Urban Wire The State of Data Disaggregation for Asian American, Native Hawaiian, and Pacific Islander Groups
Mikaela Tajo, Rita Ko
Display Date

photo of family

In response to recent pushes for more disaggregated data on the Asian American, Native Hawaiian, and Pacific Islander (AA NHPI) community and research highlighting the importance of such data, the federal government has made efforts to prioritize disaggregation by creating the White House Initiative on Asian Americans, Native Hawaiians, and Pacific Islanders, launching the Interagency Committee on Statistical Policy’s AA NHPI data catalog, and, most recently, releasing revisions to federal data collection standards. Although these steps are promising, data gaps persist.

Building off these federal datasets and with the support of The Asian American Foundation (TAAF), we conducted a scan and consulted with seven Urban Institute experts to build a snapshot of federal data sources and other data assets, such as surveys and reports, that disaggregated by AA NHPI subgroups. We hope this work can help inform how policymakers, organizations, and communities use disaggregated AA NHPI data to improve access to social services and document inequities.

The level of disaggregation remains inconsistent

Although collecting disaggregated data is increasingly prioritized at the federal level, publicly available datasets often aggregate to broader categories like “Asian” or “Native Hawaiian or Pacific Islander,” requiring additional work by researchers to access more granular data. Even among surveys that do collect more subgroups, the degree of data disaggregation for the AA NHPI population varies. The census remains one of the most comprehensive sources of disaggregated data, with the American Community Survey including more than 50 subgroups pertaining to AA NHPI people.

However, most other national surveys (15 out of the 24 included in the scan) disaggregated by just six categories: Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese. Many of these other surveys also group together the Native Hawaiian and Pacific Islander categories. These surveys come from a range of different agencies, including the Centers for Disease Control and Prevention’s National Health Interview Survey and several of the US Department of Education’s surveys, such as the Baccalaureate and Beyond Longitudinal Study.

State-level surveys can also offer disaggregated data for AA NHPI subgroups but may have limited geographic coverage and infrequent updates. California’s Health Interview Survey provides disaggregated data by 23 AA NHPI subcategories. Similarly, the Native Hawaiian Data Book collects data for several NHPI subgroups, such as Guamanian/Chamorro, Micronesian Native Hawaiian, Samoan, and Tongan.

Even when researchers can access disaggregated AA NHPI data, barriers to analysis still exist. Sample sizes for AA NHPI groups in some datasets, such as the US Bureau of Labor Statistics’ American Time Use Survey, can be small, requiring pooling multiple years for analysis and to protect the privacy of subgroups. Additionally, participants only began reporting detailed race and ethnicity responses in the 2020 Census—making longitudinal analysis of smaller subcategories difficult.

How to better use disaggregated AA NHPI data

Access to disaggregated data is crucial for understanding the diverse AA NHPI experiences, but it must be balanced with protecting the privacy of smaller subgroups. Drawing on insights from Urban experts in housing finance, philanthropy, and labor policy, we offer suggestions for those seeking to use and bolster disaggregated AA NHPI data:

  • Incorporate tools like imputation. Imputation can help address missing data or add new variables, such as race and ethnicity, in datasets lacking this information. However, researchers should be intentional about their process to avoid causing harm. Researchers at Urban have previously developed a list of checkpoints for ethical considerations of imputation, such as points where bias can occur. Additionally, the accuracy of imputation can vary, especially for some smaller subgroups.
  • Pursue community-engaged methods and qualitative data. Working with community members in quantitative studies can help researchers create and disseminate more accessible research tools. Partnering with communities for participatory input is crucial, given historical exclusion from government data collection efforts, and this approach can build trust, add transparency, and contextualize findings to better understand the experiences and outcomes of AA NHPI people.
  • Strategically leverage and improve existing data collection efforts. State and local actors are on the front lines of collecting real-time data. Tools like the National Asset Scorecard for Communities of Color (PDF), which has already been implemented in various cities throughout the country, also provide more disaggregated AA NHPI data than federal surveys. Federal policymakers can benefit from leveraging local initiatives and data, including information on AA NHPI subgroups not included in federal surveys. The Twin Cities, which has a relatively large population of Hmong Americans, may have unique insights into that subgroup, for example. Instead of relying solely on disaggregated federal data, all levels of government can collaborate to identify data gaps, share knowledge, and develop inclusive policies that reflect underrepresented subgroups.
  • Use private data with public datasets. Private companies can provide data that may not be publicly available. One researcher we spoke with merged credit score data purchased from Black Knight with race data included in the Home Mortgage Disclosure Act data. There are also private companies, such as Amplify AAPI, that can provide survey services targeted toward AA NHPI populations.

As the availability of disaggregated data increases, the privacy of AA NHPI subgroups, particularly the subgroups with smaller sample sizes, is important to consider when making decisions about what data to make publicly available. Researchers, advocacy groups, and community organizations should make sure to refer to the growing body of work on data privacy and governance, including Urban’s privacy and utility education tool.


Tune in and subscribe today.

The Urban Institute podcast, Evidence in Action, inspires changemakers to lead with evidence and act with equity. Cohosted by Urban President Sarah Rosen Wartell and Executive Vice President Kimberlyn Leary, every episode features in-depth discussions with experts and leaders on topics ranging from how to advance equity, to designing innovative solutions that achieve community impact, to what it means to practice evidence-based leadership.


Research Areas Race and equity
Tags Asian American and Pacific Islander communities Community data use Family and household data Nonprofit data and statistics Race, gender, class, and ethnicity
Policy Centers Office of Race and Equity Research
Related content