Andreas Petrou-Zeniou, Azeem M. Shaikh
arXiv 24 Oct 2024 · Econometrics
arXiv:2410.19212 · PDF · DOI · OpenAlex · Extracted main text
This paper considers the problem of inference on multiple winners. In our setting, a winner is defined abstractly as any population whose rank according to some random quantity, such as an estimated treatment effect, a measure of value-added, or benefit (net of cost), falls in a pre-specified range of values. As such, this framework generalizes the inference on a single winner setting previously considered in Andrews et al. (2023), in which a winner is understood to be the single population whose rank according to some random quantity is highest. We show that this richer setting accommodates a broad variety of empirically-relevant applications. We develop a two-step method for inference in the spirit of Romano et al. (2014), which we compare to existing methods or their natural generalizations to this setting. We first show the finite-sample validity of this method in a normal location model and then develop asymptotic counterparts to these results by proving uniform validity over a large class of distributions satisfying a weak uniform integrability condition. Importantly, our results permit degeneracy in the covariance matrix of the limiting distribution, which arises naturally in many applications. In an application to the literature on economic mobility, we find that it is difficult to distinguish between high and low mobility census tracts when correcting for selection. Finally, we demonstrate the practical relevance of our theoretical results through an extensive set of simulations.
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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 | Andrews, I., Kitagawa, T. and McCloskey, A (2023) Inference on Winners* | 1.000 | 45 | 9 | 100% |
| 2 | Zrnic, T. and Fithian, W (2024) Locally simultaneous inference | 1.000 | 36 | 7 | 100% |
| 3 | Zrnic, T. and Fithian, W (2024) A flexible defense against the winner's curse | 1.000 | 22 | 5 | 100% |
| 4 | Mogstad, M., Romano, J. P., Shaikh, A. M. and Wilhelm, D (2023) Inference for Ranks with Applications to Mobility across Neighbourhoods and Academic Achievement across Countries self | 1.000 | 20 | 3 | 100% |
| 5 | Bergman, P., Chetty, R., DeLuca, S., Hendren, N., Katz, L. F. and Pa… (2024) Creating moves to opportunity: Experimental evidence on barriers to neighborhood choice | 1.000 | 14 | 3 | 100% |
| 6 | Lee, J. D., Sun, D. L., Sun, Y. and Taylor, J. E (2016) Exact post-selection inference, with application to the lasso | 1.000 | 10 | 5 | 100% |
| 7 | Andrews, I., Bowen, D., Kitagawa, T. and McCloskey, A (2022) Inference for losers | 1.000 | 8 | 4 | 100% |
| 8 | Romano, J. P. and Shaikh, A. M (2012) On the uniform asymptotic validity of subsampling and the bootstrap self | 1.000 | 7 | 3 | 100% |
| 9 | Romano, J. P., Shaikh, A. M. and Wolf, M (2014) A practical two-step method for testing moment inequalities self | 0.928 | 4 | 3 | 100% |
| 10 | Chetty, R., Friedman, J. N., Hendren, N., Jones, M. R. and Porter, S… (2025) The opportunity atlas: Mapping the childhood roots of social mobility | 0.874 | 11 | 2 | 100% |
Showing the top 10 of 29 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Semiparametric Off-Policy Inference for Optimal Policy Values under Possible Non-Uniqueness | 0.511 | 2 | 1 |