A compositional approach for modelling SDG7 indicators: Case study applied to electricity access. J.C. Marcillo-Delgado a , M.I. Ortego b , A. P´ erez-Foguet a,* a Research group on Engineering Sciences and Global Development, Department of Civil and Environmental Engineering, Universitat Polit` ecnica de Catalunya BarcelonaTech, Spain b Research group COSDA-UPC, Department of Civil and Environmental Engineering, Universitat Polit` ecnica de Catalunya-BarcelonaTech. Abstract Monitoring energy indicators has acquired a renewed interest with the 2030 Agenda for Sustainable Development, and specifically with goal 7 (SDG7), which seeks to guarantee universal access to energy. The predominant criteria to mon- itor SDG7 are given in a set of individual indicators. Along this line, the UN indicators proposed in the 47th session of the UN Statistical commission are a practical starting point. A relevant characteristic of these indicators is that they can be expressed as proportions from a whole, i.e., they are compositions. Notably, directly implementing traditional multivariate models onto indicators that are proportions without an intermediate process can lead to spurious analy- sis. Here, we aim to assess the application of compositional data analysis(CoDa) to follow up on the temporal trend indicators of the energy sector in the context of SDG7, with a case study for the most affected areas addressing the prob- lem of electricity access. Following CoDa methodology, we first use a log-ratio transformation to bring compositions to real space and then apply three mul- tivariate methods: linear regression, generalized additive models and support vector machine. We also address other characteristic problems of the electricity access indicators, such as data quality, which was treated by considering mod- * Corresponding author at: Universitat Polit` ecnica de Catalunya, Barcelona School of Civil Engineering (ETSECCPB), Campus Nord C2-310. Jordi Girona, 1-3, 08034 Barcelona, Spain. Email addresses: juan.marcillo.delgado@gmail.com (J.C. Marcillo-Delgado), ma.isabel.ortego@upc.edu (M.I. Ortego), agusti.perez@upc.edu (A. P´ erez-Foguet) Preprint submitted to Renewable & Sustainable Energy Reviews February 12, 2019