Introduction to the Data
This set of reports sketches a picture of subsidized households across the United States. There are national and regional reports and an accompanying computer data file. Each line is identified by key numbers and letters which are explained in the Detailed Explanation section
Sources
Data on households were sent by local housing agencies to the U.S. Department of Housing and Urban Development (HUD), and were summarized by HUD. This report uses the latest report on each household, provided it was submitted in the last 30 months. Most w ere submitted in the last 12 months. Earlier data on Public and Indian Housing are available for 1993 (see Family Data for Public and Indian Housing). The completeness or incompleteness of the data is shown on every line and is discussed below. The data collection forms are printed at the end of this report.
Data on the size and location of each program and project are from HUD's own administrative records, plus a database on Tax Credit projects collected by a contractor. (This is the only source used for Tax Credits, since data on individual households are n ot collected in that program.)
Program Overview
Rents are subsidized in all programs covered in this report. Households generally pay rent equal to 30% of their incomes, after deductions, and the Federal government pays the rest. To enter the programs, people must generally be below an income limit, wh ich varies by household size and location. They apply, and wait until their name rises to the top of the waiting list for the limited number of subsidized units available. Tax Credits are a program of the Internal Revenue Service, where landlords obtain t ax benefits for renting to low income households. Some projects have a mix of subsidized and unsubsidized units; just the subsidized units are counted here.
Report Overview
The reports and the data file show summary records for: the whole United States, each state, each housing agency, neighborhood (Census tract) and individual housing project. Only the summary records are included; no records for individual households. A Ce nsus tract is a compact area averaging about 1,500 households. We lack addresses for about 19% of subsidized housing units, so they cannot be placed in tracts, and thus the tract totals are underestimates. The data file is complete; the reports include th e following types of data:
Summaries Included
| National Report | Regional Reports | Data File |
| U.S. and State Totals | All | All | All |
| Housing Agencies | Agencies with 300+ units | All | All |
| Projects | Projects with 300+ units | All | All |
| Census Tracts: |
|
|
|
Certificates+Vouchers | Tracts with 150+ C+V | Tracts with 40+ C+V | All | |
Totals of All Programs | Tracts with 300+ subsidized units, if these are 30%+ of tract | Tracts where subsidized are 20%+ of tract | All | |
| Maps | Selected areas | None | User-created |
Each summary record shows the number of housing units being summarized, completeness of the household data, average household income, percent minority, elderly, female headed, Zip code, county, metropolitan area, etc. In the reports, the information is spread across two facing pages.
Summary records are shown even when data are incomplete. To protect reliability we do not show household information where fewer than 40% of households are reported. We still show project number, project size, location, etc. To protect privacy we also do not show household information where 10 or fewer households are reported. All these households are still included in larger summaries, such as for the agency, state and United States.
Order of the Book
The records are grouped by state. Within each state they are sorted by project number, so individual project numbers are easy to find. One can also look through the list to find all projects in a city. If we had grouped them by address, it would have been somewhat easier to find cities, but impossible to find specific project numbers. The numbers for different programs are sorted with Public & Indian numbers first in each state, then Section 8 project numbers, then Federal Housing Administration (FHA) pro ject numbers, then Tax Credit projects, and finally Census tract summaries that total across all programs.
Suggestions for Using the Data File
Groups of projects can be compared. In some areas it may be useful to use the file to prepare a referral list of all subsidized housing in the area, with size, turnover, % elderly, neighborhood characteristics, etc. You can use various software tools to e xplore the data base. If you read the file on Internet, your browser probably has a 'Find' button, so you can move quickly to any city name, project name, project number, etc. If you download the data to your own computer, you can use a spreadsheet or dat abase package. Such packages let you:
- Jump to any part of the file (often using the f5 key, or a command to 'Find' a specific name)
- Sort the records to see the highest incomes, or most concentrated tracts, or most integrated large projects, etc. (for example sort by record type and income)
- Print selected items (in spreadsheet set width of other items to zero; in database list items you want in a report)
- Map the data (by selecting the records you want to map, then asking for an X-Y graph, using longitude for the X axis, and latitude for the Y axis, with a small symbol at each point, and no lines to connect the points; some databases do not give such graphs).
