The Impact Of Agricultural Production,Trade Openness And Energy Consumption On Environment Of Selected Emerging Economies

The continuous threat posed by climate change caused by carbon dioxide emission has reignited global advocacy to confront its negative ramification with the greatest possible firmness.Among pollutants,carbon dioxide emission accounts for the highest share of emerging economies carbon footprint.Most countries have pledged their support through the Kyoto Protocol 1997 to deal with global warming of which emerging economies are no exception.Emerging economies such as Brazil,Russia,India,China,and South Africa（BRICS）are considered as the main pillars for global economic growth.These five countries are ranked among countries with the highest carbon emissions globally.Despite efforts by stakeholders through the implementation of Kyoto Protocol agreement,multilateral trade and environment negotiation between World Trade Organization（WTO）and United Nations Framework Convention on Climate Change（UNFCCC）;global greenhouse-gas emission is still showing a worrying trend.Several empirical research works have been done to examine the impact of agriculture production,international trade,and energy use on the environment in both developed and developing countries.Most studies tend to focus on aggregation of agriculture production,international trade,and energy use impact on the environment.Few studies have attempted to capture the distinct effect of disaggregated components of each variable at individual country-level on actual carbon dioxide emissions.Our interest is awakened by the gap identified.The study therefore looks at the impact of these distinct components of agriculture production,international trade,and energy consumption on potential carbon emissions of selected emerging economies.The individual components of these variables are crop production（CRP）and livestock production（LVP）;trade imports（IMP）and trade exports（EXP）;and;renewable（REN）and non-renewable（NRE）energy use respectively.The study focused on selected emerging economies that formed BRICS due to several reasons.The BRICS as developing economies have an important role to play in the 2030 Agenda for Sustainable Development by guaranteeing food security,trade,affordable and clean energy and measures to combat climate change.In recent years,BRICS as developing economies of the world is characterized by an increase in population,agricultural production,high level of energy use,massive trade volume and economic growth.This current trend has led to an expansion of agricultural land use as well as an intensification of farming practices,which are detrimental to the environment in the quest to meet food requirements.Hence,an increase in population and economic development requires an overall higher food production,energy and;movement of people and merchandise from one domicile to another through trade in order to meet demand.The study,therefore seeks to achieve the following five key research objectives.First,to examine the causal relationship between agricultural production and carbon dioxide emissions;Second,to test the validity of disaggregated agricultural-induced growth-environmental pollution nexus;Third,to investigate the causal nexus between trade openness and environmental pollution;Fourth,to determine the causal correlation between energy consumption and carbon dioxide emissions and lastly,to predict the potential carbon dioxide emissions of emerging economies.To accomplish these study objectives,panel data set for four emerging economies out of five that formed BRICS were used in order to cover a lengthy period to make relevant conclusions.The study excluded Russia from the analysis since available data starts in 1992,which would make analysis and comparison difficult if not impossible.Data were procured from the World Development Indicators and FAOSTATS for the period 1971 to 2013.However,panel models may suffer from issues of heterogeneity and cross-sectional dependence.This study eliminated the issue of heterogeneity and cross-sectional dependence,inherent with panel data analysis through the application of recent econometric techniques such as Pooled（weighted）Fully Modified Ordinary Least Square（FMOLS）,Feasible Generalized Least Squares（FGLS）,Pooled Mean Group（PMG）and Driscoll-Kraay standard errors（DKSE）as main estimators.To check for robustness of the main estimator results,the study further used Pooled（weighted）Dynamic Ordinary Least Square（DOLS）,Panel Corrected Standard Errors（PCSE）and Common Correlated Effect Mean Group（CCEMG）to perform this function.These econometric approaches are more robust and provide better statistical inferences in the presence of spatial dependence and heterogeneity.Variables used throughout the analysis as explanatory variables include;Energy consumption measured as kg of oil equivalent per capita.The economic growth of emerging economies is measured as current US$of Gross Domestic Product per capita.Crop and Livestock production index（agriculture production）were both