View Information Collection Request (ICR) Package

Abstract: The purpose of the American Housing Survey (AHS) is to supply the public with detailed and timely information about housing quality, housing costs, and neighborhood assets, in support of effective housing policy, programs, and markets. Like the previous surveys, the 2019 AHS will collect ‘‘core’’ data on subjects, such as the amount and types of changes in the housing inventory, the physical condition of the housing inventory, the characteristics of the occupants, housing costs for owners and renters, the persons eligible for and beneficiaries of assisted housing, remodeling and repair frequency, reasons for moving, the number and characteristics of vacancies, and characteristics of resident’s neighborhood. In addition to the ‘‘core’’ data, HUD plans to collect supplemental data on post-secondary education, modifications made to assist occupants living with disabilities, and information on people’s concerns regarding the availability and affordability of food. The AHS national longitudinal sample consists of approximately 85,200 housing units, and includes oversample from the largest 15 metropolitan areas, and approximately 5,200 HUD-assisted housing units. In addition to the national longitudinal sample, HUD plans to conduct 10 additional metropolitan area longitudinal samples, each with approximately 3,000 housing units (for a total 30,000 metropolitan area housing units). The 10 additional metropolitan area longitudinal samples were last surveyed in 2015. To help reduce respondent burden on households in the longitudinal sample, the 2019 AHS will make use of dependent interviewing techniques, which will decrease the number of questions asked. Policy analysts, program managers, budget analysts, and Congressional staff use AHS data to advise executive and legislative branches about housing conditions and the suitability of public policy initiatives. Academic researchers and private organizations also use AHS data in efforts of specific interest and concern to their respective communities. HUD needs the AHS data for two important uses. 1. With the data, policy analysts can monitor the interaction among housing needs, demand and supply, as well as changes in housing conditions and costs, to aid in the development of housing policies and the design of housing programs appropriate for different target groups, such as first-time home buyers and the elderly. 2. With the data, HUD can evaluate, monitor, and design HUD programs to improve efficiency and effectiveness. In addition to the core 2019 AHS, HUD plans to collect supplemental data on housing insecurity in a follow-on survey to the AHS. Housing insecurity is defined as a significant lapse for a given household of one or more elements of secure housing. These elements include affordability, stable occupancy, and whether the housing is decent and safe. ‘‘Affordability’’ implies that shelter costs are manageable over the long term without severely burdening or compromising other consumption that normally is essential for health and well-being. The second element, ‘‘stable occupancy’’, implies that the household does not face substantial risk of involuntary displacement for economic or noneconomic reasons. The final element, ‘‘decent and safe’’, implies that a unit has physical attributes that satisfy functional needs for well-being related to health, security, and support for activities of daily living. Such attributes include appropriate facilities for excluding external threats, providing climate control, storing and preparing food, maintaining physical and mental hygiene, and developing human potential. Not included are aspects of the neighborhood or environment that one encounters beyond the confines of the structure or property. HUD plans to conduct the Housing Insecurity Follow-On survey concurrently with the 2019 AHS. Respondents who meet certain criteria based on their responses to the 2019.

ICR Summary of Burden

	Total Approved	Previously Approved	Change Due to Agency Discretion	Change Due to Adjustment in Estimate
Annual Number of Responses	129,937	129,297	-128,657	129,297
Annual Time Burden (Hours)	58,892	62,524	-66,156	62,524
Annual Cost Burden (Dollars)	0	0	0	0

Burden increases because of Program Change due to Agency Discretion: Yes

Burden Increase Due to: Miscellaneous Actions

Burden decreases because of Program Change due to Agency Discretion: Yes

Burden Reduction Due to: Miscellaneous Actions

Short Statement: The 2019 data collection procedures and questionnaire content are similar to the 2017 survey with the following exceptions: a. Removal of Four Supplemental Modules from the 2017 AHS: The Disaster Planning, Delinquent Payments and Notices, Commuting, and Eviction supplemental modules will not be included in the 2019 survey. b. Reinstatement of the Food Security Module: The Food Security module was first included in the 2015 AHS. For the 2019 AHS, there are no changes to this supplemental module. It will continue to collect data on the intersection between food security and housing costs. Food-insecure households lack consistent access to adequate food for one or more household members. To this point, data have not been available to enable research on housing burden and food security jointly. Food security data in the AHS would support research to understand this relationship at the household level, and to examine the role housing and energy assistance may have in moderating it. Most policy research has focused on the effects of food and nutrition assistance programs on food insecurity. The 2019 AHS will allow analysis of how HUD assistance programs, especially rental assistance, affect food security assistance. c. Introduction of Two New Supplemental Modules: To continue the strategy of supplemental modules in order to minimize respondent burden and satisfy widening needs for data content, two new supplemental modules have been added to the survey – Home Accessibility and Post-Secondary Education modules. These modules collect data on modifications made to assist occupants living with disabilities and details about the experiences of household members attending a post-secondary institution. The Home Accessibility module is derived from the 2011 AHS module on modifications made to the house to accommodate persons with disabilities. Please refer to the attached items booklet for the questions in these modules and the entire AHS questionnaire. d. Introduction of a Housing Insecurity Research Module Follow-On: The goal of developing the Housing Insecurity Research Module is to collect data that can be used to explore the feasibility of constructing a standardized series of questions to measure the continuum of housing insecurity in the model of the transferable U.S. Household Food Security Survey Module developed by the U.S. Department of Agriculture (USDA). A transferable survey module, if feasible, will help researchers build a more robust and coherent body of knowledge around housing needs, trade-offs, and correlates, enhancing the quality and consistency of policy-relevant research, and amplifying the visibility of the continuum of housing needs. A transferable module that produces a household-level housing insecurity score will be a tool for studying both the extent to which housing insecurity explains other observed outcomes and which interventions are likely to improve housing security. The Housing Insecurity Research Module follow-on will be administered after the regular AHS interview. The Module will be administered to 4,000 AHS respondents selected based on income and other criteria. e. Sample Split for Supplemental Modules: A split of the survey sample will be used to maximize the number of supplemental modules that can be included in the 2019 AHS. Fifty percent of the sample will be asked the Post-Secondary Education and Food Security modules. The other 50 percent will be asked the Home Accessibility module. As noted above, 4,000 respondents will receive the Housing Insecurity Research Module. f. AHS Incentive Pilot: The proposed incentive project will test whether offering incentives in geographic areas with a high risk of non-response can successfully increase responses from communities that would otherwise be underrepresented, resulting in lower non-response bias.

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