The Labor Dynamics Institute's mission is to create and make accessible novel data on the dynamics of the labor markets. We work with research networks and statistical agencies, developing appropriate statistics to inform policy makers, researchers, and simply people seeking knowledge. For more information, visit our website at www.ilr.cornell.edu/ldi.

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Documents from 2017

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Sorting Between and Within Industries: A Testable Model of Assortative Matching, John M. Abowd, Francis Kramarz, Sebastien Perez-Duarte, and Ian M. Schmutte

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Modeling Endogenous Mobility in Wage Determination, John M. Abowd, Kevin L. McKinney, and Ian M. Schmutte

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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

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Revisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goods, John Abowd and Ian M. Schmutte

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Understanding the Effect of Procedural Justice on Psychological Distress, Julie Cloutier, Lars Vilhuber, Denis Harrison, and Vanessa Béland-Ouellette

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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

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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

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Making Confidential Data Part of Reproducible Research, Lars Vilhuber and Carl Lagoze

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Proceedings from the 2016 NSF–Sloan Workshop on Practical Privacy, Lars Vilhuber and Ian M. Schmutte

Documents from 2016

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Why Statistical Agencies Need to Take Privacy-loss Budgets Seriously, and What It Means When They Do, John M. Abowd

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How Will Statistical Agencies Operate When All Data Are Private?, John M. Abowd

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Estimating Compensating Wage Differentials with Endogenous Job Mobility, Kurt Lavetti and Ian M. Schmutte

Documents from 2015

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Noise Infusion as a Confidentiality Protection Measure for Graph-Based Statistics, John M. Abowd and Kevin L. McKinney

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Modeling Endogenous Mobility in Wage Determination, John M. Abowd, Kevin L. McKinney, and Ian M. Schmutte

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Economic Analysis and Statistical Disclosure Limitation, John M. Abowd and Ian M. Schmutte

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Revisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goods, John M. Abowd and Ian M. Schmutte

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Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics, Javier Miranda and Lars Vilhuber

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Synthetic Establishment Microdata Around the World, Lars Vilhuber, John Abowd, and Jerome P. Reiter

Documents from 2014

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Sorting between and within Industries: A Testable Model of Assortative Matching, John M. Abowd, Francis Kramarz, Sebastien Perez-Duarte, and Ian M. Schmutte

Documents from 2013

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Presentation: Revisiting the Economics of Privacy: Population Statistics and Privacy as Public Goods, John Abowd

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Presentation: Assessing the Natural Rate of Unemployment, John Abowd, Tirupam Goel, and Lars Vilhuber

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Presentation: Improved Research Access to Census Bureau Linked Administrative Data via Public-use Products, John Abowd and Lars Vilhuber

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Discussion of "Synthetic establishment microdata" WSC 2013 session, Stefan Bender

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Replicating the Synthetic LBD with German Establishment Data, Jörg Drechsler and Lars Vilhuber

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Expanding the Role of Synthetic Data at the U.S. Census Bureau, Ron Jarmin, Thomas A. Louis, and Javier Miranda