Home » Why Disaggregate? AAPI Unemployment and Poverty

Why Disaggregate? AAPI Unemployment and Poverty

(This post is part 1 in a series)

BY SONO SHAH AND KARTHICK RAMAKRISHNAN

The White House Office of Management and Budget (OMB) has invited public comments on potential revisions to its 1997 standards. Currently, federal agencies are not required to count detailed data for Asian, Native Hawaiian and Pacific Islander Americans. In many cases, reporting by racial group can mask important differences among Asian and NHPI sub-groups. Thus, AAPI communities often remain misrepresented, under-funded, and left out of policy and program decisionmaking.

In order to address this problem, it is vital to address not only the consistent collection of disaggregated data, but also its reporting and accessibility.  Please consider joining the #CountMeIn campaign organized by a coalition of national AAPI organizations.

At AAPI Data, we seek to contribute to this conversation on federal data standards by illustrating the importance of AAPI data disaggregation. We do so in a series of blog posts this week focusing on particular outcomes, starting with unemployment and poverty.

Unemployment

Rates of unemployment are released by the Department of Labor each month and is broken down by a number of demographic characteristics including race and ethnicity. Although disaggregated data on Asian sub-groups is collected by the Current Population Survey, you won’t find these estimates in the monthly report issued by the DOL. In order get access to these data, you must rely on the sporadic release of annual data by the Department of Labor or manually compute these estimates.

The data in their report show wide differences in the rates of unemployment within the AAPI community. In 2015, AAPI unemployment was reported as 4%, lower than Whites, Blacks, and Hispanics. However, when disaggregated, we see that this rate is driven by certain groups like Chinese, Japanese, Korean, and Vietnamese Americans, while other groups report larger rates of unemployment.The DOL report also highlights the importance of Disaggregating the AAPI community with respect to long-term unemployment as well.

While AAPIs as a whole do have very low unemployment rates, the AAPI community has the second highest share of unemployed workers who are long-term unemployed (30.2 percent), trailing only the Black Non-Hispanic community (34.7 percent). The Vietnamese community has the highest share of long-term unemployed workers (41.5 percent). Of all the AAPI subgroups, only Japanese (22.8 percent) and Native Hawaiians and Other Pacific Islanders (16.5 percent) have a notably lower share of long term unemployed than both White Non-Hispanics (26.2 percent) and Hispanics (25.2 percent).

If we look at rates of unemployment over time, we can see even more instances of variation among the AAPI population. In the same report, the DOL estimated rates of unemployment for AAPIs as a racial category as well as disaggregated by subgroup. When disaggregating AAPIs, we can see significant variation across groups, with Japanese Americans regularly having the lowest levels of unemployment, and NHPIs having some of the highest levels and, in some cases, having the second-highest unemployment rate of any racial group.

Poverty

The importance of disaggregated data is also apparent when we examine rates of poverty. As a group, Asian Americans have relatively low levels of poverty, slightly higher than Whites but significantly lower than Blacks and Latinos. Disaggregating AAPIs again show large differences across groups with NHPIs and particular Asian groups reporting relatively high levels of poverty. Importantly, there are significant variations in poverty trends over time across Asian subgroups.

In both estimates of unemployment and poverty, the limits of the current standards for collection and reporting of disaggregated data are noticeable. The categories for NHPI and Other Asian do not represent distinct groups, rather they are also aggregations of many different sub-groups. Many groups that have significantly lower levels of income and educational attainment like Hmong, Samoan, Laotian, Cambodian, are aggregated and reported a single group of NHPI or “Other Asian.”

One final note: the analyses above rely on microdata from the American Community Survey and Current Population surveys, both of which are administered by the U.S. Census Bureau. We believe it is critical for the Census to continue collecting this data, expanding the number of detailed categories, and making the collection of detailed categories standard across federal datasets.  Finally, and perhaps most importantly, this data needs to be more user-friendly and publicly accessible, rather than being hidden under a maze of FactFinder tables or requiring statistical software and knowledge to work with individual-level microsample data.

We will say more about the importance of data disaggregation in health and education outcomes in future blog posts this week.

 


Department of Labor’s 2016, 2014, and 2011 reports on AAPIs.

Center for American Progress & AAPI Data collaborated on a series of reports on AAPIs, including one on Income and Poverty. You can find the consolidated report here.

For more research and data on this topic, please visit our Labor Force & Poverty pages at AAPI Data.

Please consider joining the AAPI #CountMeIn commenting campaign.