The convergence of U.S. state-level energy intensity

Burnett, J. Wesley; Madariaga, Jessica

doi:10.1016/j.eneco.2016.03.029

Cited by 64 publications

(8 citation statements)

References 31 publications

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“…We present the summary statistics in Table 5.2. Following many studies using the dynamic panel data setting in the academic literature (Bond & Caselli et al, 1996;Hoeffler, 2001;Islam, 1995;Wesley Burnett & Madariaga, 2017), we use 5-year span data to avoid business cycle fluctuations and serial correlation problem. In other words, we divide our sample into eight periods for each country (1980-1984, 1985-1989, 1990-1994, 1995-1999, 2000-2004, 2005-2009, 2010-2014, and 2015-2019).…”

Section: Methodsmentioning

confidence: 99%

Income Inequality and the Environment: Mechanisms, Empirics and Policy

Alataş

2021

Energy Policy Advancement

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Income inequality and environmental degradation are two growing threats that received significant attention from the international community at the onset of the twenty-first century. While growing concerns about income inequality have become dominant in science, policy, and society since the 1980s, environmental deterioration has been significantly accelerating since the 1950s in most countries worldwide. In this regard, the question of whether these two crises are linked becomes highly important from the environmental policy perspective as the balance of power between the poor and the rich determines the level of environmental degradation. However, despite many different theoretical and empirical studies, a clear consensus regarding the relationship between these two challenges has not yet been reached. The main objective of this chapter is to review and discuss the theoretical and empirical explanations linking income inequality and environmental deterioration by addressing some key issues. To this end, we seek to answer the following questions: how does the distribution of income affect the environment? Does environmental quality have an impact on income inequality? How should environmental policies be designed to tackle both of these challenges?

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Section: Methodsmentioning

confidence: 99%

Income Inequality and the Environment: Mechanisms, Empirics and Policy

Alataş

2021

Energy Policy Advancement

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“…Energy plays a positive and statistically significant role in economic growth. The intensity of the energy is a measure that the energy grows towards its stable state [57]. Investments in modern and energy efficient technologies and products have also affected the growth of the economy.…”

Section: Energy Intensity (Ei) = Energy/gdpmentioning

confidence: 99%

The Trends of the Energy Intensity and CO2 Emissions Related to Final Energy Consumption in Ecuador: Scenarios of National and Worldwide Strategies

Arroyo

Miguel

2019

Sustainability

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Climate change and global warming are related to the demand for energy, energy efficiency, and CO 2 emissions. In this research, in order to project the trends in final energy demand, energy intensity, and CO 2 emission production in Ecuador during a period between 2000 and 2030, a model has been developed based on the dynamics of the systems supported by Vensim simulation models. The energy matrix of Ecuador has changed in recent years, giving more importance to hydropower. It is conclusive that, if industrialized country policies or trends on the use of renewable energy and energy efficiency were applied, the production of CO 2 emissions by 2030 in Ecuador would reach 42,191.4 KTCO 2 , a value well below the 75,182.6 KTCO 2 that would be seen if the current conditions are maintained. In the same way, by 2030, energy intensity would be reduced to 54% compared to the beginning of the simulation period.Between 1750 and 2011, cumulative anthropogenic CO 2 emissions to the atmosphere were 2040 ± 310 GTCO 2 . About 40% of these emissions have remained in the atmosphere (880 ± 35 GTCO 2 ) [5]; the rest have been removed from the atmosphere and stored on land (in plants and soils) and in the ocean. People's life expectancy is threatened by climate change through the limitation of access to water, food, medical care, and land. Therefore, it is important to reduce the consumption of fossil fuels and increase the use of renewable energy in order to minimize CO 2 emissions [13].Sustainability of power systems with high renewable energy penetration rates is a topic of major interest, especially when considering the intermittency of renewable energy source (RES) production and the actual growing trend of energy consumption [6]. The transition from fossil fuels to RESs is an indispensable necessity if sustainable socio-economic systems are to be realized. RES variability now represents a major challenge when it comes to upgrading power systems. From a social and economic perspective, the RES share in meeting electricity demand has shown a steady growth [7]. The increasing renewable energy share in electricity generation as a result of several factors such as environmental constraints, technical and economic aspects, or social implications has led to a corresponding reduction in total CO 2 emissions [8].The energy return on investment (EROI) metric includes factors affecting the whole energy system that are not accounted for by the monetary costs of individual power plants (such as additional costs for the system related to distribution, intermittency of RES, etc.) [14][15][16][17][18][19][20]. The transition to new energy resources and to new energy conversion and storage devices will affect the fraction of energy reinvestment, which could have significant economic impacts [21][22][23][24][25][26]. Those RESs with a higher potential (i.e., wind, and solar) have been generally found to have a lower EROI standard (EROIst) than fossil fuels, especially when incorporating the energy costs of dealing with intermittency [9].Energy ...

