Zobrazeno 1 - 10
of 36
pro vyhledávání: '"John Abowd"'
Autor:
Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev, John Abowd
Publikováno v:
The Journal of Privacy and Confidentiality, Vol 14, Iss 3 (2024)
The 2020 Census Disclosure Avoidance System (DAS) is a formally private mechanism that first adds independent noise to cross tabulations for a set of pre-specified hierarchical geographic units, which is known as the geographic spine. After post-proc
Externí odkaz:
https://doaj.org/article/1901e69555824832ac5d145018491781
Autor:
John Abowd
Publikováno v:
Harvard Data Science Review, Vol 6, Iss 2 (2024)
Externí odkaz:
https://doaj.org/article/53964e772d8e478aa84ff72305a72705
Autor:
John Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev
Publikováno v:
Harvard Data Science Review, Iss Special Issue 2 (2022)
Externí odkaz:
https://doaj.org/article/ac7fa828d4dd4e0d815f03f541590a0e
Autor:
John Abowd
Publikováno v:
The Journal of Privacy and Confidentiality, Vol 8, Iss 1 (2018)
As readers of this Journal know, I paid my tribute to Steve Fienberg in my 2016 Julius Shiskin Lecture:As readers of this Journal know, I paid my tribute to Steve Fienberg in my 2016 Julius Shiskin Lecture: "Finally, I would like to acknowledge th
Externí odkaz:
https://doaj.org/article/60d4878bd5fe47db8a4a828de0c7326c
Publikováno v:
International Journal of Digital Curation, Vol 8, Iss 1, Pp 265-278 (2013)
Social science researchers increasingly make use of data that is confidential because it contains linkages to the identities of people, corporations, etc. The value of this data lies in the ability to join the identifiable entities with external data
Externí odkaz:
https://doaj.org/article/d04d019acf044a4a8434517f90d99a40
Autor:
Robert Moffitt, John Abowd, Christopher Bollinger, Michael Carr, Charles Hokayem, Kevin McKinney, Emily Wiemers, Sisi Zhang, James Ziliak
There is a large literature on earnings and income volatility in labor economics, household finance, and macroeconomics. One strand of that literature has studied whether individual earnings volatility has risen or fallen in the U.S. over the last se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f22a44fdc87bc0f4d71df735546b58c
The purpose of this document is to provide scholars with a comprehensive list of readings relevant to the economic analysis of formal privacy, and particularly its application to public statistics. Statistical agencies and tech giants are rapidly ado
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1f113276f245e8b0e0b77ecda6d2c06
Autor:
Lars Vilhuber, John Abowd
Publikováno v:
Journal of Business & Economic Statistics. 23:162-165
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d871bcb1f323f01b46157c28a37833a
https://doi.org/10.1198/073500104000000712
https://doi.org/10.1198/073500104000000712
Autor:
John Abowd, Martha Stinson
We quantify sources of variation in annual job earnings data collected by the Survey of Income and Program Participation (SIPP) to determine how much of the variation is the result of measurement error. Jobs reported in the SIPP are linked to jobs re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::c37a7464e41049351692225045dac7f1
https://www2.census.gov/ces/wp/2011/CES-WP-11-20.pdf
https://www2.census.gov/ces/wp/2011/CES-WP-11-20.pdf