The national data file is about 43 megabytes. State files are smaller. File names include 'hud2' to distinguish them from the first file, which had Public and Indian Housing data for 1993. Three extra files come with the data:
| hud2.wk1 | Empty spreadsheet file, ready to fill: labels and widths of variables are already defined |
| hud2.dbf | Empty data base file, ready to fill: names and widths of variables are already defined |
| Readme2.txt | Documentation |
Database Software
After downloading you can open hud2.dbf, which has the names and widths of the variables. Then import the file as delimited ASCII. In dBase:
- Hit Escape key
- . Use C:\hud2.dbf
- . Append from C:\hud2AK.txt Delimited
- . Go top
- . Assist Spreadsheet Software
After downloading you can open hud2.wk1, which has the names and widths of the variables. Then import the file as an ASCII file with numbers separated by commas (text is enclosed in quotes). In Lotus:
- /File Retrieve C:\hud2.wk1
- /File Import Numbers C:\hud2AK.txt
If your spreadsheet cannot read large files, use another package to split the file into pieces. Fixed Format Software
Names and widths of the variables are in the layout printed on pages 18–22. You can skip over the commas and quotes. The files are delimited ASCII, with double quotes around text, and commas separating all fields, so they can be read directly by most prog rams. At the same time the files are in fixed format, so they can be read by programs that need fixed formats. We have kept the record length under 240 characters, which is a limit in Lotus, since we expect some users will use Lotus.
Scope of the Data File
The following table shows record types that are present in the computer file. For example there is one national summary record in each program, and 30–55 state summaries, depending on the program. Project records are present in some programs, tract record s in others, and Moderate Rehabilitation has neither, but just agency summaries. Summaries for parts of agencies are provided where an agency uses multiple numeric codes for various reasons.
Number of Records by Type
| | Total | National Records | Size Class Records | State Records | Housing Agency Records | Parts-of-Agency Records | Project Records | Tract Records |
| Total | 180,341 | 9 | 43 | 458 | 6,572 | 115 | 48,152 | 124,992 |
|
| Totals | 61,328 | 1 | 9 | 55 |
|
|
| 61,263 |
| Indian Housing | 2,624 | 1 | 7 | 30 | 177 | 9 | 2,400 |
|
| Public Housing | 16,808 | 1 | 9 | 54 | 3,192 | 15 | 13,537 |
|
| S.8 Certificates+Vouchers | 66,404 | 1 | 9 | 55 | 2,554 | 56 |
| 63,729 |
| Moderate Rehab. | 746 | 1 | 9 | 52 | 649 | 35 |
|
|
| S.8 New+Substant.Rehab. | 15,235 | 1 |
| 55 |
|
| 15,179 |
|
| S.236 | 4,277 | 1 |
| 52 |
|
| 4,224 |
|
| Other Subsidy | 3,420 | 1 |
| 52 |
|
| 3,367 |
|
| Housing Tax Credit | 9,499 | 1 |
| 53 |
|
| 9,445 |
|
Technical Comments
Incomplete Data are shown by the column headed "% Reported," the column in the middle of the even-numbered pages.
Some agencies reported zero in some items, rather than their actual data. We have removed most of the bias, generally by treating zero as missing data. Virtually all zero rents and zero incomes are indeed missing data, since the only households with truly zero gross income and zero gross rent are formerly homeless households who for some reason do not expect any income assistance in the coming year. Zero bedrooms are meaningful (efficiency apartments), and we try to minimize bias by treating units with no bedrooms reported and more than 2 people as missing data. We did not process households with invalid project numbers, or with no people reported, since we would not have been able to categorize them properly.
Number of Subsidized Units by Missing Data
| Housing Agency Records | Project Records |
| Total | % Lack Geography | % Lack Tenant Data | Total | % Lack Geography | % Lack Tenant Data |
| Total | 2,846,000 | 17 | 19 | 3,363,000 | 19 | 27 |
| Indian Housing | 68,000 | 79 | 44 | 68,000 | 90 | 56 |
| Public Housing | 1,326,000 | 25 | 16 | 1,326,000 | 32 | 22 |
| S.8 Certificates+Vouchers | 1,346,000 | 7 | 20 |
|
|
|
| Moderate Rehab. | 106,000 | 7 | 33 |
|
|
|
| S.8 New+Substant.Rehab. |
|
|
| 897,000 | 4 | 23 |
| S.236 | 447,000 | 2 | 22 |
|
|
|
| Other Subsidy |
|
|
| 292,000 | 10 | 32 |
| Housing Tax Credit |
|
|
| 332,000 | 24 | 56 |
This table shows the number of subsidized units where agency or project records have no tenant data or geographic data (because of non-reporting of either, or suppression of tenant data to protect confidentiality). Agencies have less suppression of tenant data than projects, since they are larger. Agencies also have less missing geographic data, since we can have geographic codes for an agency if any of its projects are geographically coded. Specifically this table is based on the absence of data on bedrooms and latitude from the records. Other items may be more or less complete.
