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Quantifying the impact of regulatory policies on social welfare generally requires the identification of counterfactual distributions. Many of these policies (e.g. minimum wages or minimum working time) generate mass points and/or…

Econometrics · Economics 2025-11-25 Dalia Ghanem , Désiré Kédagni , Ismael Mourifié

This paper proposes a framewrok for analyzing how the welfare effects of policy interventions are distributed across individuals when those effects are unobserved. Rather than focusing solely on average outcomes, the approach uses readily…

Econometrics · Economics 2025-12-25 Costas Lambros , Emerson Melo

Empirical welfare analyses often impose stringent parametric assumptions on individuals' preferences and neglect unobserved preference heterogeneity. We develop a framework to conduct individual and social welfare analysis for discrete…

Theoretical Economics · Economics 2025-05-20 Bart Capéau , Liebrecht De Sadeleer , Sebastiaan Maes

Strong empirical evidence from laboratory experiments, and more recently from population surveys, shows that individuals, when evaluating their situations, pay attention to whether they experience gains or losses, with losses weighing more…

Theoretical Economics · Economics 2025-10-17 Martyna Kobus , Radosław Kurek , Thomas Parker

This paper develops theoretical criteria and econometric methods to rank policy interventions in terms of welfare when individuals are loss-averse. Our new criterion for "loss aversion-sensitive dominance" defines a weak partial ordering of…

Econometrics · Economics 2023-09-07 Sergio Firpo , Antonio F. Galvao , Martyna Kobus , Thomas Parker , Pedro Rosa-Dias

This paper develops a robust and efficient method for policy learning from observational data in the presence of unobserved confounding, complementing existing instrumental variable (IV) based approaches. We employ the marginal sensitivity…

Econometrics · Economics 2025-07-29 Zequn Jin , Gaoqian Xu , Xi Zheng , Yahong Zhou

Off-policy evaluation of sequential decision policies from observational data is necessary in applications of batch reinforcement learning such as education and healthcare. In such settings, however, unobserved variables confound observed…

Machine Learning · Computer Science 2020-07-14 Nathan Kallus , Angela Zhou

Empirical Welfare Maximization (EWM) is a framework that can be used to select welfare program eligibility policies based on data. This paper extends EWM by allowing for uncertainty in estimating the budget needed to implement the selected…

Econometrics · Economics 2025-12-18 Liyang Sun

This paper introduces a rule for policy selection in the presence of estimation uncertainty, explicitly accounting for estimation risk. The rule belongs to the class of risk-aware rules on the efficient decision frontier, characterized as…

Econometrics · Economics 2026-01-21 Victor Chernozhukov , Sokbae Lee , Adam M. Rosen , Liyang Sun

We draw attention to an important, yet largely overlooked aspect of evaluating fairness for automated decision making systems---namely risk and welfare considerations. Our proposed family of measures corresponds to the long-established…

Artificial Intelligence · Computer Science 2019-01-14 Hoda Heidari , Claudio Ferrari , Krishna P. Gummadi , Andreas Krause

This paper studies policy learning for continuous treatments from observational data. Continuous treatments present more significant challenges than discrete ones because population welfare may need nonparametric estimation, and policy…

Econometrics · Economics 2025-12-02 Chunrong Ai , Yue Fang , Haitian Xie

Empirical research shows that individuals' responses to treatments vary along latent characteristics, such as innate ability or motivation. Therefore, a policymaker seeking to maximize welfare may consider designing policies based on…

Econometrics · Economics 2026-05-06 Giacomo Opocher

Many real-life settings of consumer-choice involve social interactions, causing targeted policies to have spillover-effects. This paper develops novel empirical tools for analyzing demand and welfare-effects of policy-interventions in…

Econometrics · Economics 2024-05-09 Debopam Bhattacharya , Pascaline Dupas , Shin Kanaya

Motivated by applications such as college admission and insurance rate determination, we propose an evaluation problem where the inputs are controlled by strategic individuals who can modify their features at a cost. A learner can only…

Computer Science and Game Theory · Computer Science 2020-11-05 Nika Haghtalab , Nicole Immorlica , Brendan Lucier , Jack Z. Wang

Neuroeconomics promises to ground welfare analysis in neural and computational evidence about how people value outcomes, learn from experience and exercise self-control. At the same time, policy and commercial actors increasingly invoke…

Machine Learning · Computer Science 2025-11-26 Yiven , Zhu

The relationship of policy choice by majority voting and by maximization of utilitarian welfare has long been discussed. I consider choice between a status quo and a proposed policy when persons have interpersonally comparable cardinal…

Theoretical Economics · Economics 2024-12-30 Charles F. Manski

Current methodologies in machine learning analyze the effects of various statistical parity notions of fairness primarily in light of their impacts on predictive accuracy and vendor utility loss. In this paper, we propose a new framework…

Machine Learning · Computer Science 2018-07-04 Lily Hu , Yiling Chen

To choose between two discrete goods, a consumer pays attention to only those with prices below a threshold. From these, she chooses her most preferred good. We assume consumers in a population have the same preference but may have…

Theoretical Economics · Economics 2025-11-07 Kaushil Patel

We consider the problem of repeatedly choosing policies to maximize social welfare. Welfare is a weighted sum of private utility and public revenue. Earlier outcomes inform later policies. Utility is not observed, but indirectly inferred.…

Econometrics · Economics 2024-07-30 Nicolo Cesa-Bianchi , Roberto Colomboni , Maximilian Kasy

When inferring the causal effect of one variable on another from correlational data, a common practice by professional researchers as well as lay decision makers is to control for some set of exogenous confounding variables. Choosing an…

Theoretical Economics · Economics 2023-05-31 Ran Spiegler
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