Pragmatic investigation of the effect of green and low-carbon economy on food safety in Africa.

Pragmatic investigation of the effect of green and low-carbon economy on food safety in Africa. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pragmatic investigation of the effect of green and low-carbon economy on food safety in Africa. Igharo Amechi Endorance, Ibe Anthony Ekene, Abdulaziz Seleh Al-Faryan, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5104908/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2024 Read the published version in Discover Sustainability → Version 1 posted 12 You are reading this latest preprint version Abstract This research investigates how food safety in Africa is influenced by a green economy. The study used information from the Food and Agricultural Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and World Development Indicators to accomplish the set goal. The data covered the period 2005–2020 for 37 African countries. The generalized method of moments (GMM) was used in the study to address the endogeneity issue. The results revealed that when the economy is green, food safety increases. This proves that a one-point increase in the green economy may lead to an increase in food safety in Africa of 0.24%. - The results show that; as an economy becomes greener, the state of food insecurity decreases. In conclusion, the study capitulates that all relevant participants must focus on strategies and policies to reach green economic growth. This is key because such policies lead to environmental sustainability (reduction in biodiversity loss) causing agriculture to flourish and thereby enlightening the state of food safety. Biodiversity food safety green economy sustainable development 1. Introduction A pragmatic investigation into the effect of a green and low-carbon economy on food safety in Africa necessitates a detailed understanding of the region's unique challenges and opportunities. A shift toward sustainable development models; characterized by reduced carbon emissions and eco-friendly practices has been advocated globally as a means to mitigate climate change and promote economic stability [ 1 ]. In Africa, where agriculture is a cornerstone of many economies and a primary source of livelihood, this transition has significant implications for food safety [ 2 ]. Implementing green and low-carbon strategies can potentially enhance agricultural productivity by promoting practices that improve soil health, water conservation, and biodiversity [ 3 ]. However, there are concerns about the feasibility and immediate impacts of such transitions on food availability and affordability. This investigation seeks to explore the balance between environmental sustainability and food safety; by examining how policy frameworks, technological innovations, and local community adaptations can harmonize these objectives [ 4 ]. According to UN estimates from 2012, there will be approximately 9 billion people on the planet by the year 2050. This finding suggested that a significant number of these individuals – more billion–will reside in third-world nations, mostly in Africa. The need to boost agricultural production through the green economy to achieve the requisite degree of food safety is becoming increasingly crucial due to the geometric rise in population. Although, on the whole, food production has improved over the past 20 years, current social and economic shocks such as the COVID-19 pandemic have hindered this progress, and one out of five people in Africa is believed to be experiencing food insecurity [ 5 ]; [ 4 ]; [ 6 ]. Policies and strategies to ensure environmental sustainability are needed to increase agricultural productive capacity for feeding the growing population [ 6 ]. Research indicates that a significant number of agricultural landscapes, particularly those in the South, are globally weaker due to the combined challenges of reducing biodiversity loss and mitigating the occurrence of food insecurity [ 3 ]; [ 6 ]; [ 7 ]. Future sustainability concerns could be threatened by the increasing trend in agricultural production if biodiversity is lost [ 15 ]. Notably, 30% Worldwide greenhouse gas emissions are attributable to the agricultural sector, contributing to climate change worldwide. One other reference for growing atmospheric greenhouse gas emissions is global agriculture [ 8 ]. Methane (CH 4 ) and nitrous oxide (N 2 O) emissions from agriculture are produced by humans on average and reached 55% of the total emissions ([ 9 ]. Similarly, Foley et al.'s 2005 study proposed that the worldwide intensification of agricultural practices is responsible for biodiversity loss. Furthermore, almost 60% of Africa's carbon emissions are attributable to unfavorable agricultural practices, including deforestation [ 10 ]. Salinization, deforestation, soil erosion and desertification are a few examples of land area depletion that threatens the long-term supply of food and achievement of food safety, undermining the expansion of agricultural output in Africa in the future [ 11 ]. In line with FAO [ 12 ], food safety may be defined as a condition “ when every member of the household, at all times, has physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and a healthy living ”. In actuality, "the primary sector, such as agriculture, needs to gain the required attention in Africa to enhance food safety status for all household members" [ 13 ]. As a result, green agriculture could sustainably assist in this area. It has been acknowledged that food prices are extremely unstable and that agriculture must be vigorously pursued to fulfill its roles as a food source, an income source for many people, and an engine for growth [ 14 ]; [ 7 ]. A green economy that is robust to climate change and prioritizes agricultural intensification must be implemented by all nations [ 15 ]; [ 16 ]. This approach will assist in achieving sustainable agriculture over the long run, which is necessary to achieve food safety. Environmental deterioration and unsustainable economic development are purviewing the green economy. This is why the United Nations Environment Programme-UNEP regards a green economy as “ one that results in improved human well-being and social equity, while significantly reducing environmental risks and ecological scarcities ” [ 17 ]. [ 18 ] asserts that a low-carbon environment with minimal energy use, efficiency, pollution, and emissions is the cornerstone of a green economy, which results in a human economy that is ecologically responsible. This justifies the inclusion of green growth strategies as carbon emissions reduction procedures [ 19 ]. Actions must be taken to actualize a greener economy as the global population continues to rise and natural resource availability declines [ 20 ]. An economy that acknowledges sustainable development and economic progress through resource efficiency is known as the "green economy". Therefore, the goal of a green economy is to achieve economic growth that is earned in concert with social welfare and environmental conservation. Cutting back on the usage of nonrenewable resources and fossil fuels is also promoted. According to [ 5 ], "green growth" refers to the process of encouraging economic expansion while guaranteeing the uninterrupted provision of natural resources and environmental services that are important for human well-being. In practice, the green economic vision could help address some of the most challenging problems the world is currently facing, such as resource waste, hunger, and climate change [ 6 ]. A number of African countries, including Senegal, Ethiopia, Kenya, Rwanda, Mozambique, and Tunisia, have set out to achieve a green economy [ 21 ]. However, these countries are in different stages of the process. Thus, research on the green economy and its impact in Africa is necessary, particularly in relation to food safety. According to previous studies [ 1 ]; [ 22 ]; [ 23 ], a green economy can bridge resource gaps and contribute to the necessary improvement in human welfare without having an adverse effect on the environment or future generations. Therefore, growth processes that are resource efficient, cleaner, and more robust might be compared to those of a green economy [ 24 ]; [ 4 ]. It is claimed that the green economy will lead to a "win–win" outcome in the pursuit of development. [ 25 ] aimed to address low-carbon and sustainable development with outcomes such as job opportunities and poverty reduction. This is significant because, if countries are successful in transitioning to a green economy, at least 18 million net job opportunities are expected to be produced globally by 2030. Scholars have countered that a green economy need not always be sustainable or conducive to growth [ 26 ]. Additional empirical research has connected the tenets of the green economy to other important economic sectors. For example, [ 27 ] examined how a green economy's capabilities, concepts, instruments and approaches might assist in facilitating the shift to sustainability. The consequences of the green economy for ecological services, low-carbon development, and significant sectoral indicators were compiled by [ 28 ]. Furthermore,[ 29 ] examined how the green economy and the casual economy interact and concluded that including the casual economy in conversations about the green economy could lead to better planned policies and strategies. The potential of women in South Africa's environmental and green economic development sectors was examined by [ 30 ]. Studies that have already been conducted, as mentioned above, have rarely overlooked the connection between agricultural productivity and the green economy in accomplishing food safety or the viability of green agriculture in doing so. For example, studies on the relationship between the green economy and employment [ 25 ] or between the green economy and poverty reduction [ 31 ] have not examined food safety. The current study looks at food safety and the green economy (green agriculture) to accomplish this goal. The research contends that the interactions between agricultural practices, biodiversity, and food safety are detailed. Thus, it is necessary to model how a green economy might affect food safety. This is one of the very few studies that looks at how institutions and policies for environmental sustainability, as a stand-in for a green economy, affect food safety. The research argues that by giving agriculture a major place in the green economy and successfully managing this transition, the world community may get closer to attaining the goals of eradicating starvation and guaranteeing food and nutritional security for everyone. By addressing both the potential benefits and challenges, this study aims to contribute to the discourse on sustainable development and its critical role in ensuring food safety in Africa. The remainder of the study is structured as follows. The study's conceptualization is discussed in the next section, along with some analysis from pertinent literature. While sections four and five provide the results and a summary, section three explores the study's data and methodology. 2. Insights from the empirical literature This section provides a brief review of the literature. The literature review produced ambiguous and wide-ranging results. One group of scholars examined the relationships between agricultural production and environmental and climatic concerns and food safety. Notably, researchers such as [ 32 ], [ 33 ], and [ 34 ] have concluded that decreasing agricultural and food production due to unfavorable conditions of climate and environmental issues such as floods and droughts are the key causes of food insecurity in most countries. There is a common misconception that population expansion and declining human health are the main reasons for food crises in numerous parts of the world. Examples include the assertions made by [ 35 ], [ 36 ], [ 37 ], [ 38 ] and others that initiatives to boost food output by intensifying production have been spurred by population expansion. Consequently,research on food safety has been documented in scholarly works. On the other hand, the idea that green agriculture improves food safety is mostly unsupported in the data. Some agricultural production research in the context of the Green Revolution is qualitative, and reports on green economy-related subjects are sometimes included. [ 9 ] examined the relationships between biodiversity protection and food safety in southeast Ethiopia stakeholder organizations participated in a participatory scenario planning exercise that was used for analysis in the study. This study highlights the prospect of using agro ecological development pathways to foster synergies between biodiversity preservation and food safety. Additionally, the analysis made clear that the environment will undoubtedly suffer from courses that favor agricultural productivity, and social inequality will almost certainly follow. To compete in a green economy, agriculture needs to be successful, support economic growth, and uphold social, cultural, and economic institutions; [ 39 ]. A study by [ 40 ] suggested that there is a chance to apply green growth ideas to ensure food safety in Africa. Consequently, there is a relationship between agriculture and the green economy that affects food safety. In a concept statement written for the Rio + 20 summit, the Agricultural Organization (FAO) emphasized the role that agriculture plays in the pursuit of a green economy, saying that, without agriculture, there will be no green economy [ 41 ]. [ 42 ] investigated how Pakistan's food safety (1975–2017) was affected by the Green Revolution using annual time-series data. The study used F-bounds +++ tests and Johansen integration tests as analytical techniques that the Green Revolution has favorably and meaningfully enhanced food safety in Pakistan. The research postulated that the use of high-quality seeds and fertilizers, fuel consumption, and a rise in the area dedicated to cereal crop planting are important facets of the green revolution that have enhanced Pakistan's food safety. Additionally, [ 43 ] summarized that the use of renewable energy spurs economic development, which may result in the attainment of food safety. This is evident in a country's ability to finance public services, investments in health and education, and the ability to buy food in international markets, all of which are boosted by economic performance. [ 44 ] investigated how the green economy impacts food safety using data from thirty-five sub-Saharan African countries between 2001 and 2015. The author's research indicates that there are inconclusive data on the relationship between green economy indices and food safety, specifically with regard to food availability and the percentage of undernourished people. Indeed, the results indicated that in Sub-Saharan African countries, food safety is enhanced by renewable energy, while it is undermined by biofuels. The author claims that there is no relationship between CO 2 emissions and food safety. 