BUSCADOR RECOLECTA

Multisectoral models usually have a single representative household. However, more diversity of household types is needed to analyse the effects of multiple phenomena (i.e. ageing, gender inequality, distributional income impact, etc.). Household consumption surveys’ microdata is a rich data source for these types of analysis. However, feeding multisectoral models with this type of information is not simple and recent studies show how even slightly inaccurate procedures might result in significantly biased results. This paper presents the full procedure for feeding household consumption microdata into macroeconomic models and for the first time provides in a systematic way an estimation of the bridge matrices needed to link European Union Household Budget Surveys’ microdata with the most popular multi-regional input–output frameworks (e.g. Eurostat, WIOD, EORA, OECD).

The food, energy, and water (FEW) nexus has gained increased attention, resulting in numerous studies on management approaches. Themes of resource use, and their subsequent scarcity and economic rents, which are within the application domain of the World Trade Model, are ripe for study, with the continuing development of forward- and backward-facing economic data. Scenarios of future food and energy demand, relating to supply chains, as well as direct and indirect resource uses, are modelled in this paper. While it is possible to generate a substantial number of economic and environmental scenarios, our focus is on the development of an overarching approach involving a range of scenarios. We intend to establish a benchmark of possibilities in the context of the debates surrounding the Paris Climate Agreement (COP21) and the Green New Deal. Our approach draws heavily from the existing literature on international agreements and targets, notably that of COP21, whose application we associate with the Shared Socioeconomic Pathway (SSP). Relevant factor uses and scarcity rent increases are found and localized, e.g., on the optimal qualities of water, minerals, and land. A clear policy implication is that, in all scenarios, processes of energy transition, raw material use reduction, and recycling must be strengthened.

Migration and environmental change are deeply interconnected processes, intimately linked to development pathways. The gender dimension of these complex interactions is often overlooked. Yet there are profound linkages and implications. This paper focuses on the gender division of labour to investigate how migration and environmental change relate to gender equality and sustainability. The study draws on research conducted in the Mahanadi delta, in the eastern Indian state of Odisha. In the Mahanadi delta labour migration is largely male dominated. Women remain behind in vulnerable environments facing social and economic challenges having impacts on their empowerment and wellbeing. The findings show shifts in work burden, as women often engage in new activities alongside the traditional domestic and social reproductive work but highlight differences across age and household headship. Firstly, this paper identifies the connections between gender, sustainability and care –conceptually and empirically. Secondly, it explores the gender division of labour in the study area by discussing its structural causes. Thirdly, it provides insights into migration dynamics and examines how they feed back into gender equality and sustainability. Finally, it argues for the need of integrated analytical approaches that reflect ecological and social-equity challenges. © 2021 The Authors

In a tele-coupled and globalized World, understanding the links between demand for wood products and land use is becoming challenging. World''s economies are increasingly open and interconnected, and international trade flows of wood products are continuously growing. The increasing resource consumption of humanity is increasingly dependent on international trade. In this context, the study of forest products demand from a global-multi-regional perspective emerges as a critical issue to achieve the goal of sustainable consumption and production. In this paper, we introduce a novel accounting framework for assessing the forest footprint of nations. The method combines Multi-regional Input-Output techniques and detailed data from the Food and Agriculture Organization of the United Nations on production, consumption and bilateral trade of primary, intermediate and final wood products, advancing with respect to existing approaches with these practical distinctions for more accurate computations. The approach tracks resource flows along the global supply chain and provides detailed information on the production, transformation, international trade, and final use of 20 forest products in 223 countries, having also much wider coverage than most previous studies. We test this framework to analyse forest footprint of nations in the year 2014, showing that 22 Million hectares (Mha) of forest were harvested for the extraction of roundwood for global demand, being 9.1 Mha to satisfy the foreign demand of wood products (42% of the total forestland harvested area). Harvested forestland is concentrated in America (32%), Asia (29%) and Europe (28%), representing Africa (7%) and Oceania (4%). More than 50% of the reported forest area harvested worldwide is located in USA (15%), China (14%); Russia (11%) and Canada (8%). In terms of forest footprint, Asia shows the highest share of the total forest footprint (44%), followed by America (25%), Europe (21%), Africa (7%) and Oceania (2%). Country-wise, half is concentrated in China (24%), USA (16%), India (5%), and Russia (5%). © 2022 The Authors

Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions'' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in con sumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability. (c) 2021 Elsevier B.V. All rights reserved.

Despite the consensus that green taxation is an effective way to accelerate the decarbonization of economies, few countries are implementing ambitious tax reforms. This is the case of diesel for transport in Spain. The arguments against boosting the diesel tax stressed its potential adverse effects on the economy and society, accusing it of being a regressive policy. In this paper, we shed light on the distributional impact of raising the excise tax on diesel to the same level as on gasoline for final consumers in Spain and various compensation schemes jointly designed with several stakeholders. The 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.

Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in con sumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability., All the authors belong and thank the support to the MENTES network on Energy Modelling for a Sustainable Energy Transition, by the Spanish Ministry of Science, Innovation and Universities (project/grant RED2018-102794-T). I.A. and I.C. thank the support of the Spanish Ministry of Science, Innovation and Universities (MALCON, RTI2018-099858-A-I00) , the Spanish State Research Agency through Maria de Maeztu Excellence Unit accreditation 2018-2022 (Ref. MDM-2017-0714) and Basque Gov-ernment BERC Programme. L.J.M., I.A. and I.C. gratefully acknowledge the project LOCOMOTION H2020-LC-CLA-2018-2 (No 821105) and L.J.M. MODESLOW, funded under the Spanish National Research, Development and Innovation Programme (Ministry of Economy and Competitiveness of Spain, ref. ECO2017-85110-R). I.C. and R.L thank the Spanish Ministry of Science, Innovation and Universities (PID2019-106822RB-I00). M.A.C., L.A.L. and J.Z. thank the support of the University of Castilla-La Mancha and the European Fund for Regional Development (FEDER) (Ref. 020-GRIN-29137). P.L. gratefully acknowledges the support of project RTI2018-093692-B-I00 by the Spanish Ministry of Science and Innovation (MCI), the National Research Agency (AEI) and the European Fund for Regional Development (FEDER). Y.L. and S.B. gratefully acknowledge the support of project MUSTEC, funded by the European Union's Horizon 2020 research and innovation programme under grant agreement no. 764626.