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• W2613357855 abstract "The fall of 2015 will see a redefinition of international policy environment with the 21th UNFCCC Conference Of Parties (COP 21) in Paris and the adoption of the Sustainable Development Goals (SDGs) by United Nations. SDGs, the Millennium Development Goals follow-up, will set broader and more ambitious targets for both developed and developing countries encompassing all sustainability dimensions (economic, social, and environmental) and designing the pathway towards an inclusive green growth. The COP 21 agreement, defining new emission targets (Intended Nationally Determined Contributions - INDCs), will directly affect countries’ environmental performance, but also social and economic dimensions if we consider the possible use of climate policy revenues to reduce poverty prevalence (SDG 1) and malnutrition (SDG 2) or to extend access to electricity (SDG 7) or to lower the pressure on public debt (SDG 8). This paper aims at giving an ex-ante assessment of the co-benefits and side effects of this new policy setting and, in particular, to shed some light on the influence of COP21 agreement on achieving SDGs. Our analysis relies on a recursive-dynamic Computable General Equilibrium (CGE) model developed and enriched with indicators representative of each SDGs. CGE models have a flexible structure, and can capture trade‐offs and higher-order implications across sectors and countries that follows a shock or a policy. These models are well suited to assess the performance of economic indicators such as sectoral value added, GDP per capita, and public debt evolution; moreover, the CGE modelling literature of the past decades has highlighted that this is also a powerful tool to assess the evolution of some key environmental indicators, such as land use determined by land owners’ revenues maximisation or GHG and CO2 emissions directly linked to agents’ production and consumption choices (Bohringer and Loschel, 2006). Modelling social indicators in a CGE framework is a difficult task, especially when these imply dispersion measures such are poverty prevalence and inequality at the core of GOAL 1 and 10. In this case, we overcome the representative agent structure proper of CGE models empirically relying on the empirical literature and directly estimating the relations between indicators and endogenous variables of the model (Bourguignon et al., 2005; Ferreira et al., 2007; Montalvo and Ravallion, 2010). Extending the model with social and environmental indicators, in addition to the economic ones, allows assessing in an internally consistent framework how and at which extent changes in one sustainability sphere may affect the achievement of SDGs all around the world. Our framework considers 33 indicators covering 16 SDGs and classified into the three sustainability pillars. The analysis has world coverage, but for modelling reasons we aggregate the result in 40 countries/macro-regions. The historical records of indicators’ values rely on international databases (Commission on Sustainable Development of the United Nations, EU Sustainable Development Strategy, and World Development Indicators from World Bank) and are the starting point in our baseline scenario design. The baseline reproduces a Shared Socio-economic Pathways 2 (SSP2), consistent with a RCP4.5, and it is used as a benchmark to assess the effects of two mitigation scenarios anticipating the outcome of COP 21. The two proposed mitigation scenarios consider a coordinated effort to curb GHG emissions from 2020: 1.Post-Paris Global Trade (global ITS) scenario: the abatement pledges stated in the INDCs submitted ahead of the Paris Conference (COP 21) are effective for the committing countries. The global climate policy implementation envisions an international emission trading scheme (ITS). 2.Post Paris EU ETS scenario: in this scenario the European Union (EU28) implements an Emission Trading System (ETS) as already foreseen by the EU ETS domestic legislation, while all other countries achieve their targets unilaterally with a domestic carbon tax. Both scenarios are characterised by two different recycling schemes of the revenues collected from the carbon market or the carbon taxes: •revenues are redistributed internally in a lump sum; •revenues are used in part internally in EU28 and other developed countries and in part flow to a Development Fund benefiting LDCs: EU28 uses at least 50% of the revenues recycled to support clean energy in EU, 5% goes to the Development Fund and the rest is redistributed internally. The other committing countries allocate 1% of the carbon tax revenues to the Development Fund. In the LDCs revenues are recycled to achieve other SDGs, e.g. poverty and malnutrition reduction, access to education and electricity. This analysis will mainly focus on characterising the future trend of some social indicators, e.g. poverty prevalence and inequality, in the SSP2 baseline scenario, in addition to the usual economic and environmental indicators. Then, this baseline scenario will be used as a term of comparison to assess the impact of climate policy and different recycling scheme on environmental, social and economic indicators. Considering the INDCs as binding targets, COP21 agreement will determine a slight reduction of extreme poverty prevalence in the LDCs, but this outcome is mainly due to a leakage effect. The effect of climate policy on income distribution will be neutral and recycling carbon revenues with the creation of a Development Fund and a lump sum transfer to LDCs will have a negligible effect on poverty and inequality." @default.
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• W2613357855 date "2016-07-04" @default.
• W2613357855 modified "2023-09-27" @default.
• W2613357855 title "Can Paris deal boost SDGs achievement? An assesment of climate-sustainabilty co-benefits or side-effects" @default.
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