Weighting for incomplete data
The summaries are weighted to adjust for partial reporting in any agency: households reported are assumed representative of other occupied units in the same program and agency (or in the same project, in Office of Housing Programs). This assumption is not always correct. Furthermore, if far too many or too few households were reported in a program, the weight was limited to the range from .5 to 5, to avoid great discrepancies in weights, and resulting variance in the final data. There is no weighting to represent the places that did not report at all.
Other Errors
As many errors as possible have been corrected, but there undoubtedly remain errors, coming from household errors and from agency and HUD processing. Please tell us of any errors you find.
Processing Steps
The report merges data from 48 different computer tapes: 24 tapes of data from the September 1996 Multifamily Tenant Characteristics System (MTCS), 9 tapes of data from the December 1995 Tenant Rental Assistance and Certification System (TRACS, with data primarily through October 1995), 10 tapes of Census tract data, 4 tapes of geographic codes for Certificate+Voucher households, a tape of geographic codes for projects, and control totals for the number of units in each project.
The Office of Policy Development and Research has standards for data documentation, that require listing all the steps of processing the data, so readers can see how problems were dealt with and how far the data have been changed from the originals. The processing steps for this report included:
- Master Control File
- Extracted records of Public & Indian projects & sub-projects from MTCS, sorted by project numbers, summarized sub-projects to projects, sorted by controlling agency, summarized units by program, project, agency and controlling agency
- Created list of which Section 8 agency numbers have been converted to, or are controlled by others (primarily state agencies)
- Extracted records of Section 8 contracts by effective date, sorted & summarized by agency & program, looked up controlling agency in lists from A1 and A2, inserted empty records for agency numbers that have been converted and no longer have units (so any tenants reported under old numbers can be converted), sorted by agency and added to control file of Public & Indian units
- Converted agency names to all capitals, project names to Initial Capitals, and flagged Indian rental projects.
- Geographic Files on Projects
- Extracted Census tract summary statistics, converted to percent, & stored them in a small file.
- Extracted Public Housing project records with geographic identifiers, and sorted by state, county, tract, looked up tract statistics & added these to project records. Sorted by project number to create lookup file. Added to master file from A4.
- Extracted necessary information from a control file of valid FHA & Section 8 numbers with geocodes. Sorted by FHA number, classified each number by combination of subsidies present. Edited inconsistent subsidy information. Wrote summaries, sorted by s tate, county, tract, looked up tract statistics & added these to project records. Sorted by FHA & Section 8 numbers to create lookup file.
- MTCS - Characteristics of Households in Programs of the Office of Public and Indian Housing
- Extracted program identifiers & allowances for each household & sorted by SSN
- Summarized income & household composition for each household & sorted by SSN
- Extracted rent calculation data for households in different sub-programs into a common format & sorted by SSN
- Extracted geographic codes from four tapes (Section 8 addresses had been sent to a geocoding contractor in four separate groups at different times) & sorted by SSN
- Matched all the above data extracts by SSN, taking most recent data for each household, & sorted by project number (agency in Section 8), state, county, tract, mcd
- Counted the number of records in each sub-program in each agency, compared to control file, & wrote file of weights to adjust for non-response & over-response. (Over-response happens when agencies do not report move-outs, so more than one household is in the HUD file, for the same unit.
- Summarized the weighted data into the categories of this report, at level of project and part-of-agency. (In Section 8 also looked up tract statistics, & for Certificates+Vouchers also summarized to tract.)
- TRACS - Characteristics of Households in Office of Housing Programs
- Extracted a record for each household from a 9–tape composite file, while comparing several FHA and Section 8 numbers on each record to obtain the cleanest identifiers, & sorted by FHA number and Section 8 number
- Summarized the extracted data for each combination of FHA number & Section 8 number
- For each summary of tenants from D2, looked for FHA number in control file from B3. Appended program code, unit counts, name & geographic codes. Where FHA number was not found, looked for Section 8 number & appended FHA number if available, program code, unit counts, name & geographic codes. Deleted tenant data not matched by either way. Then extracted project numbers, program code, unit counts, name & geographic codes for valid projects that had no tenants matched to them. Resorted by FHA number & Section 8 number. Re-summarized & weighted by unit totals all records with the same valid FHA number, or with no FHA number & the same valid Section 8 number.
