A link between productivity, globalisation and carbon emissions: evidence from emissions by coal, oil and gas.

Although much has been discussed about the link between renewable energy, globalisation and carbon dioxide (CO2) emissions, yet the impact of total factor productivity (TFP) on CO2 emissions is less known in the existing literature. Therefore, the present study considers TFP as one of the determinants of CO2 as it is believed that technological enhancement plays an essential role in improving the environmental quality by raising efficiency in energy use and pollution treatment. In contrast, it may also have unfavourable impacts. In particular, this study analyses how TFP along with renewable energy and globalisation affect the aggregate and source of CO2 emissions (oil, coal and gas) in the case of top ten carbon emitters from the developing economies over the period 1980-2018. To achieve the above objective, we use the second-generation panel unit root, cointegration and causality tests. We also implement a cross-sectional autoregressive distributed lag model (CS-ARDL) to find the long-run and short-run coefficients. Findings from panel cointegration tests show that there exists a significant long-run relationship between renewable energy, non-renewable energy, globalisation, total factor productivity and CO2. Moreover, findings show that renewable energy consumption has a negative and significant impact on CO2 emissions while non-renewable energy consumption significantly increases the CO2 at aggregate and disaggregated levels. Further, our results confirm that TFP increases the CO2 emissions whereas globalisation decreases CO2. From the policy point of view, TFP growth needs to be accelerated to a higher level so that it enables low carbon growth. The slower TFP growth may enhance output which requires more energy and produces more emissions. Thus, there should be a promotion of emissions' reducing technology along with better TFP growth. Also, our findings recommend that CO2 in sample countries can be reduced through promoting low carbon technology, and globalisation.

Impact of climate change on cereal production: evidence from lower-middle-income countries.

This study empirically examines the impact of climate change on cereal production in selected lower-middle-income countries with a balanced panel dataset spanning 1971-2016. The study uses average annual temperature and rainfall to measure climate change. Besides this, CO2 emissions, cultivated land under cereal production, and rural population are used as the control variables. Second-generation unit root tests, i.e., CIPS and CADF, are used to test the stationarity of the variables. Feasible generalized least square (FGLS) and fully modified ordinary least square (FMOLS) models are used to achieve the objective. Pedroni cointegration test confirms the presence of cointegration between cereal production and climate change variables. The findings show that a rise in the temperature reduces cereal production in lower-middle-income countries. In contrast, rainfall and CO2 emissions have a positive effect on cereal production. For robustness purpose, the Driscoll-Kraay standard regression and dynamic ordinary least square (DOLS) models have also found similar results. Dumitrescu-Hurlin test has found the bidirectional causality of cereal production with temperature and CO2 emissions. Also, unidirectional causality is running from rainfall and rural population to cereal production. The adverse effects of temperature on cereal production are likely to pose severe implications for food security. The paper recommends that governments of the sample countries should research and develop heat-resistant varieties of cereal crops to cope with the adverse effects of temperature on cereal production and ensure food security.

Do renewable energy and globalization enhance ecological footprint: an analysis of top renewable energy countries?

This paper aims at estimating the dynamic impact of renewable and non-renewable energy consumption, globalization, urbanization, and economic growth on the environmental quality. Unlike previous study, this study used multi-dimensional indicator of environmental quality that is ecological footprint. Given the importance of renewable energy, a sample of top renewable energy consuming countries has been selected for analysis spanning the period 1991-2016. The analysis is carried out in panel data framework that considers the issues of cross sectional dependence and heterogeneity. The results of cointegration test show the existence of long-run equilibrium relationship among the variables. The long-run elasticity of pooled mean group shows positive impact of economic growth and non-renewable energy consumption on ecological footprint while negative impact is observed in case of renewable energy consumption, globalization and urbanization. The sensitivity of long-run elasticity has been checked with the help of fully modified ordinary least square and dynamic ordinary least square. Based on empirical findings, some policy implication has also been provided.