Research / BFI Working PaperSep 16, 2022

Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs

Takanori Ida, Takunori Ishihara, Koichiro Ito, Daido Kido, Toru Kitagawa, Shosei Sakaguchi, Shusaku Sasaki

We develop an optimal policy assignment rule that integrates two distinctive approaches commonly used in economics—targeting by observables and targeting through self-selection. Our method can be used with experimental or quasi-experimental data to identify who should be treated, be untreated, and self-select to achieve a policymaker’s objective. Applying this method to a randomized controlled trial on a residential energy rebate program, we find that targeting that optimally exploits both observable data and self-selection outperforms conventional targeting for a utilitarian welfare function as well as welfare functions that balance the equity-efficiency tradeoff. We highlight that the Local Average Treatment Effect (LATE) framework (Imbens and Angrist, 1994) can be used to investigate the mechanism behind our approach. By estimating several key LATEs based on the random variation created by our experiment, we demonstrate how our method allows policymakers to identify whose self-selection would be valuable and harmful to social welfare.

More Research From These Scholars

BFI Working Paper Feb 23, 2018

Moral Suasion and Economic Incentives: Field Experimental Evidence from Energy Demand

Koichiro Ito, Takanori Ida, Makoto Tanaka
Topics:  Energy & Environment, Industrial Organization, Financial Markets
BFI Working Paper May 19, 2022

The Dynamic Impact of Market Integration: Evidence from Renewable Energy Expansion in Chile

Luis E. Gonzales, Koichiro Ito, Mar Reguant
Topics:  Energy & Environment
BFI Working Paper Feb 1, 2021

Selection on Welfare Gains: Experimental Evidence from Electricity Plan Choice

Koichiro Ito, Takanori Ida, Makoto Tanaka
Topics:  Energy & Environment