{"title":"Distribution matters: Long-term quantification of the Sustainable Development Goals with household detail for different socio-economic pathways","authors":"Rienne Wilts, Wolfgang Britz","doi":"10.1016/j.glt.2024.06.004","DOIUrl":null,"url":null,"abstract":"<div><p>Knowledge about upcoming sustainability challenges is crucial to tackle them by political incentives, not at least to reach the United Nations’ 17 Sustainable Development Goals (SDGs). SDGs are multi-dimensional and require detail beyond an aggregate household approach to assess income inequality and other differences across households in transformative processes. Incorporating these aspects, we develop an SDG indicator framework for dynamic Computable General Equilibrium Models with a total of 68 endogenous indicators related to 15 SDGs. This enables a more differentiated assessment of the SDGs in forward looking analysis compared to existing approaches, by considering additional SDG indicators and household level detail based on micro-simulation. We apply the indicator framework in a global analysis of 3 Shared Socioeconomic Pathways (SSPs) until 2050 with a focus on selected low- and lower-middle income countries from different continents. The analysis finds sustainability gaps by 2030 and 2050 for all focus countries, especially in the environmental domain. In none of the analyzed SSPs, all indicators develop in the desired direction, underlining trade-off among and within SDGs, but also across the SSPs. Based on household detail, we find increasing inequality over time for several indicators regardless of developments at average aggregate household level, pointing at the need for targeted redistribution and compensation policies. These results highlight the importance of including distributional aspects and disaggregated data in policy and socioeconomic development studies.</p></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"6 ","pages":"Pages 173-186"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589791824000112/pdfft?md5=cb4893678bc80104f0374a176a8c0c21&pid=1-s2.0-S2589791824000112-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Transitions","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589791824000112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Knowledge about upcoming sustainability challenges is crucial to tackle them by political incentives, not at least to reach the United Nations’ 17 Sustainable Development Goals (SDGs). SDGs are multi-dimensional and require detail beyond an aggregate household approach to assess income inequality and other differences across households in transformative processes. Incorporating these aspects, we develop an SDG indicator framework for dynamic Computable General Equilibrium Models with a total of 68 endogenous indicators related to 15 SDGs. This enables a more differentiated assessment of the SDGs in forward looking analysis compared to existing approaches, by considering additional SDG indicators and household level detail based on micro-simulation. We apply the indicator framework in a global analysis of 3 Shared Socioeconomic Pathways (SSPs) until 2050 with a focus on selected low- and lower-middle income countries from different continents. The analysis finds sustainability gaps by 2030 and 2050 for all focus countries, especially in the environmental domain. In none of the analyzed SSPs, all indicators develop in the desired direction, underlining trade-off among and within SDGs, but also across the SSPs. Based on household detail, we find increasing inequality over time for several indicators regardless of developments at average aggregate household level, pointing at the need for targeted redistribution and compensation policies. These results highlight the importance of including distributional aspects and disaggregated data in policy and socioeconomic development studies.