{"id":5758,"date":"2023-03-03T13:29:59","date_gmt":"2023-03-03T13:29:59","guid":{"rendered":"https:\/\/aaep.org.ar\/?p=5758"},"modified":"2023-03-03T13:30:00","modified_gmt":"2023-03-03T13:30:00","slug":"determinants-of-sectoral-effective-carbon-rates-on-energy-use","status":"publish","type":"post","link":"https:\/\/aaep.org.ar\/?p=5758","title":{"rendered":"Determinants of sectoral effective carbon rates on energy use"},"content":{"rendered":"<iframe loading=\"lazy\" class=\"wonderplugin-pdf-iframe\" src=\"https:\/\/aaep.org.ar\/wp-content\/plugins\/wonderplugin-pdf-embed\/pdfjslight\/web\/viewer.html?v=2&file=https:\/\/aaep.org.ar\/works\/works2022\/4559.pdf\" width=\"100%\" height=\"600px\" style=\"border:0;\"><\/iframe>\n","protected":false},"excerpt":{"rendered":"<p>We extend the measurement of effective carbon rates, adapting the OECD methodology (OECD-ECR, 2019, 2021), to 18 countries in Latin America and the Caribbean (LAC) for 2018, starting from energy balances and revising comprehensively the level and structure of excises and carbon taxes across countries and accounting for specificities in the emission structure (eg biofuels) and the existence of energy subsidies, all that quite differ from OECD patterns. This allows us to build up a sample of 66 countries (which includes some Asian and African countries also captured by OECD estimates) across 6 sectors and document stylized facts about the sectoral and aggregate level and structure of carbon pricing. Such facts show a biased structure of taxation towards road transport (which has a genesis, decades ago, different from the sole objectives of carbon taxation). This motivates an econometric modelling strategy where we first account for the determinants of economy-wide effective carbon rates (ECR) and then explain differences in road transport and the rest of sectors across countries with an automatic, machine learning model selection and using large set of potential explanatory variables that cover different structural, economic and institutional dimensions. Fiscal variables such as proxies for the marginal cost of public funds are important determinants of ECR in the road transport sector, as expected from the genesis of fuel excises. Emission trading systems tend to increase the value of ECR, while the same does not happen for carbon taxes suggesting that the later are introduced in a reform that substitute for excises. We document that LAC has a lower ECR and that energy subsidies are relevant in changing results only for some countries. However, we find that LAC does not depart from the model estimated for the whole sample insofar the main determinants of ECR. The exception are ETS since these are not observed in LAC, suggesting there might be an avenue for improving ECR by the introduction of ETS in some LAC countries.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[29],"tags":[30],"class_list":["post-5758","post","type-post","status-publish","format-standard","hentry","category-anales","tag-aaep-anales-2022"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Determinants of sectoral effective carbon rates on energy use - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Determinants of sectoral effective carbon rates on energy use - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"og:description\" content=\"We extend the measurement of effective carbon rates, adapting the OECD methodology (OECD-ECR, 2019, 2021), to 18 countries in Latin America and the Caribbean (LAC) for 2018, starting from energy balances and revising comprehensively the level and structure of excises and carbon taxes across countries and accounting for specificities in the emission structure (eg biofuels) and the existence of energy subsidies, all that quite differ from OECD patterns. This allows us to build up a sample of 66 countries (which includes some Asian and African countries also captured by OECD estimates) across 6 sectors and document stylized facts about the sectoral and aggregate level and structure of carbon pricing. Such facts show a biased structure of taxation towards road transport (which has a genesis, decades ago, different from the sole objectives of carbon taxation). This motivates an econometric modelling strategy where we first account for the determinants of economy-wide effective carbon rates (ECR) and then explain differences in road transport and the rest of sectors across countries with an automatic, machine learning model selection and using large set of potential explanatory variables that cover different structural, economic and institutional dimensions. Fiscal variables such as proxies for the marginal cost of public funds are important determinants of ECR in the road transport sector, as expected from the genesis of fuel excises. Emission trading systems tend to increase the value of ECR, while the same does not happen for carbon taxes suggesting that the later are introduced in a reform that substitute for excises. We document that LAC has a lower ECR and that energy subsidies are relevant in changing results only for some countries. However, we find that LAC does not depart from the model estimated for the whole sample insofar the main determinants of ECR. The exception are ETS since these are not observed in LAC, suggesting there might be an avenue for improving ECR by the introduction of ETS in some LAC countries.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/aaep.org.ar\/?p=5758\" \/>\n<meta property=\"og:site_name\" content=\"Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"article:published_time\" content=\"2023-03-03T13:29:59+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-03-03T13:30:00+00:00\" \/>\n<meta name=\"author\" content=\"aaepolitica\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:site\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"aaepolitica\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5758#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5758\"},\"author\":{\"name\":\"aaepolitica\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#\\\/schema\\\/person\\\/7150b747ba20875259c74b2cd177316c\"},\"headline\":\"Determinants of sectoral effective carbon rates on energy use\",\"datePublished\":\"2023-03-03T13:29:59+00:00\",\"dateModified\":\"2023-03-03T13:30:00+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5758\"},\"wordCount\":24,\"publisher\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#organization\"},\"keywords\":[\"AAEP Anales 2022\"],\"articleSection\":[\"Anales\"],\"inLanguage\":\"es\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5758\",\"url\":\"https:\\\/\\\/aaep.org.ar\\\/?p=5758\",\"name\":\"Determinants of sectoral effective carbon rates on energy use - 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