Elsevier

Energy

Volume 215, Part B, 15 January 2021, 119147
Energy

Do economic development and human capital decrease non-renewable energy consumption? Evidence for OECD countries

https://doi.org/10.1016/j.energy.2020.119147Get rights and content

Highlights

  • We answer the question if development and knowledge will reduce the consumption of polluting energy.

  • We use threshold regression and second-generation cointegration techniques.

  • Development does not decrease the consumption of non-polluting energy, but human capital does.

  • We assess the role of globalization, urbanization and services on non-renewable energy consumption.

Abstract

The false hope that economic development would lead to a decrease in fossil sources’ energy consumption can be an obstacle to fighting global warming. Is it realistic to expect that more knowledge will lead public policymakers to take more decisive action to mitigate climate change’s adverse effects? This research attempts to answer both premises using data for developed countries with high human capital levels: 27-member countries of the Organization for Economic Cooperation and Development-OECD during 1980–2015. Access to energy and that it is non-polluting is raised as a goal of the Sustainable Development Goals. We combine linear and non-linear models: we specifically employ threshold regressions and second-generation cointegration techniques, FMOLS, and causality. Our results are disappointing for the first premise: economic development does not reduce energy consumption from fossil sources. However, human capital does decrease the consumption of non-renewable energy. In order to capture current trends in economies, we include the globalization index, the urbanization rate, and services. The results of the cointegration tests suggest the existence of a long-term relationship between the variables. Our results indicate that the human capital index and globalization are the last hope to promote the transition to a more sustainable energy matrix in developed countries.

Introduction

In recent years, there has been growing concern around the world among academics and policymakers about the negative consequences of excessive consumption of energy from fossil sources. The importance of the transition to a renewable energy matrix is formulated in the seventh Sustainable Development Goal (SDG7). Understanding the factors that determine non-renewable energy consumption patterns contributes to improving the design and application of environmental mitigation policies. Various researchers have noted that a relevant part of reducing polluting gas emissions requires the reduction of non-renewable energy consumption [[1], [2], [3]]. Although the environmental pollution that comes from the consumption of fossil energy impacts developed and developing countries, rich countries consume more energy and consequently are the ones who pollute the most. The commitment to achieve sustainable development requires all countries’ effort, but developed countries could lead to the reduction of polluting energy consumption. Likewise, developed countries do not face a trade-off between applying policies to increase economic growth or protect the environment. In this scenario, the search for the causes of non-renewable energy consumption requires greater interest to reach practical solutions. Recent literature has identified some patterns of non-renewable energy consumption; however, the findings are not conclusive.

Based on the environmental Kuznets hypothesis [4,5], various theoretical and empirical investigations predicted that economic development would lead to a reduction in environmental degradation [6]. However, this hypothesis was not necessarily verified after several countries reached a high development threshold. On the contrary, the two largest economies globally (the United States and China) are the most polluters on the planet. Industrial activity in both countries suggests that the demand for energy from fossil sources will increase in the coming years [7]. There is a broad consensus on the need to raise awareness of the importance of the ozone layer, forests, clean air, and soil sustainability as societies have more analytical tools, broad evidence, and reliable data. Recent research has shown that applied knowledge, which relies on advanced human capital, such as technology and innovation, can reduce non-renewable energy consumption [8]. Consequently, improvements in knowledge will reduce air, water, or soil pollution [[9], [10], [11]]. This fact supports the hypothesis that the increase in the stock of human capital should reduce non-renewable energy consumption.

Despite efforts by governments, companies, and scientists to generate clean energy, data on energy consumption suggests that fossil sources’ energy consumption is still in high demand. According to statistics from the International Energy Agency [12], the consumption of non-renewable energy in OECD countries went from 113.61 metric tons per capita in 1984 to 117.65 in 2014. Much of this energy is generated from conventional sources, especially from oil, coal, and gas. As long as non-renewable energy continues to be a source of economic growth [[13], [14], [15], [16]], it is difficult or unrealistic to think that the consumption of this energy is reduced only for environmental reasons. The dependence on this energy source in the productive processes associated with food and agriculture, manufacturing, transportation, electricity, and trade leads to non-renewable resources that continue to have strong demand [[17], [18], [19]]. In theory, the underlying logic suggests that increases in human capital would lead to a better understanding of the importance of environmental sustainability and energy sustainability [20,21].

A detailed review of the empirical literature leads to classifying the variables that affect energy consumption from polluting sources into three groups according to the level of influence: low, medium, and high. This process allows identifying the two best predictors of polluting energy consumption in a sample of developed countries. The choice of OECD countries to verify our hypotheses facilitates obtaining consistent estimators due to reliable data availability. They have high economic development levels, and the set of institutional and social arrangements can be reflected in the human capital index. Therefore, the results obtained allow a coherent answer to whether the increase in per capita income and the human capital index reduces environmental pollution in the long term, as indicated by the EKC hypothesis. In practice, although this group of countries has similar characteristics in institutionality, economic and social development, and productive specialization, specific nuances differentiate them between them. Geographical location, inequality, and the degree of social cohesion are some examples of this. Consequently, the sample of 27 countries was classified into three groups. The first group is the extremely high-income countries. The second group is the high-income countries. The third group is the upper-middle-income countries.