- Tax Credits
- Extracted needed information from original file (prepared by Abt Associates from state-provided data, with four records per Tax Credit allocation), creating one record each. Compressed state code and state-determined project ID into an 11 character number.
- Sorted by address and name. Combined multiple records with one building address, unless address was simply 'Scattered' or 'Various,' in which case records were only combined if they had the same name.
- Number of low income units was missing on 8% of projects. On half of these it could be estimated from total project units (using 98% average found elsewhere). On the others this report shows 35 units each (the national average).
Geographic Codes Used
| HUD Form 951 | Office of Housing | Summaries of Certificates+Vouchers | LIHTC | Merge Program |
| Raw data | Binary extract | Control file of Public & Indian | Raw data (in control file) | Binary extract | Summaries of Tracs | Raw data | Extract |
| columns | width | columns | width | columns | width | columns | width | columns | width | columns | width | columns | width | record/columns | width | columns | width | columns | width |
| state | 231-232 | 2 | 20 | 1 |
|
| 205-6 | 2 | 25 | 1 |
|
| 7-8 | 2 | 3/43-44 | 2 |
|
|
|
|
| county | 234-236 | 3 | 21-22 | 2 | 77-79 | 3 | 207-9 | 3 | 26-27 | 2 | 13-15 | 3 | 10-12 | 3 | 3/45-47 | 3 | 12-14 | 3 | 1-3 | 3 |
| tract | 252-258 | 7.2 | 23-26 | 4 | 80-86 | 7.2 | 221-8 | 8.2 | 28-31 | 4 | 16-22 | 7.2 | 14-20 | 7.2 | 3/48-54 | 7.2 | 15-21 | 7.2 | 4-10 | 7.2 |
| msa | 247-250 | 4 | 27-28 | 2 | 87-90 | 4 | 217-220 | 4 | 32-33 | 2 | 23-26 | 4 | 21-24 | 4 | 3/22-25 | 4 | 22-25 | 4 | 11-14 | 4 |
| place | 242-245 | 4 | 29-30 | 2 | 91-94 | 4 | 213-6 | 4 | 34-35 | 2 | 27-30 | 4 | 25-28 | 4 | 3/26-30 | 5 | 26-29 | 4 | 15-18 | 4 |
| cd | 306-7 | 2 | 31 | 1 | 95-96 | 2 | 265-6 | 2 | 36 | 1 | 31-32 | 2 | 29-30 | 2 | na |
|
|
| 19-20 | 2 |
scatter
(s.d. 100ft) | 82-86
100-104 | 5.5
5.5 | 32 | 1 | 97-98 | 2 | 69-74
87-92 | 6.4
6.4 | 37 | 1 | 33-34 | 2 |
|
|
|
|
|
|
|
|
| units | 143-147 | 5 | 33-34 | 2 |
|
| 326-31 | f6 | 38-39 | 2 | 35-38 | 4 |
|
| 3/55-58 | 4 | p1 | 4 | a-4 | 4 |
| name | 34-63 | 30 | 35-50 | 16 |
|
| 24-53 | 30 | 40-55 | 16 | 39-54 | 16 |
|
| 1/7-36 | 30 | 32-47 | 16 | 1-16 | 16 |
| address | 184-200
150-180 | 17
31 | 51-66 | 16 | 99-114 | 16 | 164-180
133-163 | 17
31 | 56-71 | 16 | 55-70 | 16 |
|
| 1/37-66 | 30 | 48-63 | 16 | 17-32 | 16 |
| city | 204-218 | 15 | 67-74 | 8 | 115-122 | 8 | 181-195 | 15 | 72-79 | 8 | 71-78 | 8 |
|
