The Annals of Applied Statistics

Extending Bayesian structural time-series estimates of causal impact to many-household conservation initiatives

Eric Schmitt, Christopher Tull, and Patrick Atwater

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Abstract

Government agencies offer economic incentives to citizens for conservation actions, such as rebates for installing efficient appliances and compensation for modifications to homes. The intention of these conservation actions is frequently to reduce the consumption of a utility. Measuring the conservation impact of incentives is important for guiding policy but doing so is technically difficult. However, the methods for estimating the impact of public outreach efforts have seen substantial developments in marketing to consumers in recent years as marketers seek to substantiate the value of their services. One such method uses Bayesian Stuctural Time Series (BSTS) to compare a market exposed to an advertising campaign with control markets identified through a matching procedure. This paper introduces an extension of the matching/BSTS method for impact estimation to make it applicable for general conservation program impact estimation when multihousehold data is available. This is accomplished by household matching/BSTS steps to obtain conservation estimates and then aggregating the results using a meta-regression step to aggregate the findings. A case study examining the impact of rebates for household turf removal on water consumption in multiple Californian water districts is conducted to illustrate the work flow of this method.

Article information

Source
Ann. Appl. Stat., Volume 12, Number 4 (2018), 2517-2539.

Dates
Received: August 2017
Revised: January 2018
First available in Project Euclid: 13 November 2018

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1542078054

Digital Object Identifier
doi:10.1214/18-AOAS1166

Mathematical Reviews number (MathSciNet)
MR3875710

Keywords
Drought water conservation meta-analysis time series

Citation

Schmitt, Eric; Tull, Christopher; Atwater, Patrick. Extending Bayesian structural time-series estimates of causal impact to many-household conservation initiatives. Ann. Appl. Stat. 12 (2018), no. 4, 2517--2539. doi:10.1214/18-AOAS1166. https://projecteuclid.org/euclid.aoas/1542078054


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