Climate cHange mitigAtioN poliCies and Equality: distributional implications for different socio-economic groups

Project Information

CHANCE

Grant agreement ID: 796650

DOI

10.3030/796650

Project closed

EC signature date 9 March 2018

Start date 13 January 2019

End date 12 January 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 239 191,20

EU contribution

€ 239 191,20

Coordinated by

ASOCIACION BC3 BASQUE CENTRE FOR CLIMATE CHANGE - KLIMA ALDAKETA IKERGAI
Spain

Periodic Reporting for period 2 - CHANCE (Climate cHange mitigAtioN poliCies and Equality: distributional implications for different socio-economic groups)

Reporting period: 2021-01-13 to 2022-01-12

Summary of the context and overall objectives of the project

The overarching goal of CHANCE is to contribute to bridging the gap between economic and social goals, through enhancing our understanding of how to foster socially fair and economically efficient climate mitigation policies. CHANCE reduces this gap through relevant multi-regional studies in settings where climate and energy policies are at the core of the current political debate. Through these analyses, identifying the factors which induce regressive policies, CHANCE could guide improvements in the design of policies.

CHANCE met the following sub-objectives:
(i) to analyse the distributional implications of climate change mitigation policies from a multi-country perspective. I have developed multiregional distributional impacts between the USA and Spain. Also the modelling work I have done is focus to achieve this objective, from the modelling work on MIT models such as MIT Emissions Prediction and Policy Analysis (EPPA) or U.S. Regional Energy Policy (USREP), to the CGE models I have developed for Europe and Spain.
(ii) to identify, through analysis of household typologies, which groups are vulnerable to these policies, that is, most prone to bearing the costs of climate protection. In different research, I have analysed the impacts on different climate protection measures on different household’s typologies.
(iii) to develop databases and methods to link multi-sectoral and multi-regional CGE and MS models. I have been working on the MIT USREP model and on the MIT EPPA Model (version 7) to introduce household microdata in both models. Also I have developed and worked on a Spanish CGE-MS model and a European CGE model (CHANCE model) with micro households data.
(iv) to conduct multi-country distributional analysis in the USA-Mexico context. Due to the pandemic, I hadn´t the opportunity to develop the Mexican analysis, but I have developed different analysis for the USA and Spain.
(v) to extend the tools and approaches developed for the USA-Mexico case study to the 28 EU Member States. I have worked on different models such as CGE model and microdata for the EU and Spain following the developments of the outgoing phase. Therefore, I have been able to develop different CGE multi-household models for the EU and Spain, as well to work with different microdata sources, where I extend and apply the methods learn and developed during the outgoing phase at MIT.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

I have performed the following tasks:

WP1:
Task 1.1. MIT EPPA modelling. I have been able to work and develop new features in the USREP model and the EPPA model.
Task 1.2. MS modelling. I have worked with US household microdata, as for example data from the Consumer Expenditure Survey (CEX), and also implement micro models in GAMS using this data source.
Task 1.3. Link EPPA and MS model: I have linked the microdata and microsimulation modelling in the USREP model and in a static version of the EPPA model.

WP2
Task 2.1. Include micro data from Mexico and the U.S. in the macro-micro model. Due to the COVID-19 pandemic and the travel restrictions, I hadn´t the opportunity to develop the Mexican work on the EPPA model. However, I have introduced U.S. microdata in USREP and EPPA models. Also, I have worked with the Spanish and Euroepan microdata and models.
Task 2.2. Analyse the interconnected distributional impacts in the U.S. and Mexico. Due to the COVID-19 pandemic and the travel restrictions, I hadn´t the opportunity to develop the Mexican analysis, but I have developed different analysis for the USA and Spain.

WP3:
Task 3.1. Disaggregate the MIT EPPA model to the 28 Member States. I have worked on a European CGE model integrating micro household data with the help of the professor Christoph Böhringer (University of Oldenburg).
Task 3.2. Adapt the methodology developed in WP1 to Europe. I have used a similar methodology as the one developed in the outgoing phase for updating a Spanish CGE model and in a European CGE model. In addition, through the CHANCE methodology I will be able to develop other relevant distributional analyses in the future, such as those related to the Horizon Europe ADJUST project, in which I am PI.

WP 4:
Task 4.1. Include European micro data in the macro-micro model. I have integrated the Spanish household microdata into the macro-micro model and also I have been working on the European HBS and EU-SILC data to integrate them into the European CGE, CHANCE model.
Task 4.2. Analyse the interconnected distributional impacts in Europe. I have analysed the impacts on different climate protection measures on different household’s typologies, in a European country such as Spain but also in the U.S. economy.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The main objective of CHANCE is to contribute to knowledge of distributional analysis of Climate Protection Measures. The distributional analysis that I have developed in the context of CHANCE provides relevant information on the social impacts of the EU Green deal.

CHANCE model is, a multiregional, multi-sectoral General Equilibrium Model that includes a large information of the European households. Therefore, CHANCE is a model designed to analyse the socioeconomic and distributional impacts of public policies that directly affect households and consumers, both economic, energy, environmental or fiscal. CHANCE is also the starting point for a more ambitious long-term project pursuing my personal mission, that is, to gather the tools and databases necessary to provide policy makers around the world with relevant and accessible information on the global distributional implications of the transition to a low carbon economy and promote my future career as an independent researcher.

The work I have done on European microdata can be used to evaluate the dimension of the energy poverty in Europe and to developed horizontal inequality analysis. I have started to explore the role of gender on the distributional analysis and on the energy poverty.

Finally, at a national level, my work is related with the Spanish policy context, since we analyse the distributional impacts of relevant policies, such as the financing of renewables or the environmental fiscal reform. On the fiscal reform, our results confirm that raising the diesel tax without offsets would have slightly regressive effects and that rural and middle-income households would bear the brunt of the increase. However, the effects become progressive when the co-designed offsetting schemes are implemented. These findings may help decision-makers in achieving a just, acceptable, and politically viable energy transition. I would like to highlight that this research has been recently cited on the expert report organized by the Spanish Financing Ministry.

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