3. Research methodology 3.1 Sources of Data and Variable Description The study employed data obtained from the FAO, WDI, and CPIA. The study included 37 African nations and spanned the years 2005 to 2018. The nations are used since they are members of the International Development Association (IDA). Appendix A lists the nations that participated in the analysis. Agricultural credit (measured by credit to agriculture, in US dollars), arable land (hectare), ICT (percentage of the population with internet access), food safety (measured by food production-gross per capita), the green economy (measured by the degree to which countries' policies and institutions support environmental sustainability), social protection (measured by overall social protection coverage), and agricultural employment (percentage of total employment) are the variables involved in the study. Table 1 lists the variables used in the investigation and their measurements. Table 1 Variables, Measurements and Sources Symbol Variable Name Measurement Source Expectations FudSec Food safety Gross per capita food production (number) FAO Not Applicable GE Green Economy Policy and institutions for environmental sustainability (scale of 1 = low to 6 = high). CPIA Positive SOP Social Protection policies for social protection coverage (scale: 1 = low to 6 = high) CPIA Positive AL Arable Land Hectare WDI Positive AC Agricultural Credit US $ , 2015 prices FAO Positive ICT Information and Communication Technology Individuals using the internet (% of the total population) WDI Positive AE Agricultural employment Employment in agriculture (% of total employment) WDI Positive Note : CPIA means country policy and institutional assessment =, FAO means Food and Agricultural organization and WDI means World Development Indicators. Source : The Authors’ Compilations. 3.2 Method of Analysis The impact of a green economy on food safety in Africa is empirically explored in this study using environmental management policies as a proxy. The research depends on the publications of [ 30 ] and [ 9 ]. Eq. ( 1 ) illustrates the baseline model that the study uses: $$\:FudSec=f(GE,\:SOP,AC,\:AL,\:ICT,\:AE)$$ 1 Equation ( 1 ) expresses the outcome variable (food production per capita an indicator of food safety) as a function of the green economy ( \(\:GE)\) , social protection \(\:\:\left(SOP\right)\) , agricultural credit \(\:\left(AC\right),\:\) arable land ( \(\:AL)\) , information and communication technology \(\:\left(ICT\right)\) , and agricultural employment ( \(\:AE).\) The explicit form of the model is specified in a double-log, as shown in Eq. ( 2 ): $$\:{lnFudSec}_{it}=\:{b}_{0}+{b}_{1}{lnGE}_{it}+{b}_{2}{lnSOP}_{it}+{b}_{3}{lnAC}_{it}+{b}_{4}{lnAL}_{it}+{b}_{5}{lnICT}_{it}+{b}_{6}{lnAE}_{it}+{e}_{it}$$ 2 where \(\:{b}_{0}\) is the intercept; \(\:{b}_{1}\) , \(\:{b}_{2}\) , \(\:{b}_{3}\) , \(\:{b}_{4}\) , \(\:{b}_{5}\) and \(\:{b}_{6}\) are the parameters to be estimated; and \(\:{e}_{it}\) is the error term. 3.3 Estimation Techniques Despite the fact that the current research uses many methodologies due to endogeneity, conclusions are derived from the generalized method of moments (GMM) results. Based on the empirical research conducted by [ 9 ], [ 30 ] and [ 4 ], it is possible to specify the baseline model (pooled OLS) and fixed effect using the formula in Eq. ( 3 ). $$\:{lFudSec}_{it}=\:\rho\:+{b}_{1}l{GE}_{it}+\phi\:lX{\prime\:}it\:+{e}_{it}$$ 3 where \(\:\:FudSec\) is food safety, is the constant term, \(\:\:GE\) captures the green economy and X ′ it is a vector of control variables. The control variables are agricultural credit, social protection, arable land, information and communication technology, and agricultural employment, while \(\:e\) is the error term. Eq. ( 3 ) is estimated using pooled OLS and fixed effect regression. We conducted the Hausman test to help decide on the use of the fixed effect. The individually specific effects are not considered in the estimations when dealing with a pooled OLS. This may cause orthogonality problems. -- However, this orthogonality problem is often solved with random effects estimation because the random effect method executes an individually specified intercept in the model, which may lead to endogeneity, and the Hausman test verifies this. The study employed the Hausman specification to choose between fixed and random effects. Preference is given to the fixed effect model over the random effect model by the Hausman specification. The benchmark regression's Hausman test result, x 2 = 11.35 (p = 0.0781), indicates that the premise that a model with random effects is better is not supported. The argument behind choosing the GMM is that endogeneity problems can arise with both pooled OLS and fixed effect analysis. When endogeneity issues arise, the GMM generates the most reliable estimates [ 45 ]; [ 46 ]. Eq. ( 4 ) specifies the GMM model in accordance with the study's goals and references to [ 9 ], [ 47 ], and [ 48 ]. $$\:{lFudSec}_{it}=\:\rho\:+\vartheta\:{lFudSec}_{it-1}\:+{b}_{1}l{GE}_{it}+\:\phi\:lX{\prime\:}it\:+{e}_{it}$$ 4 where \(\:{FudSec}_{it}\) is the food safety status of country \(\:i\:(i\:=\:1,\:2\dots\:,\:N)\) at time \(\:t\:(t\:=\:2,\:3,\dots\:,\:T),\rho\:\) is a constant term, \(\:{FudSec}_{it-1}\) is the lagged dependent variable (food safety) with coefficient \(\:\:\vartheta\:\) , \(\:{GE}_{it}\) is the green economy with coefficient \(\:{b}_{1},\:\) and \(\:X{\prime\:}it\) is a covariate of the independent variables with the coefficient \(\:\phi\:\) ( \(\:\phi\:=1,\:2,\:3\dots\:N)\) . The current study applied the two-step system GMM to help handle endogeneity problems. In situations where endogeneity is a concern, the two-stage least square (2SLS) approach may be more appropriate. However, in the face of heteroscedasticity, the 2SLS model likewise offers flimsy estimates [ 49 ]. Therefore, when the outcome variable is not highly exogenous, the generalized method of moment (GMM) approach generates good estimators and is more efficient [ 50 ]. Because of the link that exists between the mean of the lagged dependent variable and the idiosyncratic error factor, the results of the elementary pooled OLS and fixed effect methods may not be consistent in these situations [9; 45; 51]. Several solutions to this problem have been provided by [ 45 ], [ 51 ]), and [ 52 ], who demonstrate how system GMM estimators can lessen the bias associated with fixed effects in short panels and address the endogeneity problem in dynamic panel data. According to [ 4 ], when assessing the authenticity of the tools used in a GMM, the AR (2) tests of Hansen and Arellano‒Bond for the calculation of autocorrelation may be utilized. The two-step method GMM estimators have been found to be effective in previous work [ 47 ]. 4. Results and Discussion 4.1 Correlation analysis and summary statistics Table 2 displays the relationship between the outcome and the control variables, and Table 3 displays the summary statistics of the variables. Table 2 's correlation analysis results indicate that there is no evidence of significant multicollinearity among the variables. This is because less than 80% of the variables in the table are related to one another (0.8). Table 2 Correlation Matrix Variables Food safety Credit Arable land Social protection Green economy Agric employment Information Technology Food safety 1.0000 Credit 0.0264 1.0000 Arable land -0.1129 0.7448 1.0000 Social protection 0.2202 0.0099 -0.0363 1.0000 Green economy 0.2010 -0.0513 -0.0488 0.7713 1.0000 Agric employment -0.2375 -0.1065 0.0423 0.0276 -0.0578 1.0000 Information technology 0.4927 0.3106 0.0584 0.2160 0.2097 -0.4817 1.0000 Source : The authors Table 3 provides the descriptive statistics for the variables that were chosen and used in the study. According to the descriptive and summary statistics of the variable, Africa produces almost $ 91 million in worth of food per person. Conversely, the average employment rate in agriculture stands at 57%. This finding provides evidence that the agricultural industry in Africa accounts for approximately 57% of all jobs across the continent. In a similar vein,the data indicate that, on average, fewer than 9% of Africa's total population has access to mobile internet services. This finding indicates that Africa has a low percentage of internet users. In a similar vein, Africa has 6484710 hectares of arable land, despite the continent receiving an average of $ 259.43 million in credit for agriculture. Social protection and the green economy are ranked from 1 (lowest) to 6 (best). A score between 1 and 2, which is considered the lowest, indicates that a person has very little social protection and poor environmental management. A country with moderate social protection coverage and moderate environmental protection regulations is said to have a moderate score, which falls between three and four.Finally, a score between five and six, which denotes the highest range, indicates that social protection and environmental management and sustainability policies are effective. The social security benefits (such as monetary and in-kind help for farmers, elderly individuals, and the most vulnerable), social insurance (such as health insurance), and labor market intervention (such as unemployment compensation) are the social protection benefits that are examined here. According to previous studies, the degree to which institutions and policies address environmental sustainability, a key component of the green economy, should be gauged by how well they support the preservation and sustainable use of natural resources [ 51 ]. According to the summary statistics in Table 3 , the examined nations are performing at social protection and green economy scales of 3.36 and 3.27, respectively. This indicates that the social protection coverage and environmental sustainability policies of such nations are regarded as modest. Thus, for the analyzed countries to attain food safety in the future, efforts must be made to expand the scope of social protection and transition to an environmentally friendly economy. Table 3 Summary Statistics of the Variables Variable Mean Standard Deviation Minimum Maximum Food safety 90.77138 16.99253 46.22000 138.7800 Credit 259.4299 433.9795 0.029302 2559.826 Arable land 6484710 7598382 48000.00 37000000 Social protection 3.359486 4.300000 2.200000 0.437550 Green economy 3.274920 0.457004 2.000000 4.000000 Employment in agriculture 57.03453 17.24880 15.27000 89.11000 Information and communication technology 8.783574 9.068427 0.219660 43.83992 Source : Authors’ Computation 4.1 Results of the two-step system GMM, fixed effect and pooled OLS analyses. The findings from the two-step system GMM, fixed effects, and pooled OLS analyses are summarized in Table 4 . Initially, pooled OLS and fixed effects methods were used for the baseline analysis, with the primary analysis relying on the two-step system GMM approach to address endogeneity concerns [9; 45; 51]. While pooled OLS and fixed effects methods have certain limitations, the two-step system GMM provides more robust results, which form the basis for policy recommendations. The system GMM method assumes strong autocorrelation in both the first-order (AR(1)) and second-order (AR(2)) autoregressive processes. In this study, the Sargan test indicates that the instruments are valid, as they are uncorrelated with the residuals. The analysis reveals that the green economy significantly contributes to improving food safety. Specifically, the green economy coefficient of 0.2422 suggests that a 1% improvement in organizational effectiveness and environmental sustainability efforts would lead to a 0.24% increase in food safety. Additionally, expanding social security coverage is found to have an even greater impact on food safety. A 1% increase in social protection coverage would result in a 0.46% improvement in food safety, demonstrating that social protection initiatives have a stronger effect on food safety than green economy efforts. Moreover, a 1% increase in arable land is associated with a 0.21% rise in food safety, highlighting its positive and significant impact on food security in Africa. Other key variables also positively influence food safety. An increase in access to information technology, agricultural financing, and employment in the agricultural sector is expected to enhance food safety by 0.17%, 0.96%, and 0.125%, respectively. Together, these findings emphasize the importance of technological access, agricultural funding, and employment in improving food safety outcomes. Table 4 Outcomes of the Two-step GMM, Fixed Effect, and Pooled OLS Dependent Variable: Food safety Variable Pooled OLS Fixed Effect Two-Step System GMM FS(-1) 0.3726* (0.000) Arable land -0.009 0.6321* 0.0274** (0.61) (0.000) (0.017) Agricultural employment 0.0610 -0.107 0.1677* (0.184) (0.245) (0.008) Information technology 0.1407* 0.0856* 0.0958* (0.000) (0.000) (0.000) Credit to agriculture -0.0084 0.0277** 0.0125** (0.383) (0.028) (0.029) Social protection 0.0348 -0.0372 0.4601* (0.428) (0.495) (0.001) Green economy -0.0195 -0.0045 0.2422* (0.558) (0.894) (0.000) Constant 4.1043* -4.6542* 1.605* (0.000) (0.000) (0.000) R-squared 0.54 0.64 Groups/Observation 26/311 26/311 26/311 Wald chi2(6) 336.55* (0.000) F-stat 82.73* (0.000) AR (1) -2.78* (-0.005) AR (2) 1.320 (-0.185) Note : The p values are in parentheses (-- ), * and **indicate that the coefficients are significant at the 1% and 5% levels,, respectively. Source : The authors 4.2 Discussion of the Results Most of the time, poor farming methods lead to environmental damage. This occurs as a result of detrimental effects on the nutrients and physical characteristics of the soil. Technology, economic activity, and social domains all contribute significantly to the greening of the economy. For instance, deforestation contributes significantly to environmental degradation, which hinders the endeavor to establish a green economy [ 53 ] and demands innovation from producers [ 54 ]. The results of the two-step GMM show that the green economy, as represented by institutions and policies for environmental management, may be a statistically significant and favorable explanation for the level of food safety in Africa. This suggests that there is a 0.24% increase in food safety that may be achieved by efficient environmental management. This result confirms that inadequate environmental management causes a number of environmental problems, including drought, landslides, floods, and hailstorms [ 4 ]. Erosions and other inappropriate farming practices, such as overgrazing and burning, which affect a significant amount of forestland, the loss of nutrients from the soil, and land salinization, wash away the protective layer of soil [ 55 ]. Furthermore, actions that result in a reduction in the amount of vegetation cover have an undesirable impact on the sustainability of ecological systems and the green economy. Therefore, measures are required to steer this trajectory, as this study reveals that the green economy has a favorable impact on food safety. Other factors in our model account for a considerable portion of the variation in food safety across Africa. The findings show that adopting technology and expanding social protection coverage both increase food safety levels by 0.46% and 0.96%, respectively. This finding is in line with [ 9 ]’s summary of the favorable elements boosting food safety in Africa, which included inventiveness and social inclusion as examples. These results also validate the findings of [ 55 ], who reported that the environmental impact caused by nanoparticle emission from physical and chemical processes that produce hazardous substances harms the food system. Similar results were previously published in studies on Mexico [ 56 ] and Brazil [ 57 ]. However, [ 56 ] showed that the rumen microbiome produces methane, one of the most effective greenhouse gasses, which accounts for approximately 18% of all anthropogenic emissions[ 57 ]. came to the conclusion that agricultural production needs to be sustainable to meet the world's expanding food demand. According to previous studies, traditional methods only partially and often only temporarily decrease ruminant methane output. Thus, the results of [58; 59; 60; 61] showed that improving agricultural efficiency requires boosting soil fertility by lowering environmental risks. In a similar vein, the study revealed that finance, arable land, and employment in agriculture were important and beneficial factors influencing food safety in Africa. Thus, a 1% increase in the hectares of arable land would result in a 0.027%, 0.17%, and 0.013% increase in food safety levels, respectively, in agricultural employment and credit availability. 