Household Surveys ACS – CPS - AHS INFO 7470 / ECON 8500 Warren A. Brown University of Georgia February 22,

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Outline Purpose Target Population Sampling Frame Data Collection Non-Response Missing Data Weighting Sampling Error PUF / IUF Data Access to Reports Research Questions Resources

American Community Survey Sponsor: Census Bureau Collector: Census Bureau Purpose: “The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year.” 12

13 ACS: Purpose Key Component for Re-Engineered Census Replacing the Decennial Census “Long-Form” Continuous measurement rather than snapshot Meet federal legislative and program needs Other stakeholders in state and local government and private sectors Provide annual data on demographic, social, economic and housing characteristics. Improve the Federal Statistical System

14 Advantages of the ACS Timeliness Comparability Reliability Numerous data products

15 ACS: Target Population Current residence not “Usual Residence” –“two-month rule” Household population in 2005 Total (HH + GQ) in 2006 and …. GQ residency is “de facto”

16 ACS: Sampling Frame Master Address File (MAF) –Official inventory of known living quarters –Linked to TIGER Housing Units –Based on Census 2000 MAF and updates from the USPS’ Delivery Sequence File Group Quarters –… and updates from the administrative records and the FSCPE –Excluded from ACS are domestic violence shelters, soup kitchens, commercial maritime vessels,…

17 ACS: Design of the Sample Annual Sample Size of 3 million addresses Series of Monthly Samples of 250,000 addresses HU sample in each of the 3,141 Counties Areas with smaller populations sampled at higher rates than those with larger populations HU Address sampling rate set by Block based on entity (municipality, school district, tract) Final sampling rate varies between 1.6% and 10% No HU address can be sampled more than once in 5 years

18 ACS: Questionnaire Content designed to meet the needs of federal government agencies 21 housing and 48 population questions Household Respondent provides responses for all other residents of the household Householder or Reference Person is “Person 1”

19 ACS: Data Collection HU addresses by three modes –Mailout of paper questionnaire in 1 st month –Telephone (CATI) non-response follow-up in 2 nd month –Personal visit (CAPI) non-response follow- up in 3 rd month to a sub-sample GQ –Personal visit within 6 weeks of sample selection

20 Data Collection Timetable

Non-Response Follow Up 1 st Month – Mailed Questionnaire 2 nd Month – Attempt at Telephone Interview 3 rd Month – Sub-Sample of Non- Respondents –67% unmailable addresses –50% low response tracts –33% high response tracts

ACS: Response Rates Participation is mandatory Sample addresses eligible for interviewing: –51% Mail response – 9% CATI non-response follow-up –38% CAPI non-response follow-up – 2% Non-interview

23 ACS: Missing Data Item non-response or failed edit check FEFU – failed-edit follow-up –More than 5 household members –Critical questions not answered –33% of mail return questionnaires in 2005 Imputation –Assignment used other data on respondent –Allocation – hot deck procedure –Flags variables

24 ACS: Weighting Person and Housing Unit weights Three stages –Probability of selection (initial sampling rate) –Adjust for non-response –Control to Population Estimates Sum the weights –Person weights for person characteristics –HU weights for family, household or housing unit characteristics Householders = Households ???

ACS: Weighty Issues ACS 2005 for United States 288,378,137 Persons in Households 111,090,617 Households 114,763,475 Householders Average Household Size –2.60 based on Households –2.51 based on Householders

26 ACS: Sampling Error Publishing margins of error in tables More sample less error 1, 3, and 5 year estimates and associated sampling error Sampling error for small area data is proving to be a problem

Complex Sample Surveys and Weights Weight - numeric variable expressing the number of housing units or people that an individual microdata record represents Sum of the housing unit and person weights for a geographic area is equal to the estimate of the total number of housing units and people in that area Values for weights vary –Different Probability of Selection –Differential Response Rate –Control to Population Estimates 27

28 Alternatives for Estimating Standard Error Design Factor Replicate Weights Ignore

29 Alternatives for Estimating Standard Error Design Factor –Design factors are factors to multiply times the standard error of a simple random sample. –Easier to use than the replicate weights Replicate Weights –Generally, more accurate –Somewhat more work than design factors

Estimate of Sampling Error Using Design Factors 30

Design Factors CharacteristicDesign Factor Age1.1 Employment Status1.2 Person Income * West Virginia is 1.0 for Age and 1.5 for Person Income

32 Estimate of Standard Error Using Replicate Weights where: –X is the estimate formed from the PUMS weight –X r is the estimate formed from the r th replicate weight.

PUF / IUF 1% Sample PUMA Top Coding Collapsed Categories Perturbation No Administrative 2.5% Sample Block/Tract/Place Full Distribution Actual Ages Details of Collection 33

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ACS: Research Questions

Resources Census Bureau IPUMS Michigan Population Studies Center National Academy Sciences-CNSTAT 36

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NAS-CNSTAT ACS Reports *********** 2001, CNSTAT’s 2007, Census 2008, core sponsors BureauNSF/SRS