A data-driven model to evaluate the medium-term effect of contingent pricing policies on residential water demand

Abstract

The relative scarcity of water resources has encouraged cities to create mechanisms to control water demand and avoid water stress. In the decision-making process, water companies need to assess the price influence on water demand predictions to design better policies. The aim of this study is to estimate the medium-term effectiveness of the implementation of a contingent tariff and its consequences for water demand elasticity to price. A novel model that requires only secondary data is proposed, that can be useful for guiding the drought planning process. The methodology consists of a framework that provides monthly predictions of water demand at the household level, considering price, seasonality, and previous water use. The results indicated that the contingent tariff promoted a reduction of 11–17% in water demand, but at a higher cost for low income households. Also, reduction in water demand was found to be inelastic to price increase. Using google search hits as a proxy for public interest, we found that water cost has a higher influence on users’ decision to save water than drought awareness.