Central to our mission at Carolina Demography is helping people get the data they need to make informed decisions. With this in mind, we strongly advocate for a robust and transparent federal data infrastructure. That said, it’s not lost on us that sometimes issues related to how data is collected or methodological policies that may impact data accessibility are not at the top of everyone’s news feed. However, state agencies, local governments, nonprofits, and private businesses use federal data every day and recent policy changes at the US Department of Commerce may limit the data available to NC communities. Our friend and colleague, John Quinterno, the State Data Center Coordinator and Census Liaison, summarized what these changes mean in this piece which was originally published on September 1, 2026 here.
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In June 2026, the US Department of Commerce issued Department Administrative Order (DAO) 216-26, which limits the privacy protections the US Census Bureau may use in the decennial census and programs like the American Community Survey (ACS). This change has disrupted Census 2030 planning and data release schedules; for instance, the Census Bureau recently announced an indefinite delay in the release of ACS one-year data for 2025. Once implemented, the new policy may reduce the timeliness, usefulness, and granularity of community-level data.
This guide explains what is known about the new policy and its effects.
The two agencies affected by this directive—the Census Bureau and US Bureau of Economic Analysis—must publish useful data while protecting the personal information shared by respondents. Since the 1970s, the Census Bureau has developed sophisticated methods of disclosure avoidance—called “noise infusion”—to enable the publication of more data for smaller places and populations. DAO 216-26, however, states that “any use of noise infusion is inconsistent with the Department’s policies.” Instead, the Census Bureau must “coarsen” data before publication or “suppress” data if that is the only way to maintain privacy.
DAO 216-26 offered no details on implementation, with most decisions—such as identifying which statistical products are covered—left to be determined. The order bans noise infusion in any covered statistical product (i.e., official Census Bureau releases that use data subject to Title 13 confidentiality restrictions). The order states that “coarsening shall be the preferred category of Disclosure Avoidance methods for all statistical products” and that “suppression shall be permitted as a last resort, only to be used when coarsening is prohibited by law or would substantially defeat the accuracy or usability of a statistical product.”
The published order offered no reason for the policy change. In public remarks, Census Bureau officials have stated that noise infusion erodes trust in published statistics because advanced techniques are difficult to explain. Officials say there is a trade-off between the goals of statistical accuracy, respondent confidentiality, and data granularity. The decision of how to balance is a policy choice. The Department of Commerce determined accuracy is the most important of the goals, even if it limits the data published for smaller places and populations.
Methodological changes to federal statistical programs require expert and public review to ensure integrity. Although banning noise infusion seems like a methodological change, the Department of Commerce’s position is that it is a policy choice that can be made internally.
Consider a town with a census block that has one Asian American household. Releasing unedited results would provide granular data at the cost of the household’s privacy. In contrast, withholding the results would protect the household’s privacy but deprive the town of data.
Noise infusion resolves this trade-off by, as a former Census Bureau official explained, “slightly altering granular data in such a way that the privacy and identity of individual people and businesses are protected in the statistics derived from them.” For instance, the Asian American household in the census block could be swapped with a household in an adjoining block that is identical to it in every way except for race. This swapping would protect personal data and permit the release of data for more census blocks without altering the town’s overall results.
Differential privacy is a form of noise infusion used in Census 2020. Differential privacy, the Census Bureau explains, adds “statistical noise—small, random additions or subtractions—to every published statistic so no one can reidentify a specific person or household with any certainty using any combination of the published data.” The systematic injection of randomness into a dataset allows statisticians to better assess trade-offs between data accuracy and privacy.
The adoption of differential privacy attracted concern, especially from technical experts and data users focused on small places and populations. Methodological debates aside, neither differential privacy, nor noise infusion generally, are forms of “error” or data fabrication. They are tools for balancing the competing goals of data accuracy, privacy, and granularity.
Now the preferred disclosure avoidance method, data coarsening refers to “techniques that reduce precision,” such as rounding values, aggregating data, and reporting ranges. Each technique has trade-offs. Rounding is simple, yet it offers little protection for small counts and prevents totals from summing. Geographic aggregation is also straightforward, but it sacrifices granularity and disproportionately affects rural and tribal communities.
Data suppression, which is now the disclosure method of last resort, redacts individual values or whole categories of data by, for example, blanking out a cell in a table and noting the omission. To prevent a user from recalculating the suppressed value, multiple values in other tables must often be suppressed as well, which can create cascading data gaps.
To see how different techniques can alter the data available for a hypothetical community, visit the Disclosure Avoidance Calculator built by the nonprofit Population Reference Bureau.
The Census Bureau Disclosure Review Board (DRB) will be responsible for implementing DAO 216-26. The board is an internal 12-person committee that clears official data releases in advance to prevent the release of confidential information.
In July, the DRB released initial parameters (see pp. 10-11 in the document). For instance, the DRB defined “data swapping” as an impermissible form of noise infusion while also clarifying where the ban on noise infusion would not apply (e.g., products produced under contract for other agencies). The board also identified when certain types of synthetic data (e.g., imputation) could be used and the dates before and after which DAO 216-26 applies to data releases.
In a recent blog post, the Census Bureau’s acting director wrote that DAO 216-26 applies to “all statistical products disseminated by the Census Bureau” and “covers any information produced by our staff or contractors using data protected under the confidentiality provisions of Title 13.” There currently is no comprehensive list of all affected Census Bureau products, but those likely to be affected include, but are not limited to, the following:
The most immediate impact on North Carolina communities will come in September, which is when the Census Bureau typically releases the one-year American Community Survey (ACS) estimates for places with more than 65,000 residents. In August, the Census Bureau announced an indefinite delay in the release of the 2025 data to determine DAO 216-26 compliance.
It is probable the Census Bureau will also delay the release of the five-year ACS estimates, which normally happens in December. The five-year estimates provide detailed social, economic, housing, and demographic data for all places, regardless of population size. Even if the estimates are released on time, they likely will likely mix data subject to both the new and old privacy standards, which may compromise the accuracy and usability of the information.
Using coarsening and suppression as the primary forms of privacy protection likely will result in the publication of much less social, economic, housing, and demographic data for North Carolina communities, with smaller places and populations affected disproportionately. As the State Demographer has noted, 21% of the state’s counties have fewer than 20,000 residents, while 59% of all incorporated municipalities have no more than 2,500 residents.
In the absence of detailed ACS data, less populous communities will have limited insight into their economic and social dynamics, as well as into the needs of relatively small population groups (e.g., tribal communities) and sub-geographies (e.g., rural fire districts). A lack of detailed data will also limit the accuracy of demographic forecasts and prevent officials from calculating statistical rates (e.g., cancer rates) and mapping trends (e.g., vacancy patterns).
Lastly, DAO 216-26 has upended planning for Census 2030, which had assumed the use of noise infusion for products like the redistricting files. The Census Bureau has announced plans to release a demonstration data product in 2027, but compliance will require a significant redesign on a compressed timeline. This increases the odds that communities will be improperly enumerated and, ultimately, lose the political and financial resources determined by census data.
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