A Picture of Subsidized Households File Sizes and Technical Comments

* Before printing, please set your printer to 'landscape' format, since some tables below are quite wide.

	Records	Bytes	Records	Bytes
	Projects		Census Tracts
Total	55,349	13,283,760	124,992	29,998,080
US	52	12,480	0	0
AK	428	102,720	299	71,760
AL	1,448	347,520	2,089	501,360
AR	844	202,560	1,354	324,960
AZ	689	165,360	1,700	408,000
CA	3,293	790,320	12,192	2,926,080
CO	701	168,240	2,129	510,960
CT	788	189,120	1,881	451,440
DC	229	54,960	192	46,080
DE	144	34,560	313	75,120
FL	1,450	348,000	5,406	1,297,440
GA	1,787	428,880	2,420	580,800
GQ	21	5,040	0	0
HI	185	44,400	685	164,400
IA	652	156,480	1,598	383,520
ID	287	68,880	540	129,600
IL	2,221	533,040	4,641	1,113,840
IN	999	239,760	2,542	610,080
KS	802	192,480	1,340	321,600
KY	1,228	294,720	2,099	503,760
LA	1,098	263,520	2,005	481,200
MA	1,434	344,160	3,583	859,920
MD	900	216,000	1,842	442,080
ME	537	128,880	960	230,400
MI	1,755	421,200	4,578	1,098,720
MN	1,468	352,320	2,614	627,360
MO	1,825	438,000	2,926	702,240
MS	792	190,080	1,012	242,880
MT	417	100,080	581	139,440
NC	2,096	503,040	3,006	721,440
ND	388	93,120	476	114,240
NE	700	168,000	852	204,480
NH	311	74,640	670	160,800
NJ	1,148	275,520	4,611	1,106,640
NM	648	155,520	826	198,240
NV	283	67,920	642	154,080
NY	2,446	587,040	10,594	2,542,560
OH	2,449	587,760	4,948	1,187,520
OK	1,173	281,520	2,221	533,040
OR	749	179,760	1,556	373,440
PA	2,535	608,400	6,226	1,494,240
RI	400	96,000	601	144,240
RQ	710	170,400	0	0
SC	791	189,840	1,768	424,320
SD	591	141,840	381	91,440
TN	1,578	378,720	2,596	623,040
TQ	14	3,360	0	0
TX	3,139	753,360	9,330	2,239,200
UT	285	68,400	854	204,960
VA	918	220,320	2,479	594,960
VQ	52	12,480	0	0
VT	241	57,840	415	99,600
WA	1,123	269,520	2,324	557,760
WI	1,529	366,960	2,772	665,280
WV	430	103,200	1,052	252,480
WY	148	35,520	271	65,040

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

	Total	% Lack Geography	% Lack Tenant Data	Total	% Lack Geography	% Lack Tenant Data
	Housing Agency Records			Project Records
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
1. 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
2. Created list of which Section 8 agency numbers have been converted to, or are controlled by others (primarily state agencies)
3. 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
4. Converted agency names to all capitals, project names to Initial Capitals, and flagged Indian rental projects.
Geographic Files on Projects
1. Extracted Census tract summary statistics, converted to percent, & stored them in a small file.
2. 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.
3. 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
1. Extracted program identifiers & allowances for each household & sorted by SSN
2. Summarized income & household composition for each household & sorted by SSN
3. Extracted rent calculation data for households in different sub-programs into a common format & sorted by SSN
4. 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
5. 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
6. 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.
7. 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
1. 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
2. Summarized the extracted data for each combination of FHA number & Section 8 number
3. 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
1. 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.
2. 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.
3. 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

	Raw data		Binary extract		Control file of Public & Indian		Raw data (in control file)		Binary extract		Summaries of Tracs		Summaries of Certificates+Vouchers		Raw data		Extract		Merge Program
	HUD Form 951						Office of Housing						Summaries of Certificates+Vouchers		LIHTC				Merge Program
	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	Indian Housing	Public Housing	S.8 New + Substantial Rehab	S.236	Other Subsidy	Housing Tax Credit	Certificates + Vouchers	Totals of All Programs
	Total	Agency+Other Summary Records	Project Records						Tract Records
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