000			01950nam a22001577a 4500
999			_c527088 _d527088
008			240802b ||||| |||| 00| 0 eng d
100			_aRuggles, Steven _956301
245			_aWhen privacy protection goes wrong: How and why the 2020 census confidentiality program failed
260			_aThe Journal of Economic Perspectives
300			_a38(2), Spring, 2024: p.201-226
520			_aThe US Census Bureau implemented a new disclosure control strategy for the 2020 Census that adds deliberate error to every population statistic for every geographic unit smaller than a state, including metropolitan areas, cities, and counties. This article traces the evolving rationale for the new procedures and assesses the impact of the 2020 disclosure control on data quality. The Census Bureau argues that the traditional disclosure controls used for the 2010 and earlier censuses revealed the confidential responses of millions of Americans. I argue that this claim is unsupported, and that there is no evidence that anyone's responses were compromised. The new disclosure control strategies introduce unnecessary error with no clear benefit; in fact, the new procedures may actually be less effective for protecting confidentiality than the procedures they replaced. I conclude with recommendations for minimizing disclosure risk while maximizing data utility in future censuses.-Reproduced https://www.aeaweb.org/articles?id=10.1257/jep.38.2.201
650			_aCensus Bureau, Disclosure control, Population statistics, Data quality, Confidentiality risk, Geographic units, Metropolitan areas, Cities and counties, Deliberate error, Traditional procedures, 2020 Census, 2010 Census, Privacy protection, Data utility, Statistical integrity, Policy evaluation, Confidential responses, Procedural critique, Future recommendations, United States Census _956194
773			_aThe Journal of Economic Perspectives
906			_aPOPULATION
942			_cAR