 High-frequency analytics and residential water consumption: Estimating heterogeneous effectsMehdi Nemati, Steven Buck and Hilary Soldati Resource and Energy Economics, 2025, vol. 83, issue C Abstract: This paper estimates how high-frequency online Home Water Use Reports (HWURs) affect household-level water consumption. The HWURs under the study share social comparisons, consumption analytics, leak alerts, and conservation information to residential accounts, primarily through digital communications. The data utilized in this paper is a daily panel dataset that tracks single-family residential households from January 2013 to September 2019. We found a 6.2 % reduction in average daily household water consumption for a typical household enrolled in the program. We estimate heterogeneous treatment effects by the day of the week, the content of push notifications, and baseline consumption quintile. For the latter, we provide an illustrative test to emphasize how mean reversion can severely bias a naïve panel data estimator for heterogeneous treatment effects when the source of heterogeneity is the outcome variable. We also find evidence that leak alerts effectively reduce water consumption immediately following the alert. Keywords: Automated meters; California; HWURs; leak alerts; Non-price intervention; Social-norms; Urban water demand (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:resene:v:83:y:2025:i:c:s0928765525000247 DOI: 10.1016/j.reseneeco.2025.101500 Access Statistics for this article Resource and Energy Economics is currently edited by J. F. Shogren and S. Smulders More articles in Resource and Energy Economics from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.