Replication data for: An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
Principal Investigator(s): View help for Principal Investigator(s) John M. Abowd; Ian M. Schmutte
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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Original-Sources-and-Research-Concerning-Census-Bureau | 10/20/2021 10:46:AM | ||
Title_I | 10/20/2021 10:46:AM | ||
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application/pdf | 512.8 KB | 10/12/2019 03:16:AM |
Project Description
Summary:
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Statistical agencies face a dual mandate to publish accurate statistics while protecting respondent privacy. Increasing privacy protection requires decreased accuracy. Recognizing this as a resource allocation problem, we propose an economic solution: operate where the marginal cost of increasing privacy equals the marginal benefit. Our model of production, from computer science, assumes data are published using an efficient differentially private algorithm. Optimal choice weighs the demand for accurate statistics against the demand for privacy. Examples from U.S. statistical programs show how our framework can guide decision-making. Further progress requires a better understanding of willingness-to-pay for privacy and statistical accuracy.
Scope of Project
Subject Terms:
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[economics, public goods, algorithmic fairness, data privacy, differential privacy]
JEL Classification:
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C38 Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
C81 Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
C38 Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
C81 Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Geographic Coverage:
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United States
Data Type(s):
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[survey data, administrative records data]
Collection Notes:
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This is an archive of data publicly available elsewhere
Methodology
Unit(s) of Observation:
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school district,
state,
Related Publications
Published Versions
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