Influential factors of carbon emissions intensity in OECD countries: Evidence from symbolic regression

Pan, Xiongfeng; Uddin, Md. Kamal; Ai, Bowei; Pan, Xianyou; Saima, Umme

doi:10.1016/j.jclepro.2019.02.195

Cited by 85 publications

(29 citation statements)

References 52 publications

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“…To summarize, literature has highlighted the positive benefits of renewable energy consumption to OECD economic growth, whereas results also contradict this claim and reinstate the need to focus on non-renewable energy source to support industrial output. Further, literature considers public policy measures to be extremely important for promoting utilization of green energy in OECD countries (Pan et al, 2019…”

Section: Literature Reviewmentioning

confidence: 99%

How renewable energy consumption contribute to environmental quality? The role of education in OECD countries

Zafar

Shahbaz

Sinha³

et al. 2020

Journal of Cleaner Production

312

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Designing a comprehensive policy framework for ascertaining sustainable development is a problem faced by most of the countries around the globe, and the developed nations are no exception to that. Environmental awareness-oriented policy design for achieving sustainable development goals is a challenge for the developed nations, and there lies the contribution of this study. This study analyzes the impact of renewable energy on carbon emissions, in presence of education, natural resource abundance, foreign direct investment, and economic growth for the Organization for Economic Cooperation and Development countries over the period of 1990-2015. Second generation methodologies are adapted for the empirical estimation. The results show the stimulating role of renewable energy consumption in shaping environmental quality. Education declines carbon emissions. Natural resource abundance and foreign direct investment deteriorate environmental quality. Moreover, the time series individual country analysis also confirms that renewable energy has a positive impact on economic growth. The heterogeneous causality analysis reveals the feedback effect, i.e., bidirectional causal associations among carbon emissions, education, and renewable energy consumption. This empirical evidence suggests that countries should increase investment in education and renewable energy sectors and plan for research and development in renewable energy for ensuring environmental sustainability.

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Section: Literature Reviewmentioning

confidence: 99%

How renewable energy consumption contribute to environmental quality? The role of education in OECD countries

Zafar

Shahbaz

Sinha³

et al. 2020

Journal of Cleaner Production

312

View full text Add to dashboard Cite

show abstract

“…This feature provides a quick overview of the most relevant interactions between variables and can help to identify new unknown links. As a result, due to its suitability to find patterns in large datasets and to handle complex modelling tasks, this empirical modelling approach is attracting researchers from different areas (Alexandridis et al, 2017;Álvarez-Díaz et al, 2009;Pan et al, 2019). Koza (1992) used GP to estimate SR. One of the first applications of GP in economic research is that of Koza (1995), who used this procedure to assess the non-linear interactions between the price level, gross national product, money supply, and the velocity of money.…”

Section: Applications Of Gp In Economic Researchmentioning

confidence: 99%

Unemployment expectations: A socio-demographic analysis of the effect of news

et al. 2019

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In this study, we evaluate the effect of news on consumer unemployment expectations for sixteen socio-demographic groups. To this end, we construct an unemployment sentiment indicator and extract news about several economic variables. By means of genetic programming we estimate symbolic regressions that link unemployment rates in the Euro Area to qualitative expectations about a wide range of economic variables. We then use the evolved expressions to compute unemployment expectations for each consumer group. We first assess the out-of-sample forecast accuracy of the evolved indicators, obtaining better forecasts for the leading unemployment sentiment indicator than for the coincident one. Results are similar across the different socio-demographic groups. The best forecast results are obtained for respondents between 30 and 49 years. The group where we observe the bigger differences among categories is the occupation, where the lowest forecast errors are obtained for the unemployed respondents. Next, we link news about inflation, industrial production, and stock markets to unemployment expectations. With this aim we match positive and negative news with consumers' unemployment sentiment using a distributed lag regression model for each news item. We find asymmetries in the responses of consumers' unemployment expectations to economic news: they tend to be stronger in the case of negative news, especially in the case of inflation.

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“…This function allows not only to visualise relevant links but also makes it possible to detect unknown relationships. Given the suitability of genetic algorithms for detecting patterns in large data sets and for the automatic resolution of optimisation problems, GP is increasingly being applied in more areas (Alexandridis et al, 2017;Eliiyi et al, 2009;Fernández et al, 2019;Pan et al, 2019). Most of its applications in economics have been made in finance (Acosta-González & Fernández, 2014;Larkin & Ryan, 2008;Vasilakis et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

A Genetic Programming Approach for Estimating Economic Sentiment in the Baltic Countries and the European Union

Clavería

Monte

Porras

2021

Technological and Economic Development of Economy

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In this study, we introduce a sentiment construction method based on the evolution of survey-based indicators. We make use of genetic algorithms to evolve qualitative expectations in order to generate country-specific empirical economic sentiment indicators in the three Baltic republics and the European Union. First, for each country we search for the non-linear combination of firms’ and households’ expectations that minimises a fitness function. Second, we compute the frequency with which each survey expectation appears in the evolved indicators and examine the lag structure per variable selected by the algorithm. The industry survey indicator with the highest predictive performance are production expectations, while in the case of the consumer survey the distribution between variables is multi-modal. Third, we evaluate the out-of-sample predictive performance of the generated indicators, obtaining more accurate estimates of year-on-year GDP growth rates than with the scaled industrial and consumer confidence indicators. Finally, we use non-linear constrained optimisation to combine the evolved expectations of firms and consumers and generate aggregate expectations of of year-on-year GDP growth. We find that, in most cases, aggregate expectations outperform recursive autoregressive predictions of economic growth.

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Influential factors of carbon emissions intensity in OECD countries: Evidence from symbolic regression

Cited by 85 publications

References 52 publications

How renewable energy consumption contribute to environmental quality? The role of education in OECD countries

How renewable energy consumption contribute to environmental quality? The role of education in OECD countries

Unemployment expectations: A socio-demographic analysis of the effect of news

A Genetic Programming Approach for Estimating Economic Sentiment in the Baltic Countries and the European Union

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