We estimate the spatial distribution profile of the population living without access in Sub-Saharan Africa. Using NOAA’s VIIRS satellite night light imagery and the CIESIN’s GPW gridded population dataset, we produce a high-resolution map of the unlit population in the region for year 2015. We determine which countries are characterised by the greatest access inequality (calculating Gini coefficients of access to electricity), what role travel time (i.e. effective distance) to urban areas, population density and energy resources proximity play, and up to which degree access is spatially autocorrelated. Then, using estimation results, we run regression models based on instrumental variable (IV) approach and spatial econometric specifications (SAR-SEM-SARAR-GNS) to assess the impact of economic growth on the process of electrification in rural areas (and the mediatory role of exogenous climate factors) at the sub-national scale of FAO’s Global Administrative Unit Layers. The spatially-explicit results enable drawing implications for energy and development policy.

This seminar has been jointly organized by FEEM and IEFE, Bocconi University.