| 1/67-96 | 30 | 64-71 | 8 | 33-40 | 8 |
| zip | 221-229 | 9 | 75-76 | 2 | 123-7 | 5 | 196-204 | 9 | 80-81 | 2 | 79-83 | 5 | 31-35 | 5 | 1/99-108 | 10 | 72-76 | 5 | 21-25 | 5 |
| mcd | 238-240 | 3 | 77-78 | 2 | 128-30 | 3 | 210-212 | 3 | 82-83 | 2 | 84-86 | 3 | 36-38 | 3 | na |
|
|
| 26-28 | 3 |
| lat? 0-1 |
|
| p1 | 4 | 131 | 1 |
|
| 84-87 | 4 | b62 | 4 | a(62) | 4* |
|
| p7 | 4* | a62 | 4* |
| latitude | 71-80 | 10.6 | p2 | 4 | 132-37 | 6.3 | 58-68 | 11.6 | 88-91 | 4 | b63 | 4 | a(63) | 4* | 3/1-9 | 9.6 | p8 | 4* | a63 | 4* |
| longitude | 88-98 | 11.6 | p3 | 4 | 138-45 | 8.3 | 75-86 | 12.6 | 92-95 | 4 | b64 | 4 | a(64) | 4* | 3/10-20 | 11.6 | p9 | 4* | a64 | 4* |
| tract? 0-1 |
|
| p4 | 4 | 146 | 1 |
|
| 96-99 | 4 | b65 | 4 | a(65) | 4* |
|
| p10 | 4* | a65 | 4* |
| poor |
|
| p5 | 4 | 147-8 | 2 |
|
| 100-103 | 4 | b66 | 4 | a(66) | 4* |
|
| p11 | 4* | a66 | 4* |
| minority |
|
| p6 | 4 | 149-50 | 2 |
|
| 104-107 | 4 | b67 | 4 | a(67) | 4* | 4/95-99 | 5.2 | p12(10) | 4* | a67 | 4* |
| sfd-own |
|
| p7 | 4 | 151-2 | 2 |
|
| 108-111 | 4 | b68 | 4 | a(68) | 4* |
|
| p13 | 4* | a68 | 4* |
* Stored as multiple of number of units, for convenient averaging
Notes:
1. When numeric items are stored in fewer characters than the raw data have, they are stored in binary format, where each position holds 9 bits (0-511 decimal). However the final public file expands them back to normal ascii codes.
2. 'Scatter' measures scattered site projects: it is the standard deviation of the distance of each address from the average, measured in hundreds of feet. It may be included in a future release.
Total Number of Records by State
| | Total | Agency+Other Summary Records | Project Records | Tract Records |
| Indian Housing | Public Housing | S.8 New + Substantial Rehab | S.236 | Other Subsidy | Housing Tax Credit | Certificates + Vouchers | Totals of All Programs |
| Total | 180,341 | 7,197 | 2,400 | 13,537 | 15,179 | 4,224 | 3,367 | 9,445 | 63,729 | 61,263 |
| U.S. Summaries | 52 | 52 |
|
|
|
|
|
|
|
|
| AK | 727 | 35 | 302 | 41 | 21 | 9 | 9 | 11 | 109 | 190 |
| AL | 3,537 | 244 | 7 | 601 | 267 | 48 | 24 | 257 | 1,027 | 1,062 |
| AR | 2,198 | 207 | 0 | 263 | 219 | 35 | 50 | 70 | 761 | 593 |
| AZ | 2,389 | 75 | 294 | 108 | 104 | 40 | 19 | 49 | 890 | 810 |
| CA | 15,485 | 262 | 123 | 685 | 1,139 | 584 | 226 | 274 | 6,334 | 5,858 |
| CO | 2,830 | 111 | 27 | 162 | 235 | 62 | 45 | 59 | 1,150 | 979 |
| CT | 2,669 | 108 | 4 | 191 | 240 | 81 | 96 | 68 | 1,047 | 834 |
| DC | 421 | 12 | 0 | 62 | 79 | 36 | 32 | 8 | 0 | 192 |
