In a piece just published in the Journal of Economic Perspectives, Steven Ruggles argues that U.S. Census Bureau’s new procedure of deliberately adding noise to Census data as a confidentiality measure is counterproductive. The article first argues that the rationale for the change—that the 2010 Census jeopardized the confidentiality of millions of responses—is unsupported. It then argues that the new procedure provides no clear confidentiality benefit and may even increase disclosure risk. These new procedures, which essentially introduce error into data for all sub-state geographic units, have significant implications for the utility of census data to researchers and policymakers.

From the JEP article:

The Census Bureau maintains that strong confidentiality guarantees are essential for maximizing response rates to censuses and surveys, but little evidence supports this view. Indeed, experimental studies have consistently found that assurances of confidentiality actually increase concerns about confidentiality and reduce response rates to surveys (Berman, McCombs, and Boruch 1977; Frey 1986; Reamer 1979; Singer, Hippier, and Schwarz 1992). A Census Bureau analysis in the 1990s found that promises of confidentiality had no significant impact on response rates (Dillman et al. 1996).

The US Census Bureau recently implemented a new disclosure control strategy that marks a “sea change for the way that official statistics are produced and published” (Garfinkel, Abowd, and Powazek 2018, p. 136). The new disclosure control system adds deliberate error to every population statistic for every geographic unit smaller than a state, including metropolitan areas, cities, and counties.

Population data describing small geographic areas are essential for core political functions like drawing boundaries for state legislative districts and for the US House of Representatives. Towns, cities, counties, states, and the federal government use small area statistics for planning and policy purposes, ranging from decisions about delivery of public services to infrastructure needs. Moreover, economists and other social scientists rely on these demographic data to understand social changes and to evaluate policy outcomes. There is no historical precedent and no demonstrated need for introducing deliberate error into every population statistic for geographic units below the state level. These steps do nothing to allay public concern about the invasion of privacy by the government or about government misuse of data.