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Journal Article
Abowd, John M., and Kevin L. McKinney. "Noise infusion as a confidentiality protection measure for graph-based statistics." Statistical Journal of the International Association for Official Statistics 32, no. 1 (2016): 127-135. DOI: 10.3233/SJI-160958, available at http://content.iospress.com/articles/statistical-journal-of-the-iaos/sji958.
Report
Abowd, John M., Kevin L. McKinney, and Nellie Zhao. Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data. Cornell University Preprint 1813:52609, 2017, available at http://hdl.handle.net/1813/52609.
Abowd, John M., Kevin L. McKinney, and Ian M. Schmutte. Modeling Endogenous Mobility in Earnings Determination. Cornell University Preprint 1813:40306, 2016, available at http://hdl.handle.net/1813/40306.
Abowd, John M., Kevin L. McKinney, and Ian M. Schmutte. Modeling Endogenous Mobility in Wage Determination. Cornell University Preprint 1813:40306, 2015, available at http://hdl.handle.net/1813/40306.
Abowd, John M., Kevin L. McKinney, and Ian M. Schmutte. Modeling Endogenous Mobility in Wage Determination. NCRN Coordinating Office Preprint 1813:52608, 2015, available at http://hdl.handle.net/1813/52608.
Abowd, John A., and Kevin L. McKinney. Noise Infusion as a Confidentiality Protection Measure for Graph-Based Statistics. Cornell University Preprint 1813:42338, 2015, available at http://hdl.handle.net/1813/42338.