| DE | 457 | 21 | 0 | 34 | 54 | 7 | 7 | 21 | 138 | 175 |
| FL | 6,856 | 225 | 17 | 419 | 392 | 128 | 116 | 153 | 2,958 | 2,448 |
| GA | 4,207 | 235 | 0 | 858 | 275 | 122 | 71 | 226 | 950 | 1,470 |
| GQ | 21 | 11 | 0 | 9 | 1 | 0 | 0 | 0 | 0 | 0 |
| HI | 870 | 18 | 0 | 61 | 67 | 20 | 6 | 13 | 420 | 265 |
| IA | 2,250 | 120 | 1 | 110 | 276 | 36 | 21 | 88 | 814 | 784 |
| ID | 827 | 31 | 29 | 19 | 107 | 20 | 11 | 70 | 271 | 269 |
| IL | 6,862 | 202 | 0 | 763 | 595 | 105 | 132 | 424 | 1,800 | 2,841 |
| IN | 3,541 | 123 | 0 | 197 | 318 | 140 | 116 | 105 | 1,159 | 1,383 |
| KS | 2,142 | 146 | 14 | 169 | 257 | 49 | 40 | 127 | 656 | 684 |
| KY | 3,327 | 188 | 0 | 332 | 349 | 62 | 85 | 212 | 1,102 | 997 |
| LA | 3,103 | 225 | 3 | 348 | 151 | 52 | 67 | 252 | 900 | 1,105 |
| MA | 5,017 | 214 | 0 | 284 | 463 | 189 | 107 | 177 | 2,252 | 1,331 |
| MD | 2,742 | 71 | 0 | 181 | 288 | 101 | 56 | 203 | 691 | 1,151 |
| ME | 1,497 | 71 | 21 | 74 | 247 | 17 | 9 | 98 | 576 | 384 |
| MI | 6,333 | 223 | 31 | 314 | 461 | 237 | 212 | 277 | 2,028 | 2,550 |
| MN | 4,082 | 214 | 77 | 289 | 529 | 94 | 54 | 211 | 1,384 | 1,230 |
| MO | 4,751 | 211 | 0 | 276 | 394 | 85 | 86 | 773 | 1,678 | 1,248 |
| MS | 1,804 | 80 | 16 | 259 | 231 | 32 | 50 | 124 | 431 | 581 |
| MT | 998 | 38 | 174 | 46 | 70 | 29 | 19 | 41 | 295 | 286 |
| NC | 5,102 | 212 | 19 | 427 | 723 | 71 | 63 | 581 | 1,524 | 1,482 |
| ND | 864 | 68 | 78 | 36 | 144 | 11 | 12 | 39 | 244 | 232 |
| NE | 1,552 | 143 | 22 | 158 | 182 | 19 | 18 | 158 | 406 | 446 |
| NH | 981 | 52 | 0 | 63 | 140 | 19 | 7 | 30 | 404 | 266 |
| NJ | 5,759 | 192 | 0 | 331 | 348 | 124 | 85 | 68 | 2,673 | 1,938 |
| NM | 1,474 | 94 | 228 | 100 | 75 | 20 | 33 | 98 | 436 | 390 |
| NV | 925 | 32 | 84 | 53 | 42 | 17 | 14 | 41 | 373 | 269 |
| NY | 13,040 | 323 | 17 | 573 | 933 | 300 | 129 | 171 | 5,736 | 4,858 |
| OH | 7,397 | 157 | 0 | 522 | 765 | 246 | 292 | 467 | 2,086 | 2,862 |
| OK | 3,394 | 169 | 396 | 213 | 125 | 53 | 54 | 163 | 1,229 | 992 |
| OR | 2,305 | 67 | 13 | 131 | 217 | 70 | 56 | 195 | 829 | 727 |
| PA | 8,761 | 222 | 0 | 698 | 620 | 158 | 74 | 763 | 3,059 | 3,167 |
| RI | 1,001 | 68 | 0 | 102 | 136 | 38 | 15 | 41 | 366 | 235 |
| RQ | 710 | 106 | 0 | 332 | 180 | 21 | 24 | 47 | 0 | 0 |
| SC | 2,559 | 96 | 0 | 251 | 237 | 50 | 63 | 94 | 914 | 854 |
| SD | 972 | 77 | 151 | 40 | 152 | 23 | 56 | 92 | 184 | 197 |
| TN | 4,174 | 146 | 0 | 490 | 371 | 66 | 84 | 421 | 1,375 | 1,221 |
| TQ | 14 | 5 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 |
| TX | 12,469 | 610 | 6 | 992 | 426 | 171 | 262 | 672 | 5,284 | 4,046 |
