An empirical analysis of energy intensity and the role of policy instruments

This study investigates the dynamic relationships between carbon emission, urbanization, energy consumption, and economic growth in a panel of 42 Asian countries for the period 2000–2014 using dynamic common correlated effects panel data modeling. This study employs second generation cross-sectional Pesaran (J. Appl. Econom., 2007, 22(2), 265-312) panel unit root, Westerlund panel cointegration tests (Econom. Stat., 2007, 69(6), 709-748), and Pesaran’s (Econometrica, 2006, 74(4), 967-1012) common correlated effects mean group estimation technique. These approaches allow for cross-sectional dependence, and are robust to the presence of common factors, serial correlation, and slope heterogeneity. The Common Correlated Effect Mean Group test reveals a high average coefficient of 0.602 between carbon emission and energy consumption while low coefficients of 0.114 and 0.184 for the pairs of carbon emission-urbanization and carbon emission-GDP, respectively for the panel as a whole, suggesting a cointegration between carbon emission, urbanization, energy consumption, and economic growth. The results indicate that there is relatively high carbon emission especially for highly populated and geopolitical risk Asian countries in the short run. Findings reveal long run relationships between the variables, which is attributed to the on-going carbon taxation and energy prices. Our results are robust to PMG-ARDL estimator. Overall, these findings cast important implications on renewable energy policy and urban planning insights for the policymakers.

Impact of heat and electricity consumption on energy intensity: A panel data analysis

This paper, by applying the recent panel data error‐correction modelling developed by Gengenbach et al., Panel error correction testing with global stochastic trends, 2008 University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 tests the validity of the Feldstein–Horioka puzzle (1980) in a panel of 27 African countries for the period 1965–2015. Unlike the existing studies in the literature, this paper, for the first time, addresses several important panel data econometric issues such as slope heterogeneity, cross‐section dependence, unobservable common factors, non‐stationarity and endogeneity that would yield inconsistent and biased estimates of the parameters of interest. Unlike the previous residual‐based error‐correction modelling that has low power, the Gengenbach et al., Panel error correction testing with global stochastic trends, 2008, University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 estimator explicitly considers structural dynamics in modelling a cointegrated panel that allows for the presence of non‐stationary unobserved common factors. As the GUW modelling depends on the Pesaran Common Correlated Effects Mean Group Estimator (CCEMG; 2006) and the Chudik and Pesaran Dynamic Common Correlated Effects Mean Group Estimator (DCCEMG; 2015), we report the results based on these estimators. The econometric exercises performed in the paper show that slope heterogeneity; cross‐section dependence and non‐stationarity are present in the panel data sample used in the estimation. Estimations yield a relatively low magnitude of the savings retention coefficient for the panel members included in the study with a negative error‐correction term that is statistically significant at the individual and panel levels. The empirical evidence rejects the presence of the Feldstein–Horioka puzzle in the panel of 27 African countries studied.

Testing the environmental Kuznets curve hypothesis across the U.S.: Evidence from panel mean group estimators

We estimate the Food–Energy–Water (FEW) nexus for 21 countries worldwide, with data available from year 1990–2000 in order to investigate the relationship between food production and two scarce resources: energy and water. Food production is proxied by four alternative variables: The index of agricultural production, the index of crops production, the index of livestock production and the value added from agriculture. Water and energy as independent variables are controlled by methane and nitrogen emissions, capital, labor and five versions of fertilizer proxy: pesticides, insecticides, fungicides, herbicide and other. For robust estimation, we have perused a number of standard and novel panel estimators such as the common correlated effects mean group estimator and the augmented mean group estimator (AMG). These estimators can account both for non-stationarity and the cross-dependence problems. Based on standard estimators such as the generalized least squares estimator or the Arellano-Bond generalized method of moments GMM, they reveal the existence of a significant FEW nexus while the mean group estimator, the group mean DOLS estimator, the common correlated effects and the augmented mean group estimator (AMG) do not yield significant coefficients for water and energy. In the latter models only labor and pesticides are significant at 5%. Also, the unobserved total factor productivity appears significant at 5% under the AMG estimation. When significant, energy and water elasticities ranged from − 0.001 to − 0.256 and from − 0.014 to − 0.084 respectively.

The issue of increased renewable energy consumption has been widely debated, and this has become a central energy policy concern for developing and developed countries. The existing literature provides evidence that there is a positive relationship between energy consumption and economic growth in developed economies. However, findings in respect of developing/emerging economies remain inconclusive. Thus, this paper aims to investigate the impact on renewable energy consumption on economic growth by controlling other macroeconomic variables for regions of Sub-Saharan Africa (East, Central and West) covering the 1990–2018 sample period. For this purpose, common correlated effects mean group estimator (CCEMG) and Dumitrescu-Hurlin Granger causality test approach are used to consider both cross-sectional dependency and cross-country heterogeneity across countries. The CCEMG result indicates that an increase in renewable energy consumption led to reduction in economic growth even when the sample is analyzed based on geographical locations as East, West, and Central Africa. Granger causality results validate the feedback hypothesis for only Central Africa; the growth hypothesis is supported for East and West Africa. The empirical results suggest that energy planners, governments, and policy makers must act together to increase the renewable energy consumption share in her energy mix to promote economic growth for regions of Sub-Saharan Africa.

