• Corpus ID: 245335288

Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs

  title={Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs},
  author={Takanori Ida and Takunori Ishihara and Koichiro Ito and Daido Kido and Toru Kitagawa and Shosei Sakaguchi and Shusaku Sasaki},
Identifying who should be treated is a central question in economics. There are two competing approaches to targeting—paternalistic and autonomous. In the paternalistic approach, policymakers optimally target the policy given observable individual characteristics. In contrast, the autonomous approach acknowledges that individuals may possess key unobservable information on heterogeneous policy impacts, and allows them to self-select into treatment. In this paper, we propose a new approach that… 


Who should be Treated? Empirical Welfare Maximization Methods for Treatment Choice
It is shown that when the propensity score is known, the average social welfare attained by EWM rules converges at least at n^(-1/2) rate to the maximum obtainable welfare uniformly over a minimally constrained class of data distributions, and this uniform convergence rate is minimax optimal.
Selection on Welfare Gains: Experimental Evidence from Electricity Plan Choice
We study a problem in which policymakers need to screen self-selected individuals by unobserved heterogeneity in social welfare gains from a policy intervention. In our framework, the marginal
Statistical treatment rules for heterogeneous populations
An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. This paper studies minimax-regret treatment choice
Take-Up and Targeting: Experimental Evidence from Snap
A randomized field experiment in which 30,000 elderly individuals not enrolled in the SNAP program are provided with information that they are likely eligible, provided with this information and also offered assistance in applying suggests that the poor targeting properties of the interventions reduce their welfare gains.
Program evaluation as a decision problem
I argue for thinking of program evaluation as a decision problem. There are two steps. First, a counselor determines which program (treatment or control) each individual joins, based for example on
Causal Inference in Hybrid Intervention Trials Involving Treatment Choice
Randomized allocation of treatments is a cornerstone of experimental design but has drawbacks when a limited set of individuals are willing to be randomized, or the act of randomization undermines
Targeting In-Kind Transfers through Market Design: A Revealed Preference Analysis of Public Housing Allocation
In-kind transfer programs aim to provide valuable resources to beneficiaries while targeting those who most need assistance. This problem is particularly challenging for public housing authorities
Design, Identification, and Sensitivity Analysis for Patient Preference Trials
Abstract Social and medical scientists are often concerned that the external validity of experimental results may be compromised because of heterogeneous treatment effects. If a treatment has
Default Effects And Follow-On Behaviour: Evidence From An Electricity Pricing Program
We study default effects in the context of a residential electricity-pricing program. In the large-scale randomized controlled trial we analyse, one treatment group was given the option to opt-in
This paper considers an individual making a treatment choice. The individual has access to data on other individuals, with values for a list of characteristics, treatment assignments, and outcomes.