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The institutional determinants of CO2 emissions: a computational modeling approach using Artificial Neural Networks and Genetic Programming

descriptionPublicationkeyboard_double_arrow_right Article , Journal 24 Jan 2011 Spain Publisher:WileyJournal:Environmetrics, volume 22, pages 42-49 (issn: 1180-4009,

Authors: Álvarez-Díaz, M.; Caballero-Miguez, G.; Soliño, M.;

doi: 10.1002/env.1025

handle: 11093/7806 , 20.500.12792/4855 , 10261/290390

The institutional determinants of CO2 emissions: a computational modeling approach using Artificial Neural Networks and Genetic Programming

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Abstract

Understanding the complex process of climate change implies the knowledge of all possible determinants of CO2 emissions. This paper studies the influence of several institutional determinants on CO2 emissions, clarifying which variables are relevant to explain this influence. For this aim, Genetic Programming and Artificial Neural Networks are used to find an optimal functional relationship between the CO2 emissions and a set of historical, economic, geographical, religious, and social variables, which are considered as a good approximation to the institutional quality of a country. Besides this, the paper compares the results using these computational methods with that employing a more traditional parametric perspective: ordinary least squares regression (OLS). Following the empirical results of the cross-country application, this paper generates new evidence on the binomial institutions and CO2 emissions. Specifically, all methods conclude a significant influence of ethnolinguistic fractionalization (ETHF) on CO2 emissions.

Ministerio de Educación y Ciencia | Ref. MTM2005-01274

Ministerio de Ciencia e Innovación | Ref. MTM2008-3219

Xunta de Galicia | Ref. PGIDIT07PXIB300191PR

Country

Spain

Related Organizations

Universidade de Vigo
Spain
Institute for Research and Technology in Food and Agriculture
Spain
Center for International Forestry Research
Indonesia
Spanish National Research Council
Spain
Universidade de Vigo
Spain

Keywords

Artificial neural networks, CO2 emissions, Genetic programming, Computational methods, 5308 Economía General, Institutional determinants

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	13
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%