Purpose The purpose of this paper is to investigate the problem of fiscal sustainability for a panel of developing Asian economies. Design/methodology/approach In this study, cross-section dependence and heterogeneity are controlled while estimating the fiscal reaction function, which shows how governments react to the accumulation of public debt. The study employs the common correlated effects mean group estimator in Pesaran (2006) for a panel of 22 developing Asian economies for the period 1999‒2017. Findings It is found that the fiscal sustainability issue in the region is not so benign as in previous studies. Overall, fiscal policy is unsustainable, even for the nonlinear fiscal rule. Country-specific long-run coefficients are also examined in the study. Research limitations/implications The findings show that many developing economies in the region could not satisfy the intertemporal budget constraint, which raises concerns about debt sustainability in the area, especially for the post-crisis period. Originality/value This study investigates whether governments can maintain the sustainability of public finances in the long-run, if the ratios of public debt over GDP and primary deficit over GDP continue their recent problematic trends. Another novelty is controlling for heterogeneous effects among the countries in the region to give a more precise picture of debt sustainability. The empirical evidence also supports that insolvency risk can occur at low levels of public debt.

This paper aims to define the effects of military expenses and renewable energy consumption on carbon dioxide emissions for the ten countries with the highest military expenses, namely, Saudi Arabia, Israel, Russia, the USA, South Korea, India, France, Australia, China, and the UK from 1993 to 2017. The research applied the common correlated effects mean group estimator (CCEMG), dynamic CCEMG, and cross-sectional augmented autoregressive distributed lag (CS-ARDL) approaches. These dynamic techniques elucidate slope heterogeneity and cross-sectional dependency and solve the problem of unit root bias. It is found that the environmental Kuznets curve (EKC) hypothesis does not apply for this region. The findings demonstrate that military expenses increase carbon dioxide emissions; thus, the treadmill theory of destruction is valid for the panel of these countries, and it is also found that the consumption of sustainable energy decreases CO2 emissions. This suggests that a reduction in pollution can be achieved by increasing sustainable energies in the use of military vehicles to decrease emissions. Further important policy implications for the 10 countries with the highest military expenses are provided at the end of the paper.

This article introduces a new Stata command, xtmg, that implements three panel time-series estimators, allowing for heterogeneous slope coefficients across group members: the Pesaran and Smith (1995, Journal of Econometrics 68: 79–113) mean group estimator, the Pesaran (2006, Econometrica 74: 967– 1012) common correlated effects mean group estimator, and the augmented mean group estimator introduced by Eberhardt and Teal (2010, Discussion Paper 515, Department of Economics, University of Oxford). The latter two estimators further allow for unobserved correlation across panel members (cross-section dependence).

World trade suddenly plummeted in the last quarter of 2008 after the bankruptcy of Lehman brothers and the subsequent meltdown in financial markets. Even if the following recovery was impressive, trade growth is now noticeably below trend. The anaemic momentum in global export volume questions whether the financial crisis has permanently changed the trade landscape. In this paper, we address trade elasticities in some Central and Eastern European economies by estimating a standard import function equation. We employ a dynamic panel Auto Regressive Distributed Lag model with the Common Correlated Effects Mean Group estimator to cope with cross-sectional dependence. The model is fit on a sample of eight countries over the period 1995:q1–2017:q1. First, we estimate long-run import elasticities with respect to GDP and the relative import price. Then, we discriminate between booms and slowdowns. Results confirm imports respond differently over the business cycle.

Canada is one of the top energy users and CO2 emitters among the OECD countries. However, energy intensity has been declining, on average, by about 1.4 percent since 1980. In this paper, we use the Fisher Ideal Index to determine the contribution of changes in the composition of economic activities and efficiency to a decline in energy intensity in Canada at national, provincial, and industry levels. We also apply panel data estimation methods to further investigate the factors driving energy intensity, efficiency and activity indexes for the period 1981-2008. We test for endogeneity as well as cross-section dependency in the provincial data and control for factors such as climate, policy, and energy endowment. The national and provincial decomposition results suggest that most of the reduction in energy intensity has occurred mainly due to improvements in energy efficiency rather than shifts in economic activities. Within the industry, while energy intensity has declined significantly in manufacturing, it has remained stable in transportation, utilities, and construction, and increased significantly in oil extraction and mining industries. The provincial panel regression results indicate that energy intensity is higher in provinces with higher average incomes, faster population growth, colder climate, and a higher capital-labour ratio, and lower in provinces with higher energy prices and higher investment. The industry panel regression results show that investment has contributed to energy efficiency in utilities and mining and to a shift away from energy-intensive activities in manufacturing and transportation industries. Technological advances have been most effective in increasing energy efficiency in construction and utilities and in decreasing energy-intensive activities in manufacturing industries. The results indicate that although efficiency contributes to a reduction in energy intensity in Canada, increasing activity in energy-intensive industries, such as oil and mining, partially offsets the efficiency gains in other industries.

