The provision of food security promotes sustainable economic growth by fostering healthier and more productive populations. However, achieving food security can impose environmental costs, as production and distribution processes contribute to deforestation, greenhouse gas emissions, and resource depletion. Environmental policy stringency plays a critical role in mitigating these impacts by regulating industrial practices and promoting sustainable technologies. This study examines the relationship between food security and environmental policy stringency in shaping greenhouse gas emissions and ecological footprints, while accounting for energy consumption, geopolitical risks, and technological innovation. Using Canadian annual time series data from 1990 to 2022, the study employs the dynamic autoregressive distributed lag (DARDL) model to analyze long-run dynamics. The empirical results indicate that a 1% increase in food security raises CO₂ emissions by 0.16% and ecological footprint by 0.14%, confirming its environmentally detrimental effect. Energy consumption exerts the largest impact, increasing CO₂ emissions by 0.60% and ecological footprint by 0.67%. Geopolitical risk contributes positively to environmental degradation, increasing CO₂ emissions by 0.01% and ecological footprint by 0.79%. In contrast, environmental policy stringency reduces CO₂ emissions by 0.13% and ecological footprint by 0.16%, while technological innovation decreases emissions by 0.11% and ecological footprint by 0.10% in the long run. All estimated coefficients are statistically significant at conventional levels. Counterfactual analysis further evaluates the effects of ± 1% and ± 5% shocks among variables, revealing asymmetric environmental responses. The robustness of the findings is confirmed using Kernel-based Regularized Least Squares (KRLS). These results suggest that policymakers must balance food security objectives with environmental sustainability by strengthening environmental regulations and promoting green agricultural technologies.

This study attempts to forecast the potential economic growth effect of President Trump's tariff measures on the Canadian economy. To achieve this objective, it undertook a series of analytical procedures ranging from econometric estimations to model simulation. Econometric estimates (Dynamic ARDL) indicate that Canada's exports to the USA affect its economic growth. Findings were robust from DOLS estimation. Toda Yamamoto causality tests confirmed causal connectedness between them. The International Trade Closeness model shows that despite losing trade flexibility during the former Trump administration, Canadian exports to the United States were not significantly affected. Results from the Forest Simulation method provide predictions of response to tariffs on Canadian exports to the USA across multiple potential tariff scenarios ranging from 15 % to 50 %. Under a minimum 15 % tariff rate, total exports are likely to be the highest at 58.91 units. However, if US tariffs on Canadian exports keep rising, exports are expected to decline steadily across all categories, with total exports likely to fall to 34.65 units under a 50 % tariff. Canada’s retaliatory move on its imports from the USA is expected to impact its economy. A 40 % tariff is expected to lead to a nearly 30 % contraction in import volume. Policy implications and recommendations are discussed.

Over the past two decades, numerous developed and developing nations have witnessed a remarkable shift from manufacturing-based economies to those that center around the service sector. This development has led to a staggering growth in the consumption of energy-intensive goods, and Canada has not been immune to this trend. Despite being home to abundant energy reserves, the country’s economic expansion has manifestly relied on prodigious energy consumption. Within this context of symbiotic energy-economic growth, this study investigates the empirical relationship between energy consumption and economic growth using Canadian time-series data from 1980 to 2020. In doing so, this paper offers a vital contribution to the development of theoretical frameworks within the sphere of endogenous growth. Besides, to arrive at empirical findings, a model known as the autoregressive distributed lag (ARDL) model, renowned for its ability to discern both short- and long-term coefficients, is employed. The results reveal that economic growth has a significant positive long-run effect on energy consumption and other explanatory variables. All variables other than trade openness demonstrate a positive relationship with economic growth in the short run. From Toda-Yamamoto causality test, it is evident that there exist bidirectional causal links between economic growth and energy consumption and between economic growth and financial development. Several unidirectional causalities were also observed for other variables. Based on these findings, it is recommended that Canada boosts its investment in energy infrastructure, especially in rural and backward regions, to deliver necessary energy services. An optimal trade-off between Canada’s vast energy resources and economic growth can perhaps be achieved by minimizing the disparity in access to energy services across all parts of the country. Other policy implications are discussed.

