since natural resources constitute an integral aspect of every developing nation's economic output growth (Aladejare, 2018;Aladejare et al., 2020), the diminishing tendency of natural resources suggests that continuous reliance on resource productivity for growth cannot ensure SD.
Likewise, rising consumer prices negatively and significantly affect SD; thus, aligning with prior findings by Koirala and Pradhan (2020) for 12 Asian countries.This result is plausible given that as the cost of consumer goods and services continues trending upward, individuals may begin to shed off their eco-consciousness in attempts to seek alternative survival measures.Also, rising prices of goods and services will further exacerbate inflationary challenges and lower the purchasing power of individuals.Thus, quality of life will depreciate and, by extension, SD.Poor purchasing power limits access to quality healthcare, nutrition and education, and humane shelters.Therefore, it is reasonable to say that rising poverty levels and crime rates, ecological degeneration, unemployment, etc., are some of the implications of rising prices in developing countries which adversely and significantly determine SD attainment.
Growth in government outlay was found to hinder significantly SD.This inference suggests that as public spending on public and market goods grows, however, instead of enhancing, they restrict the actualisation of SD in African countries.This finding aligns with studies such as Cristobal et al. 2021;Guerrero and Castaneda, 2022;Guerrero et al., 2022.There are several factors responsible for this outcome.First, as accustomed with every government, African governments invest in human resources training through scholarships and grants within and outside the continent.Developing countries, for years, have been argued cannot grow without having a skilled labour force.However, a common trend with these labour forces, after completing their training is that many find their way to other countries, especially the developed world.For instance, as of 2021, of every 1000 national health staff in the United Kingdom (UK), 25 are Africans (Baker, 2021), and about 5% of active physicians in the United States of America (USA) are of African origin (AAMC, 2022).
In addition, when there is prevalent unemployment in a country, most of the skilled labours would find their way into other industries where they can get jobs instead of in their trained sector.Hence, the invested sum in their training will have an adverse effect on their country's development.For instance, the chronic shortfall of human resources in Africa's health sector constrains access to and availability of health services.Therefore, it is challenging for African countries to achieve SD with such a phenomenon.Second, misappropriation and or embezzlement of budgeted funds for the provision of public and market goods will also leave an inverse effect on SD.Both vices undermine growth and development and hinder measures to achieve SD in any country.They also play a critical role in weakening public institutions by encouraging poor accountability and effectiveness at all government levels.
Furthermore, globalisation exhibited an inverse long-term effect on SD.It demonstrates that a substantial volume of the continent's international trade and investment flows have been unsustainable.This contradicts the blessing effects of globalisation on SD in studies such as Sart (2022) for 11 new EU member states and Gasimli et al. (2022) for the commonwealth of independent states.Thus, implies that most of the technologies and knowledge shipped from developed to developing countries are often less efficient and obsolete; therefore, they fail to promote ecological sustainability (Aladejare and Nyiputen, 2022).In addition, globalisation may not be supporting the speedy advancement of financial markets in many African economies.Intuitively, adequate long-term instruments to fund substantial mega projects that are economically, socially, and environmentally sustainable are in short supply.Hence, most domestic investors have constrained production alternatives, which, in recent times, have been found to be ecologically degenerating.
On the other hand, a rise in income is a significant enhancer of SD.This is expected as SD cannot be achieved if the income level does not improve.Empirically, the estimated mean poverty rate for SSA is 41%, and 27 of the world's 28 poorest economies are in SSA, with a poverty rate of 30% (Atangana, 2022).Furthermore, a 5% decline in Africa's income growth (i.e., GDP per capita) will create 50 million Africans surviving below the international poverty threshold (World Bank, 2020).These statistics point to the fact that income growth is imperative for SD in developing countries.Thus, higher income is expected to translate to a better quality of life through affordable access to primary health care, nutrition, education, sanitation, housing, etc., and SD.
Similar to the aggregated long-term effects, deductions from the cross-sectional result indicated that resource rents adversely impacted SD in most studied countries.The product was positive for Algeria, Botswana, Burkina Faso, Ghana, Mali and Mauritius.Similarly, higher consumer prices inversely impacted SD in most studied countries.However, the effect was positive only in Algeria, Cabo Verde, Congo, Mauritius, Namibia, Rwanda and Tunisia.Government spending and SD are suggested to be positively related in Botswana, Congo, Egypt, Gambia, Guinea, Madagascar, Mali, Mauritius, Niger, Nigeria, Senegal, Togo, and Tunisia.Globalisation negatively affected SD for most of the studied countries; however, Burkina Faso, Cameroon, Cote d'Ivoire, Mozambique, Niger, Rwanda, and Tunisia showed positive outcomes.Likewise, SD followed the same direction as income growth for most countries except Cameroon, Kenya, Madagascar, Mali, Namibia, Niger, and Senegal.

