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

• Published in: Environmental challenges (Amsterdam, Netherlands) Vol. 3; p. 100033
• Main Authors: Nunes Carvalho, Taís Maria, de Souza Filho, Francisco de Assis
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2021; Elsevier
• Subjects: Contingent pricing; Data-driven modeling; Drought planning; Water demand; Data-driven modeling; Drought planning; Water demand; Contingent pricing
• ISSN: 2667-0100; 2667-0100
• DOI: 10.1016/j.envc.2021.100033

•A predictive model that accounts for water pricing policies is presented.•Increasing block rate tariff and penalty fees might be unfair to low income classes.•Water cost increase is more compelling to consumers than information on drought.•A contingent tariff promoted water demand reduction of 11–17% in Brazil. 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.