Ethiopia is one of the fastest growing economies in Africa. During the last three decades, it has been thriving with stupendous efforts for a transition from non-renewable energy use to a renewable energy-dominant economy. It is against this background that this study attempts to highlight the role of renewable energy and non-renewable energy in affecting CO2 emissions under an augmented EKC framework. To achieve this goal, the study exploits data for the period 1981–2015. The Autoregressive Distributed Lag (ARDL) model is employed and the results surprisingly revealed that both renewable and non-renewable energy use reduce Ethiopia’s CO2 emissions. The unexpected inhibiting effect of non-renewable energy on CO2 emissions might be attributed to the fact that share of non-renewable energy in the overall energy mix of Ethiopia has become insignificant after experiencing decline consistently during the last three decades. The outcome supports the existence of the EKC hypothesis as well as a N-shaped pattern of association between real GDP per capita and CO2 emissions per capita, particularly in the long run. There is evidence for long run causality, especially from the explanatory variables to CO2 emissions per capita. Policy implications are discussed.

Agriculture is the backbone of most sub-Saharan Africa economies, but environmental quality, so vital for agricultural production, is being challenged by climate change. However, most studies measure environmental quality using one variable, CO2 emissions. In this study, a more enhanced measure of environmental quality, which incorporates three indicators (per capita CO2 emissions, energy intensity and adjusted national savings), is used. A set of second-generation panel data techniques that address some potentially crucial panel data estimation issues such as cross sectional dependence and cross country heterogeneity, are employed. Data on 24 sub-Saharan Africa countries over the period 1984 to 2016 were analysed. The impact on agricultural productivity of two of the three indicators of environmental quality, namely CO2 emissions and adjusted national savings, has expected signs, negative and positive, respectively. Estimates using different methods suggest a detrimental effect of per capita CO2 emissions on agricultural productivity in sub-Saharan Africa. A 1% rise in per capita CO2 emissions induces a 0.04% to 0.06% decline in agricultural productivity. Deteriorating environment quality as a result of climate change is slowly but negatively impacting sub-Saharan Africa agricultural productivity.

Poverty and corruption can both immiserate a nation. Globalisation through open trade can potentially increase economic growth, providing employment and increased incomes to the poor. Corruption can dampen or even reduce these positive developments. Although globalisation is considered instrumental in development strategies, theoretically, the impact of globalisation on poverty reduction is ambiguous, an ambiguity that is also reflected in the empirical literature. The corruption-poverty literature clearly reveals that empirical findings on such association are at best heterogeneous. This article examines the effects of globalisation and corruption on poverty using time series data for South Africa for the period 1991?2016. Three indicators of poverty and recently developed measures of globalisation and corruption were employed in the logistic regression model used for estimation. The results confirm that globalisation reduces poverty while corruption intensifies it. The globalisation findings are robust across the different measures of poverty while unidirectional results show corruption increases poverty.

This study employs dynamic panel data for 34 Sub Saharan Africa (SSA) countries for the period 1984-2016 to estimate the effects of renewable energy on environmental quality measured by three indicators, namely, per capita CO2 emissions, energy intensity (EI) and Aggregate National Savings (ANS). The study leveraged a battery of second-generation econometric tests and estimation and causality methods to obtain the coefficients between the regressed and the regressors. Results reveal that use of renewable energy reduces CO2 emissions and energy intensity while it enhances ANS. Economic growth still seems to be expensive for the region as it stimulates CO2 emissions. However, it has a positive effect on ANS. As expected, fossil fuels exacerbate CO(2 )emissions and energy intensity. FDI is found to be detrimental for the environment of SSA region with its positive significant coefficient on CO2 emissions. Financial development is reported to reduce CO2 emissions. Some causal links between variables are also noted.

This study examines the effects of economic growth and foreign direct investment (FDI) on child health outcomes measured by Infant Mortality Rate (IMR) and Child Mortality Rate Under 5 (CMRU5) with several control variables such as corruption, inequality and HIV among others. It analyzes South Africa's annual time series data for the period 1985–2016. As variables were found with mixed order of integration, Autoregressive Distributed Lag (ARDL) model is applied to determine cointegration and estimate short-run and long-run coefficients. Results indicate that economic growth and FDI have negative significant effects on both indicators of child health outcomes in both the short run and the long run. This implies that both economic growth and FDI contribute towards reducing IMR and CMRU5 in South Africa and thus help improve child health outcomes. Toda and Yamamoto (TY) causality test confirms causal association between these variables. Policy implications are discussed.

