References
Barrientos, Andrés F, Aaron R Williams, Joshua Snoke, and Claire McKay
Bowen. 2024. “A Feasibility Study of Differentially Private
Summary Statistics and Regression Analyses with Evaluations on
Administrative and Survey Data.” Journal of the American
Statistical Association 119 (545): 52–65.
Bierbrauer, Felix J, Pierre C Boyer, and Andreas Peichl. 2021.
“Politically Feasible Reforms of Nonlinear Tax Systems.”
American Economic Review 111 (1): 153–91.
Bowen, Claire McKay. 2021. Protecting Your Privacy in a Data-Driven
World. Chapman; Hall/CRC.
———. 2024. “Government Data of the People, by the People, for the
People: Navigating Citizen Privacy Concerns.” Journal of
Economic Perspectives 38 (2): 181–200.
Bowen, Claire McKay, and Simson Garfinkel. 2021. “Philosophy of
Differential Privacy.” Notices of the American Mathematical
Society 68 (10): 1727–39.
Bowen, Claire McKay, and Joshua Snoke. 2023. “Do No Harm
Guide: Applying Equity Awareness In Data Privacy Methods.”
Urban Institute. https://www.urban.org/research/publication/do-no-harm-guide-applying-equity-awareness-data-privacy-methods.
Choi, Jung Hyun, Alanna McCargo, Michael Neal, Laurie Goodman, and
Caitlin Young. 2019. “Explaining the Black-White Homeownership
Gap.” Urban Institute. https://www.urban.org/research/publication/explaining-black-white-homeownership-gap-closer-look-disparities-across-local-markets.
Cohen, Mychal, Amy Rohan, Kathleen Pritchard, and Kathryn LS Pettit.
2022. “Guide to Data Chats: Convening Community Conversations
about Data.” Urban Institute. https://www.urban.org/research/publication/guide-data-chats-convening-community-conversations-about-data.
DeBacker, Jason, Richard W Evans, and Kerk L Phillips. 2019.
“Integrating Microsimulation Models of Tax Policy into a Dge
Macroeconomic Model.” Public Finance Review 47 (2):
207–75.
Denning, Dorothy Elizabeth Robling. 1982. Cryptography and Data
Security. Vol. 112. Addison-Wesley Reading.
Drechsler, Jörg. 2022. “Challenges in Measuring Utility for Fully
Synthetic Data.” In International Conference on Privacy in
Statistical Databases, 220–33. Springer.
Drechsler, Jörg, Stefan Bender, and Susanne Rässler. 2008.
“Comparing Fully and Partially Synthetic Datasets for Statistical
Disclosure Control in the German IAB Establishment Panel.”
Transactions on Data Privacy 1 (December): 105–30.
Fellegi, Ivan P. 1972. “On the Question of Statistical
Confidentiality.” Journal of the American Statistical
Association 67 (337): 7–18.
Fienberg, Stephen E. 1994. “Sharing Statistical Data in the
Biomedical and Health Sciences: Ethical, Institutional, Legal, and
Professional Dimensions.” Annual Review of Public Health
15 (1): 1–18.
Fienberg, Stephen E, and Jiashun Jin. 2018. “Statistical
Disclosure Limitation for~ Data~ Access.” In Encyclopedia of
Database Systems (2nd Ed.).
Foote, Andrew David, Ashwin Machanavajjhala, and Kevin McKinney. 2019.
“Releasing Earnings Distributions Using Differential Privacy:
Disclosure Avoidance System for Post-Secondary Employment Outcomes
(Pseo).” Journal of Privacy and Confidentiality 9 (2).
Glickman, Jodi. 2011. Great on the Job: What to Say, How to Say It.
The Secrets of Getting Ahead. St. Martin’s Griffin.
Hu, Jingchen, and Claire McKay Bowen. 2024. “Advancing Microdata
Privacy Protection: A Review of Synthetic Data Methods.”
Wiley Interdisciplinary Reviews: Computational Statistics 16
(1): e1636.
ICPSR. n.d. “Guide to Social Science Data Preparation and
Archiving: Best Practice Throughout the Data Life Cycle: 6th
Edition.” https://www.icpsr.umich.edu/web/pages/deposit/guide/.
Kitchin, Rob. 2014. The Data Revolution: Big Data, Open Data, Data
Infrastructures and Their Consequences. Sage.
Matthews, Gregory J, and Ofer Harel. 2011. “Data Confidentiality:
A Review of Methods for Statistical Disclosure Limitation and Methods
for Assessing Privacy.”
