Methodology Changes in 2003

Population controls that reflect the results of the 2000 decennial census were used in the CPS/HVS 
estimation process for the first time in the first quarter 2003. This change had a slight effect 
on vacancy and homeownership rates, as described below. As a final additional step in the 
estimation process, the estimates were controlled to independent housing counts used for the first 
time in order to produce a more accurate estimate of housing units. This should make the CPS/HVS 
estimates of housing units more consistent with other Census Bureau housing surveys. The new 
housing controls affected the count of all housing units in the sense that both occupied and vacant 
units were ratio estimated to the new control total. Vacancy rates and homeownership rates were 
not affected by this change. The CPS/HVS began computing first-stage factors (used for weighting 
purposes) based on year-round and seasonal counts of housing units from the 2000 decennial census 
in the first quarter 2003. From 1980 to 2002, the CPS/HVS first-stage factors were based on 
year-round estimates only. We believe that this improves our counts of year-round and seasonal 
units. The shift from 1990-based to 2000-based population controls (including the weighting 
revision) had a very slight effect on vacancy rates and homeownership rates. Research has shown 
that the new 2000-based controls dropped the rental vacancy rate in the first quarter 2002 from 
9.14 percent to 9.08 percent---a difference of less than 1/10 of one percent. The homeowner 
vacancy rate was revised from 1.67 percent to 1.65 percent, while the homeownership rate was 
revised from 67.82 percent to 67.81 percent. The questions on race on the CPS were modified 
beginning in the first quarter 2003 to comply with the revised standards for federal statistical 
agencies. Respondents may now select more than one race. The Hispanic/Nonhispanic origin question 
continues to be asked separately.

INTRODUCTION OF COMPUTER ASSISTED SURVEY COLLECTION (CASIC) AND REWEIGHTING CURRENT POPULATION 
SURVEY/HOUSING VACANCY SURVEY (CPS/HVS) BASED ON THE 1990 CENSUS

Major changes related to the Current Population Survey/Housing Vacancy Survey (CPS/HVS) were 
effective beginning with the first quarter 1994 data. First, a new weighting procedure was 
implemented based on the 1990 decennial census. The 1990-based weighting produces, on average, 
estimates of the total housing inventory that were about 0.1 percent lower than the 1980-based 
weighting. Generally, the vacancy rates were only minimally affected, while the homeownership 
rate was about one-half of a percentage point lower with the new weighting procedures. A second 
change was that the CPS/HVS became a totally computerized survey with the implementation of the 
Computer Assisted Survey Information Collection (CASIC). The CASIC tools consist of 
state-of-the-art computer-assisted modules for data collection and processing. Although the 
concepts, definitions, and questionnaire items remain the same, the shift to CASIC may affect 
vacancy rates and homeownership rates. We were unable to determine the quantitative effects of 
the use of CASIC on the vacancy and homeownership rates. Data users should use caution when 
comparing data for 1994 and later with earlier data. Beginning the second quarter of 1999, a 
change was made in the way data for housing units in structure were collected. In the past, there 
was one category to show 1-unit in structure. That has been broken into two categories: 1-unit 
attached and 1-unit detached.
SOURCE OF DATA 

The estimates presented in this report were based on data obtained from two surveys conducted 
by the Bureau of the Census. Data concerning vacancy rates and tenure of occupied housing units 
were from the monthly sample of the Current Population Survey (CPS). Characteristics of occupied 
housing units in table 3 were from the American Housing Survey (AHS). 