4.3 Robustness test The fascinating aspect of using GMM is that it is designed to handle endogeneity through the use of instruments. In any case, the validity and reliability of using GMM depend on having valid instruments that will meet the conditions of relevance and exogeneity. The endogeneity test performed in this research ensures that the instruments satisfy these conditions and that the model provides consistent estimates. The Hausman test is used to compare the GMM estimates with the OLS results. To perform the test, we specify the null hypothesis that the regressors are exogenous, while the alternative hypothesis is that the regressors are endogenous. Hausman test result Chi-square = 11.35 p–value = 0.0781 The result followed a chi-squared distribution following the null hypothesis. However, because the p-value is more than 5%, we fail to reject the null hypothesis at the 5% level of significance, suggesting that there is no strong evidence of endogeneity in the model. This is an indicator that the OLS estimator is consistent, and we do not need to rely on the GMM or other estimates designed to handle endogeneity. However, this is not applicable at the 10% significance level. 5. Summary and conclusion This study contributes to the understanding of how a green economy can enhance food safety in Africa, with a focus on supporting the achievement of several Sustainable Development Goals (SDGs) by 2030, including no poverty (SDG 1), zero hunger (SDG 2), clean water and sanitation (SDG 6), sustainable cities and communities (SDG 11), responsible consumption and production (SDG 12), climate action (SDG 13), life below water (SDG 14), and life on land (SDG 15). Using panel data from 37 African countries that are members of the International Development Association (IDA) of the World Bank, the study applied the two-step Generalized Method of Moments (GMM) to address potential endogeneity issues. The data for the period 2005–2020 was sourced from the Food and Agriculture Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and the World Development Indicators (WDI) provided by the World Bank. The results indicate that the green economy, particularly through effective environmental management, has a significant positive impact on food safety in Africa. The analysis shows that successful environmental management could lead to a 0.24% improvement in food safety. Furthermore, several other factors were found to be influential in enhancing food safety, such as technology adoption, arable land expansion, agricultural employment, access to agricultural credit, and social protection. Specifically, a 1% increase in the use of technology, arable land, agricultural employment, agricultural financing, and social protection is associated with respective improvements in food safety of 0.96%, 0.03%, 0.17%, 0.03%, and 0.46%. The study concludes that sustainable development and environmental management are closely tied to human activities, and sound economic governance can help achieve sustainability. On the contrary, unsustainable human practices that disregard economic considerations can lead to environmental degradation and hinder development. Factors such as resource depletion, pollution, deforestation, and declining well-being contribute to poverty and hunger, highlighting the critical need for effective economic management. Achieving sustainability requires balancing human activities with economic priorities to avoid conflict and promote long-term viability. The report also emphasizes the role of environmental sustainability in national development, advocating for the adoption of green practices such as pollution control, afforestation, sustainable agriculture, and reductions in greenhouse gas emissions. A green economy, it argues, must be supported by strong institutions, regulatory frameworks, and socio-economic drivers. The study calls for further research in two key areas: (i) investigating specific green economy policies and their impacts on food safety at the national or household level, and (ii) exploring additional indicators of food safety beyond per capita food production. One limitation of the study is the use of environmental sustainability institutions and regulations as proxies for the green economy, which may not fully reflect its broader scope. Future research should consider incorporating other green economy indicators that offer a more accurate representation given the available data. Declarations Declaration of competing interest: The authors declare no conflicts of interest . Credit Statement: Igharo Amechi Endurance, Conceptualization and Methodology, Ibe Eke Anthony; Data source, Dr . Ifere Eugne Okoi; Data analysis, Abdulaziz Saleh Al-Faryan ; Literature Review, Dr . Ovat Okey Oyama , ; Discussion of findings, Jeniboy Kimpah , Reviewing , Editing and Formatting, Solomon Caulker Robustness test and editing. Funding : The authors did not receive any funding . Data availability statement (DAS): The datasets generated during and/or analyzed during the current study are available from the corresponding authors on reasonable request. Author Contribution I.A.E. (Igharo Amechi Endurance) conceptualized the research idea and led the methodology development. I.A.E. and I.A.Ek. (Ibe Anthony Ekene) collected and analyzed the data. P.E.E. (Pamela Eno-Obong Eyo) performed the literature review. O.G.O. (Okoh Gloria Onyemariechi) and I.E.O. (Dr. Ifere Eugene Okoi) contributed to the data analysis and interpretation of the results. O.O.O. (Dr. OkeyOyama Ovat) and S.C. (Solomon Caulker) were responsible for reviewing, editing, and formatting the manuscript. I.A.E. wrote the main manuscript text. All authors reviewed and approved the final version of the manuscript for submission.Finally, Solomon Caulker performed the robustness test that checked for endogenuity. References Osabuohien, E., Odularu, G., Ufua, D., Augustine, D., and Osabohien, R. (2022). Socioeconomic shocks, inequality and food systems in the Global South: an introduction. Contemporary Social Science, 17(2), 77-83. https://doi.org/10.1080/21582041.2022.2059549 FAO (2019). Greening the economy with agriculture. Food and Agriculture Organi z s ation (FAO), Rome, Italy.Available from: http://www.fao.org/docrep/015/i2745e/i2745e00.pdf Jiren, T. S.,Hanspach, J.,Schultner, J., Fischer, J., Bergsten, A., Senbeta, F., Hylander, K., and Dorresteijn, I.(2020). Reconciling food safety and biodiversity conservation: participatory scenario planning in southwestern Ethiopia. Ecology and Society 25(3):24. https://doi.org/10.5751/ES-11681-250324 Osabohien, R. (2022). Soil technology and post post- harvest losses in Nigeria. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-08-2022-0181 FAO. (2018). Two related but distinctly different concepts are organic farming and sustainable agriculture. Small Farm Today, 10 (1), 30–31 . Osabuohien, E.S., Efobi, U. R. and Gitau, C.M.W. (2015). Environmental Challenges in Africa: Further Dimensions to the Trade, MNCs and Energy Debate. Management of Environmental Quality: 26(1), 118- 137. DOI: http://dx.doi.org/10.1108/MEQ-04-2014-0058 Osabohien, R., Ufua, D., Moses, C. L., and Osabuohien, E. (2020). Accountability in agricultural governance and food safety in Nigeria. Brazilian Journal of Food Technology , 23. e2019089 Paustian, K. et al . (2016). Climate-Smart Soils. Nature (London), vol. 532, no. 7597, Nature Portfolio, 2016, pp. 49–57, https://doi.org/10.1038/nature17174. Anser, M.K., Osabohien, R., Olonade, O., Karakara, A.A., Olalekan, I.B., Ashraf, J., and Igbinoba, A. (2021). Impact of ICT Adoption and Governance Interaction on Food safety in West Africa. Sustainability 2021, 13 (10), 5570; Doi: https://doi.org/10.3390/su1315570 African Union (AU) (2010), Comprehensive Africa Agriculture Development Programme: Pillar III Framework for African Food safety (FAFS), 4th Conference of African Union Ministers of Agriculture Member States Expert’s Meeting, February 26 – 27, Addis Ababa, Ethiopia. Tyagi, A.C. (2016). Towar d ds a Second green revolution. Irrig. Drain . https://doi.org/10. 1002/ird.2076. FAO (1996). World Food Summit, Rome Declaration on World Food safety. Food and Agriculture Organi z s ation (FAO), Rome, Italy Headey, D. (2012). Déjà vu in the Horn of Africa. 2011 Global Food Policy Report, International Food Policy Research Institute (IFPRI), Washington, DC. Oriola, E. O. (2009), “A Framework for Food safety and Poverty Reduction in Nigeria”, European Journal of Social Sciences 8 (1) 132 – 139. Adeleye, B. N., Daramola, P., Onabote, A., and Osabohien, R. (2021). Agro-productivity amidst environmental degradation and energy usage in Nigeria. Scientific Reports , 11 :18940, https://doi.org/10.1038/s41598-021-98250-y Brems, E., C. Van der Beken, and S. A. Yimer. (2015). Human rights and development. Legal perspectives from and for Ethiopia. Koninklijke Brill NV, Leiden, The Netherlands. https://doi. org/10.1163/9789004280250 UNEP (United Nations Economy Programme) (2010). Green economy reports a preview. UNEP, Nairobi, Kenya, p. 4-5. Jin, X. (2012). Guang Yuan Low-carbon Development Path based on SWOT analysis. Journal of Sustainable Development 5(8): 78-83. DOI: https://doi.org/10.5539/jsd.v5n8p78 . Meybeck, A., Burlingame, B., Dernini, S., Gitz, V., Raymond, R. and Ryder, J. (2012). Improving food systems for sustainable diets in a Green Economy. Working paper no. 4, FAO, Vialedelle Terme di Caracalla, 00153 Rome, Italy. International Food Policy Research Institute (IFPRI) (2011). Increasing Agricultural Productivity and Enhancing Food safety in Africa: New Challenges and Opportunities, IFPRI, Washington, DC. UNECA. (2020). Political economy of a green economy Transition in Africa. United Nations Economic Commission for Africa. Schmitz, H., and Becker, B. (2013). From sustainable development to the green transformation-a rough guide. IDS Briefing Paper, Brighton: IDS Adeleke, O. and Josue, M. (2019). Poverty and green economy in South Africa: What is the nexus? Cogent Economics & Finance, 7(1), 1646847. Doi: https://doi.org/10.1080/23322039.2019.1646847 Hallegatte, S., Heal, G., Fay, M., & Treguer, D. (2012). From Growth to Green Growth—A Framework (NBER Working Paper No. 17841). National Bureau of Economic Research, Inc. Jacob, K., Quitzow, R., and Baer, H. (2015). Green jobs: Impacts of a green economy on employment. Federal Ministry of Economic Cooperation and Development. GIZ publications. Barbier, E. B. (2016). Is green growth relevant for poor economies? Resource and Energy Economics, 45, 178–191. Doi: https://doi.org/10.1016/j.reseneeco.2016.05.001 Loiseau, E., Saikku, L., Antikainen, R., Droste, N., Hansjürgens, B., Pitkänen, K., and Thomsen, M. (2016). Green economy and related concepts: An overview. Journal of cleaner production, 139, 361-371. Musango, J. K., Brent, A. C. and Bassi, A. M. (2014). Model Modell ing the transition towar d ds a green economy in South Africa. Technological Forecasting and Social Change, 87, 257-273 . Smith, S., and Musango, J. K. (2015). Towar d ds connecting green economy with an informal economy in South Africa: A review and way forward. Ecological Economics, 116, 154159. Nhamo, G. and Mukonza, C. (2020). Opportunities for women in the green economy and environmental sectors. Sustainable Development. 2020; 28:823–832. https://doi.org/10.1002/sd.2033. Adeleke, O. and Josue, M. (2019). Poverty and green economy in South Africa: What is the nexus? Cogent Economics & Finance, 7(1), 1646847. Doi: https://doi.org/10.1080/23322039.2019.1646847 Smith, L. C. and Haddad (2000). Explaining Child Malnutrition in Developing Countries: A Cross-Country Analysis. International Food Policy Research Institute (IFPRI) Research Report 111, IFPRI, Washington, DC. Bouis, H. and Hunt, J. (1999). Linking Food and Nutrition Security: Past Lessons and Future Opportunities. Asian Development Review 17: 168 – 213. Benson, T (2004), “Africa’s Food and Nutrition Security Situation: Why are We Here and How Did We Get Here?” International Food and Policy Research Institute (IFPRI) 2020 Discussion Paper 37. Iseki, M. (1994). Effects of Increases in the World’s Population and the Globalization of Human Life on the Incidence of Parasitic Diseases. Japanese Journal of Parasitology 43 448 – 452. Akhtar, R. and Verhasselt, Y. (1990), Disease, Ecology, and Health: Readings in Medical Geography, Jaippur, Rawat Publications, India. Hopfenberg, R. and Pimentel, D. (2001). Human Population as a Function of Food Supply. Minnesotans for Sustainability. Retrieved from www.oilcrash.com/population.htm Lunn, J. and Theobald, H. E. (2006). The Health Effects of Dietary Unsaturated Fatty Acids. Nutrition Bulletin 31 (3), 178–224, September Musvoto, C., Nortje, K., De Wet, B., Mahumani, B.K., and Nahman, A. (2014). Imperatives for an agricultural green economy in South Africa. South African Journal of Science, 111(1/2), Art. #2014-0026, 8 pages. http://dx.doi.org/10.17159/sajs.2015/20140026 Kinda, S.R. and Akol, C. (2016). Would Inclusive Green Growth Improve Food safety. DOI: https://dx.doi.org/10.2139/ssrn.2741749y in Africa? Social Science Research Network, pp. 1-19 FAO (2012). Greening the economy with agriculture. Food and Agriculture Organi z s ation (FAO), Rome, Italy.Available from: http://www.fao.org/docrep/015/i2745e/i2745e00.pdf Nouman, M., Khan, D., Ul Haq, I., Naz, N., Zahra, B.T.E. and Ulla, A. (2021). Assessing the implication of green revolution for food safety in Pakistan: A multivariate cointegration decomposition analysis. Journal of Public Affairs , Doi: https://doi.org/10.1002/pa.2758 Narayan, S., and Doytch, N. (2017). An investigation of renewable and non non- renewable energy consumption and economic growth nexus using industrial and residential energy consumption. Energy Economics , 68, 160–176. https://doi.org/10.1016/j.eneco.2017.09.005 Kinda, S.R. (2021). Does the green economy tru l ly foster food safety in Sub-Saharan Africa?, Cogent Economics & Finance, 9:1, 1921911, DOI: https://doi.org/10.1080/23322039.2021.1921911 Arellano, M. and Bond, S., (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58,277–297 IFAD (2011), Adoption of Technologies for Sustainable Farming Systems: Wageningen Workshop Proceedings, OECD, Paris, France Baltagi, B. (2008). Econometric Analysis of Panel Data. John Wiley & Sons. Roodman, D. (2006). How to Do Xtabond2: an Introduction to Difference and System GMM in Stata. Center for Global Development Working Paper, No. 103. Lin, X. and Lee, L.