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Quantifying SDG indicators for multiple SSPs up to 2050 with a focus on selected low and low-middle income countries and the bio-economy based on CGE analysis

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  • Wilts, Rienne
  • Britz, Wolfgang

Abstract

A wide range of indicators beyond GDP growth is necessary to measure progress towards more sustainability as reflected by the indicator frameworks developed by the United Nations (2021). Still, such progress builds on its core on economic growth and related structural change. Given its multi-sector and global perspective, dynamic CGE analysis depicts these key processes and thus offers a starting point to quantify various SDG indicators. Multiple scholars have therefore developed SDG indicator frameworks which fit their CGE models, such as Philippidis et al. (2020) and Lui et al. (2021). Existing auxiliary data available from GTAP, such as CO2 (Peters, 2016), non-CO2 (Chepeliev, 2020a) and air emissions (Chepeliev, 2020b) already help to access important aspects of environmental sustainability and to relate emissions to human health. Further indicators require partly sector and product detail beyond the GTAP Data Base which motivates the development of more detail data base in this study. Distributional aspects of economic growth, also beyond income distribution, remain a challenge in CGE analysis, and are addressed in this study by micro-simulations. We propose to quantify 75 indicators relating to 13 of the 17 SDGs in order to assess SDG developments up to 2050 for different Socio-Economic Pathways to extend existing work in this field.

Suggested Citation

  • Wilts, Rienne & Britz, Wolfgang, 2022. "Quantifying SDG indicators for multiple SSPs up to 2050 with a focus on selected low and low-middle income countries and the bio-economy based on CGE analysis," Conference papers 333473, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    • Handle: RePEc:ags:pugtwp:333473
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    References listed on IDEAS

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    1. United Nations, 2016. "The Sustainable Development Goals 2016," Working Papers id:11456, eSocialSciences.
    2. Jeffrey C Peters, 2016. "GTAP-E-Power: An Electricity-detailed Economy-wide Model," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 1(2), pages 156-187, December.
    3. Konstantin Stadler & Richard Wood & Tatyana Bulavskaya & Carl†Johan Södersten & Moana Simas & Sarah Schmidt & Arkaitz Usubiaga & José Acosta†Fernández & Jeroen Kuenen & Martin Bruckner & Stefan, 2018. "EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi†Regional Input†Output Tables," Journal of Industrial Ecology, Yale University, vol. 22(3), pages 502-515, June.
    4. Dominique van der Mensbrugghe, 2018. "The Standard GTAP Model in GAMS, Version 7," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 3(1), pages 1-83, June.
    5. Mun Ho & Wolfgang Britz & Ruth Delzeit & Florian Leblanc & Roberto Roson & Franziska Schuenemann & Matthias Weitzel, 2020. "Modelling Consumption and Constructing Long-Term Baselines in Final Demand," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 5(1), pages 63-108, June.
    6. Angel Aguiar & Maksym Chepeliev & Erwin L. Corong & Robert McDougall & Dominique van der Mensbrugghe, 2019. "The GTAP Data Base: Version 10," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 4(1), pages 1-27, June.
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