McCartan, Cory, Tyler Simko, and Kosuke Imai. (2023). ``Making Differential Privacy Work for Census Data Users.'' Harvard Data Science Review, Vol. 5, No. 4 (Fall).

The U.S. Census Bureau collects and publishes detailed demographic data about Americans which are heavily used by researchers and policymakers. The Bureau has recently adopted the framework of differential privacy in an effort to improve confidentiality of individual census responses. A key output of this privacy protection system is the Noisy Measurement File (NMF), which is produced by adding random noise to tabulated statistics. The NMF is critical to understanding any biases in the data, and performing valid statistical inference on published census data. Unfortunately, the current release format of the NMF is difficult to access and work with. We describe the process we use to transform the NMF into a usable format, and provide recommendations to the Bureau for how to release future versions of the NMF. These changes are essential for ensuring transparency of privacy measures and reproducibility of scientific research built on census data.

A shorter version is published as: McCartan, Cory, Tyler Simko, and Kosuke Imai. (2023). ``Researchers need better access to US Census data.'' Science, Vol. 380, No. 6648 pp. 902-903.

Our rejonder is published as: McCartan, Cory, Tyler Simko, and Kosuke Imai. (2024). ``Rejoinder: We Can Improve the Usability of the Census Noisy Measurements File.'' Harvard Data Science Review, Vol. 6, No. 2 (Spring).

Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan T.R. Rosenman, Tyler Simko, and Kosuke Imai. (2021) ``The Use of Differential Privacy for Census Data and its Impact on Redistricting: The Case of the 2020 U.S. Census.'' Science Advances, Vol. 7, No. 7 (October), pp. 1-17.

Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan Rosenman, Tyler Simko, and Kosuke Imai. (2023). ``Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System..'' Harvard Data Science Review, Special Issue 2: Dierential Privacy for the 2020 U.S. Census (January), pp. 1-16.

Kenny, Christopher, Cory McCartan, Tyler Simko, and Kosuke Imai. (2024). ``Census officials must constructively engage with independent evaluations.'' Proceedings of the National Academy of Sciences (Letter), Vol. 121, No. 11, e2321196121.

Kenny, Christopher, Cory McCartan, Shiro Kuriwaki, Tyler Simko, and Kosuke Imai. (2024). ``Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods.'' Science Advances, Vol 10, No. 18 (May), pp. 1-13.