-F., (2010). GMM estimation of spatial autoregressive models with unknown heteroskedasticity. J. Econom. 157, 34–52. Lee, L.-F., (2007). GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. J. Econom. 137, 489–514 Arellano, M., Bover, O., (1995). Another look at the instrumental variable estimation of error-components models. J. Econom. 68, 29–51. Blundell, R., and Bond, S., (1998). Initial conditions and moment restrictions in dynamic panel data models. J. Econom. 87, 115–143. Karakara, A. A. and Osabuohien, E. (2020). ICT Adoption, Competition and Innovation of Informal Firms in West Africa: Comparative Study of Ghana and Nigeria. Journal of Enterprising Communities, 14(3), 397-414. DOI: https://doi.org/10.1108/JEC-03-2020-0022. Karakara, A. and Osabuohien, E (2021). The Role of Institutions in the Discourse of Sustainable Development in West African Countries. In Osabuohien, E., Oduntan, E., Gershon, O., Onanuga, O. and Ola-David, O. (Eds). Handbook of Research on Institutions Development for Sustainable and Inclusive Development in Africa (pp.15-27). Hershey, PA: IGI Global. DOI: https://doi.org/4018/978-1-7998-4817-2.ch002 Bahrulolum, H., Nooraei, S., Javanshir, N., Tarrahimofrad, H., Mirbagheri, V. S., Easton, A. J.,and Ahmadian, G. (2021). Green synthesis of metal nanoparticles using microorganisms and their application in the agri-food sector. Journal of Nanobiotechnology, 19(1), 1-26. Monroy-Torres, R., Castillo-Chávez, Á., Carcaño-Valencia, E., Hernández-Luna, M., Caldera-Ortega, A., Serafín-Muñoz, A., Linares-Segovia, B., Medina-Jiménez, K., Jiménez-Garza, O., and Méndez-Pérez, M. (2021). Food safety, Environmental Health, and the Economy in Mexico: Lessons Learned with the COVID-19. Sustainability, 13(13), 7470. Anghinoni, G., Anghinoni, F. B. G., Tormena, C. A., Braccini, A. L., de Carvalho Mendes, I., Zancanaro, L., & Lal, R. (2021). Conservation agriculture strengthens the sustainability of Brazilian grain production and food safety. Land use policy, 108, 105591. Pyrchenkova, G., Sedikh, V., and Radchenko, E. (2021). Increasing soil fertility is an important factor in ensuring the food safety of the state. E3S Web of Conferences, Asim, Z., Sorooshian, S., Al Shamsi, I. R., Muniyanayaka, D., & Al Azzani, A. (2025). Supply Chain 4.0 A Source of Sustainable Initiative across Food Supply Chain: Trends and Barriers. In Human Perspectives of Industry 4.0 Organizations (pp. 17-37). CRC Press. Teng, P. K., Heng, B. L. J., Abdullah, S. I. N. W., Ping, W. T., & Yao, X. J. (2020). Consumer adoption of mobile payments: a distinctive analysis between China and Malaysia. International Journal of Business Continuity and Risk Management, 10(2-3), 207-223.https://doi.org/10.1504/IJBCRM.2020.108505 Kit Teng, P., Abdullah, S. I. N. W., & Lim, B. J. H. (2021). The future of green food consumption in Peninsular Malaysia. Malaysian Journal of Consumer and Family Economics, 26, 80-109. https://irep.ntu.ac.uk/id/eprint/50064 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2024 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 24 Oct, 2024 Reviews received at journal 24 Oct, 2024 Reviews received at journal 23 Oct, 2024 Reviewers agreed at journal 20 Oct, 2024 Reviewers agreed at journal 18 Oct, 2024 Reviewers agreed at journal 18 Oct, 2024 Reviews received at journal 06 Oct, 2024 Reviewers agreed at journal 30 Sep, 2024 Reviewers invited by journal 30 Sep, 2024 Editor assigned by journal 30 Sep, 2024 Submission checks completed at journal 30 Sep, 2024 First submitted to journal 17 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5104908","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369984817,"identity":"d05afdd0-d4e5-493f-ae7c-194e8240e8db","order_by":0,"name":"Igharo Amechi Endorance","email":"","orcid":"","institution":"British Canadian University, Obudu","correspondingAuthor":false,"prefix":"","firstName":"Igharo","middleName":"Amechi","lastName":"Endorance","suffix":""},{"id":369984822,"identity":"5db8ab85-adad-4fb6-8565-754d7defabb1","order_by":1,"name":"Ibe Anthony Ekene","email":"","orcid":"","institution":"British Canadian University, Obudu","correspondingAuthor":false,"prefix":"","firstName":"Ibe","middleName":"Anthony","lastName":"Ekene","suffix":""},{"id":369984825,"identity":"c3d1126f-0561-4d80-8a30-4212f853f384","order_by":2,"name":"Abdulaziz Seleh Al-Faryan","email":"","orcid":"","institution":"Saudi Economic Association Riyadh Saudi Arabia","correspondingAuthor":false,"prefix":"","firstName":"Abdulaziz","middleName":"Seleh","lastName":"Al-Faryan","suffix":""},{"id":369984826,"identity":"ce73486f-c8ef-4bb1-af0f-c2c246dde898","order_by":3,"name":"Jeniboy Kimpah","email":"","orcid":"","institution":"International University Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Jeniboy","middleName":"","lastName":"Kimpah","suffix":""},{"id":369984827,"identity":"7f251065-5bc6-47d4-a4d6-16ed0c246477","order_by":4,"name":"Dr. Ifere Eugene Okoi","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"prefix":"Dr.","firstName":"Ifere","middleName":"Eugene","lastName":"Okoi","suffix":""},{"id":369984828,"identity":"fd685da5-821d-438d-9863-f315220381ee","order_by":5,"name":"Dr. Okey Oyama Ovat","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"prefix":"Dr.","firstName":"Okey","middleName":"Oyama","lastName":"Ovat","suffix":""},{"id":369984829,"identity":"6b0ce1d1-f463-491c-81e6-e6787506b0a9","order_by":6,"name":"Solomon Caulker","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3PoQrCUBSA4XO9cCxHrPcy2V5hMrD4NBYtNqMGZbCVabb4Dj6CcmEWH0DQMBWWDCZZGm4m07w2wfuHk84H5wCYTD8Zn5azJQBYArDRIexFqCDc/Zqg0CJOOJsl2USRDOfpmCYnuwn8fDlUEHe/9dtRrMiiXedIcerJKXresIqIXmABKrJFH4+EqrfeEFpVxFmWJC+Ik+KIcg0Ch4KwoDhMIPJGoEFev8wXA5JRn8vVQnnS//CLE/rbJHt0bbGL2f32UHaz7p+vlYe9V6Nyct31MpZ9s20ymUx/0xPb30lH7h7CugAAAABJRU5ErkJggg==","orcid":"","institution":"United Methodist University","correspondingAuthor":true,"prefix":"","firstName":"Solomon","middleName":"","lastName":"Caulker","suffix":""}],"badges":[],"createdAt":"2024-09-17 17:19:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5104908/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5104908/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s43621-024-00740-2","type":"published","date":"2024-12-18T15:57:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":72201683,"identity":"b3175d70-8cf8-4434-bc17-338a965ee45c","added_by":"auto","created_at":"2024-12-23 16:09:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":760023,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5104908/v1/167675fb-0738-42a9-9307-ccd37acff091.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pragmatic investigation of the effect of green and low-carbon economy on food safety in Africa.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eA pragmatic investigation into the effect of a green and low-carbon economy on food safety in Africa necessitates a detailed understanding of the region's unique challenges and opportunities. A shift toward sustainable development models; characterized by reduced carbon emissions and eco-friendly practices has been advocated globally as a means to mitigate climate change and promote economic stability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Africa, where agriculture is a cornerstone of many economies and a primary source of livelihood, this transition has significant implications for food safety [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImplementing green and low-carbon strategies can potentially enhance agricultural productivity by promoting practices that improve soil health, water conservation, and biodiversity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, there are concerns about the feasibility and immediate impacts of such transitions on food availability and affordability. This investigation seeks to explore the balance between environmental sustainability and food safety; by examining how policy frameworks, technological innovations, and local community adaptations can harmonize these objectives [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to UN estimates from 2012, there will be approximately 9\u0026nbsp;billion people on the planet by the year 2050. This finding suggested that a significant number of these individuals \u0026ndash; more billion\u0026ndash;will reside in third-world nations, mostly in Africa. The need to boost agricultural production through the green economy to achieve the requisite degree of food safety is becoming increasingly crucial due to the geometric rise in population. Although, on the whole, food production has improved over the past 20 years, current social and economic shocks such as the COVID-19 pandemic have hindered this progress, and one out of five people in Africa is believed to be experiencing food insecurity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]; [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePolicies and strategies to ensure environmental sustainability are needed to increase agricultural productive capacity for feeding the growing population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Research indicates that a significant number of agricultural landscapes, particularly those in the South, are globally weaker due to the combined challenges of reducing biodiversity loss and mitigating the occurrence of food insecurity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]; [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]; [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Future sustainability concerns could be threatened by the increasing trend in agricultural production if biodiversity is lost [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, 30% Worldwide greenhouse gas emissions are attributable to the agricultural sector, contributing to climate change worldwide. One other reference for growing atmospheric greenhouse gas emissions is global agriculture [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Methane (CH\u003csub\u003e4\u003c/sub\u003e) and nitrous oxide (N\u003csub\u003e2\u003c/sub\u003eO) emissions from agriculture are produced by humans on average and reached 55% of the total emissions ([\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Similarly, Foley et al.'s 2005 study proposed that the worldwide intensification of agricultural practices is responsible for biodiversity loss.\u003c/p\u003e \u003cp\u003eFurthermore, almost 60% of Africa's carbon emissions are attributable to unfavorable agricultural practices, including deforestation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Salinization, deforestation, soil erosion and desertification are a few examples of land area depletion that threatens the long-term supply of food and achievement of food safety, undermining the expansion of agricultural output in Africa in the future [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn line with FAO [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], food safety may be defined as a condition \u0026ldquo;\u003cem\u003ewhen every member of the household, at all times, has physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and a healthy living\u003c/em\u003e\u0026rdquo;. In actuality, \"the primary sector, such as agriculture, needs to gain the required attention in Africa to enhance food safety status for all household members\" [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. As a result, green agriculture could sustainably assist in this area. It has been acknowledged that food prices are extremely unstable and that agriculture must be vigorously pursued to fulfill its roles as a food source, an income source for many people, and an engine for growth [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA green economy that is robust to climate change and prioritizes agricultural intensification must be implemented by all nations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This approach will assist in achieving sustainable agriculture over the long run, which is necessary to achieve food safety. Environmental deterioration and unsustainable economic development are purviewing the green economy. This is why the United Nations Environment Programme-UNEP regards a green economy as \u0026ldquo;\u003cem\u003eone that results in improved human well-being and social equity, while significantly reducing environmental risks and ecological scarcities\u003c/em\u003e\u0026rdquo; [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] asserts that a low-carbon environment with minimal energy use, efficiency, pollution, and emissions is the cornerstone of a green economy, which results in a human economy that is ecologically responsible. This justifies the inclusion of green growth strategies as carbon emissions reduction procedures [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eActions must be taken to actualize a greener economy as the global population continues to rise and natural resource availability declines [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. An economy that acknowledges sustainable development and economic progress through resource efficiency is known as the \"green economy\". Therefore, the goal of a green economy is to achieve economic growth that is earned in concert with social welfare and environmental conservation. Cutting back on the usage of nonrenewable resources and fossil fuels is also promoted. According to [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], \"green growth\" refers to the process of encouraging economic expansion while guaranteeing the uninterrupted provision of natural resources and environmental services that are important for human well-being.\u003c/p\u003e \u003cp\u003eIn practice, the green economic vision could help address some of the most challenging problems the world is currently facing, such as resource waste, hunger, and climate change [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A number of African countries, including Senegal, Ethiopia, Kenya, Rwanda, Mozambique, and Tunisia, have set out to achieve a green economy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, these countries are in different stages of the process. Thus, research on the green economy and its impact in Africa is necessary, particularly in relation to food safety.\u003c/p\u003e \u003cp\u003eAccording to previous studies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]; [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]; [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], a green economy can bridge resource gaps and contribute to the necessary improvement in human welfare without having an adverse effect on the environment or future generations. Therefore, growth processes that are resource efficient, cleaner, and more robust might be compared to those of a green economy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]; [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is claimed that the green economy will lead to a \"win\u0026ndash;win\" outcome in the pursuit of development. