Response to comment on "Policy impacts of statistical uncertainty and privacy"

• Published in: Science (American Association for the Advancement of Science) Vol. 380; no. 6648; p. eadh2297
• Main Authors: Steed, Ryan, Acquisti, Alessandro, Wu, Zhiwei Steven, Liu, Terrance
• Format: Journal Article
• Language: English
• Published: United States The American Association for the Advancement of Science 02.06.2023
• ISSN: 0036-8075; 1095-9203
• DOI: 10.1126/science.adh2297

We offer our thanks to the authors for their thoughtful comments. Cui, Gong, Hannig, and Hoffman propose a valuable improvement to our method of estimating lost entitlements due to data error. Because we don't have access to the unknown, "true" number of children in poverty, our paper simulates data error by drawing counterfactual estimates from a normal distribution around the official, published poverty estimates, which we use to calculate lost entitlements relative to the official allocation of funds. But, if we make the more realistic assumption that the published estimates are themselves normally distributed around the "true" number of children in poverty, Cui .'s proposed framework allows us to reliably estimate lost entitlements relative to the unknown, ideal allocation of funds-what districts would have received if we knew the "true" number of children in poverty.