Concluding Remarks
Africa's inability to achieve the SDGs is excepted to have far-reaching consequences on the rest of the world since some of the goals carry a transboundary feature such as climate change, resource management, and globalisation.Thus, this study examined the long-term effect of contemporary challenges such as growing resource income, rising consumer prices, inefficient public spending, and globalisation on Africa's quest for SD.The study period spanned from 1991 to 2021, and data sourced from 24 African countries.The empirical output for this study was derived using long-term methodologies, including FGLS, D-K, and PDOLS.The estimation of the models was to capture the consequential effects of contemporary issues on SD.Empirically, their outcome revealed that increases in resources income, consumer prices, public outlay, and globalisation are deterrents to SD.However, rising income (the control variable) enhanced SD.Also, similar effects were demonstrated in the individual crosssectional regression outputs.Hence, the study proposed the following policy responses.
Given the increasing threat posed by non-renewable energy sources worldwide, policymakers and governments must consider it imperative to evolve sustainable strategies to decelerate the significance of highly ecologically-adverse non-renewable natural resources.Although this may impact energy sources and fiscal planning in the short term, the long-term dividends are excepted to be far more overwhelming in ensuring sustainability.Thus, research and investment in renewables such as hydropower, hydrogen, solar, wind, geothermal, tidal, and wind should be scaled-up.Also, governments, especially those in developing countries, will need to stop foot-dragging as the world accelerates its transition from fossil-reliant to renewable energy sources, especially for transportation and manufacturing energy demands.Renewable energy sources are increasingly becoming eco-friendlier and more efficient than traditional energy.However, a mitigating measure for the ecologically-degrading impact of natural wealth exploration and exploitation will be adopting an efficient, conservative management approach.Africa and other developing economies should also give utmost preference to certified innovative technologies for efficient resource exploration and exploitation.
In tackling the hindering effect of rising consumer prices on SD, restoration of macroeconomic stability in the economy is critical.Failure to do such will worsen and compromise the continent's poverty reduction and alleviation efforts.Hence, fiscal and monetary policy formulation and implementation must complement each other to arrest rising prices and the attendant effect of falling purchasing power.Also, a restructuring of government food and agricultural expenditure is required to ensure future resilience.Governments should move away from subsidising agricultural consumption through food imports.Instead, investment in productive agrarian ventures such as nutrition-sensitive social protection programs, research and development, and irrigation farming should be prioritised for higher returns.A restructured agricultural sector tailored along this path will provide climate-proof food cultivation and production; provide agricultural and human capital development.The productivity of the sector will be further enhanced, and resilience to climate change and food security can also be guaranteed.
It is not enough for public spending on developmental projects to increase; complementarily, there is a need to improve budgetary accountability for the earmarked projects.This approach will check the deployment of revenue and external borrowings for frivolous activities divergent from development goals.Thus, ensuring that such funds are expended exclusively on longterm developmental projects.Also, complementary micro-policies are critically required to overcome long-term structural bottlenecks associated with budgetary implementation.The implication is that for SD to be attained, more spending will be necessary to provide security, and quality education, improve health care, and close the infrastructure gap.Also, strengthening appropriate institutions can help enhance the rule of law, reduce corruption, and promote environmental protection in any country.
Furthermore, the ills of globalisation on SD can be controlled by promoting the shipping of green technologies to aid green GDP.Thus, business strategies that align with such sustainability measures should be prioritised to ease the path to SD.In addition, a national sustainability policy framework should be developed to discourage unsustainable FDI inflows.For this purpose, relevant domestic monitoring and implementing institutions can be established where they do not exist.They should have the government and stakeholders' full commitment to formulating and administering suitable punitive measures to aid compliance with SD practices in the economy.Public-private partnerships can be forged, and tax relieves offered to eco-friendly investments as incentives.It is expected that the result of such policies will immensely illuminate the chances of attaining SD in Africa.In accelerating foreign trade, countries should ensure only the inflow of trade in goods and services that comply with SD requirements in multi and bilateral trade deals.All these action plans can mitigate the longterm adverse effects of globalisation on SD.
Since income growth is imperative for SD, it must be anchored on developing an investorreceptive economy.Thus, policymakers and governments must be sensitive to their investment climate by creating conducive grounds for businesses to thrive.Hence, advancing infrastructure development is critical for business growth and development.Also, governments must display a commitment to bringing to the minimum environmentally unsustainable productive ventures pervasive in most African and developing countries.These include trading in charcoal and firewood energy, bush burning for farming and hunting, unsustainable fishing methods, crude fabrication and recycling, poor mining methods, etc.These activities heighten greenhouse gas pollution and deforestation and pollute and degrade water bodies and soil composition.Instead, the speedy modernisation of these economies through small, medium and large enterprises should be pursued for SD.
However, the incompleteness and non-availability of SSI and ASI data for African countries are limitations of this study.Hence, it would be interesting to see how future SD study using these indicators respond to the contemporary challenges identified in this study for African countries.

Table 1 :
Variable description This study's objective entails determining the long-term effect of contemporary challenges such as growing resource income, rising consumer prices, inefficient public spending, and globalisation on Africa's quest for SD.Thus, the study's general long-term equation is expressed as:  =  0 +  1  , +  2  , +  3  , +  4  , +  5  , +  , .1

Table 4
reveals the output of the four CSD tests conducted.Evidence shows that the null hypothesis of cross-sectional independence is invalidated.Hence, the submission shows significant CSD exists in African countries, given the study variables.

Table 5 :
Slope heterogeneity Test

Table 6 :
Unit root test output Note: a and b represent stationarity at the level and first difference, respectively, while ** and *** indicate statistical significance at 5% and 1%, respectively.Source: Authors' Computation.