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Quantile-Only Regression: Inference and Partial Identification under Quantile Disclosure

Masamune Iwasawa, Hayato Nakanishi

arXiv 19 Oct 2026 · Econometrics

arXiv:2610.27224 · PDF · Extracted main text

Abstract

Researchers often observe group quantiles but not group means, raising the question of whether these summaries alone support conventional regression analysis. We develop estimation and inference methods for linear models of group means under quantile-only and mixed disclosure. We establish conditions on disclosure design for consistent estimation and asymptotic normality at the parametric rate. Under fixed disclosure, we characterize sharp identified sets and construct simultaneous confidence regions, clarifying how informativeness depends on the number and placement of disclosed quantiles. Applications to education, social care, and medical expenditure illustrate the methods. The R package qonlyreg implements the proposed procedures.

Citation extraction

27
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40
in-text mentions
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distinct cited
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main-text words

appendix boundary found by appendix_command · 29% 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
1Bahadur, R Raj (1966) A note on quantiles in large samples0.64422100%
2Farebrother, Richard William (1979) Estimation with Aggregated Data0.64422100%
3Kiefer, Jack (1967) On Bahadur's representation of sample quantiles0.64422100%
4Li, Hao and Liu, Xinliang and Cui, Dan and Wang, Quan and Mao, Zongf… (2017) Estimating the Direct Medical Economic Burden of Health Care-Associated Infections in Public Tertiary Hospitals in Hubei Provinc…0.6066233%
5Alonso, José M and Andrews, Rhys (2020) Political ideology and social services contracting: evidence from a regression discontinuity design0.5112250%
6Atkinson, Kendall E (1989) An Introduction to Numerical Analysis0.5112250%
7Cai, Siyu and Zhou, Jie and Pan, Jianxin (2021) Estimating the sample mean and standard deviation from order statistics and sample size in meta-analysis0.40511100%
8Cowell, Frank A and Mehta, Fatemeh (1982) The estimation and interpolation of inequality measures0.40511100%
9Department for Education (2024) Children in Need: Methodology0.40511100%
10Department for Education (2026) Working Together to Safeguard Children 2026: A Guide to Multi-Agency Working to Help, Protect and Promote the Welfare of Children0.40511100%

Showing the top 10 of 27 scored citations.