Income limits used to determine the income eligibility of applicants for assistance under three programs authorized by the National Housing Act. These programs are the Section 221(d)(3) Below Market Interest Rate (BMIR) rental program, the Section 235 program, and the Section 236 program. These income limits are listed by dollar amount and family size, and they are effective on the date issued. Due to the Housing and Economic Recovery Act of 2008 (Public Law 110-289), Income Limits used to determine qualification levels as well as set maximum rental rates for projects funded with tax credits authorized under section 42 of the Internal Revenue Code (the Code) and projects financed with tax exempt housing bonds issued to provide qualified residential rental development under section 142 of the Code (hereafter referred to as Multifamily Tax Subsidy Projects (MTSPs)) are now calculated and presented separately from the Section 8 income limits.

HUD’s Office of Policy Development and Research (PD&R) is pleased to announce that Fair Market Rents and Income Limits data are now available via an application programming interface (API). With this API, developers can easily access and customize Fair Market Rents and Income Limits data for use in existing applications or to create new applications. To create an account and get an access token, please visit the API page here: https://www.huduser.gov/portal/dataset/fmr-api.html. The Department of Housing and Urban Development (HUD) sets income limits that determine eligibility for assisted housing programs including the Public Housing, Section 8 project-based, Section 8 Housing Choice Voucher, Section 202 housing for the elderly, and Section 811 housing for persons with disabilities programs. HUD develops income limits based on Median Family Income estimates and Fair Market Rent area definitions for each metropolitan area, parts of some metropolitan areas, and each non-metropolitan county.

HOME Income Limits are calculated using the same methodology that HUD uses for calculating the income limits for the Section 8 program. These limits are based on HUD estimates of median family income, with adjustments based on family size. The Department's methodology for calculating nationwide median family income figures is described in Notice PDR-2001-01. For more information about how HUD calculates the HOME Program income limits, visit huduser.gov, the website for HUD's Office of Policy Development and Research, for more general information.

The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building.This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by County Date of Coverage: 2016-2020

Text source: https://www.huduser.gov/portal/datasets/HOME-Income-limits.htmlLanding page description:HOME Income Limits data are available from FY 1998 to the present. The HOME Income Limits are calculated using the same methodology that HUD uses for calculating the income limits for the Section 8 program, in accordance with Section 3(b)(2) of the U.S. Housing Act of 1937, as amended. These limits are based on HUD estimates of median family income, with adjustments based on family size. Please note that the 30 percent income limits for the HOME program have been calculated based on the definition of Extremely Low–Income Family (ELI) as described in Consolidated Submission for CPD Programs section of 24 CFR part 91.5. Therefore, the ELI Limit is calculated as 30 percent of median family income for the area and may not be the same as the Section 8 ELI Limit for your jurisdiction. The Section 8 Limit is calculated based on the definition of ELI as described in The 2014 Consolidated Appropriations Act, (Section 238 on page 128 Stat 635) which defines ELI as very low–income families whose incomes do not exceed the higher of the Federal poverty level or 30% of area median income. Family sizes in excess of 8 persons are calculated by adding 8% of the four-person income limit for each additional family member. That is, a 9-person limit should be 140% of the 4-person limit, the 10-person limit should be 148%.The HOME income limit values for large households (9-12 persons) must be rounded to the nearest $50. Therefore, all values from 1 to 24 are rounded down to 0, and all values from 25 to 49 are rounded up to 50.Note: The FY 2024 HOME Income Limits effective date is June 01, 2024.

This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

The Department of Housing and Urban Development (HUD) is required by law to set income limits that determine the eligibility of applicants for HUD's assisted housing programs. The major active assisted housing programs are the Public Housing program, the Section 8 Housing Choice Voucher program, Section 202 housing for the elderly program, and Section 811 housing for persons with disabilities program. FY2013.

