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Modelling with Sensitive Variables

Felix Chan, Laszlo Matyas, Agoston Reguly

arXiv 22 Mar 2024 · Econometrics · publishedAStA Advances in Statistical Analysis (2026)

arXiv:2403.15220 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The paper deals with models in which the dependent variable, some explanatory variables, or both represent sensitive data. We introduce a novel discretization method that preserves data privacy when working with such variables. A multiple discretization method is proposed that utilizes information from the different discretization schemes. We show convergence in distribution for the unobserved variable and derive the asymptotic properties of the OLS estimator for linear models. Monte Carlo simulation experiments presented support our theoretical findings. Finally, we contrast our method with a differential privacy method to estimate the Australian gender wage gap.

Citation extraction

33
references
50
in-text mentions
33
distinct cited
1
self-citations
11,619
main-text words

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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
1Bi, X., Shen, X (2023) Distribution-invariant differential privacy0.87452100%
2Beresteanu, A., Molinari, F (2008) Asymptotic properties for a class of partially identified models0.81142100%
3Manski, C.F., Tamer, E (2002) Inference on regressions with interval data on a regressor or outcome0.81142100%
4Cai, T.T., Wang, Y., Zhang, L (2021) The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy0.64422100%
5Dwork, C (2006) Differential privacy0.64422100%
6Pacini, D (2019) The two-sample linear regression model with interval-censored covariates0.58531100%
7Abrevaya, J., Muris, C (2020) Interval censored regression with fixed effects0.51121100%
8Beresteanu, A., Molchanov, I., Molinari, F (2011) Sharp identification regions in models with convex moment predictions0.51121100%
9Chernozhukov, V., Hong, H., Tamer, E (2007) Estimation and confidence regions for parameter sets in econometric models0.51121100%
10Duchi, J.C., Jordan, M.I., Wainwright, M.J (2018) Minimax optimal procedures for locally private estimation0.40511100%

Showing the top 10 of 33 scored citations.