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2.
Proc Natl Acad Sci U S A ; 120(43): e2220558120, 2023 Oct 24.
Article in English | MEDLINE | ID: mdl-37831744

ABSTRACT

The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. We argue that any proposal for quantifying disclosure risk should be based on prespecified, objective criteria. We illustrate this approach to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. More research is needed, but in the near term, the counterfactual approach appears best-suited for privacy versus utility analysis.


Subject(s)
Confidentiality , Disclosure , Privacy , Risk Assessment , Censuses
3.
Bus Econ ; 57(2): 64-77, 2022.
Article in English | MEDLINE | ID: mdl-35221344

ABSTRACT

The data demands during the pandemic heightened the need to blend information from numerous sources to get a more timely and granular picture of economic developments. Ongoing efforts include the Chicago Fed's weekly retail sales estimate, the Census Bureau's work on higher-frequency state-level retail sales data, the Federal Reserve Board's computations of business closures and weekly payrolls, and the academic Opportunity Insights team's estimates of spending, business revenues and employment by income and ZIP code.

4.
Science ; 350(6266): 1367-71, 2015 Dec 11.
Article in English | MEDLINE | ID: mdl-26659054

ABSTRACT

In evaluating research investments, it is important to establish whether the expertise gained by researchers in conducting their projects propagates into the broader economy. For eight universities, it was possible to combine data from the UMETRICS project, which provided administrative records on graduate students supported by funded research, with data from the U.S. Census Bureau. The analysis covers 2010-2012 earnings and placement outcomes of people receiving doctorates in 2009-2011. Almost 40% of supported doctorate recipients, both federally and nonfederally funded, entered industry and, when they did, they disproportionately got jobs at large and high-wage establishments in high-tech and professional service industries. Although Ph.D. recipients spread nationally, there was also geographic clustering in employment near the universities that trained and employed the researchers. We also show large differences across fields in placement outcomes.

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