arXiv 25 Aug 2024 · Econometrics · publishedJournal of Business and Economic Statistics (2023) · 5 citations (OpenAlex)
arXiv:2408.13949 · PDF · DOI · OpenAlex · Extracted main text
Instead of testing for unanimous agreement, I propose learning how broad of a consensus favors one distribution over another (of earnings, productivity, asset returns, test scores, etc.). Specifically, given a sample from each of two distributions, I propose statistical inference methods to learn about the set of utility functions for which the first distribution has higher expected utility than the second distribution. With high probability, an "inner" confidence set is contained within this true set, while an "outer" confidence set contains the true set. Such confidence sets can be formed by inverting a proposed multiple testing procedure that controls the familywise error rate. Theoretical justification comes from empirical process results, given that very large classes of utility functions are generally Donsker (subject to finite moments). The theory additionally justifies a uniform (over utility functions) confidence band of expected utility differences, as well as tests with a utility-based "restricted stochastic dominance" as either the null or alternative hypothesis. Simulated and empirical examples illustrate the methodology.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Goldman, Matt and David M. Kaplan (2018) Comparing distributions by multiple testing across quantiles or CDF values | 0.874 | 7 | 2 | 100% |
| 2 | Atkinson, A. B (1987) On the Measurement of Poverty | 0.811 | 4 | 2 | 100% |
| 3 | R Core Team (2022) R: A Language and Environment for Statistical Computing | 0.737 | 3 | 3 | 67% |
| 4 | Harsanyi, John C (1953) Cardinal Utility in Welfare Economics and in the Theory of Risk-taking | 0.737 | 3 | 2 | 100% |
| 5 | Merton, Robert C (1971) Optimum consumption and portfolio rules in a continuous-time model | 0.737 | 3 | 2 | 100% |
| 6 | Vickrey, William (1945) Measuring Marginal Utility by Reactions to Risk | 0.737 | 3 | 2 | 100% |
| 7 | Atkinson, Anthony B (1970) On the Measurement of Inequality | 0.644 | 2 | 2 | 100% |
| 8 | Rawls, John (1971) A Theory of Justice | 0.644 | 2 | 2 | 100% |
| 9 | Lehmann, E. L. and Joseph P. Romano (2005) Testing Statistical Hypotheses | 0.585 | 3 | 3 | 33% |
| 10 | Armstrong, Timothy B. and Shu Shen (2015) Inference on Optimal Treatment Assignments | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 38 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Comparing latent inequality with ordinal data | 0.644 | 2 | 2 |