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] aimed to address low-carbon and sustainable development with outcomes such as job opportunities and poverty reduction. This is significant because, if countries are successful in transitioning to a green economy, at least 18\u0026nbsp;million net job opportunities are expected to be produced globally by 2030. Scholars have countered that a green economy need not always be sustainable or conducive to growth [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditional empirical research has connected the tenets of the green economy to other important economic sectors. For example, [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] examined how a green economy's capabilities, concepts, instruments and approaches might assist in facilitating the shift to sustainability. The consequences of the green economy for ecological services, low-carbon development, and significant sectoral indicators were compiled by [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore,[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] examined how the green economy and the casual economy interact and concluded that including the casual economy in conversations about the green economy could lead to better planned policies and strategies. The potential of women in South Africa's environmental and green economic development sectors was examined by [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Studies that have already been conducted, as mentioned above, have rarely overlooked the connection between agricultural productivity and the green economy in accomplishing food safety or the viability of green agriculture in doing so. For example, studies on the relationship between the green economy and employment [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] or between the green economy and poverty reduction [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] have not examined food safety. The current study looks at food safety and the green economy (green agriculture) to accomplish this goal.\u003c/p\u003e \u003cp\u003eThe research contends that the interactions between agricultural practices, biodiversity, and food safety are detailed. Thus, it is necessary to model how a green economy might affect food safety. This is one of the very few studies that looks at how institutions and policies for environmental sustainability, as a stand-in for a green economy, affect food safety. The research argues that by giving agriculture a major place in the green economy and successfully managing this transition, the world community may get closer to attaining the goals of eradicating starvation and guaranteeing food and nutritional security for everyone.\u003c/p\u003e \u003cp\u003eBy addressing both the potential benefits and challenges, this study aims to contribute to the discourse on sustainable development and its critical role in ensuring food safety in Africa.\u003c/p\u003e \u003cp\u003eThe remainder of the study is structured as follows. The study's conceptualization is discussed in the next section, along with some analysis from pertinent literature. While sections four and five provide the results and a summary, section three explores the study's data and methodology.\u003c/p\u003e"},{"header":"2. Insights from the empirical literature","content":"\u003cp\u003eThis section provides a brief review of the literature. The literature review produced ambiguous and wide-ranging results. One group of scholars examined the relationships between agricultural production and environmental and climatic concerns and food safety. Notably, researchers such as [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] have concluded that decreasing agricultural and food production due to unfavorable conditions of climate and environmental issues such as floods and droughts are the key causes of food insecurity in most countries.\u003c/p\u003e \u003cp\u003eThere is a common misconception that population expansion and declining human health are the main reasons for food crises in numerous parts of the world. Examples include the assertions made by [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and others that initiatives to boost food output by intensifying production have been spurred by population expansion. Consequently,research on food safety has been documented in scholarly works. On the other hand, the idea that green agriculture improves food safety is mostly unsupported in the data.\u003c/p\u003e \u003cp\u003eSome agricultural production research in the context of the Green Revolution is qualitative, and reports on green economy-related subjects are sometimes included. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] examined the relationships between biodiversity protection and food safety in southeast Ethiopia stakeholder organizations participated in a participatory scenario planning exercise that was used for analysis in the study. This study highlights the prospect of using agro ecological development pathways to foster synergies between biodiversity preservation and food safety. Additionally, the analysis made clear that the environment will undoubtedly suffer from courses that favor agricultural productivity, and social inequality will almost certainly follow.\u003c/p\u003e \u003cp\u003eTo compete in a green economy, agriculture needs to be successful, support economic growth, and uphold social, cultural, and economic institutions; [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A study by [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] suggested that there is a chance to apply green growth ideas to ensure food safety in Africa. Consequently, there is a relationship between agriculture and the green economy that affects food safety. In a concept statement written for the Rio\u0026thinsp;+\u0026thinsp;20 summit, the Agricultural Organization (FAO) emphasized the role that agriculture plays in the pursuit of a green economy, saying that, without agriculture, there will be no green economy [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] investigated how Pakistan's food safety (1975\u0026ndash;2017) was affected by the Green Revolution using annual time-series data. The study used F-bounds +++ tests and Johansen integration tests as analytical techniques that the Green Revolution has favorably and meaningfully enhanced food safety in Pakistan. The research postulated that the use of high-quality seeds and fertilizers, fuel consumption, and a rise in the area dedicated to cereal crop planting are important facets of the green revolution that have enhanced Pakistan's food safety. Additionally, [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] summarized that the use of renewable energy spurs economic development, which may result in the attainment of food safety. This is evident in a country's ability to finance public services, investments in health and education, and the ability to buy food in international markets, all of which are boosted by economic performance.\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] investigated how the green economy impacts food safety using data from thirty-five sub-Saharan African countries between 2001 and 2015. The author's research indicates that there are inconclusive data on the relationship between green economy indices and food safety, specifically with regard to food availability and the percentage of undernourished people. Indeed, the results indicated that in Sub-Saharan African countries, food safety is enhanced by renewable energy, while it is undermined by biofuels. The author claims that there is no relationship between CO\u003csub\u003e2\u003c/sub\u003e emissions and food safety.\u003c/p\u003e"},{"header":"3. Research methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Sources of Data and Variable Description\u003c/h2\u003e \u003cp\u003eThe study employed data obtained from the FAO, WDI, and CPIA. The study included 37 African nations and spanned the years 2005 to 2018. The nations are used since they are members of the International Development Association (IDA). Appendix A lists the nations that participated in the analysis.\u003c/p\u003e \u003cp\u003eAgricultural credit (measured by credit to agriculture, in US dollars), arable land (hectare), ICT (percentage of the population with internet access), food safety (measured by food production-gross per capita), the green economy (measured by the degree to which countries' policies and institutions support environmental sustainability), social protection (measured by overall social protection coverage), and agricultural employment (percentage of total employment) are the variables involved in the study. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists the variables used in the investigation and their measurements.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariables, Measurements and Sources\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExpectations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFudSec\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFood safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGross per capita food production (number)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFAO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot Applicable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen Economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePolicy and institutions for environmental sustainability (scale of 1\u0026thinsp;=\u0026thinsp;low to 6\u0026thinsp;=\u0026thinsp;high).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCPIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial Protection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epolicies for social protection coverage (scale: 1\u0026thinsp;=\u0026thinsp;low to 6\u0026thinsp;=\u0026thinsp;high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCPIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArable Land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHectare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgricultural Credit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUS\u003cspan\u003e$\u003c/span\u003e, 2015 prices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFAO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation and Communication Technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndividuals using the internet (% of the total population)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgricultural employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmployment in agriculture (% of total employment)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote\u003c/b\u003e: CPIA means country policy and institutional assessment =, FAO means Food and Agricultural organization and WDI means World Development Indicators. \u003cb\u003eSource\u003c/b\u003e: The Authors\u0026rsquo; Compilations.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Method of Analysis\u003c/h2\u003e \u003cp\u003eThe impact of a green economy on food safety in Africa is empirically explored in this study using environmental management policies as a proxy. The research depends on the publications of [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) illustrates the baseline model that the study uses:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:FudSec=f(GE,\\:SOP,AC,\\:AL,\\:ICT,\\:AE)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eEquation (\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) expresses the outcome variable (food production per capita an indicator of food safety) as a function of the green economy (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:GE)\\)\u003c/span\u003e\u003c/span\u003e, social protection\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\left(SOP\\right)\\)\u003c/span\u003e\u003c/span\u003e, agricultural credit \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(AC\\right),\\:\\)\u003c/span\u003e\u003c/span\u003earable land (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:AL)\\)\u003c/span\u003e\u003c/span\u003e, information and communication technology\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(ICT\\right)\\)\u003c/span\u003e\u003c/span\u003e, and agricultural employment (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:AE).\\)\u003c/span\u003e\u003c/span\u003e The explicit form of the model is specified in a double-log, as shown in Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e):\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{lnFudSec}_{it}=\\:{b}_{0}+{b}_{1}{lnGE}_{it}+{b}_{2}{lnSOP}_{it}+{b}_{3}{lnAC}_{it}+{b}_{4}{lnAL}_{it}+{b}_{5}{lnICT}_{it}+{b}_{6}{lnAE}_{it}+{e}_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the intercept; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{1}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{2}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{3}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{4}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{5}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{6}\\)\u003c/span\u003e\u003c/span\u003e are the parameters to be estimated; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}_{it}\\)\u003c/span\u003e\u003c/span\u003e is the error term.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Estimation Techniques\u003c/h2\u003e \u003cp\u003eDespite the fact that the current research uses many methodologies due to endogeneity, conclusions are derived from the generalized method of moments (GMM) results. Based on the empirical research conducted by [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], it is possible to specify the baseline model (pooled OLS) and fixed effect using the formula in Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{lFudSec}_{it}=\\:\\rho\\:+{b}_{1}l{GE}_{it}+\\phi\\:lX{\\prime\\:}it\\:+{e}_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:FudSec\\)\u003c/span\u003e\u003c/span\u003eis food safety, is the constant term, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:GE\\)\u003c/span\u003e\u003c/span\u003ecaptures the green economy and \u003cb\u003eX\u003c/b\u003e\u003csup\u003e\u0026prime;\u003c/sup\u003e\u003csub\u003eit\u003c/sub\u003e is a vector of control variables. The control variables are agricultural credit, social protection, arable land, information and communication technology, and agricultural employment, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:e\\)\u003c/span\u003e\u003c/span\u003e is the error term. Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) is estimated using pooled OLS and fixed effect regression. We conducted the Hausman test to help decide on the use of the fixed effect. The individually specific effects are not considered in the estimations when dealing with a pooled OLS. This may cause orthogonality problems. -- However, this orthogonality problem is often solved with random effects estimation because the random effect method executes an individually specified intercept in the model, which may lead to endogeneity, and the Hausman test verifies this.