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“…In fact, since there are distinct differences in economic development, demographic indicators, energy utilization efficiency, geopolitical position and wealth of energy resources among different countries, energy consumption differs conspicuously as well. Accordingly, the international differences in energy consumption have generated abundant research interest and there are lots of studies on energy intensity convergence [20][21][22][23][24]. "Convergence" means decline in the differences of environmental indicator among countries, therefore, divergence in energy intensity indicates more attention should be paid to promoting knowledge diffusion in regions with high energy intensity [25].…”

Section: Literature Reviewmentioning

confidence: 99%

“…It should be noted that the objective of this study is to investigate the regional disparities in EP and EI rather than LnEP and LnEI. Thus, solving the regression equations following Model III and Model VII, we obtain: (20) Based on Equations (19) and (20), EPD (EID) is estimated by using the original EP (EI) not the natural logarithm of EP (EI). In addition, it should be noted that EPD and EID are gauged by relative indices, that is, Gini coefficient, GE1 and GE0, as shown in Section 4.2.…”

Section: Determining the Estimated Equationsmentioning

confidence: 99%

What Contributes to Regional Disparities of Energy Consumption in China? Evidence from Quantile Regression-Shapley Decomposition Approach

Dong

Zhang

2018

Sustainability

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Given the binding provincial goals of energy intensity reduction and total energy consumption control in China, the main purpose of this study is to analyze the regional disparities of energy consumption from the perspectives of energy consumption per capita (EP) and energy intensity (EI), as well as to propose differentiated energy conservation policies. In doing so, quantile regression and regression-based Shapley value decomposition are performed in the case of 30 provinces in China during 2000-2015. The results of quantile regression specify that the impact of each determinant on EP differs distinctly at different quantiles. Income has a positive effect on EP, conversely, industrial structure, population density and transportation infrastructure have negative effects on EP. Similarly, the effect of each influencing factor on EI presents distinct dynamic varying process at different quantiles. Industrial structure, FDI and technological progress have significantly negative effects on EI, while energy mix has a positive effect on EI. Furthermore, based on the results of median regression, the assessment of contributions of individual variables to regional disparities of energy consumption per capita and energy intensity (i.e., EPD and EID) is conducted by the Shapley value decomposition method. It is found that inequality in income level is the most important reason for EPD and its annual average contribution rate is 70%. In addition, differences in population density play an important role in explaining EPD, while the inequality in transportation infrastructure contributes little to EPD. By contrast, EID is mainly due to differences in technological progress, whose annual average contribution rate is up to 46%. Following technological progress, the inequalities of FDI and energy mix are also important factors accounting for EID. On the whole, the contribution of industrial structure or regional factors is always small. Then, this study explores the provincial energy-saving development path based on the actual conditions of all provinces.

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The convergence of U.S. state-level energy intensity

Cited by 64 publications

References 31 publications

Income Inequality and the Environment: Mechanisms, Empirics and Policy

Income Inequality and the Environment: Mechanisms, Empirics and Policy

The Trends of the Energy Intensity and CO2 Emissions Related to Final Energy Consumption in Ecuador: Scenarios of National and Worldwide Strategies

What Contributes to Regional Disparities of Energy Consumption in China? Evidence from Quantile Regression-Shapley Decomposition Approach

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