John M. Abowd

University of Western Ontario|Cornell University

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Male Earnings Volatility in LEHD before, during, and after the Great Recession

Kevin L. McKinney,John M. Abowd

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Total Error and Variability Measures for the Quarterly Workforce Indicators and LEHD Origin-Destination Employment Statistics in OnTheMap

Kevin L. McKinney, Andrew S. Green,Lars Vilhuber,John M. Abowd

Journal of Survey Statistics and Methodology, (2020)

Bibtex

Why the Economics Profession Must Actively Participate in the Privacy Protection Debate

John M. Abowd,Ian M. Schmutte, William N. Sexton,Lars Vilhuber

AEA PAPERS AND PROCEEDINGS, (2019): 397-402

Bibtex

Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods

John M. Abowd,Ian M. Schmutte, William Sexton,Lars Vilhuber

CoRR, (2019)

EIBibtex

Understanding Database Reconstruction Attacks on Public Data

Simson L. Garfinkel,John M. Abowd, Christian Martindale

ACM Queue, no. 5 (2018): 50-53

EIBibtex

Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System

Daniel H Weinberg,John M Abowd,Robert F Belli,Noel Cressie,David C Folch,Scott H Holan,Margaret C Levenstein,Kristen M Olson,Jerome P Reiter,Matthew D Shapiro,Jolene D Smyth,Leen-Kiat Soh

Journal of survey statistics and methodology, (2018)

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Issues Encountered Deploying Differential Privacy

Simson L. Garfinkel,John M. Abowd, Sarah Powazek

WPES@CCS, (2018): 133-137

Cited by27EIBibtex

The U.S. Census Bureau Adopts Differential Privacy

John M. Abowd

KDD, pp.2867-2913, (2018)

Cited by48EIBibtex

An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices

John M. Abowd,Ian M. Schmutte

AMERICAN ECONOMIC REVIEW, no. 1 (2018): 171-202

EIBibtex

Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics

Samuel Haney,Ashwin Machanavajjhala,John M. Abowd, Matthew Graham,Mark Kutzbach,Lars Vilhuber

SIGMOD Conference, pp.1339-1354, (2017)

Cited by36EIBibtex

Modeling Endogenous Mobility in Earnings Determination

John M. Abowd,Kevin L. McKinney,Ian M. Schmutte

Journal of Business & Economic Statistics, no. 3 (2017): 0-418

Cited by1WOSBibtex

Privacy-Preserving Data Analysis for the Federal Statistical Agencies

John M. Abowd,Lorenzo Alvisi,Cynthia Dwork,Sampath Kannan,Ashwin Machanavajjhala,Jerome P. Reiter

arXiv: Computers and Society, (2017)

Cited by5EIBibtex

Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data

John M. Abowd,Kevin L. McKinney, Nellie L. Zhao

Social Science Research Network, (2017)

Bibtex

Synthetic establishment microdata around the world

Lars Vilhuber,John M. Abowd

Statistical journal of the IAOS, no. 1 (2016): 65-68

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Earnings Inequality Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data

John M Abowd,Kevin Mckinney, Nellie Zhao

(2015)

Cited by3Bibtex

NCRN Meeting Spring 2015: Revisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goods

John M Abowd,Ian M Schmutte

(2015)

Bibtex

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

John M Abowd,Ian M Schmutte

(2015)

Cited by8Bibtex

Economic Analysis and Statistical Disclosure Limitation

John M. Abowd,Ian M. Schmutte

BROOKINGS PAPERS ON ECONOMIC ACTIVITY, pp.221-293, (2015)

Bibtex

A new method for protecting interrelated time series with Bayesian prior distributions and synthetic data

Matthew J Schneider,John M Abowd

Journal of The Royal Statistical Society Series A-statistics in Society, (2015)

Cited by4Bibtex

Economic Analysis and Statistical Disclosure Limitation

Ian M Schmutte,John M Abowd

(2015)

Cited by12Bibtex

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John M. AbowdBinding

Papers191 papers

John M. Abowd