CREAT: Census Research Exploration and Analysis Tool

Revisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goods

January 2017

Working Paper Number:

CES-17-37

Abstract

We consider the problem of determining the optimal accuracy of public statistics when increased accuracy requires a loss of privacy. To formalize this allocation problem, we use tools from statistics and computer science to model the publication technology used by a public statistical agency. We derive the demand for accurate statistics from first principles to generate interdependent preferences that account for the public-good nature of both data accuracy and privacy loss. We first show data accuracy is inefficiently undersupplied by a private provider. Solving the appropriate social planner's problem produces an implementable publication strategy. We implement the socially optimal publication plan for statistics on income and health status using data from the American Community Survey, National Health Interview Survey, Federal Statistical System Public Opinion Survey and Cornell National Social Survey. Our analysis indicates that welfare losses from providing too much privacy protection and, therefore, too little accuracy can be substantial.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

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:
economist, estimating, researcher, statistical, survey, disclosure, respondent, confidentiality, statistician, privacy, datasets, statistical disclosure, public

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:
National Science Foundation, Cornell University, Georgetown University, American Community Survey, National Health Interview Survey, Cornell Institute for Social and Economic Research, Sloan Foundation, National Academy of Sciences, George Mason University, Society of Labor Economists

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