{"title":"Institutions and carbon emissions: an investigation employing STIRPAT and machine learning methods","authors":"","doi":"10.1007/s00181-024-02579-y","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>We employ an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model combined with the environmental Kuznets curve and machine learning algorithms, including ridge and lasso regression, to investigate the impact of institutions on carbon emissions in a sample of 22 European Union countries over 2002 to 2020. Splitting the sample into two: those with weak and strong institutions, we find that the results differ between the two groups. Our results suggest that changes in institutional quality have a limited impact on carbon emissions. Government effectiveness leads to an increase in emissions in the European Union countries with stronger institutions, whereas voice and accountability lead to a fall in emissions. In the group with weaker institutions, political stability and the control of corruption reduce carbon emissions. Our findings indicate that variables such as population density, urbanization and energy consumption are more important determinants of carbon emissions in the European Union compared to institutional governance. The results suggest the need for coordinated and consistent policies that are aligned with climate targets for the European Union as a whole.</p>","PeriodicalId":11642,"journal":{"name":"Empirical Economics","volume":"18 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Empirical Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s00181-024-02579-y","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
We employ an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model combined with the environmental Kuznets curve and machine learning algorithms, including ridge and lasso regression, to investigate the impact of institutions on carbon emissions in a sample of 22 European Union countries over 2002 to 2020. Splitting the sample into two: those with weak and strong institutions, we find that the results differ between the two groups. Our results suggest that changes in institutional quality have a limited impact on carbon emissions. Government effectiveness leads to an increase in emissions in the European Union countries with stronger institutions, whereas voice and accountability lead to a fall in emissions. In the group with weaker institutions, political stability and the control of corruption reduce carbon emissions. Our findings indicate that variables such as population density, urbanization and energy consumption are more important determinants of carbon emissions in the European Union compared to institutional governance. The results suggest the need for coordinated and consistent policies that are aligned with climate targets for the European Union as a whole.
期刊介绍：
Empirical Economics publishes high quality papers using econometric or statistical methods to fill the gap between economic theory and observed data. Papers explore such topics as estimation of established relationships between economic variables, testing of hypotheses derived from economic theory, treatment effect estimation, policy evaluation, simulation, forecasting, as well as econometric methods and measurement. Empirical Economics emphasizes the replicability of empirical results. Replication studies of important results in the literature - both positive and negative results - may be published as short papers in Empirical Economics. Authors of all accepted papers and replications are required to submit all data and codes prior to publication (for more details, see: Instructions for Authors).The journal follows a single blind review procedure. In order to ensure the high quality of the journal and an efficient editorial process, a substantial number of submissions that have very poor chances of receiving positive reviews are routinely rejected without sending the papers for review.Officially cited as: Empir Econ
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