American Community Survey (ACS) Employment

[kawine]

Predict whether an individual is employed, after filtering the ACS PUMS data sample to only include individuals between the ages of 16 and 90. See https://github.com/zykls/folktables. Copy the existing ACSEmployment setup in that repo, but add the RELSHIPP feature in addition to RELP, since that represents a coding change that was overlooked in the repo.

X: coded features (see dictionary here)

• 'AGEP': person age
• 'SCHL': schooling
• 'MAR': marital status
• RELP: relationship to head-of-household (old)
• RELSHIPP: relationship to head-of-household (new)
• 'DIS': disabled
• 'ESP': employment status of parents
• 'CIT': citizenship status
• 'MIG': mobility status
• 'MIL': military service
• 'ANC': ancestry records
• 'NATIVITY': nativity or foreign-born
• 'DEAR': hearing difficulty
• 'DEYE': vision difficulty
• 'DREM': cognitive difficulty
• SEX: sex
• RAC1P: race code

Y: ESR (employment status recode)

Domains:

• State
• Survey year (2014 – 2018)

[shreyashankar]

What horizon? Person or household? https://github.com/zykls/folktables/blob/c4fc62bd357fcf19e2d5f4643f21aa931ef9e718/folktables/acs.py#L17

Also, should we be using race code as a domain / group? Survey year seems less interesting than race code (IMO)

cc @kawine