McClelland, Robert, Daniel Berger, Alyssa Harris, Chenxi Lu, and Kyle
Ueyama. 2019. “The Tcja: What Might Have Been.”
Urban-Brookings Tax Policy Center.
McKenna, L, and M Haubach. 2019. “Legacy Techniques and Current
Research in Disclosure Avoidance at the Us Census Bureau.”
Research and Methodology Directorate, US Census Bureau, Washington,
DC.
Mitra, Robin, and Jerome P Reiter. 2006. “Adjusting Survey Weights
When Altering Identifying Design Variables via Synthetic Data.”
In Privacy in Statistical Databases: CENEX-SDC Project International
Conference, PSD 2006, Rome, Italy, December 13-15, 2006.
Proceedings, 177–88. Springer.
Murray, Brittany, Elsa Falkenburger, and Priya Saxena. 2015. “Data
Walks: An Innovative Way to Share Data with Communities.” https://www.urban.org/research/publication/data-walks-innovative-way-share-data-communities.
Reiter, Jerome P, Quanli Wang, and Biyuan Zhang. 2014. “Bayesian
Estimation of Disclosure Risks for Multiply Imputed, Synthetic
Data.” Journal of Privacy and Confidentiality 6 (1).
Reiter, Jerry, Claire McKay Bowen, Aloni Cohen, Diana Farrell, Robert
Goerge M., Nicholas Hart, Jagadish Hosagrahar V., et al. 2024.
“Toward a 21st Century National Data Infrastructure: Managing
Privacy and Confidentiality Risks with Blended Data.”
National Academies of Sciences, Engineering, and Medicine.
Schwabish, Jonathan. 2021. Better Data Visualizations: A Guide for
Scholars, Researchers, and Wonks. Columbia University Press.
Schwabish, Jonathan A. 2020. Elevate the Debate: A Multilayered
Approach to Communicating Your Research. John Wiley & Sons.
Schwabish, Jonathan, Donovan Harvey, Mel Langness, Vincent Pancini, Amy
Rogin, and Gabi Velasco. 2023. “Do No Harm Guide: Collecting,
Analyzing, and Reporting Gender and Sexual Orientation Data.”
Sonoda, Paige, and Heather Hahn. 2023. “Disaggregating Data Is
Critical to Dismantling the Model Minority Stereotype.” https://www.urban.org/urban-wire/disaggregating-data-critical-dismantling-model-minority-stereotype.
Stern, Alena, and Ajjit Narayanan. 2021. “Ethics and Empathy in
Using Imputation to Disaggregate Data for Racial Equity.” https://www.urban.org/research/publication/ethics-and-empathy-using-imputation-disaggregate-data-racial-equity-case-study-imputing-credit-bureau-data.
Sweeney, Latanya, Akua Abu, and Julia Winn. 2013. “Identifying
Participants in the Personal Genome Project by Name (a Re-Identification
Experiment).” https://arxiv.org/abs/1304.7605.
Tarran, Brian. 2023. “JSM Session Touches on Equity.”
Amstat News. https://magazine.amstat.org/blog/2023/11/01/jedi-corner-jsm-session-equity/.
Traub, Amy, and Sean McElwee. 2016. “Bad Credit Shouldn’t Block
Employment: How to Make State Bans on Employment Credit Checks More
Effective.” Washington, DC: Demos.
Turow, Joseph, Yphtach Lelkes, Nora Draper, and Ari Ezra Waldman. 2023.
“Americans Can’t Consent to Companies’ Use of Their Data: They
Admit They Don’t Understand It, Say They’re Helpless to Control It, and
Believe They’re Harmed When Firms Use Their Data–Making What Companies
Do Illegitimate.” Say They’re Helpless to Control It, and
Believe They’re Harmed When Firms Use Their Data–Making What Companies
Do Illegitimate (February 15, 2023).
Wilkinson, Mark D, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle
Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al. 2016.
“The FAIR Guiding Principles for Scientific Data Management and
Stewardship.” Scientific Data 3 (1): 1–9.
Williams, Aaron R, and Claire McKay Bowen. 2023. “The Promise and
Limitations of Formal Privacy.” Wiley Interdisciplinary
Reviews: Computational Statistics 15 (6): e1615.
Williams, Aaron R, Joshua Snoke, Claire McKay Bowen, and Andrés F
Barrientos. 2023. “Disclosing Economists’ Privacy Perspectives: A
Survey of American Economic Association Members on Differential Privacy
and Data Fitness for Use Standards.” In Data Privacy
Protection and the Conduct of Applied Research: Methods Approaches and
Their Consequences NBER Conference, Cambridge, MA, May. Vol. 4.