| UT | 1,139 | 47 | 21 | 69 | 78 | 16 | 9 | 45 | 454 | 400 |
| VA | 3,397 | 83 | 0 | 179 | 287 | 122 | 56 | 191 | 806 | 1,673 |
| VQ | 52 | 9 | 0 | 32 | 4 | 0 | 0 | 7 | 0 | 0 |
| VT | 656 | 36 | 0 | 33 | 132 | 6 | 3 | 31 | 234 | 181 |
| WA | 3,447 | 100 | 112 | 240 | 263 | 80 | 115 | 213 | 1,172 | 1,152 |
| WI | 4,301 | 200 | 95 | 206 | 536 | 80 | 56 | 356 | 1,432 | 1,340 |
| WV | 1,482 | 81 | 0 | 88 | 168 | 13 | 13 | 67 | 579 | 473 |
| WY | 419 | 29 | 18 | 23 | 57 | 10 | 8 | 3 | 109 | 162 |
Number of Subsidized Units, by State and Program
| | Total | Indian Housing | Public Housing | Certificates + Vouchers | Moderate Rehabilitation | S.8 New + Substantial Rehabilitation | S.236 | Other Subsidy | Housing Tax Credit |
| Total | 4,814,983 | 67,744 | 1,326,224 | 1,346,306 | 105,845 | 897,160 | 447,382 | 292,237 | 332,085 |
| AK | 11,448 | 5,047 | 1,629 | 2,618 | 0 | 887 | 642 | 238 | 387 |
| AL | 94,771 | 155 | 45,175 | 18,369 | 1,770 | 13,775 | 5,234 | 1,555 | 8,738 |
| AR | 53,632 | 0 | 15,666 | 19,203 | 255 | 7,939 | 2,955 | 3,880 | 3,734 |
| AZ | 49,631 | 13,523 | 6,623 | 14,283 | 790 | 6,188 | 3,726 | 1,641 | 2,857 |
| CA | 403,914 | 2,339 | 46,252 | 196,872 | 7,466 | 61,149 | 53,525 | 21,122 | 15,189 |
| CO | 53,057 | 547 | 8,695 | 16,825 | 2,269 | 12,011 | 7,068 | 2,631 | 3,011 |
| CT | 77,162 | 45 | 19,211 | 19,960 | 1,780 | 16,044 | 10,229 | 7,632 | 2,261 |
| DC | 32,428 | 0 | 11,788 | 3,508 | 1,346 | 6,190 | 4,508 | 3,931 | 1,157 |
| DE | 13,005 | 0 | 3,360 | 3,095 | 149 | 3,830 | 709 | 563 | 1,299 |
| FL | 186,606 | 378 | 44,631 | 63,419 | 7,840 | 25,785 | 18,535 | 11,874 | 14,144 |
| GA | 134,882 | 0 | 57,692 | 27,534 | 1,361 | 17,234 | 13,300 | 7,236 | 10,525 |
| GQ | 2,295 | 0 | 751 | 1,419 | 75 | 5 | 0 | 0 | 0 |
| HI | 20,581 | 0 | 5,263 | 8,238 | 46 | 2,591 | 2,205 | 1,587 | 651 |
| IA | 40,504 | 20 | 4,682 | 15,583 | 1,066 | 11,727 | 3,133 | 1,366 | 2,927 |
| ID | 13,393 | 793 | 817 | 4,529 | 144 | 3,497 | 820 | 399 | 2,394 |
| IL | 223,965 | 0 | 80,870 | 45,998 | 3,815 | 46,844 | 12,633 | 16,738 | 17,067 |
| IN | 95,912 | 0 | 18,574 | 25,720 | 1,491 | 21,304 | 14,999 | 9,809 | 4,015 |
| KS | 39,540 | 416 | 9,279 | 7,163 | 350 | 9,082 | 3,209 | 3,381 | 6,660 |
| KY | 82,320 | 0 | 25,888 | 20,213 | 1,613 | 18,438 | 6,531 | 5,856 | 3,781 |
| LA | 93,472 | 40 | 32,722 | 23,364 | 1,843 | 11,789 | 6,131 | 6,419 | 11,164 |
| MA | 163,465 | 0 | 35,396 | 46,070 | 3,675 | 36,320 | 20,497 | 12,650 | 8,857 |
| MD | 99,866 | 0 | 26,216 | 23,099 | 2,702 | 17,869 | 14,918 | 5,843 | 9,219 |