\u003c/p\u003e \u003cp\u003eThe study employed the Hausman specification to choose between fixed and random effects. Preference is given to the fixed effect model over the random effect model by the Hausman specification. The benchmark regression's Hausman test result, x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;11.35 (p\u0026thinsp;=\u0026thinsp;0.0781), indicates that the premise that a model with random effects is better is not supported. The argument behind choosing the GMM is that endogeneity problems can arise with both pooled OLS and fixed effect analysis. When endogeneity issues arise, the GMM generates the most reliable estimates [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]; [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Eq.\u0026nbsp;(\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) specifies the GMM model in accordance with the study's goals and references to [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], and [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{lFudSec}_{it}=\\:\\rho\\:+\\vartheta\\:{lFudSec}_{it-1}\\:+{b}_{1}l{GE}_{it}+\\:\\phi\\:lX{\\prime\\:}it\\:+{e}_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{FudSec}_{it}\\)\u003c/span\u003e\u003c/span\u003e is the food safety status of country \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\:(i\\:=\\:1,\\:2\\dots\\:,\\:N)\\)\u003c/span\u003e\u003c/span\u003e at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\:(t\\:=\\:2,\\:3,\\dots\\:,\\:T),\\rho\\:\\)\u003c/span\u003e\u003c/span\u003e is a constant term, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{FudSec}_{it-1}\\)\u003c/span\u003e\u003c/span\u003e is the lagged dependent variable (food safety) with coefficient\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\vartheta\\:\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{GE}_{it}\\)\u003c/span\u003e\u003c/span\u003e is the green economy with coefficient \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{b}_{1},\\:\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:X{\\prime\\:}it\\)\u003c/span\u003e\u003c/span\u003e is a covariate of the independent variables with the coefficient \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\phi\\:\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\phi\\:=1,\\:2,\\:3\\dots\\:N)\\)\u003c/span\u003e\u003c/span\u003e. The current study applied the two-step system GMM to help handle endogeneity problems.\u003c/p\u003e \u003cp\u003eIn situations where endogeneity is a concern, the two-stage least square (2SLS) approach may be more appropriate. However, in the face of heteroscedasticity, the 2SLS model likewise offers flimsy estimates [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Therefore, when the outcome variable is not highly exogenous, the generalized method of moment (GMM) approach generates good estimators and is more efficient [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Because of the link that exists between the mean of the lagged dependent variable and the idiosyncratic error factor, the results of the elementary pooled OLS and fixed effect methods may not be consistent in these situations [9; 45; 51].\u003c/p\u003e \u003cp\u003eSeveral solutions to this problem have been provided by [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]), and [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], who demonstrate how system GMM estimators can lessen the bias associated with fixed effects in short panels and address the endogeneity problem in dynamic panel data. According to [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], when assessing the authenticity of the tools used in a GMM, the AR (2) tests of Hansen and Arellano‒Bond for the calculation of autocorrelation may be utilized. The two-step method GMM estimators have been found to be effective in previous work [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Correlation analysis and summary statistics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the relationship between the outcome and the control variables, and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the summary statistics of the variables. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e's correlation analysis results indicate that there is no evidence of significant multicollinearity among the variables. This is because less than 80% of the variables in the table are related to one another (0.8).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Matrix\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFood safety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCredit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArable land\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSocial protection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGreen economy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAgric employment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInformation Technology\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCredit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArable land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.1129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial protection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.0363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreen economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.0513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.0488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgric employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.1065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.0578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.4927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.4817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eSource\u003c/b\u003e: The authors\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides the descriptive statistics for the variables that were chosen and used in the study. According to the descriptive and summary statistics of the variable, Africa produces almost \u003cspan\u003e$\u003c/span\u003e91\u0026nbsp;million in worth of food per person. Conversely, the average employment rate in agriculture stands at 57%. This finding provides evidence that the agricultural industry in Africa accounts for approximately 57% of all jobs across the continent. In a similar vein,the data indicate that, on average, fewer than 9% of Africa's total population has access to mobile internet services. This finding indicates that Africa has a low percentage of internet users. In a similar vein, Africa has 6484710 hectares of arable land, despite the continent receiving an average of \u003cspan\u003e$\u003c/span\u003e259.43\u0026nbsp;million in credit for agriculture.\u003c/p\u003e \u003cp\u003eSocial protection and the green economy are ranked from 1 (lowest) to 6 (best). A score between 1 and 2, which is considered the lowest, indicates that a person has very little social protection and poor environmental management. A country with moderate social protection coverage and moderate environmental protection regulations is said to have a moderate score, which falls between three and four.Finally, a score between five and six, which denotes the highest range, indicates that social protection and environmental management and sustainability policies are effective. The social security benefits (such as monetary and in-kind help for farmers, elderly individuals, and the most vulnerable), social insurance (such as health insurance), and labor market intervention (such as unemployment compensation) are the social protection benefits that are examined here. According to previous studies, the degree to which institutions and policies address environmental sustainability, a key component of the green economy, should be gauged by how well they support the preservation and sustainable use of natural resources [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to the summary statistics in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the examined nations are performing at social protection and green economy scales of 3.36 and 3.27, respectively. This indicates that the social protection coverage and environmental sustainability policies of such nations are regarded as modest. Thus, for the analyzed countries to attain food safety in the future, efforts must be made to expand the scope of social protection and transition to an environmentally friendly economy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary Statistics of the Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.77138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.99253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.22000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138.7800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCredit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e259.4299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e433.9795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.029302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2559.826\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArable land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6484710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7598382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48000.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37000000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial protection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.359486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.300000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.200000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.437550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreen economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.274920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.457004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.000000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.000000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment in agriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.03453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.24880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.27000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.11000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation and communication technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.783574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.068427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.219660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.83992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eSource\u003c/b\u003e: Authors\u0026rsquo; Computation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Results of the two-step system GMM, fixed effect and pooled OLS analyses.\u003c/h2\u003e \u003cp\u003eThe findings from the two-step system GMM, fixed effects, and pooled OLS analyses are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Initially, pooled OLS and fixed effects methods were used for the baseline analysis, with the primary analysis relying on the two-step system GMM approach to address endogeneity concerns [9; 45; 51]. While pooled OLS and fixed effects methods have certain limitations, the two-step system GMM provides more robust results, which form the basis for policy recommendations. The system GMM method assumes strong autocorrelation in both the first-order (AR(1)) and second-order (AR(2)) autoregressive processes. In this study, the Sargan test indicates that the instruments are valid, as they are uncorrelated with the residuals.\u003c/p\u003e \u003cp\u003eThe analysis reveals that the green economy significantly contributes to improving food safety. Specifically, the green economy coefficient of 0.2422 suggests that a 1% improvement in organizational effectiveness and environmental sustainability efforts would lead to a 0.24% increase in food safety. Additionally, expanding social security coverage is found to have an even greater impact on food safety. A 1% increase in social protection coverage would result in a 0.46% improvement in food safety, demonstrating that social protection initiatives have a stronger effect on food safety than green economy efforts.\u003c/p\u003e \u003cp\u003eMoreover, a 1% increase in arable land is associated with a 0.21% rise in food safety, highlighting its positive and significant impact on food security in Africa. Other key variables also positively influence food safety. An increase in access to information technology, agricultural financing, and employment in the agricultural sector is expected to enhance food safety by 0.17%, 0.96%, and 0.125%, respectively. Together, these findings emphasize the importance of technological access, agricultural funding, and employment in improving food safety outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcomes of the Two-step GMM, Fixed Effect, and Pooled OLS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDependent Variable: Food safety\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePooled OLS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFixed Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTwo-Step System GMM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFS(-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3726*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArable land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6321*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0274**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAgricultural employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1677*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.184)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.245)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInformation technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1407*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0856*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0958*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCredit to agriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0277**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0125**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSocial protection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4601*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.428)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.495)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGreen economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2422*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.558)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.894)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1043*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.6542*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.605*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroups/Observation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26/311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26/311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26/311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWald chi2(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e336.55*\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF-stat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.73*\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.78*\u003c/p\u003e \u003cp\u003e(-0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.320\u003c/p\u003e \u003cp\u003e(-0.185)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNote\u003c/b\u003e: The p values are in parentheses (-- ), * and **indicate that the coefficients are significant at the 1% and 5% levels,, respectively. \u003cb\u003eSource\u003c/b\u003e: The authors\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Discussion of the Results\u003c/h2\u003e \u003cp\u003eMost of the time, poor farming methods lead to environmental damage. This occurs as a result of detrimental effects on the nutrients and physical characteristics of the soil. Technology, economic activity, and social domains all contribute significantly to the greening of the economy. For instance, deforestation contributes significantly to environmental degradation, which hinders the endeavor to establish a green economy [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and demands innovation from producers [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of the two-step GMM show that the green economy, as represented by institutions and policies for environmental management, may be a statistically significant and favorable explanation for the level of food safety in Africa. This suggests that there is a 0.24% increase in food safety that may be achieved by efficient environmental management. This result confirms that inadequate environmental management causes a number of environmental problems, including drought, landslides, floods, and hailstorms [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eErosions and other inappropriate farming practices, such as overgrazing and burning, which affect a significant amount of forestland, the loss of nutrients from the soil, and land salinization, wash away the protective layer of soil [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Furthermore, actions that result in a reduction in the amount of vegetation cover have an undesirable impact on the sustainability of ecological systems and the green economy. Therefore, measures are required to steer this trajectory, as this study reveals that the green economy has a favorable impact on food safety.