The choice of the econometric strategy is proposed to achieve the research’s objective and is based on the previous empirical literature. In order to compare the possible differences in results due to the methodology, we use linear and non-linear estimation techniques. First, we employ threshold regressions developed by Hansen [22]; where we assess the human capital index’s impact and output on non-renewable energy consumption below and above the threshold. The use of this methodology allows the EKC to be verified implicitly in OECD countries. The threshold variables are the output, the human capital index, and the globalization index. Second, the dependence on the cross-sections [[23], [24], [25]] and the heterogeneity in the slope [26] conditions the estimation of unit root tests [25,27,28], and second-generation cointegration techniques [29]. The use of Fully Modified Least Squares (FMOLS) allows obtaining long-term estimators. The second-generation tests are based on less restrictive assumptions concerning first-generation cointegration tests. Similar recent research has used linear and non-linear techniques to search for the factors that determine non-renewable energy consumption patterns [13,30,31]. Finally, we use the causality test formalized by Dumitrescu & Hurlin [32] based on the Granger [33,34] causality test. In all regressions, we added three covariates related to recent trends in OECD countries: high globalization and urbanization levels, and strong specialization in services.

Our results contribute to the debate on the factors that determine the consumption of non-renewable energy in a sample of developed countries, facilitating the verification of whether knowledge and economic development constitute a mechanism for solving the problem of environmental pollution. First, our findings show that economic development is not a solution to the pollution problem. Simultaneously, the human capital index, the globalization index, and services can reduce non-renewable energy consumption in OECD countries. Second, we find the existence of a long-term equilibrium relationship among non-renewable energy consumption, output, human capital index, globalization index, urbanization rate, and services. The association is stable in the global sample and for the three subsamples. The FMOLS results show that the human capital index, the globalization index, and services reduce the consumption of non-renewable energy in the sample of countries analyzed. Finally, we find a causal relationship that goes from the non-renewable energy consumption to the output. The globalization index and non-renewable energy consumption have a causal relationship in both directions. Our results show that knowledge and globalization are policy mechanisms to apply policies to reduce energy consumption from fossil sources. Research and development and innovation processes associated with human capital and the reduction of input costs associated with globalization can mitigate global warming’s adverse effects.

The rest of the article is organized as follows. The second section contains a review of the previous literature on non-renewable energy consumption focusing on linear and non-linear methods. The third section describes the statistical sources. The fourth section presents the econometric strategy. The results are analyzed and discussed in the fifth section. Finally, the conclusions of the work and the political implications appear in the sixth section.

Section snippets

Literature review

In recent years, the debate on countries’ mechanisms to reduce emissions of polluting gases has increased. Several recent empirical studies have noted that one of the largest greenhouse gas emissions sources comes from energy consumption from polluting sources [[35], [36], [37], [38]]. The theoretical and empirical understanding of the factors that determine non-renewable energy consumption constitutes the first part of a broader global warming mitigation strategy [39,40]. In this context, a

Statistical sources

The research is carried out for 27 (n=27) OECD member during the period 1980–2015 (T=36). Our research uses cross-sectional and temporal statistical information from two databases. The dependent variable is the consumption of non-renewable energy measured as energy consumption (Kg of oil per capita). The independent variables are economic growth taken as the real per capita output and the human capital index. The real per capita output and non-renewable energy consumption come from the World

Econometric strategy

The advantage of combining temporal and cross-sectional data is that it allows capturing the variability of both dimensions in the same model [81,82] and obtaining more consistent estimators. In this context, we propose a set of panel data estimates to answer the premises on whether economic growth and human capital reduce the consumption of non-renewable energy, the leading cause of greenhouse gas emissions. First, we propose a threshold model, where the dependent variable is the logarithm of

Empirical analysis

The research objective is to examine whether output and human capital are mechanisms for reducing non-renewable energy consumption using a sample of developed countries: 27 OECD countries. Following the underlying logic of the Environmental Kuznets Curve, the existence of a possible threshold, where the problem of contamination is solved with economic and social development, requires a broad set of quantitative techniques that offer more robust results. To that end, we incorporate a threshold

Policy implications and conclusions

The seventh Sustainable Development Goal is aimed at ensuring that the population has affordable and clean energy. Incentives for policymakers to promote the transition from polluting energy consumption to clean energy require identifying the factors that determine current consumption patterns. This research examines whether when countries achieve high per capita income levels and are more knowledgeable, they consume less non-renewable energy. The consumption of energy from fossil sources is

Credit author statement

Rafael Alvarado: Supervision, Estimates. Qiushi Deng: Writing- Reviewing, Data. Brayan Tillaguango: Data curation, Software, Estimates. Priscila Méndez: Visualization, Initial draft. Diana Bravo: Literature review. José Chamba: Conceptualization. María Alvarado-Lopez: Editing. Munir Ahmad: Methodology, Software.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors express their gratitude with the Club de Investigación de Economía. Loja, Ecuador.

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