Energy efficiency in the framework of the energy trilemma will guide to energetic policies focused on economic growth and development of the Developing Countries. Many of the International Organizations: such as the International Energy Agency (IEA) agreed to promote the rational use of the expressed sources in reducing energy intensity to mitigate accelerated climate change through the reduction of CO2 emissions as agreed at COP21 in Paris. The transition from Oil to Natural Gas in Argentina was marked in the years 1994 - 1999, because of an intense productive activity, causing an exponential increase in consumption. Although, if the Natural Gas less pollutant than oil, currently, the change in the matrix, did not report a reduction of C02 as expected due to the lack of technology and the rational use of these sources as energy. This implied that currently, the share of fossil fuels in the energy matrix more than 84 % above dealer, with nearly 51.1 % of Natural Gas. Therefore, the study focuses on the energy security of Argentina's growing energy demand and environmental Commitments; through, increased energy efficiency with the assumptions in reducing Energy Intensity towards a more sustainable energy trilemma to the medium and long term. It is worth mentioning that the reduction of the total demand of a country is associated with levels of energy efficiency. In our case, by 2035 an increase in energy efficiency of 19% could we reduce demand 36%; that is, a reduction in energy intensity of 29 % compared to 2015. The scenarios with reduction in energy intensity by 2035 are 1 %, 1.5 % and 2 % annually, which will involve a reduction in the consumption of primary sources and consequently a reduction in CO2 emissions of 5.3%, 14.4% and 20.2% respectively in each case. In this way, we could diversify the energy matrix progressively, towards more sustainable developments. To project the demand for primary sources from 2015 to 2035, it is necessary to design a macro-econometric model, based on an annual GDP growth of 2.77% and the projection of energy intensity according to 3 proposed scenarios. Then the relationship population country / world, will enable us to project the maximum allowable CO2 emissions by 2035, with a commitment not to increase the temperature more than 2 °C by 2100 and the commitment of Argentina with COP21 to reduce 15% CO2 emissions by 2030. Finally, the overall objective of the research will be to adjust energy policies of the country in the medium and long term through of the Evolution of Energy Matrix Primary versus the Evolution of Energy Efficiency, under the precept of securing the demand and comply with COP 21 under a more sustainable energy trilemma.

The impact of natural resources on technology innovation from cross-country panel data: A comparative analysis and policy-level insights

Based on threshold regression models, this paper analyzes the effect of economic growth on energy intensity by using panel data from 21 developed countries from 1996 to 2015. Results show that a 1% increase in GDP per capita can lead to a 0.62–0.78% reduction in energy intensity, implying economic growth can significantly reduce energy intensity. The extent of the reduction in energy intensity varies depending on the economic development stages represented by key influencing factors including energy mix in consumption, urbanization, industrial structure, and technological progress. Specifically, the reduction in energy intensity due to economic growth can be enhanced with relatively more renewable energy consumption and more urban population until a threshold point, where the enhancement disappears. On the other hand, the extent of the energy intensity reduction due to economic growth can be weakened with relatively more tertiary industry activities and more research and development (R&D) investment in an economy until a threshold point, where the weakening cannot continue. However, compared to the early stages represented by the low ends of renewable energy consumption, urban population, tertiary industry activities, and R&D investment, the later stages represented by the high ends of these key factors after a threshold show the weakened effect of economic growth on the decline of energy intensity. Hence, when an economy is well-developed, policy makers are advised to put fewer expectations on the role of economic growth to reduce energy intensity, while pursuing relatively cleaner energy, greater urbanization, more tertiary industry activities, and advanced technologies.

Environmental pollution and climate warming have become global issues affecting human life, and the burning of fossil fuels is a major source of greenhouse gases. Ownership structure is related to energy efficiency and a change in ownership structure has a significant potential for energy saving. However, few papers have studied the impact of ownership structure on energy intensity from the perspective of technological innovation in the past. Based on panel data from 29 Chinese provinces from 2005 to 2020, we systematically investigate the impact of industrial department ownership structure on energy intensity and study the function of technological innovation in this relationship from the perspective of ownership heterogeneity by using empirical models including ordinary least squares, two-way fixed effects and random effects. The empirical results of this study reveal three findings. First, as the proportion of state-owned industrial enterprises increases by one unit, energy intensity increases by 0.803 units. However, as the proportion of Hong Kong, Macao and Taiwan-invested industrial enterprises, private industrial enterprises and foreign-invested industrial enterprises increases by one unit, energy intensity decreases by 0.847 units and 0.549 units. Second, R&D activities, FDI, capital intensity and exports can significantly reduce energy intensity, but imports can increase energy intensity. Third, the ownership structure can affect energy intensity by influencing R&D expenditure. The increase in the proportion of state-owned industrial enterprises can reduce R&D expenditure, but results in the opposite situation in private firms. Foreign-invested enterprises can reduce energy intensity by making more use of the parent company’s technology. Based on the above empirical results, we propose suggestions to reduce energy intensity, which can provide reference for government to formulate more effective energy policies and realize sustainable development.