\u003c/p\u003e \u003cp\u003eOther factors in our model account for a considerable portion of the variation in food safety across Africa. The findings show that adopting technology and expanding social protection coverage both increase food safety levels by 0.46% and 0.96%, respectively. This finding is in line with [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u0026rsquo;s summary of the favorable elements boosting food safety in Africa, which included inventiveness and social inclusion as examples. These results also validate the findings of [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], who reported that the environmental impact caused by nanoparticle emission from physical and chemical processes that produce hazardous substances harms the food system.\u003c/p\u003e \u003cp\u003eSimilar results were previously published in studies on Mexico [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and Brazil [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. However, [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] showed that the rumen microbiome produces methane, one of the most effective greenhouse gasses, which accounts for approximately 18% of all anthropogenic emissions[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. came to the conclusion that agricultural production needs to be sustainable to meet the world's expanding food demand. According to previous studies, traditional methods only partially and often only temporarily decrease ruminant methane output. Thus, the results of [58; 59; 60; 61] showed that improving agricultural efficiency requires boosting soil fertility by lowering environmental risks. In a similar vein, the study revealed that finance, arable land, and employment in agriculture were important and beneficial factors influencing food safety in Africa. Thus, a 1% increase in the hectares of arable land would result in a 0.027%, 0.17%, and 0.013% increase in food safety levels, respectively, in agricultural employment and credit availability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 \u003cb\u003eRobustness test\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe fascinating aspect of using GMM is that it is designed to handle endogeneity through the use of instruments. In any case, the validity and reliability of using GMM depend on having valid instruments that will meet the conditions of relevance and exogeneity. The endogeneity test performed in this research ensures that the instruments satisfy these conditions and that the model provides consistent estimates. The Hausman test is used to compare the GMM estimates with the OLS results. To perform the test, we specify the null hypothesis that the regressors are exogenous, while the alternative hypothesis is that the regressors are endogenous.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHausman test result\u003c/b\u003e \u003c/p\u003e \u003cp\u003eChi-square\u0026thinsp;=\u0026thinsp;11.35\u003c/p\u003e \u003cp\u003ep\u0026ndash;value\u0026thinsp;=\u0026thinsp;0.0781\u003c/p\u003e \u003cp\u003eThe result followed a chi-squared distribution following the null hypothesis. However, because the p-value is more than 5%, we fail to reject the null hypothesis at the 5% level of significance, suggesting that there is no strong evidence of endogeneity in the model. This is an indicator that the OLS estimator is consistent, and we do not need to rely on the GMM or other estimates designed to handle endogeneity. However, this is not applicable at the 10% significance level.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Summary and conclusion","content":"\u003cp\u003eThis study contributes to the understanding of how a green economy can enhance food safety in Africa, with a focus on supporting the achievement of several Sustainable Development Goals (SDGs) by 2030, including no poverty (SDG 1), zero hunger (SDG 2), clean water and sanitation (SDG 6), sustainable cities and communities (SDG 11), responsible consumption and production (SDG 12), climate action (SDG 13), life below water (SDG 14), and life on land (SDG 15). Using panel data from 37 African countries that are members of the International Development Association (IDA) of the World Bank, the study applied the two-step Generalized Method of Moments (GMM) to address potential endogeneity issues. The data for the period 2005\u0026ndash;2020 was sourced from the Food and Agriculture Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and the World Development Indicators (WDI) provided by the World Bank.\u003c/p\u003e \u003cp\u003eThe results indicate that the green economy, particularly through effective environmental management, has a significant positive impact on food safety in Africa. The analysis shows that successful environmental management could lead to a 0.24% improvement in food safety. Furthermore, several other factors were found to be influential in enhancing food safety, such as technology adoption, arable land expansion, agricultural employment, access to agricultural credit, and social protection. Specifically, a 1% increase in the use of technology, arable land, agricultural employment, agricultural financing, and social protection is associated with respective improvements in food safety of 0.96%, 0.03%, 0.17%, 0.03%, and 0.46%.\u003c/p\u003e \u003cp\u003eThe study concludes that sustainable development and environmental management are closely tied to human activities, and sound economic governance can help achieve sustainability. On the contrary, unsustainable human practices that disregard economic considerations can lead to environmental degradation and hinder development. Factors such as resource depletion, pollution, deforestation, and declining well-being contribute to poverty and hunger, highlighting the critical need for effective economic management. Achieving sustainability requires balancing human activities with economic priorities to avoid conflict and promote long-term viability.\u003c/p\u003e \u003cp\u003eThe report also emphasizes the role of environmental sustainability in national development, advocating for the adoption of green practices such as pollution control, afforestation, sustainable agriculture, and reductions in greenhouse gas emissions. A green economy, it argues, must be supported by strong institutions, regulatory frameworks, and socio-economic drivers. The study calls for further research in two key areas: (i) investigating specific green economy policies and their impacts on food safety at the national or household level, and (ii) exploring additional indicators of food safety beyond per capita food production. One limitation of the study is the use of environmental sustainability institutions and regulations as proxies for the green economy, which may not fully reflect its broader scope. Future research should consider incorporating other green economy indicators that offer a more accurate representation given the available data.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest: \u003c/strong\u003eThe authors declare no conflicts of interest\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e.\u003c/ins\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit Statement:\u003c/strong\u003e Igharo Amechi Endurance, Conceptualization and Methodology, Ibe Eke Anthony; Data source, Dr\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e.\u003c/ins\u003e Ifere Eugne Okoi; Data analysis, Abdulaziz Saleh Al-Faryan\u003cstrong\u003e;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiterature Review, Dr\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e.\u003c/ins\u003e Ovat Okey Oyama\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e,\u003c/del\u003e\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e;\u003c/ins\u003e Discussion of findings, Jeniboy Kimpah\u003cstrong\u003e, \u003c/strong\u003eReviewing\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e,\u003c/ins\u003e Editing and Formatting, Solomon Caulker Robustness test and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors did not receive any funding\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e.\u003c/ins\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement (DAS):\u003c/strong\u003e The datasets generated during and/or analyzed during the current study are available from the corresponding authors on reasonable request.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eI.A.E. (Igharo Amechi Endurance) conceptualized the research idea and led the methodology development. I.A.E. and I.A.Ek. (Ibe Anthony Ekene) collected and analyzed the data. P.E.E. (Pamela Eno-Obong Eyo) performed the literature review. O.G.O. (Okoh Gloria Onyemariechi) and I.E.O. (Dr. Ifere Eugene Okoi) contributed to the data analysis and interpretation of the results. O.O.O. (Dr. OkeyOyama Ovat) and S.C. (Solomon Caulker) were responsible for reviewing, editing, and formatting the manuscript. I.A.E. wrote the main manuscript text. All authors reviewed and approved the final version of the manuscript for submission.Finally, Solomon Caulker performed the robustness test that checked for endogenuity.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOsabuohien, E., Odularu, G., Ufua, D., Augustine, D., and Osabohien, R. (2022). Socioeconomic shocks, inequality and food systems in the Global South: an introduction. Contemporary Social Science, 17(2), 77-83. https://doi.org/10.1080/21582041.2022.2059549\u003c/li\u003e\n\u003cli\u003eFAO (2019). Greening the economy with agriculture. Food and Agriculture Organi\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ez\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003es\u003c/del\u003eation (FAO), Rome, Italy.Available from: http://www.fao.org/docrep/015/i2745e/i2745e00.pdf\u003c/li\u003e\n\u003cli\u003eJiren, T. S.,Hanspach, J.,Schultner, J., Fischer, J., Bergsten, A., Senbeta, F., Hylander, K., and Dorresteijn, I.(2020). Reconciling food safety and biodiversity conservation: participatory scenario planning in southwestern Ethiopia. Ecology and Society 25(3):24. https://doi.org/10.5751/ES-11681-250324\u003c/li\u003e\n\u003cli\u003eOsabohien, R. (2022). Soil technology and \u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003epost\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003epost-\u003c/del\u003eharvest losses in Nigeria. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-08-2022-0181 \u003c/li\u003e\n\u003cli\u003eFAO. (2018). Two related but distinctly different concepts are organic farming and sustainable agriculture. \u003cem\u003eSmall Farm Today, 10 (1), 30\u0026ndash;31\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eOsabuohien, E.S., Efobi, U. R. and Gitau, C.M.W. (2015). Environmental Challenges in Africa: Further Dimensions to the Trade, MNCs and Energy Debate. Management of Environmental Quality: 26(1), 118- 137. DOI: http://dx.doi.org/10.1108/MEQ-04-2014-0058\u003c/li\u003e\n\u003cli\u003eOsabohien, R., Ufua, D., Moses, C. L., and Osabuohien, E. (2020). Accountability in agricultural governance and food safety in Nigeria. \u003cem\u003eBrazilian Journal of Food Technology\u003c/em\u003e, 23. e2019089\u003c/li\u003e\n\u003cli\u003ePaustian, K. \u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eet al\u003c/ins\u003e\u003cem\u003e.\u003c/em\u003e (2016). Climate-Smart Soils. Nature (London), vol. 532, no. 7597, Nature Portfolio, 2016, pp. 49\u0026ndash;57, https://doi.org/10.1038/nature17174.\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003e \u003cem\u003e \u003c/em\u003e\u003c/del\u003e\u003c/li\u003e\n\u003cli\u003eAnser, M.K., Osabohien, R., Olonade, O., Karakara, A.A., Olalekan, I.B., Ashraf, J., and Igbinoba, A. (2021). Impact of ICT Adoption and Governance Interaction on Food safety in West Africa. \u003cem\u003eSustainability\u003c/em\u003e 2021, 13 (10), 5570; Doi: https://doi.org/10.3390/su1315570 \u003c/li\u003e\n\u003cli\u003eAfrican Union (AU) (2010), Comprehensive Africa Agriculture Development Programme: Pillar III Framework for African Food safety (FAFS), 4th Conference of African Union Ministers of Agriculture Member States Expert\u0026rsquo;s Meeting, February 26 \u0026ndash; 27, Addis Ababa, Ethiopia.\u003c/li\u003e\n\u003cli\u003eTyagi, A.C. (2016). Towar\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ed\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eds\u003c/del\u003e a Second green revolution. \u003cem\u003eIrrig. Drain\u003c/em\u003e. https://doi.org/10. 1002/ird.2076.\u003c/li\u003e\n\u003cli\u003eFAO (1996). World Food Summit, Rome Declaration on World Food safety. Food and Agriculture Organi\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ez\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003es\u003c/del\u003eation (FAO), Rome, Italy\u003c/li\u003e\n\u003cli\u003eHeadey, D. (2012). D\u0026eacute;j\u0026agrave; vu in the Horn of Africa. 2011 Global Food Policy Report, International Food Policy Research Institute (IFPRI), Washington, DC.\u003c/li\u003e\n\u003cli\u003eOriola, E. O. (2009), \u0026ldquo;A Framework for Food safety and Poverty Reduction in Nigeria\u0026rdquo;, \u003cem\u003eEuropean Journal of Social Sciences 8 (1) 132 \u0026ndash; 139.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eAdeleye, B. N., Daramola, P., Onabote, A., and Osabohien, R. (2021). Agro-productivity amidst environmental degradation and energy usage in Nigeria. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e:18940, https://doi.org/10.1038/s41598-021-98250-y\u003c/li\u003e\n\u003cli\u003eBrems, E., C. Van der Beken, and S. A. Yimer. (2015). Human rights and development. Legal perspectives from and for Ethiopia. Koninklijke Brill NV, Leiden, The Netherlands. https://doi. org/10.1163/9789004280250\u003c/li\u003e\n\u003cli\u003eUNEP (United Nations Economy Programme) (2010). Green economy reports a preview. UNEP, Nairobi, Kenya, p. 4-5.\u003c/li\u003e\n\u003cli\u003eJin, X. (2012). Guang Yuan Low-carbon Development Path based on SWOT analysis. \u003cem\u003eJournal of Sustainable Development 5(8): 78-83. DOI: \u003c/em\u003e\u003cem\u003ehttps://doi.org/10.5539/jsd.v5n8p78\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eMeybeck, A., Burlingame, B., Dernini, S., Gitz, V., Raymond, R. and Ryder, J. (2012). Improving food systems for sustainable diets in a Green Economy. \u003cem\u003eWorking paper no. 4,\u003c/em\u003e FAO, Vialedelle Terme di Caracalla, 00153 Rome, Italy.\u003c/li\u003e\n\u003cli\u003eInternational Food Policy Research Institute (IFPRI) (2011). Increasing Agricultural Productivity and Enhancing Food safety in Africa: New Challenges and Opportunities, IFPRI, Washington, DC.\u003c/li\u003e\n\u003cli\u003eUNECA. (2020). Political economy of a green economy Transition in Africa. United Nations Economic Commission for Africa.\u003c/li\u003e\n\u003cli\u003eSchmitz, H., and Becker, B. (2013). From sustainable development to the green transformation-a rough guide. IDS Briefing Paper, Brighton: IDS\u003c/li\u003e\n\u003cli\u003eAdeleke, O. and Josue, M. (2019). Poverty and green economy in South Africa: What is the nexus? \u003cem\u003eCogent Economics \u0026amp; Finance, 7(1), 1646847. \u003c/em\u003eDoi: https://doi.org/10.1080/23322039.2019.1646847 \u003c/li\u003e\n\u003cli\u003eHallegatte, S., Heal, G., Fay, M., \u0026amp; Treguer, D. (2012). From Growth to Green Growth\u0026mdash;A Framework (NBER Working Paper No. 17841). National Bureau of Economic Research, Inc.\u003c/li\u003e\n\u003cli\u003eJacob, K., Quitzow, R., and Baer, H. (2015). Green jobs: Impacts of a green economy on employment. Federal Ministry of Economic Cooperation and Development. GIZ publications.\u003c/li\u003e\n\u003cli\u003eBarbier, E. B. (2016). Is green growth relevant for poor economies? Resource and Energy Economics, 45, 178\u0026ndash;191. Doi: https://doi.org/10.1016/j.reseneeco.2016.05.001\u003c/li\u003e\n\u003cli\u003eLoiseau, E., Saikku, L., Antikainen, R., Droste, N., Hansj\u0026uuml;rgens, B., Pitk\u0026auml;nen, K., and Thomsen, M. (2016). Green economy and related concepts: An overview. \u003cem\u003eJournal of cleaner production, 139, 361-371.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eMusango, J. K., Brent, A. C. and Bassi, A. M. (2014). \u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eModel\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eModell\u003c/del\u003eing the transition towar\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ed\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eds\u003c/del\u003e a green economy in South Africa. \u003cem\u003eTechnological Forecasting and Social Change, 87, 257-273\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eSmith, S., and Musango, J. K. (2015). Towar\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ed\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eds\u003c/del\u003e connecting green economy with an informal economy in South Africa: A review and way forward. Ecological Economics, 116, 154159.\u003c/li\u003e\n\u003cli\u003eNhamo, G. and Mukonza, C. (2020). Opportunities for women in the green economy and environmental sectors. Sustainable Development. 2020; 28:823\u0026ndash;832. https://doi.org/10.1002/sd.2033.\u003c/li\u003e\n\u003cli\u003eAdeleke, O. and Josue, M. (2019). Poverty and green economy in South Africa: What is the nexus? \u003cem\u003eCogent Economics \u0026amp; Finance, 7(1), 1646847. \u003c/em\u003eDoi: https://doi.org/10.1080/23322039.2019.1646847\u003c/li\u003e\n\u003cli\u003eSmith, L. C. and Haddad (2000). Explaining Child Malnutrition in Developing Countries: A Cross-Country Analysis. International Food Policy Research Institute (IFPRI) Research Report 111, IFPRI, Washington, DC.\u003c/li\u003e\n\u003cli\u003eBouis, H. and Hunt, J. (1999). Linking Food and Nutrition Security: Past Lessons and Future Opportunities.\u003cem\u003eAsian Development Review 17: 168 \u0026ndash; 213.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eBenson, T (2004), \u0026ldquo;Africa\u0026rsquo;s Food and Nutrition Security Situation: Why are We Here and How Did We Get Here?\u0026rdquo; International Food and Policy Research Institute (IFPRI) 2020 Discussion Paper 37.\u003c/li\u003e\n\u003cli\u003eIseki, M. (1994). Effects of Increases in the World\u0026rsquo;s Population and the \u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003eGlobalization\u003c/ins\u003e of Human Life on the Incidence of Parasitic Diseases. \u003cem\u003eJapanese Journal of Parasitology 43 448 \u0026ndash; 452.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eAkhtar, R. and Verhasselt, Y. (1990), \u003cem\u003eDisease, Ecology, and Health: Readings in Medical Geography, \u003c/em\u003eJaippur, Rawat Publications, India.\u003c/li\u003e\n\u003cli\u003eHopfenberg, R. and Pimentel, D. (2001). Human Population as a Function of Food Supply. Minnesotans for Sustainability. Retrieved from www.oilcrash.com/population.htm\u003c/li\u003e\n\u003cli\u003eLunn, J. and Theobald, H. E. (2006). The Health Effects of Dietary Unsaturated Fatty Acids. \u003cem\u003eNutrition Bulletin 31 (3), 178\u0026ndash;224, September\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eMusvoto, C., Nortje, K., De Wet, B., Mahumani, B.K., and Nahman, A. (2014). Imperatives for an agricultural green economy in South Africa. South African Journal of Science, 111(1/2), Art. #2014-0026, 8 pages. http://dx.doi.org/10.17159/sajs.2015/20140026 \u003c/li\u003e\n\u003cli\u003eKinda, S.R. and Akol, C. (2016). Would Inclusive Green Growth Improve Food safety. DOI: https://dx.doi.org/10.2139/ssrn.2741749y in Africa? \u003cem\u003eSocial Science Research Network, pp. 1-19\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eFAO (2012). Greening the economy with agriculture. Food and Agriculture Organi\u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003ez\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003es\u003c/del\u003eation (FAO), Rome, Italy.Available from: http://www.fao.org/docrep/015/i2745e/i2745e00.pdf\u003c/li\u003e\n\u003cli\u003eNouman, M., Khan, D., Ul Haq, I., Naz, N., Zahra, B.T.E. and Ulla, A. (2021). Assessing the implication of green revolution for food safety in Pakistan: A multivariate cointegration decomposition analysis. \u003cem\u003eJournal of Public Affairs\u003c/em\u003e, Doi: https://doi.org/10.1002/pa.2758\u003c/li\u003e\n\u003cli\u003eNarayan, S., and Doytch, N. (2017). An investigation of renewable and \u003cins cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003enon\u003c/ins\u003e\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003enon-\u003c/del\u003erenewable energy consumption and economic growth nexus using industrial and residential energy consumption. \u003cem\u003eEnergy Economics\u003c/em\u003e, \u003cem\u003e68, 160\u0026ndash;176. \u003c/em\u003ehttps://doi.org/10.1016/j.eneco.2017.09.005 \u003c/li\u003e\n\u003cli\u003eKinda, S.R. (2021). Does the green economy tru\u003cdel cite=\"mailto:Curie\" datetime=\"2024-09-23T14:09\"\u003el\u003c/del\u003ely foster food safety in Sub-Saharan Africa?, \u003cem\u003eCogent Economics \u0026amp; Finance, 9:1, 1921911, DOI:\u003c/em\u003e https://doi.org/10.1080/23322039.2021.1921911 \u003c/li\u003e\n\u003cli\u003eArellano, M. and Bond, S., (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58,277\u0026ndash;297\u003c/li\u003e\n\u003cli\u003eIFAD (2011), \u003cem\u003eAdoption of Technologies for Sustainable Farming Systems:\u003c/em\u003e Wageningen Workshop Proceedings, OECD, Paris, France\u003c/li\u003e\n\u003cli\u003eBaltagi, B. (2008). \u003cem\u003eEconometric Analysis of Panel Data.\u003c/em\u003e John Wiley \u0026amp; Sons.\u003c/li\u003e\n\u003cli\u003eRoodman, D. (2006). How to Do Xtabond2: an Introduction to Difference and System GMM in Stata. Center for Global Development Working Paper, No. 103.\u003c/li\u003e\n\u003cli\u003eLin, X. and Lee, L.-F., (2010). GMM estimation of spatial autoregressive models with unknown heteroskedasticity. J. Econom. 157, 34\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eLee, L.-F., (2007). GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. J. Econom. 137, 489\u0026ndash;514\u003c/li\u003e\n\u003cli\u003eArellano, M., Bover, O., (1995). Another look at the instrumental variable estimation of error-components models. J. Econom. 68, 29\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eBlundell, R., and Bond, S., (1998). Initial conditions and moment restrictions in dynamic panel data models. J. Econom. 87, 115\u0026ndash;143.\u003c/li\u003e\n\u003cli\u003eKarakara, A. A. and Osabuohien, E. (2020). ICT Adoption, Competition and Innovation of Informal Firms in West Africa: Comparative Study of Ghana and Nigeria. Journal of Enterprising Communities, 14(3), 397-414. DOI: https://doi.org/10.1108/JEC-03-2020-0022.\u003c/li\u003e\n\u003cli\u003eKarakara, A. and Osabuohien, E (2021). The Role of Institutions in the Discourse of Sustainable Development in West African Countries. In Osabuohien, E., Oduntan, E., Gershon, O., Onanuga, O. and Ola-David, O. (Eds). Handbook of Research on Institutions Development for Sustainable and Inclusive Development in Africa (pp.15-27). Hershey, PA: IGI Global. DOI: https://doi.org/4018/978-1-7998-4817-2.ch002\u003c/li\u003e\n\u003cli\u003eBahrulolum, H., Nooraei, S., Javanshir, N., Tarrahimofrad, H., Mirbagheri, V. S., Easton, A. J.,and Ahmadian, G. (2021). Green synthesis of metal nanoparticles using microorganisms and their application in the agri-food sector. \u003cem\u003eJournal of Nanobiotechnology, 19(1), 1-26.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eMonroy-Torres, R., Castillo-Ch\u0026aacute;vez, \u0026Aacute;., Carca\u0026ntilde;o-Valencia, E., Hern\u0026aacute;ndez-Luna, M., Caldera-Ortega, A., Seraf\u0026iacute;n-Mu\u0026ntilde;oz, A., Linares-Segovia, B., Medina-Jim\u0026eacute;nez, K., Jim\u0026eacute;nez-Garza, O., and M\u0026eacute;ndez-P\u0026eacute;rez, M. (2021). Food safety, Environmental Health, and the Economy in Mexico: Lessons Learned with the COVID-19. \u003cem\u003eSustainability, 13(13), 7470.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eAnghinoni, G., Anghinoni, F. B. G., Tormena, C. A., Braccini, A. L., de Carvalho Mendes, I., Zancanaro, L., \u0026amp; Lal, R. (2021). Conservation agriculture strengthens the sustainability of Brazilian grain production and food safety. Land use policy, 108, 105591.\u003c/li\u003e\n\u003cli\u003ePyrchenkova, G., Sedikh, V., and Radchenko, E. (2021). Increasing soil fertility is an important factor in ensuring the food safety of the state. E3S Web of Conferences,\u003c/li\u003e\n\u003cli\u003eAsim, Z., Sorooshian, S., Al Shamsi, I. R., Muniyanayaka, D., \u0026amp; Al Azzani, A. (2025). Supply Chain 4.0 A Source of Sustainable Initiative across Food Supply Chain: Trends and Barriers. In Human Perspectives of Industry 4.0 Organizations (pp. 17-37). CRC Press.\u003c/li\u003e\n\u003cli\u003eTeng, P. K., Heng, B. L. J., Abdullah, S. I. N. W., Ping, W. T., \u0026amp; Yao, X. J. (2020). Consumer adoption of mobile payments: a distinctive analysis between China and Malaysia. International Journal of Business Continuity and Risk Management, 10(2-3), 207-223.https://doi.org/10.1504/IJBCRM.2020.108505\u003c/li\u003e\n\u003cli\u003eKit Teng, P., Abdullah, S. I. N. W., \u0026amp; Lim, B. J. H. (2021). The future of green food consumption in Peninsular Malaysia. Malaysian Journal of Consumer and Family Economics, 26, 80-109. https://irep.ntu.ac.uk/id/eprint/50064\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biodiversity, food safety, green economy, sustainable development","lastPublishedDoi":"10.21203/rs.3.rs-5104908/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5104908/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research investigates how food safety in Africa is influenced by a green economy. The study used information from the Food and Agricultural Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and World Development Indicators to accomplish the set goal. The data covered the period 2005\u0026ndash;2020 for 37 African countries. The generalized method of moments (GMM) was used in the study to address the endogeneity issue. The results revealed that when the economy is green, food safety increases. This proves that a one-point increase in the green economy may lead to an increase in food safety in Africa of 0.24%. - The results show that; as an economy becomes greener, the state of food insecurity decreases. In conclusion, the study capitulates that all relevant participants must focus on strategies and policies to reach green economic growth. This is key because such policies lead to environmental sustainability (reduction in biodiversity loss) causing agriculture to flourish and thereby enlightening the state of food safety.\u003c/p\u003e","manuscriptTitle":"Pragmatic investigation of the effect of green and low-carbon economy on food safety in Africa.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-13 14:38:26","doi":"10.21203/rs.3.rs-5104908/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-24T12:41:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-24T07:51:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-23T11:17:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166716548040661080379649810983289599688","date":"2024-10-20T08:19:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267225644776742710544567293536758237794","date":"2024-10-19T01:55:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"97281094972053158628469087121136010718","date":"2024-10-18T18:51:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-06T11:40:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5259249993671782168208330327551896237","date":"2024-10-01T03:40:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-30T19:10:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-30T12:42:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-30T05:21:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2024-09-17T17:18:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8626cbb6-d0cd-42c5-8f55-07f101e75f2c","owner":[],"postedDate":"November 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:00:22+00:00","versionOfRecord":{"articleIdentity":"rs-5104908","link":"https://doi.org/10.1007/s43621-024-00740-2","journal":{"identity":"discover-sustainability","isVorOnly":false,"title":"Discover Sustainability"},"publishedOn":"2024-12-18 15:57:12","publishedOnDateReadable":"December 18th, 2024"},"versionCreatedAt":"2024-11-13 14:38:26","video":"","vorDoi":"10.1007/s43621-024-00740-2","vorDoiUrl":"https://doi.org/10.1007/s43621-024-00740-2","workflowStages":[]},"version":"v1","identity":"rs-5104908","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5104908","identity":"rs-5104908","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}