Disclosure Avoidance and the 2020 Census: What Do Researchers Need to Know?

The U.S. Census Bureau’s plans for release of data from the 2020 Decennial Census of Population and Housing will publicly and transparently address the unavoidable trade-off between data privacy and data accuracy. Statistical analysts can and should, therefore, take into account the planned presence of well-specified, well-justified noise in data releases based on the 2020 Decennial Census.To aid researchers’ preparations, this article highlights both what is new as well as what seems new but is actually little changed. We examine strategies, trade-offs, and rationales associated with processing and releasing the decennial results. Based on this review, we offer specific conclusions to help promote appropriate and well-informed usage of the 2020 Census. Our strongest recommendation is that, in addition to publishing official tables, the Census Bureau also make either the noisy measurements file (NMF) or unbiased estimates of released table entries available for research purposes. To create official counts, the Census Bureau applies processes to restore face validity to privacy-protected counts (that is, they eliminate disturbing features such as negative and fractional counts). These processes also introduce statistical bias and intractable distortions that researchers may wish to avoid whenever possible. By contrast, the NMF entries do not suffer from the statistical ills added by restoring face validity, and can be easily interpreted by trained analysts. Our other recommendations address critical needs for input to Census Bureau decisions from researchers, for development of suitable statistical tools that work with privacy-protected data, for expanded options with regard to microdata, and for steps to improve the accuracy of decennial census data overall.