TY  - BOOK
AU  - Ida,Takanori
AU  - Ishihara,Takunori
AU  - Ito,Koichiro
AU  - Kido,Daido
AU  - Kitagawa,Toru
AU  - Sakaguchi,Shosei
AU  - Sasaki,Shusaku
ED  - National Bureau of Economic Research.
TI  - Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs 
T2  - NBER working paper series
PY  - 2022///
CY  - Cambridge, Mass.
PB  - National Bureau of Economic Research
KW  - Econometrics
KW  - jelc
KW  - Energy
KW  - Government Policy
KW  - Environmental Economics
N1  - September 2022; Hardcopy version available to institutional subscribers
N2  - 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 trade-off. 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
UR  - https://www.nber.org/papers/w30469
UR  - http://dx.doi.org/10.3386/w30469
ER  -