Recently Published Documents
- Understanding Database Reconstruction Attacks on Public Data
Simson L. Garfinkel, John M. Abowd, and Christian Martindale - The U.S. Census Bureau Adopts Differential Privacy
John M. Abowd - An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
John M. Abowd and Ian M. Schmutte - Disclosure Limitation and Confidentiality Protection in Linked Data
John M. Abowd, Ian M. Schmutte, and Lars Vilhuber - Total Error and Variability Measures with Integrated Disclosure Limitation for Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in OnThe Map
Kevin L. McKinney, Andrew Green, Lars Vilhuber, and John Abowd - Recalculating - How Uncertainty in Local Labor Market Definitions Affects Empirical Findings
Andrew Foote, Mark Kutzbach, and Lars Vilhuber - Proceedings from the Synthetic LBD International Seminar
Lars Vilhuber, Saki Kinney, and Ian M. Schmutte - Proceedings from the 2017 Cornell-Census- NSF-Sloan Workshop on Practical Privacy
Lars Vilhuber and Ian M. Schmutte - Hours Off the Clock
Andrew Green - Making Confidential Data Part of Reproducible Research
Lars Vilhuber and Carl Lagoze - Sorting Between and Within Industries: A Testable Model of Assortative Matching
John M. Abowd, Francis Kramarz, Sebastien Perez-Duarte, and Ian M. Schmutte - Two Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files
Andrew Green, Mark Kutzbach, and Lars Vilhuber - Revisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goods
John Abowd and Ian M. Schmutte - Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics
Samuel Haney, Ashwin Machanavajjhala, John M. Abowd, Matthew Graham, Mark Kutzbach, and Lars Vilhuber - Understanding the Effect of Procedural Justice on Psychological Distress
Julie Cloutier, Lars Vilhuber, Denis Harrison, and Vanessa Béland-Ouellette - Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data
John M. Abowd, Kevin L. McKinney, and Nellie Zhao - Proceedings from the 2016 NSF–Sloan Workshop on Practical Privacy
Lars Vilhuber and Ian M. Schmutte - Why Statistical Agencies Need to Take Privacy-loss Budgets Seriously, and What It Means When They Do
John M. Abowd - Science, Confidentiality, and the Public Interest
John Abowd and Lars Vilhuber - How Will Statistical Agencies Operate When All Data Are Private?
John M. Abowd