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

TL;DR

This paper extends Bayesian structural time-series methods to estimate the impact of household conservation initiatives across multiple households, using matching and meta-regression techniques, demonstrated through a water rebate case study.

Contribution

It introduces a novel extension of BSTS impact estimation methods for multi-household conservation programs, combining household matching with meta-regression for aggregated impact analysis.

Findings

Effective estimation of conservation impact across multiple households.

Method applied successfully to water rebate case study.

Provides a scalable approach for policy impact evaluation.

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 multi-household 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.