The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income. For CDBG, a person is considered to be of low income only if he or she is a member of a household whose income would qualify as "very low income" under the Section 8 Housing Assistance Payments program. Generally, these Section 8 limits are based on 50% of area median. Similarly, CDBG moderate income relies on Section 8 "lower income" limits, which are generally tied to 80% of area median. These data are from the 2016-2020 American Community Survey (ACS).To learn more about the Low to Moderate Income Populations visit: https://www.hudexchange.info/programs/acs-low-mod-summary-data/ Data Dictionary: DD_Low to Moderate Income Populations by Block Group Date of Coverage: ACS 2016-2020 Data Updated: Every Five Years

California State Income Limits reflect updated median income and household income levels for acutely low-, extremely low-, very low-, low- and moderate-income households for California’s 58 counties (required by Health and Safety Code Section 50093). These income limits apply to State and local affordable housing programs statutorily linked to HUD income limits and differ from income limits applicable to other specific federal, State, or local programs.

The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income. For CDBG, a person is considered to be of low income only if he or she is a member of a household whose income would qualify as "very low income" under the Section 8 Housing Assistance Payments program. Generally, these Section 8 limits are based on 50% of area median. Similarly, CDBG moderate income relies on Section 8 "lower income" limits, which are generally tied to 80% of area median. These data are from the 2011-2015 American Community Survey (ACS). To learn more about the Low to Moderate Income Populations visit: https://www.hudexchange.info/programs/acs-low-mod-summary-data/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Low to Moderate Income Populations by Block GroupDate of Coverage: ACS 2020-2016

Since passage of the U.S. Housing Act of 1937, the federal government has provided housing assistance to low-income renters. Most of these housing subsidies were provided under programs administered by the U.S. Department of Housing and Urban Development (HUD) or predecessor agencies. All programs covered in this report provide subsidies that reduce rents for low-income tenants who meet program eligibility requirements. Generally, households pay rent equal to 30 percent of their incomes, after deductions, while the federal government pays the remainder of rent or rental costs. To qualify for a subsidy, an applicant’s income must initially fall below a certain income limit. These income limits are HUD-determined, location specific, and vary by household size. Applicants for housing assistance are usually placed on a waiting list until a subsidized unit becomes available.Assistance provided under HUD programs falls into three categories: public housing, tenant-based, and privately owned, project-based.In public housing, local housing agencies receive allocations of HUD funding to build, operate or make improvements to housing. The housing is owned by the local agencies. Public housing is a form of project-based subsidy because households may receive assistance only if they agree to live at a particular public housing project.Currently, tenant based assistance is the most prevalent form of housing assistance provided. Historically, tenant based assistance began with the Section 8 certificate and voucher programs, which were created in 1974 and 1983, respectively. These programs were replaced by the Housing Choice Voucher program, under legislation enacted in 1998. Tenant based programs allow participants to find and lease housing in the private market. Local public housing agencies (PHAs) and some state agencies serving as PHAs enter into contracts with HUD to administer the programs. The PHAs then enter into contracts with private landlords. The housing must meet housing quality standards and other program requirements. The subsidies are used to supplement the rent paid by low-income households. Under tenant-based programs, assisted households may move and take their subsidy with them. The primary difference between certificates and vouchers is that under certificates, there was a maximum rent which the unit may not exceed. By contrast, vouchers have no specific maximum rent; the low-income household must pay any excess over the payment standard, an amount that is determined locally and that is based on the Fair Market Rent. HUD calculates the Fair Market Rent based on the 40th percentile of the gross rents paid by recent movers for non-luxury units meeting certain quality standards.The third major type of HUD rental assistance is a collection of programs generally referred to as multifamily assisted, or, privately-owned, project-based housing. These types of housing assistance fall under a collection of programs created during the last four decades. What these programs have in common is that they provide rental housing that is owned by private landlords who enter into contracts with HUD in order to receive housing subsidies. The subsidies pay the difference between tenant rent and total rental costs. The subsidy arrangement is termed project-based because the assisted household may not take the subsidy and move to another location. The single largest project-based program was the Section 8 program, which was created in 1974. This program allowed for new construction and substantial rehabilitation that was delivered through a wide variety of financing mechanisms. An important variant of project-based Section 8 was the Loan Management Set Aside (LMSA) program, which was provided in projects financed under Federal Housing Administration (FHA) programs that were not originally intended to provide deep subsidy rental assistance. Projects receiving these LMSA “piggyback” subsidies were developed under the Section 236 program, the Section 221(d)(3) Below Market Interest Rate (BMIR) program, and others that were unassisted when originally developed.Picture of Subsidized Households does not cover other housing

