My da|ra Login

Detailed view

metadata language: English

Replication data for: A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples

Version
V0
Resource Type
Dataset
Creator
  • Chetty, Raj
  • Friedman, John N.
Publication Date
2019-05-01
Description
  • Abstract

    Building on insights from the differential privacy literature, we develop a simple noise-infusion method to reduce privacy loss when disclosing statistics such as OLS regression estimates based on small samples. Although our method does not offer a formal privacy guarantee, it outperforms widely used methods of disclosure limitation such as count-based cell suppression both in terms of privacy loss and statistical bias. We illustrate how the method can be implemented by discussing how it was used to release estimates of social mobility by census tract in the Opportunity Atlas. We provide a step-by-step guide and code to implement our approach.
Availability
Download
Relations
  • Is supplement to
    DOI: 10.1257/pandp.20191109 (Text)
Publications
  • Chetty, Raj, and John N. Friedman. “A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples.” AEA Papers and Proceedings 109 (May 2019): 414–20. https://doi.org/10.1257/pandp.20191109.
    • ID: 10.1257/pandp.20191109 (DOI)

Update Metadata: 2020-05-18 | Issue Number: 2 | Registration Date: 2019-12-07

Chetty, Raj; Friedman, John N. (2019): Replication data for: A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples. Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E116494