• Energy Research
• Open Access close
• Closed Access close
• Embargo close
• 8. Economic growth close
• PK close
• BG close

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.

Abstract Energy poverty has evolved as an important issue of research from academic and policy perspectives during the last two decades. The energy poverty estimates exhibit widespread variations across regions, methodologies and datasets, making the task of energy and development policies challenging. The variations in energy poverty estimates necessitate a systematic and rigorous analysis of these empirical studies to obtain a true measure of energy poverty. The present study conducts a meta-analysis of 30 studies and 103 estimates of energy poverty. On average, 71.1 percent of the population in the overall sample studies has been identified as energy poor. High I-square statistic values suggest heterogeneity bias in the sample studies; therefore, analysis at the subgroup level has been conducted. Meta-regression analysis of overall sample and subgroups has identified type of methodology, citations, impact factor of the journal, regional dummies, average key crude oil price and gross domestic product as significant factors that explain heterogeneity in the energy poverty effect sizes. We recommend inclusion of local and regional factors in assessment of energy poverty for developing a uniform methodology to assess energy poverty across developing economies.

A key factor in social development and sustainable urban expansion is the establishment of sustainable and affordable transport systems. This study aims to investigate the impact of transport infrastructure investment on environmental degradation and economic growth and to test the validity of the EKC hypothesis in China, India, Russia, and Japan over the period 1995-2020. The results show that GDP has a significant positive effect, and GDP2 and GDP3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U-shaped EKC hypothesis in selected emerging Asian economies. Rail infrastructure investment has significant adverse effects, while road infrastructure investment and aviation infrastructure investment have significant positive effects on environmental degradation. Likewise, the impact of investment in transport infrastructure system (roads, rail, and aviation) on economic growth is positive and statistically significant. Country-level estimates confirm the validity of the inverted U-shaped EKC hypothesis in China, India, and Russia, while the N-shaped EKC is only valid in Japan. Investments in rail infrastructure based on modern rail systems that run on electricity are believed to be less polluting in the transport mix, help create sustainable and safe transport systems, and reduce emissions at the urban and intercity levels in emerging Asian countries. In addition, the growing impact of free trade on environmental pollution should be strengthened to harmonize the strict enforcement of environmental conditions dominated by trade agreements.

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress.

Abstract This article analyzes the CFTC's Disaggregated Commitments of Traders (DCOT) Report to get more insights into the behavior of different traders during the 2008 oil bubble. The analysis shows that: (1) the Money Manager category perfectly played the oil bubble, got in early and started selling shortly before the bubble peak; (2) the Producer/Merchant/Processor/User category and the Nonreportable category were covering their short positions into the peak of the bubble; (3) the Swap/Dealer category benefited while the price of oil was rising, but incurred heavy losses as the price of oil collapsed; (4) we find no indications of speculation by any group of traders via the positive feedback trading or rational destabilization; and (5) we do, however, criticize the commercial hedgers for failing to arbitrage the soaring oil prices in 2008.

Abstract Although the “resource curse” hypothesis has been supported by many empirical studies focusing on the transnational and regional levels, there has always been a point of contention about the proper method of estimating and selecting natural resource indicators in literature. This paper proposes a mixed estimation method for panel data of 10 typical oil and gas resource-based cities in China from 1998 to 2015. The results show that resource industry agglomeration can mirror the distribution and dependence on the resource industry by location rather than by merely measuring the influence of the relative scale of resource extraction on economic growth. Using resource industry agglomeration as the main explanatory variable for regional economic growth verifies the resource curse hypothesis and shows the nonlinear characteristics of the negative correlation between resources and economic growth. Despite mostly similar indicator parameter estimates, marked differences exist in measured effects for material capital investments and technological innovation investments. The result of using resource industry agglomeration as the main explanatory variable is basically consistent with the economic theory and is more in line with observed reality than the alternative indicator. The research conclusions can provide evidence and data for index selection in the studies on the mediating effect of resource curse transmission and international comparison.

Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.

Globalization has resulted in several technical advancements, including the ability to connect people all over the world and drive the economies with higher agricultural output. With agricultural productivity expanding quickly, the negative impact of globalization on environmental degradation is being disregarded. Rapid agricultural expansion and globalization have resulted in significant increases in energy consumption and CO2 emissions. The primary purpose of this research is to assess the role of Pakistan’s massive agriculture industry in encouraging or discouraging CO2 emissions under Globalization scenario. Therefore, we applied Non-linear Autoregressive Distributive Lag Nonlinear Autoregressive Distributed Lag model from 1971 to 2021. Our results showed that in presence of globalization, agricultural production shows asymmetries in case of positive and negative shocks. A positive shock in Agricultural production increased the CO2 emissions while negative shock in agricultural production decreased CO2 emissions. Furthermore, GDP, energy consumption and economic globalization have positive association with economic globalization while on the other hand, surprisingly trade and urbanization in the presence of globalization have negative association with CO2 emissions. Environmental deterioration due to greenhouse emissions causes climatic variation in the economy and several mitigation strategies are required on sustainable basis in Pakistan. So, our study recommends that farmers of Pakistan should adopt organic farming this will help to reduce CO2 emissions.