AGGREGATION AND PROJECTION OF SUSTAINABILITY INDICATORS: A NEW APPROACH Elisa Lanzi Fondazione Eni Enrico Mattei 3 rd OECD World Forum Busan, South Korea Thu 29 th October
1. Introduction Sustainability is a complex multi-faceted concept which is hard to quantify Aggregate sustainability indices can help address this problem Need to use indices in an operative way useful to stakeholders and policy-makers The FEEM Sustainability Index is a new sustainability index with two main novelties: A new non-linear aggregation method which responds to the need to take into account interactions between indicators The possibility to project the index and its indicators in the future to check what sustainability will look like in the future under different growth and policy assumptions Built in a dynamic computable general equilibrium model 1
2. The FEEM Sustainability Index The FEEM Sustainability Index (FEEM SI) is the first aggregate index able to provide future projections of sustainability of countries The construction of the FEEM SI is made in 4 different steps Selection of Indicators Survey of existing literature on sustainability indicators to achieve the selection of the most well-known and reliable international datasets Construction of the indicators from the ICES-SI Indicators are constructed in a dynamic computable general equilibrium model and projected over time so as to be able to study sustainability in the future Normalisation of indicators Indicators are normalised following a policy-oriented benchmarking procedure in order to achieve full comparability of the indicators Aggregation of indicators FEEM SI manages to condense in a unique way the information included in each of its components, using a novel aggregation methodology that exploits all the interactions between indicators 2
2.1 Selection of indicators What is sustainability? Answering this question is a not so easy task that the FEEM SI tries to resolve starting from the indicator selection Identification of the three main pillars of sustainability economic social environmental Selection of indicators from ones used by international institutions EU Sustainable Development Strategy UN Commission on Sustainable Development World Development Indicators European Environmental Agency core set of indicators 3
2.1.1 Selected indicators Theme Sub-theme Indicator ECONOMIC SOCIAL ENVIRONMENTAL ECONOMIC STRUCTURE COMPETITIVENESS POPULATION POVERTY PRIVATE EXPENDITURE ON SOCIAL SERVICES EDUCATION HEALTH CLIMATE CHANGE WATER ENERGY NATURAL RESOURCES 1.GDP per capita 2. Consumption expenditure as % GDP 3. Total R&D expenditure as % GDP 4. Population growth 5. Share of food in primary goods consumption 6. Energy per capita 7. Expenditure in insurance and pensions % GDP 8. Public expenditure on education as % GDP 9. Health expenditure by privates as % overall 10. Overall health expenditure as % GDP 11. Carbon intensity of energy 12. GHG emission per capita 13. Water use as % total renewable water 14. Energy intensity (energy/gdp) 15. Imported energy as % overall energy use 16. Share of clean energy in primary energy 17. Biodiversity index-plants 18. Biodiversity index-animals 4
2.2 Modelling Framework Use of a Dynamic CGE model to project sustainability in the future and according to different growth and policy scenarios ICES-SI Model Modified version of ICES (Inter-temporal Computable Equilibrium System) Dynamic CGE model based on a Social Accounting Matrix relative to 2001 Cost minimising representative firm Utility maximising representative households Dynamics Exogenous: exogenously imposed growth paths for some key variables - population, labour stock, labour productivity, land productivity Endogenuos: the process of capital accumulation, according to which capital stock is updated over time in order to take into account endogenous investment decisions Projections up to 2020 Possibility to use the model s output to calculate the FEEM SI for each year 5
2.2.1 Modelling Framework: Indicators calculation Construction of indicators starting from the model s output variables 6
2.3 Normalisation of indicators Use of a benchmarking normalisation technique Benchmarks are policy-oriented Rescaling of indicators in the interval 0-1 which allows full comparison between indicators 7
2.4 Aggregation of indicators: aggregation tree Once selected indicators are organised in a themebased logical framework, which is at the basis of the aggregation procedure 8
2.4.1 Aggregation of indicators: aggregation methodology The aggregation methodology accounts for the interrelation between indicators Weights are the result of a careful reconstruction of individual preferences that respects the synergies or conflicts that are naturally built into the aggregate concept of global sustainability Preferences are studied by assigning a weight to all possible combination of extreme-valued indicators 9
2.4.2 Aggregation of indicators: sensitivity analysis For the construction of the FEEM SI subjective weights obtained from a simulated andness-biased decision maker An andness decision maker believes that different indicators are not substitutable, and that in order for a country to be sustainable it should have a high score in each of its component of sustainability How do results change if we consider different attitudes and preferences? orness traits: the decision maker is satisfied when only one criterion is satisfied The sensitivity analysis approaches this problem by considering the results for the FEEM SI under different levels of andness for the decision makers. 10
4. Conclusion The FEEM SI is built on a comprehensive methodology Its aggregation methodology improves existing indices by considering interactions between indicators Being built in a dynamic computable general equilibrium model it gives the possibility to study sustainability in the future and according to different assumptions The FEEM SI has wide potential in terms of sustainability policy-studies 11
THANK YOU Elisa Lanzi Fondazione Eni Enrico Mattei elisa.lanzi@feem.it feemsi@feem.it 12