HOME Rent Limit data are available from FY 1998 to the present. Per 24 CFR Part 92.252, HUD provides the following maximum HOME rent limits. The maximum HOME rents are the lesser of: The fair market rent for existing housing for comparable units in the area as established by HUD under 24 CFR 888.111; or A rent that does not exceed 30 percent of the adjusted income of a family whose annual income equals 65 percent of the median income for the area, as determined by HUD, with adjustments for number of bedrooms in the unit. The HOME rent limits provided by HUD will include average occupancy per unit and adjusted income assumptions. In rental projects with five or more HOME-assisted rental units, twenty (20) percent of the HOME-assisted units must be occupied by very low-income families and meet one of following rent requirements: The rent does not exceed 30 percent of the annual income of a family whose income equals 50 percent of the median income for the area, as determined by HUD, with adjustments for smaller and larger families. HUD provides the HOME rent limits which include average occupancy per unit and adjusted income assumptions. However, if the rent determined under this paragraph is higher than the applicable rent under 24 CFR 92.252(a), then the maximum rent for units under this paragraph is that calculated under 24 CFR 92.252(a). The rent does not exceed 30 percent of the family's adjusted income. If the unit receives Federal or State project-based rental subsidy and the very low-income family pays as a contribution toward rent not more than 30 percent of the family's adjusted income, then the maximum rent (i.e., tenant contribution plus project-based rental subsidy) is the rent allowable under the Federal or State project-based rental subsidy program. Fair Market Rents are established by HUD each year for the Section 8 Program. For more information on the annual calculation of Fair Market Rents, visit the Fair Market Rents page. The FMRs for unit sizes larger than 4 bedroom are calculated by adding 15 percent to the 4 bedroom FMR for each extra bedroom. For example, the FMR for a 5 bedroom unit is 1.15 times the 4 bedroom FMR, and the FMR for a 6 bedroom unit is 1.30 times the 4 bedroom FMR, and so on... 5 BR = 1.15 x 4 BR FMR 6 BR = 1.30 x 4 BR FMR 7 BR = 1.45 x 4 BR FMR 8 BR = 1.60 x 4 BR FMR 9 BR = 1.75 x 4 BR FMR 10 BR = 1.90 x 4 BR FMR 11 BR = 2.05 x 4 BR FMR 12 BR = 2.20 x 4 BR FMR Note: The FY 2024 HOME Rent Limits effective date is June 01, 2024.

The U.S. Department of Housing and Urban Development’s (HUD) Housing Choice Voucher (HCV) Program assists very low-income families, the elderly, and the disabled in obtaining decent, safe, and sanitary housing in the private market.

Public Housing Authorities (PHAs) receive federal funds from HUD to administer the voucher program, and housing subsidies are paid to the landlord directly by the PHA on behalf of the participating family. The voucher recipient remains responsible for paying any difference that exists between the actual rent charged by the landlord and the amount subsidized by the program.

Voucher recipients are responsible for finding a suitable housing unit where the owner agrees to rent under the program. Because housing assistance is provided on behalf of the family or individual, participants are free to choose their own housing, including single-family homes, townhouses, and apartments provided that the chosen housing meets the requirements of the program, and is not limited to units located in subsidized housing projects. Qualified housing may also include the family's present residence. Furthermore, under certain circumstances, and if authorized by the PHA, a family may use its voucher to purchase a modest home. Please note that to restrict access to tenant information HCV locations are identified in public records by the owner, and not the tenant. Public data pertaining to the locations of HCV program participants are only available as U.S. Census Tract aggregations. Moreover, to protect the confidentiality of those receiving Housing Choice Voucher Program assistance, tracts containing 10 or fewer voucher holders have been omitted from this service. This dataset includes both tenant-based vouchers and project-based vouchers. HCV_PUBLIC_PCT are calculated using 2020 Census Demographic and Housing Characteristics File (DHC) table H4 Tenure Renter Occupied field. To learn more about the Housing Choice Voucher Program visit: https://www.hud.gov/program_offices/public_indian_housing/programs/hcv/about/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Housing Choice Vouchers by Tract Date of Coverage: Up to 04/2025Last Updated: 5/1/2025

