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On the power properties of inference for parameters with interval identified sets

Federico A. Bugni, Mengsi Gao, Filip Obradovic, Amilcar Velez

arXiv 29 Jul 2024 · Econometrics

arXiv:2407.20386 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper studies the power properties of confidence intervals (CIs) for a partially-identified parameter of interest with an interval identified set. We assume the researcher has bounds estimators to construct the CIs proposed by Stoye (2009), referred to as CI1, CI2, and CI3. We also assume that these estimators are "ordered": the lower bound estimator is less than or equal to the upper bound estimator. Under these conditions, we establish two results. First, we show that CI1 and CI2 are equally powerful, and both dominate CI3. Second, we consider a favorable situation in which there are two possible bounds estimators to construct these CIs, and one is more efficient than the other. One would expect that the more efficient bounds estimator yields more powerful inference. We prove that this desirable result holds for CI1 and CI2, but not necessarily for CI3.

Citation extraction

5
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appendix boundary found by appendix_titled_section at “Appendix” · 28% of the source is main text. Read the extracted text to check this.

Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Stoye, J (2009) More on Confidence Intervals for Partially Identified Parameters1.000174100%
2Imbens, G. and C. F. Manski (2004) Confidence Intervals for Partially Identified Parameters1.00053100%
andrews/soares:2010unmatched citation key andrews/soares:20100.40511100%
4Bugni, F. A., M. Gao, F. Obradovic, and A. Velez (2024) Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance, Working paper self0.40511100%
bugni:2010unmatched citation key bugni:20100.40511100%
bugni:2015unmatched citation key bugni:20150.40511100%
7Hahn, J (1998) On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects0.40511100%
8Hirano, K., G. Imbens, and G. Ridder (2003) Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score0.40511100%

Showing the top 8 of 8 scored citations. 3 of these could not be matched to a bibliography entry, so only the citation key is shown.