The environmental effects of urbanization and globalization are still subject to debate among scholars. South Africa is the most globalized, most urbanized and the most carbon-intensive economy in Sub Saharan Africa (SSA) region. Taking this into cognizance, this study examines the effects of urbanization and globalization on CO2 emissions for South Africa using time series annual data for the period 1980–2017. Zivot and Andrews single and Bai and Perron multiple structural break unit root tests are employed to assess if all the series are stationary. This procedure follows ARDL cointegration test to check the presence of a long-run association among variables. Having been confirmed about such a cointegrating relation, ARDL short-run and long run coefficients indicate that urbanization induces CO2 emissions while only long-run significant emissions effect of globalization was noted. Toda-Yamamoto non-causality test reports a bi-directional causal link between urbanization and CO2 emissions. No causal link is observed between globalization and CO2 emissions. Variance decomposition results do not rule out these effects in future. Policy implications are discussed.

This study examines the empirical effects of four variables: economic growth, energy consumption, foreign direct investment, and financial development on environmental quality in Qatar. Three environmental quality indicators, namely, per capita CO 2 emissions, energy intensity (EI), and Adjusted National Savings (ANS) are used to examine the interactions between the variables using a time series dataset for the period 1980−2016. Following an appropriate multiple structural breaks unit root and cointegration tests, short- and long-run coefficients were estimated through the application of Autoregressive Distributive Lag (ARDL) model. The Toda-Yamamoto (TY) causality test was conducted to determine the causal link, if any, among the variables. Estimated results suggest a detrimental long-run effect of energy consumption on all three indicators of environmental quality. FDI has a negative long-run effect on environmental quality when it is measured by EI only. Financial development has no significant effect on any of the indicators. Bidirectional causality are noted between three variables: economic growth, energy consumption, and financial development and all three indicators of environmental quality. Policy implications are discussed.

Due to mixed empirical findings, FDI-growth nexus is still an issue of debate. This paper estimates the long-run association between FDI and economic growth for Bangladesh using time series data for the period 1985-2014. Results from Dynamic Ordinary Least Squares (DOLS) demonstrate positive and significant long-run relationship between FDI and economic growth. A bidirectional causality also exists between them. The study further indicates that financial development and trade openness also Granger cause economic growth. Variance decomposition analysis results confirm the future positive role of FDI, trade openness and financial development in the context of Bangladesh. Policy implications are discussed.Keywords: Bangladesh, DOLS, economic growth, FDIJEL Classifications: F21, F43

This study examined the empirical effects of economic growth, electricity consumption, foreign direct investment (FDI), and financial development on carbon dioxide (CO2) emissions in Kuwait using time series data for the period 1980–2013. To achieve this goal, we applied the autoregressive distributed lag (ARDL) bounds testing approach and found that cointegration exists among the series. Findings indicate that economic growth, electricity consumption, and FDI stimulate CO2 emissions in both the short and long run. The VECM Granger causality analysis revealed that FDI, economic growth, and electricity consumption strongly Granger-cause CO2 emissions. Based on these findings, the study recommends that Kuwait reduce emissions by expanding its existing Carbon Capture, Utilization, and Storage plants; capitalizing on its vast solar and wind energy; reducing high subsidies of the residential electricity scheme; and aggressively investing in energy research to build expertise for achieving electricity generation efficiency.

Ecological modernization theories suggest that it is hard to determine a priori the environmental effects of urbanization, while neoliberal doctrine advocates a positive role of globalization in developing economies especially in terms of reducing poverty and inequality. Yet, the environmental effect of globalization is not unanimous. This study employs second-generation panel regression techniques that account for heterogeneous slope coefficients and cross-sectional dependence to estimate the impacts that urbanization and globalization have on CO2 emissions for a panel of 44 Sub-Saharan Africa (SSA) countries for the period 1984–2016. Also, a causality test that considers both these issues is performed. The estimated coefficient of urbanization is positive, statistically significant, and highly consistent across different estimation techniques. The magnitude of the coefficient and level of significance are different in different econometric estimations. In most specifications, the estimated coefficient on the globalization variable is statistically insignificant. Urbanization is found to cause emissions. The environmental implications of these results are discussed with a set of policy recommendations for an environmentally better SSA region.

This study examines the effects of real income, financial development and trade openness on the ecological footprint (EF) of consumption using a panel data of leading world EF contributors during the period 1991-2012. A number of panel unit root tests confirm that the data are first-difference stationary. Results from Pedroni co-integration tests show that the variables are co-integrated. The panel dynamic ordinary least squares (DOLS) method is then employed to estimate the long run association between the variables. The results indicate a positive and significant association between ecological footprint (EF) and real income, and a negative and insignificant impact of trade openness on EF. Financial development is also observed to reduce EF. Afterwards, the group-mean fully modified ordinary least squares method is applied to check the robustness of the DOLS estimates. The findings are partially robust as only real income confirms the positive significant impact on EF. In addition, the vector error correction model supports a unidirectional causal impact running from real income to EF. Finally, findings from variance decomposition analysis and impulse response functions reveal that real income will have an increasing effect on EF for the selected countries into the future. (C) 2017 Elsevier Ltd. All rights reserved.

