Race Categories in ACS 5 Years file


I extracted and download the aging population in New York City thru 2015-2019, ACS 5-year. I was surprised when I checked the SPSS syntax file to read the raw data. The Race category (variable name: RACE) is different from the most frequently used one. The following is the value label syntax for RACE. As presented below, there are Chinese and Japanese as race groups.

Is there any reason for this kind of grouping?

|RACE||Race [general version]|

|2||Black/African American/Negro|
|3||American Indian or Alaska Native|
|6||Other Asian or Pacific Islander|
|7||Other race, nec|
|8||Two major races|
|9||Three or more major races|

You are correct that the current RACE variable doesn’t map neatly onto the 7 standard major categories that the Census Bureau uses in summary tables (White, Black, AIAN, Asian, Native Hawaiian & Pacific Islander, Some other race, Two or more races). The actual underlying microdata offer much more detail than these broad groups (e.g., many national origin groups are included); the RACE variable (as well as the detailed version–see below for how to toggle between the two on our website) seeks to provide as much of that detail as possible. Chinese and Japanese are included as far back as 1880 in the PUMS data, as such, we include them in the code listed for RACE.

That being said, the IPUMS USA team has plans to create an additional variable that maps the detailed race values onto the standard 7-category scheme. Until this is available, you can do this yourself using the detailed version of the RACE variable (called RACED in your data extract).

General codes (RACE) are used for the most broadly comparable categories across time:

Detailed codes (RACED) use additional digits to convey detail not available in all years, but have the same first digit as one another and as the single digit code used in the general version of the variable (note that there is no broad “other Asian or Pacific Islander” header on the 600 group here: