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Rehabilitation Dataset Directory: Dataset Profile

Dataset: American Housing Survey (AHS)

Basic Information
Dataset Full Name American Housing Survey
Dataset Acronym AHS

The American Housing Survey (AHS) is the nation's most comprehensive housing survey. It is a nationally representative longitudinal residential housing unit survey collected by the U.S. Census Bureau and sponsored by the Department of Housing and Urban Development (HUD). A housing unit is defined by the AHS as a house, apartment, group of rooms, or single room occupied or intended for occupancy as separate living quarters. The survey collects data on occupant owned, rental, and vacant housing units. The survey respondent is a knowledgeable household member (renter or owner) age 16 or older. In the case of a vacant housing unit, a landlord, owner, real estate agent, or knowledgeable neighbor is asked to provide the data. 

Although the AHS's primary focus is on the housing unit, it also gathers extensive information on occupant characteristics including  the ACS 6 question disability series as of 2009. This combination of data allows understanding of how occupant characteristics relate to housing characteristics. The longitudinal design permits HUD to see how housing units and people residing in those units change over time and can be used to monitor housing supply and demand, as well as changes in housing conditions and costs, in order to assess housing needs.

The survey is conducted every two years and is comprised of two parts: permanent core questions asked in every survey and topical modules that rotate in and out of the survey. The core survey collects information on a wide range of housing topics, including housing costs and value, mortgage characteristics, household income and demographics, disabilities, housing size and amenities, quality, migration, and plumbing, water, and sewage. The survey also includes a number of items relating to the resident's assessment of neighborhood "quality" such as quality/type of nearby buildings and their condition, trash, school quality, transportation availability, and crime. 

The topical modules cover a wide range of topics. The 2017 topical modules included 1) commuting to work, 2) evictions, 3) delinquent payments and notices, and 4) emergency and disaster preparedness. To maximize the number of module topics covered beginning with the 2013 AHS, HUD and the Census Bureau adopted a strategy of splitting the AHS sample in two groups, then administering some topical modules to Group 1 and some modules to Group 2.

Key Terms

Housing, Housing unit, Household, Neighborhood 

Study Design Longitudinal
Data Type(s) Survey
Sponsoring Agency/Entity

Department of Housing and Urban Development (HUD) 

Health Conditions/Disability Measures
Health Condition(s)


Disability Measures

ACS 6 question disability series: Ambulatory disability, Cognitive disability, Hearing disability, Independent living disability, Self-care disability, Visual disability 

Measures/Outcomes of Interest

Housing features, Household demographics, Occupancy & tenure, Rental units, Housing quality, Healthy homes, Accessibility features, Housing problems, Home improvements, Public housing, Housing costs, Income, Mortgage details, Renter subsidy, Delinquency/foreclosure/eviction, Housing instability, Disaster planning, Neighborhood features, School quality, Public transportation, Commuting,  Food security, Arts & cultural events, Crime

Sample Population

Housing unit/Households

The same sample of housing units is interviewed every two years until a new sample is selected. The sampling frame includes representative oversamples of each of the 15 largest metropolitan areas as well as a representative sample of HUD-assisted housing units. An additional rotating sample of twenty other Metropolitan areas are surveyed every four years, ten in each survey year.*  The U.S. Census Bureau updates the sample by adding newly constructed housing units

* Note that the 10 metropolitan areas selected for 2015 are different than the 10 selected for 2017. The 10 metropolitan areas selected for 2015 will be surveyed next in 2019, while the 10 metropolitan areas selected in 2017 will be surveyed next in 2021.

Sample Size/Notes

Approximately 115,000 housing units (2015)

Unit of Observation

Housing unit/occupants


North America


United States

Geographic Coverage


Geographic Specificity

Region and larger MSAs are identifiable in Public Use Files 

Restricted Internal Use File (IUF) contains more detailed geographic information

Data Collection
Data Collection Mode

Computer–Assisted Personal Interviewing (CAPI)

Years Collected

1973 - present 

(Disability included from 2009 - present)

Data Collection Frequency

Biennially (odd-numbered years) 

Strengths and Limitations

Housing units participating in the AHS are selected to to be nationally representative of all housing units in the United States and includes an over-sample of  HUD-assisted units. Weights are included to allow national level estimates.

High 80% response rate.

Survey includes topical modules covering unique topics such as commuting, disaster planning, housing counseling, arts and culture, healthy homes, and food security.


In 2015 the AHS underwent a major redesign – a new sample was redrawn for the first time since 1985 and new households were asked to participate in the survey, variables were dropped, added, or modified, recodes and imputation methods were streamlined, and the weighting methodology changed. As a result of these changes some estimates became incomparable with previous years.

Metro definitions have changed over the period that the AHS has been fielded.

Only Census regions and select MSAs can be identified in the Public Use Files (PUF) due to limited geographic information provided.  Restricted Use Files (IUF) do contain this information but access requires an application process and data access is only through a Census Bureau Research Data Center (RDC).

HUD and the Census Bureau often make small changes to the text of various questions between surveys. AHS users comparing estimates with prior-year surveys should consult the document “Changes Between Surveys” that is published with each new AHS.

Topical modules utilize a "split sample" approach requiring unique statistical weights depending on the topic.

Data Details
Primary Website

Data Access

Data Access Requirements

Public-Use dataset (some variable availability limitations)

Restricted Internal Use File (IUF)

Provides access to more variables and detailed content, but requires application for access at a Census Bureau Research Data Center (RDC)

Summary Tables/Reports
AHS Table Creator:

Data Components

Integrated national sample file:

Contains data for the entire nation and each of the top 15 largest metropolitan areas, as well as an over-sample of HUD-assisted housing units.

Independent metropolitan area sample file:

Contains data from 10 metropolitan areas selected for each survey year.*

* Note that the 10 metropolitan areas selected for 2015 are different than the 10 selected for 2017. The 10 metropolitan areas selected for 2015 will be surveyed next in 2019, while the 10 metropolitan areas selected in 2017 will be surveyed next in 2021. 

Selected Papers
Other Papers

AHS Bibliography & Working papers:


Technical Documentation:

Getting Started With the Public Use File (PUF): 2015 and Beyond 

AHS Codebook Interactive Tool (includes all variables in AHS collected from 1997-2017) : 

Sample Design, Weighting, and Error Estimation:,%20Weighting,%20and%20Error%20Estimation.pdf?# 

Technical Survey Research:

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

Other CLDR supported resources and collaborative opportunities:

Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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