Partial Identification, Distributional Preferences, and the Welfare Ranking of Policies
By: Researcher
Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).
| Authors | Maximilian Kasy |
| Journal/Conference Name | Review of Economics and Statistics |
| Paper Category | Social Sciences |
| Paper Abstract | We discuss the tension between “what we can get” (identification) and “what we want” (parameters of interest) in models of policy choice (treatment assignment). Our nonstandard empirical object of interest is the ranking of counterfactual policies. Partial identification of treatment effects maps into a partial welfare ranking of treatment assignment policies. We characterize the identified ranking and show how the identifiability of the ranking depends on identifying assumptions, the feasible policy set, and distributional preferences. An application to the project STAR experiment illustrates this dependence. This paper connects the literatures on partial identification, robust statistics, and choice under Knightian uncertainty. |
| Date of publication | 2016 |
| Code Programming Language | MATLAB |
| Comment |
Copyright Researcher 2022