Post on 02-Feb-2016
description
Household SurveysACS – CPS - AHS
INFO 7470 / ECON 8500
Warren A. Brown
University of Georgia
February 22, 2011
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CES Discussion Papers
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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.”
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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
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Advantages of the ACS
• Timeliness
• Comparability
• Reliability
• Numerous data products
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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”
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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,…
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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
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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”
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ACS: Data Collection
• HU addresses by three modes – Mailout of paper questionnaire in 1st month– Telephone (CATI) non-response follow-up in 2nd
month – Personal visit (CAPI) non-response follow-up in
3rd month to a sub-sample
• GQ– Personal visit within 6 weeks of sample
selection
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Data Collection Timetable
Non-Response Follow Up
• 1st Month – Mailed Questionnaire• 2nd Month – Attempt at Telephone Interview• 3rd 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
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ACS: Missing DataItem 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
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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
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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
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Alternatives for Estimating Standard Error
• Design Factor
• Replicate Weights
• Ignore
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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
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Design Factors
Characteristic Design Factor
Age 1.1
Employment Status 1.2
Person Income 1.6
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* West Virginia is 1.0 for Age and 1.5 for Person Income
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Estimate of Standard Error Using Replicate Weights
where:– X is the estimate formed from the PUMS
weight
– Xr is the estimate formed from the rth replicate weight.
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2r XX
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4SE
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PUF / IUF
• 1% Sample• PUMA• Top Coding• Collapsed Categories• Perturbation• No Administrative
• 2.5% Sample• Block/Tract/Place• Full Distribution• Full Distribution• Actual Ages• Details of Collection
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Resources
• Census Bureau
• IPUMS
• Michigan Population Studies Center
• National Academy Sciences-CNSTAT
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http://www.psc.isr.umich.edu/dis/acs/dataanalysis/UsingReplicateWeights.html
NAS-CNSTAT ACS Reports
***********2001, CNSTAT’s 2007, Census 2008,
core sponsors Bureau NSF/SRS