This map is made using content created and owned by the federal Department of Housing and Urban Development (Esri user HUD.Official.Content). The map uses their Low to Moderate Income Population by Tract layer, filtered for only census tracts in Monroe County, NY where at least 51% of households earn less than 80 percent of the Area Median Income (AMI). The map is centered on Rochester, NY, with the City of Rochester, NY border added for context. Users can zoom out to see the Revitalization Areas for the broader county region.The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income. For CDBG, a person is considered to be of low income only if he or she is a member of a household whose income would qualify as "very low income" under the Section 8 Housing Assistance Payments program. Generally, these Section 8 limits are based on 50% of area median. Similarly, CDBG moderate income relies on Section 8 "lower income" limits, which are generally tied to 80% of area median. These data are derived from the 2011-2015 American Community Survey (ACS) and based on Census 2010 geography.Please refer to the Feature Layer for date of last update.Data Dictionary: DD_Low to Moderate Income Populations by Tract

This data, maintained by the Mayor’s Office of Housing (MOH), is an inventory of all income-restricted units in the city. This data includes public housing owned by the Boston Housing Authority (BHA), privately- owned housing built with funding from DND and/or on land that was formerly City-owned, and privately-owned housing built without any City subsidy, e.g., created using Low-Income Housing Tax Credits (LIHTC) or as part of the Inclusionary Development Policy (IDP). Information is gathered from a variety of sources, including the City's IDP list, permitting and completion data from the Inspectional Services Department (ISD), newspaper advertisements for affordable units, Community Economic Development Assistance Corporation’s (CEDAC) Expiring Use list, and project lists from the BHA, the Massachusetts Department of Housing and Community Development (DHCD), MassHousing, and the U.S. Department of Housing and Urban Development (HUD), among others. The data is meant to be as exhaustive and up-to-date as possible, but since many units are not required to report data to the City of Boston, MOH is constantly working to verify and update it. See the data dictionary for more information on the structure of the data and important notes. The database only includes units that have a deed-restriction. It does not include tenant-based (also known as mobile) vouchers, which subsidize rent, but move with the tenant and are not attached to a particular unit. There are over 22,000 tenant-based vouchers in the city of Boston which provide additional affordability to low- and moderate-income households not accounted for here. The Income-Restricted Housing report can be directly accessed here:
https://www.boston.gov/sites/default/files/file/2023/04/Income%20Restricted%20Housing%202022_0.pdf

Learn more about income-restricted housing (as well as other types of affordable housing) here: https://www.boston.gov/affordable-housing-boston#income-restricted

Special Tabulations of Householdsby Income, Tenure, Age of Householder, and Housing ConditionsThe Economic and Market Analysis Division (EMAD) "Special Tabulations" data retrieval system produces tabular statistical summaries of counts of households by tenure, by income intervals, by age of householder, by size of household, by housing conditions based on the 1990 and 2000 Census, for select geographic areas in the United States. This system allows a user to extract data to conduct a longitudinal analysis of changes in a particular area.These special cross tabulations of decennial and ACS census data are the most detailed available for a qualitative analysis of housing demand based on incomes and age of householder. These data are a key element in the allocation formulae for the Section 8 and the Section 202 rental assistance programs, as well as a key element in EMAD qualitative demand market analysis activities for review of program applications and multifamily mortgage insurance applications submitted to FHA.For 1990 and 2000, the system contains decennial data for all counties and county equivalents in the United States, places with populations of 50,000 (subject to disclosure requirements), the nation, all states and the District of Columbia, and MSAs and PMSAs (except those in New England) based on the 1999 OMB definitions in effect at the time of the 2000 Census. Year 2000 data are also provided for selected areas in the Commonwealth of Puerto Rico. Beginning in 2010, the system uses data from the Census ACS 5-year survey, which is available at the CBSA, State, and County level. A detailed description of the exact content and format of the database is presented in the Help section of the system (Uploader's note: this help section was not available due to 404 error).

he Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income. For CDBG, a person is considered to be of low income only if he or she is a member of a household whose income would qualify as "very low income" under the Section 8 Housing Assistance Payments program. Generally, these Section 8 limits are based on 50% of area median. Similarly, CDBG moderate income relies on Section 8 "lower income" limits, which are generally tied to 80% of area median. These data are from the 2011-2015 American Community Survey (ACS). To learn more about the Low to Moderate Income Populations visit: https://www.hudexchange.info/programs/acs-low-mod-summary-data/ Data Dictionary: DD_Low to Moderate Income Populations by Block Group Date of Coverage: ACS 2011-2015 Data Updated: Every Five Years

This month's Map of the Month shows the locations and number of households that receive housing aid through a United States Department of Housing and Urban Affairs (HUD) program known as the Section 8 Project-Based Rental Assistance Program. Funding that goes to families within these households has expired or is set to expire by the end of February 2019. Under the program, rental assistance contracts provide housing aid to seniors or individuals with disabilities with average incomes typically below the federal poverty limit. Due to the government shutdown, roughly 1,150 contracts between HUD and private owners of multi-tenant buildings are in limbo across the United States. Another 500 contracts are set to expire in January, with another 550 contracts to follow in February. According to the National Low-Income Housing Coalition, should the shutdown persist into February, an estimated 1,500 Bay Area households could face the real prospect of eviction.

Abstract

The Household Integrated Survey (HIS) in Georgia is conducted regularly from 1996 and has served to assess the level of consumption-based poverty since then. The HIS represents quarterly panel data. Each month 1/12 of the sample is refreshed.

Geographic coverage

National coverage

Analysis unit

• Households;
• Individuals.

Universe

The survey covered all household members excluding persons fully supported by the state, for example persons staying in homes for the elderly and the disabled, children in public care institutions, prisoners and etc.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Integrated Survey consists in quarterly interviewing households in Tbilisi and 9 Regions of Georgia: 1. Kakheti; 2. Tbilisi; 3. Shida Kartli, including Mtskheta-Mtianeti1; 4. Kvemo Kartli; 5. Mtskheta-Mtianeti; 6. Samtskhe-Javakheti; 7. Adjara; 8. Guria; 9. Samegrelo; 10. Imereti, including Racha-Lechkhumi and Kvemo Svaneti.

The sampling frame of households covers non-institutional part of the population. Those households are subject of observation which live at the sampled addresses. The sample size was selected so that various parameters could be estimated with satisfactory statistical precision not only on the level of the whole country but also on the level of the above listed regions.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Integrated Survey 2011 Questionnaire consists of 8 sections:

• Shinda01: General information about living conditions, housing, durables, etc. This section remained unchanged since the household survey was introduced in 1996.
• Shinda02: Household composition. This section also remained unchanged since the survey inception.
• Shinda03: Diary expenditure form. This section includes all diary expenditures during one week and it is filled out four times during the households' period of survey.
• Shinda04: Quarterly expenditures and agricultural activity form. This section covers quarterly expenditures on durables, energy supplies, health care, education, and other services. The questionnaire also collects information about harvest and processing of agricultural products produced by the household, sale and income from selling these products. The questionnaire is filled out four times, simultaneously with diary expenditures form. This section also features “reminder questions”, which help households remember their expenditures.
• Shinda05: Information about public and private transfers, as well as on changes in household financial and demographic conditions is collected in the section. The substance of the questions was not changed; however their phrasing was adjusted to make them more understandable for respondents.
• Shinda05-1: Includes information on employment and incomes from employment of adult household members.
• Shinda07: Refusal form. This section covers information on non-response or non-eligibility. This form helps correct the weights before data processing.
• Shinda09: Education Questionaire

NOTE: "Shinda" - Georgian abbreviation for "Observation of Households”.

Abstract

The GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture. This report has three main objectives: firstly, to present the key findings of GHS 2014. Secondly, it provides trends across a thirteen year period, i.e. since the GHS was introduced in 2002; and thirdly, it provides a more in-depth analysis of selected service delivery issues. As with previous reports, this report will not include tables with specific indicators measured, as these will be included in a more comprehensive publication of development indicators, entitled Selected development indicators

Geographic coverage

The General Household Survey 2014 had national coverage. The lowest level of geographic aggregation for this dataset is province.

