Electricity consumption as a predictor of household income: an spatial statistics approach

Abstract

This paper investigates the relationship between electricity consumption, economic classification and household income, by means of comparing Brazilian Census Micro-Data with the customer database of AES Eletropaulo, a large Brazilian electric distribution company, using traditional statistics and spatial auto-regressive models. Income and economic classification are recognized as efficient proxies for purchasing power. Income indicators based on Electricity Consumption can be almost automatically generated by electric companies using GIS techniques, and this is a potential new business model for electric companies.