Climate Change versus Economic Growth: Case of Greenhouse Apply a Study of European Union Countries and England from 2010 to 2019 Using Linear Regression and Neural Networks

Juan Antonio Torrents Arevalo ()
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Juan Antonio Torrents Arevalo: Department of Management, Polytechnic University of Catalonia, Barcelona-Tech, Building P, Room 209 2nd Plant, 44-50, 08028 Barcelona, Spain

Sustainability, 2024, vol. 16, issue 5, 1-22

Abstract: Climate change, encompassing the greenhouse effect, is a scientifically acknowledged fact. Factors such as population increase and limited resources for economic growth warrant consideration. This paper aims to develop a new approach to explore the relationship between the greenhouse effect (including climate change) and economic growth and the social/welfare state and find if the government really focus on the reduction of the greenhouse or is marketing. The objective is to develop a study employing linear regression, neural networks, and other statistical tools to elucidate these relationships. The data comprise figures for the human development index (HDI), the greenhouse effect, the GDP, and environmental indicators. The method used will be a parametric workout about the variables that affect the greenhouse gas emissions, the relationship between it and the HDI, and finally, will apply a prediction of greenhouse effects incorporating a neural network. Since 2020, in European Union countries, and especially in new members, focus has been placed on the HDI rather than on the reduction in the greenhouse effect. On the other hand, neural networks allow advances that enable the European Union to focus on climate change, with large investments planned until 2030 because the reduction in greenhouse gases can be effectively lowered when the countries’ expenditures are focused on environmental protection, including enhancing biodiversity.

Keywords: greenhouse; human development index (HDI); European Union environment policy; climate change; neuronal networks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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