Analysis unit

The units of anaylsis for the General Household Survey 2014 are individuals and households.

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage design was used in this survey, which is based on a stratified design with probability proportional to size selection of primary sampling units (PSUs) at the first stage and sampling of dwelling units (DUs) with systematic sampling at the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2001 data (secondary stratification).Survey officers employed and trained by Stats SA visited all the sampled dwelling units in each of the nine provinces. During the first phase of the survey, sampled dwelling units were visited and informed about the coming survey as part of the publicity campaign. The actual interviews took place four weeks later. A total of 25 363 households (including multiple households) were successfully interviewed during face-to-face interviews. Two hundred and thirty-three enumerators (233) and 62 provincial and district coordinators participated in the survey across all nine provinces. An additional 27 quality assurors were responsible for monitoring and ensuring questionnaire quality. National training took place over a period of four days. The national trainers then trained provincial trainers for five days at provincial level. They in turn provided district training to the survey officers for a period of six days.

Sampling deviation

The sample design for the GHS 2014 was based on a master sample (MS) that was originally designed for the Quarterly Labour Force Survey (QLFS) and was used for the first time for the GHS in 2008. This master sample is shared by the QLFS, GHS, Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Survey (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: • Where possible, PSU sizes were kept between 100 and 500 DUs; • EAs with fewer than 25 DUs were excluded; • EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; • Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and • Informal PSUs were segmented.

A randomised-probability-proportional-to-size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The details of the questions included in the GHS questionnaire are covered in 10 sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

   A summary of the contents of the GHS 2014 questionnaire

Section Number of Details of each section questions Cover page Household information, response details, field staff information, result codes, etc. Flap 6 Demographic information (name, sex, age, population group, etc.) Section 1 41 Biographical information (education, health, disability, welfare) Section 2 13 Health and general functioning section 3 3 Social grants and social relief Section 4 19 Economic activities Section 5 59 Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation, environmental issues, services, transport, etc.) Section 6 11 Communication, postal services and transport Section 7 15 Health, welfare and food security section 8 28 Households Livelihoods (agriculture, household income sources and expenditure)
Section 9 7 Mortality in the last 12 months Section 10 3 Questions to interviewers
All sections 202 Comprehensive coverage of living conditions and service delivery

The GHS questionnaire has undergone some revisions over time. These changes were primarily the result of shifts in focus of government programmes over time. The 2002–2004 questionnaires were very similar. Changes made to the GHS 2005 questionnaire included additional questions in the education section with a total of 179 questions. Between 2006 and 2008, the questionnaire remained virtually unchanged. For GHS 2009, extensive stakeholder consultation took place during which the questionnaire was reviewed to be more in line with the monitoring and evaluation frameworks of the various government departments. Particular sections that were modified substantially during the review were the sections on education, social development, housing, agriculture, and food security. Even though the number of sections and pages in the questionnaire remained the same, questions in the GHS 2009 were increased from 166 to 185 between 2006 and 2008. Following the introduction of a dedicated survey on Domestic Tourism, the section on tourism was dropped for GHS 2010. Due to a further rotation of questions, particularly the addition of a module on mortality, the GHS 2014 questionnaire contained 202 questions.

Cleaning operations

Historically the GHS used a conservative and hands-off approach to editing. Manual editing, and little if any imputation was done. The focus of the editing process was on clearing skip violations and ensuring that each variable only contains valid values. Very few limits to valid values were set and data were largely released as they were received from the field. With GHS 2009, Stats SA introduced an automated editing and imputation system that was continued for GHSs 2010–2014. The challenge was to remain true, as much as possible, to the conservative approach used prior to GHS 2009, and yet, at the same time, to develop a standard set of rules to be used during editing which could be applied consistently across time. When testing for skip violations and doing automated editing, the following general rules are applied in cases where one question follows the filter question and the skip is violated:

• If the filter question had a missing value, the filter is allocated the value that corresponds with the subsequent question which had a valid value. • If the values of the filter question and subsequent question are