| ME | 26,786 | 467 | 4,167 | 8,468 | 1,491 | 7,308 | 1,655 | 624 | 2,606 |
| MI | 149,287 | 772 | 29,261 | 26,282 | 1,192 | 40,618 | 23,351 | 16,908 | 10,903 |
| MN | 92,977 | 1,735 | 22,002 | 23,002 | 890 | 23,866 | 10,243 | 4,362 | 6,877 |
| MO | 103,122 | 0 | 21,910 | 28,916 | 3,285 | 21,204 | 8,277 | 7,146 | 12,384 |
| MS | 55,108 | 719 | 16,338 | 12,651 | 1,082 | 11,932 | 3,234 | 4,230 | 4,922 |
| MT | 18,616 | 5,203 | 2,074 | 3,457 | 764 | 2,762 | 2,222 | 1,136 | 998 |
| NC | 122,251 | 1,261 | 39,924 | 35,455 | 3,925 | 21,547 | 6,750 | 5,318 | 8,071 |
| ND | 16,111 | 2,726 | 1,939 | 5,457 | 554 | 3,146 | 859 | 384 | 1,046 |
| NE | 30,977 | 677 | 7,823 | 9,727 | 715 | 5,625 | 1,789 | 835 | 3,786 |
| NH | 19,275 | 0 | 4,310 | 6,142 | 424 | 4,938 | 1,969 | 432 | 1,060 |
| NJ | 153,250 | 0 | 48,269 | 41,792 | 3,149 | 36,788 | 11,698 | 7,597 | 3,957 |
| NM | 28,546 | 3,126 | 4,857 | 9,761 | 504 | 3,173 | 1,968 | 2,449 | 2,708 |
| NV | 20,096 | 1,772 | 4,500 | 5,334 | 750 | 2,249 | 1,836 | 1,354 | 2,301 |
| NY | 483,048 | 514 | 194,359 | 137,483 | 9,905 | 81,453 | 37,104 | 15,732 | 6,498 |
| OH | 220,779 | 0 | 57,037 | 50,474 | 5,090 | 46,453 | 26,042 | 18,778 | 16,905 |
| OK | 70,486 | 12,343 | 13,391 | 18,544 | 2,711 | 7,070 | 4,778 | 3,894 | 7,755 |
| OR | 48,473 | 436 | 6,157 | 20,567 | 1,448 | 7,364 | 3,375 | 1,889 | 7,237 |
| PA | 225,424 | 0 | 81,195 | 54,333 | 4,060 | 45,719 | 20,196 | 6,631 | 13,290 |
| RI | 35,074 | 0 | 9,999 | 6,161 | 658 | 12,095 | 3,595 | 890 | 1,676 |
| RQ | 112,869 | 0 | 57,288 | 21,302 | 3,095 | 18,388 | 4,511 | 4,328 | 3,957 |
| SC | 60,048 | 0 | 16,870 | 14,790 | 2,066 | 12,884 | 5,030 | 4,817 | 3,591 |
| SD | 21,357 | 6,131 | 1,695 | 3,887 | 599 | 3,582 | 1,099 | 2,130 | 2,234 |
| TN | 110,452 | 0 | 42,958 | 18,897 | 1,917 | 21,621 | 8,530 | 8,036 | 8,493 |
| TQ | 253 | 0 | 0 | 61 | 0 | 192 | 0 | 0 | 0 |
| TX | 269,949 | 210 | 66,420 | 84,603 | 5,816 | 27,712 | 21,924 | 27,361 | 35,903 |
| UT | 16,146 | 337 | 2,233 | 6,385 | 831 | 3,339 | 859 | 402 | 1,760 |
| VA | 107,044 | 0 | 22,604 | 25,370 | 3,791 | 23,299 | 14,720 | 6,869 | 10,391 |
| VQ | 5,101 | 0 | 4,376 | 444 | 0 | 124 | 0 | 0 | 157 |
| VT | 10,493 | 0 | 2,013 | 3,646 | 268 | 3,045 | 292 | 279 | 950 |
| WA | 73,072 | 3,180 | 17,108 | 22,023 | 965 | 9,992 | 5,348 | 6,338 | 8,118 |
| WI | 82,538 | 2,268 | 13,904 | 20,267 | 890 | 25,610 | 6,278 | 3,509 | 9,812 |
| WV | 33,954 | 0 | 7,368 | 12,054 | 983 | 9,030 | 1,891 | 1,004 | 1,624 |
| WY | 6,172 | 564 | 695 | 1,489 | 181 | 2,489 | 452 | 224 | 78 |