measured for their production for each year relative to the base period 2004-2006.Trade export and import（International trade）both measured in current US$of total merchandise.Renewable and non-renewable（energy consumption）both measured in kg of oil equivalent.To ensure that the study is devoid of any omitted variable bias,this study additionally added population,industrialization,and urbanization.A population is measured as the total number of people.Industrialization is measured as current US$of industry value added whiles Urbanization is measured as a total of urban population.CO₂ eq-Carbon dioxide equivalent emissions（Giga grams/Kt CO₂e）as the proxy of environmental impact,is used as a dependent variable.Preliminary analysis shows that variables are cross-sectionally dependent and heterogeneous using（Pesaran,2004）CD and（Pesaran&Yamagata,2008）test respectively.Therefore,application of the first-generation test will lead to spurious results.We accordingly,employed second-generation techniques such as cross-sectionally augmented Dicker-Fuller（CADF）and cross-sectional augmented IPS（CIPS）to test for panel unit root.Our empirical findings showed that all of the variables under investigation are non-stationary at level.However,the null hypothesis of non-stationary is rejected at the first difference under the two unit root methods.A subsequent test of cointegration using Kao,Pedroni,and Westerlund cointegration test shows that variables are cointegrated and hence have long run association.Empirical results of the first objective revealed that increase in crop production,livestock production as well as economic growth causes a proportional increase in emissions.Results of the second objective on the validity test of disaggregated agriculture-induced EKC,shows that all the variables have the expected sign and are highly significant.The study clearly shows the existence of cubic polynomial or N-shaped EKC.The N-shaped curve means that the degradation of the environment begins to increase after a reduction to a specific level.That is,the rebound effect is expected to lead to more environmental destruction as the economies progress.Our third objective results suggest that 1%rise in imports,energy usage and industrialization cause’s upsurge emissions by 0.471%,1.176%and 0.596%respectively.However,trade exports and urbanization increase were found to improves the environment of emerging economies but statistically inconsequential.Findings of our fourth objective exposed renewable-energy use to improve the ecological structure of emerging economies whiles population and nonrenewable energy use increase the carbon stock.Results of the fifth objective revealed that best training performance is achieved at the epoch 11 when the value of the Mean Square Error（MSE）is 0.0003345 which indicates that the model errors are less than 0.05.This smaller error provides more accurate prediction results,which can contribute to emissions control.Artificial Neural Network prediction results further indicate non-renewable energy use as the most important contributor to emissions followed by livestock production with renewable energy consumption as the least important variable.The Granger causality test results of both PMG and Dumitrescu-Hurlin test indicate no evidence of causality between population and energy use;and also between urbanization and trade imports.The results supports the neutrality hypothesis,which suggests that population increase will not have an impact on the energy use of the emerging economies.Likewise,urban growth does not contribute to trade imports.However,population and urban growth were found to Granger cause the carbon dioxide equivalent emissions.Moreover,industrial growth Granger causes the trade export whiles renewable and non-renewable energy use Granger cause industrial evolution of emerging economies.The results further reveal that crop and livestock production Granger cause the emissions and economic growth without any feedback.The unidirectional causality of crop and livestock（agriculture）production and the economic development shows that agriculture production stimulates economic development while the increase in the level of economic expansion influences carbon stock.Therefore,reduction in both crop and livestock production can hamper the economic development of the selected emerging countries.However,the feedback effect is found between economic growth and population,between economic growth and carbon dioxide equivalent emissions,and;between industrialization and carbon dioxide equivalent emissions.The bi-directional causality between economic expansion and carbon dioxide equivalent emissions means that the emerging countries achieve economic development at the cost of environment.Likewise,bi-directional relationship between industrialization and carbon dioxide equivalent emissions reflects the similar.This thesis provides the following key contributions crucial for emerging economies:Firstly,the findings emanating from the estimation of various agriculture production indexes