This study estimates the effects of the Internet and economic growth on the accumulation of social capital (measured by trust) using panel data for 19 OECD countries for the period 1985-2012. A cross sectional dependence (CD) test is performed. Having found the cross sectional dependence, a cross-sectionally augmented IPS (CIPS) unit root test is conducted to check for stationarity of data. All the variables were found first-difference stationary. Pedroni cointegration test confirms the presence of long-run relationship among the variables. This follows the application of Pooled Mean Group regression (PMG) technique to estimate the short- and long-run association between the variables. The findings suggest a highly significant negative long- run relationship between Internet usage and social capital and a positive relationship between them in the short-run. However, both long-run and short-run coefficients are small in magnitude. Economic growth stimulates social capital both in the short- and the long-run. That the Internet reduces social capital in the long-run implies that the gains in trust obtained from online connectivity were perhaps offset by the loss in the same due to decline in frequency of offline interaction caused by increasing online engagement. Economic growth stimulates activities in markets that engage into more frequent transactions between businesses that may result in increased trust. Finally, the findings of this study do not rule out the potential of including social capital issue into the digital divide policies of these countries. Keywords: Economic growth, Internet usage, OECD, panel data, social capital JEL Classifications: C23; F43; O

Based on the premise that the Internet has the potential to generate trust, this study estimates the effects of the Internet and real GDP per capita on the creation of social capital (measured by trust) for Australia for the period 1985-2013. We use ARDL bounds testing approach (Pesaran et al., 2001) to estimate the short-and long-run relationship and Granger (1969) causality test to assess the causal linkages among the variables. Findings indicate that Internet use reduces social capital in the long-run but contributes slightly to its enhancement in the short-run. There is positive significant association between the level of real GDP per capita and the stock of social capital in the long-run while the relationship in the short-run is negative and significant. No causal link is found between Internet use and social capital while a unidirectional causality running from social capital to real GDP per capita is observed. The negative association between Internet use and the formation of social capital in the long-run may occur because the trust generated through greater online interaction is outweighed by the loss in trust arising from reduced face to face interaction. (C) 2015 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.

This study estimates the short- and long-run effects of Information and Communication Technology (ICT) use and economic growth on electricity consumption using OECD panel data for the period of 1985-2012. The study employs a panel unit root test accounting for the presence of cross-sectional dependence, a panel cointegration test, the Pooled Mean Group Regression technique and Dumitrescu-Hurlin causality test. The results confirm that both ICT use and economic growth stimulate electricity consumption in both the short- and the long run. Causality results suggest that electricity consumption causes economic growth. Both mobile and Internet use cause electricity consumption and economic growth. The findings imply that OECD countries have yet to achieve energy efficiency gains from ICT expansion. Effective coordination between energy efficiency from ICT policy and existing emissions reduction policies have the potential to enable OECD countries reduce environmental hazards arising from electricity consumption for ICT products and services. Introducing green IT and IT for green are also recommended as potential solutions to curb electricity consumption from ICT use especially in the data centers. (C) 2015 Elsevier Ltd. All rights reserved.

This paper estimates the short- and long-run effects of Internet usage and economic growth on carbon dioxide (CO2) emissions using OECD panel data for the period 1991–2012. The Pedroni panel cointegration test confirms that the variables are cointegrated. Although Pooled Mean Group (PMG) estimates indicate a positive significant long-run relationship between Internet usage and CO2 emissions, the coefficient is very small and no causality exists between them, which both imply that the rapid growth in Internet usage is still not an environmental threat for the region. The study further indicates that economic growth has no significant short-run and long-run effects on CO2 emissions. Internet use stimulates both financial development and trade openness. The findings offer support in favor of the argument that OECD countries can promote their Internet usage without being significantly concerned about its environmental consequences. But the future emissions effect of Internet usage cannot be ruled out, as is evident from the variance decomposition analysis. Therefore, this study recommends that in addition to boosting the existing measures for combating CO2 emissions, OECD countries need to use ICT equipment not to simply reduce its own carbon footprint but also to exploit ICT-enabled emissions abatement potential to reduce emissions in other sectors, such as the power, energy, agricultural, transport and service sectors.