effect on the environment will help to evaluate all possible mitigation approaches with respect to ecological efficacy and economic feasibility.Secondly,the idea of testing for agriculture-induced EKC is to reveal the effect of economic growth on ecological air quality induced by disaggregated agriculture production.Furthermore,with the introduction of nonstructural variables as agriculture production indexes into the EKC model,advances the relationship between income and pollution.This will help us to know the effect of other variables on the EKC model when analyzing the correlation between income and environmental pollution.Thirdly,the essence to uncover the influence of trade imports and exports on emissions would provide clear evaluation and establishment of all possible approaches to environmental efficiency of trade to emerging economies.Fourthly,the analysis of renewable and non-renewable energy consumption is meant to reveal the varying effect of energy use by sources on the environment.The study exposes whether or not increases in the share of renewable energy and a decrease in the share of non-renewable energy are statistically and economically meaningful in explaining reductions in the level of potential emissions for the emerging economies.This is to guide policymakers and agencies on how to decarbonize the heat sector to achieve Paris’s Greenhouse Effect Treaty.Lastly,the prediction of potential carbon dioxide emissions is to ensure that emerging economies have a clear understanding of expected future emissions so that appropriate measures can be implemented to mitigate its impact.This study,therefore,suggests that,for emerging countries to achieve Sustainable Development Goal of ensuring zero hunger for their citizenry require the need to alter their farming production techniques and also adopt agricultural technology method,which is more environmentally friendly.In terms of trade,emerging economies should minimize or control imports to reduce the impact on the environment.This will ensure that international trade benefits the environment,boosts economic growth,protects the environment and generates income to mitigate ecological pollution.Emerging economies should increase awareness on how to protect the environment and offer a reduction of the carbon tax to green industries.Rising economic power states are also encouraged to ensure energy efficiency and replace fossil fuel use with a renewable source for heating to reduce carbon stock.The main innovations of this research are:Firstly,this study innovatively,considers the influence of agricultural production,international trade,and energy consumption on environment by disaggregating them into their individual components to explicate their distinct influence on environment from the perspective of selected emerging economies.Surprisingly,most studies aggregated agricultural production,international trade,and energy consumption in finding their respective relationship with emissions,thereby providing mixed results.It is believed that application of an aggregated form of these variables is a key contributing factor for the contradictory and mixed findings from various researchers.Secondly,the study also investigated the validity of disaggregated agriculture-induced Environmental Kuznets Curve theory.To the best of the researchers’knowledge,a scanty study has tested the validity of disaggregated agricultural-induced Growth-Environmental Pollution nexus in a cubic form of Gross Domestic Product（GDP）in emerging economies.Thirdly,the study extends the frontiers of empirical studies by using potential carbon dioxide emissions instead of actual carbon dioxide emissions as a proxy of environmental impact.Potential carbon dioxide emissions are a conversion of the various gases into equivalent amounts of carbon dioxide emissions based on Global Warming Potential（GWP）standard ratios.The use of potential carbon dioxide emissions is explained by the fact that it takes into account all other greenhouse gases,including CO₂.Hence,the emissions expressed as an amount of CO₂,which would have the same instantaneous warming effect.Explicitly,the use of real CO₂ can lead to an underestimation of the total impact of global warming.As a result,inventories of greenhouse gases for analysis are completed when they include all greenhouse gases and not just CO₂.Fourthly,the research work contributes to existing findings by utilizing econometric approaches that are more robust and provide better statistical inferences than the conventional estimator such as Ordinary Least Square（OLS）.Ordinary Least Square produces biased and inconsistent results when variables are co-integrated,cross-sectionally dependent and heterogeneous.Investigation of the impact of disaggregated components of agriculture production,trade openness and energy consumption of emerging economies are critical for policy formulation and future strategies to fight emissions.This will ensure food security,economic expansion,energy efficiency and above all environmental sustainability.