CPS AND AHS DESIGNS

Since the inception of the CPS in 1940, the sample has been redesigned several times to upgrade 
the quality and reliability of the data and to meet changing data needs. From July 1995 to March 
2004, the CPS/HVS sample was selected from a frame based on the 1990 decennial census and was 
spread over 754 sample areas, which represent 2,007 geographic areas in the United States. 
Beginning in April 2004, the new sample drawn from Census 2000 was phased in over a 15-month 
period. From April 2004 to June 2005, the sample consisted of sample units drawn from both the 
1990 and 2000 decennial censuses. Beginning in July 2005, the sample consists only of housing 
units drawn from Census 2000, along with housing units built after April 1, 2000. This sample is 
spread over 824 sample areas and represents the 2,025 geographic areas of the United States that 
existed at the time of Census 2000. Beginning in the first quarter 1986, vacant seasonal mobile 
homes were included in the count of vacant seasonal units. This change resulted in a 12 percent 
increase in the number of vacant seasonal housing units. Beginning with the first quarter 2002 
Housing Vacancy Report, the size of the CPS/HVS sample increased to approximately 72,000 housing 
units. This expansion was one of the Census Bureau's plans to meet the requirements of the State 
Children's Health Insurance Program (SCHIP) legislation. Of the 72,000 housing units contained in 
the CPS/HVS sample, approximately 61,200 are eligible for interview each month; of this number, 
3,900 occupied units, on the average, are visited but interviews are not obtained because 
occupants are not found at home after repeated calls or are unavailable for some other reason. In 
addition to the 61,200, there are also about 10,800 sample units in an average month which are 
visited but are found to be vacant or otherwise not to be interviewed. About half of the 10,800 
are vacant and interviewed for the HVS. The CPS estimation procedure for occupied units involves 
the inflation of the weighted sample results to independent estimates of the total civilian 
noninstitutional population of the United States by age, race, sex, and Hispanic/non-Hispanic 
categories. These independent estimates were based on statistics from the decennial censuses of 
population; statistics on births, deaths, immigration, and emigration; and statistics on the 
strength of the Armed Forces. The HVS estimation procedure for vacant units is similar to that 
used for occupied units. Weighted sample results were adjusted at the state level using 2000 
census vacant counts. A second adjustment inflated these results based on the CPS coverage of 
occupied units by geographic areas. As a final step for both the CPS and HVS, all housing unit 
counts were adjusted to reflect independent housing control totals. This change was effective, 
beginning in the first quarter 2003. Data shown in all tables (except table 3) on vacancy rates 
and tenure of occupied units for the third quarter 2006 are from the CPS/HVS and are averaged 
for the three months, July, August, and September 2006. The data concerning the distribution of 
characteristics for occupied housing units, shown in table 3, were obtained primarily from the 
AHS national sample. Distributions of characteristics of occupied housing units from the AHS 
estimates were applied to CPS current housing inventory independent estimates to obtain the 
characteristics of occupied housing units used in this report. The Survey of Construction (SOC) 
and the Consumer Price Index also were used to improve estimates of the rent distribution. The 
2003 AHS sample was spread over 394 sample areas comprising 878 counties and independent cities 
with coverage in each of the 50 States and the District of Columbia. Of the 63,300 housing units 
both occupied and vacant contained in the AHS sample, 61,050 were interviewed and 5,650 were 
classified as "Type A noninterviews" for various reasons. 2,250 units were visited but were not 
eligible to be interviewed for the purposes of AHS. A detailed description of the AHS sample 
design and estimation procedure can be found in the H-150 report for 2003. 

COMPARABILITY WITH CENSUS OF HOUSING DATA 

Most of the concepts and definitions were the same for items that appear in both the 1980 and 1990 
censuses and the Housing Vacancy Survey. However, there was one minor difference in the housing 
unit definition between the CPS/HVS and the 1980 and 1990 decennial censuses. The difference was 
that, in the CPS/HVS prior to 1983, living arrangements containing five or more persons, not 
related to the person in charge, were classified as group quarters; for the 1980 and 1990 census, 
the requirement was raised to nine or more persons not related to the person in charge. For Census 
2000, the conversion requirement was eliminated. There were some differences in what has been 
counted as housing units between the earlier censuses and the CPS/HVS. Descriptions of the 
differences between earlier censuses and the HVS appear in the 1985 and earlier reports of this 
series. Prior to the first quarter 1990, there were significant differences between the CPS/HVS 
and the decennial censuses. The 1980 and 1990 decennial censuses included vacant mobile homes as 
housing units, whereas prior to 1986 the CPS/HVS did not. However, beginning in the first quarter 
1986, vacant seasonal mobile homes were counted as housing units in the CPS/HVS. In addition, 
year-round vacant mobile homes were counted as housing units, beginning in the first quarter 1990 
in the CPS/HVS. Another difference in the housing unit definition between the CPS/HVS (prior to 
1986) and the 1980 and 1990 censuses was that the CPS/HVS required units to be separate living 
quarters and have direct access or have complete kitchen facilities. For the 1980 and 1990 
decennial censuses, the complete kitchen facilities alternative was dropped with direct access 
required of all units. However, beginning in 1990, the CPS/HVS requirement for complete kitchen 
facilities was dropped with direct access required of all units. Thus, the earlier definitional 
differences were eliminated. In addition, there are differences between the methodologies used to 
collect data for the CPS/HVS and the censuses. These differences include interviewing procedures, 
staff experience and training; differences in processing procedures and sample designs; the 
sampling variability associated with the CPS/HVS and the sample data from the census; and the 
non-sampling errors associated with the CPS/HVS and census data. Research has shown that the 
CPS/HVS and the 1990 census produced significant differences for vacancy characteristics. The 
rental vacancy rate from the April 1990 census was 8.5 percent, whereas, the CPS/HVS reported 
the rental vacancy rate of 7.2 percent for the first half of 1990. The April 1990 census had a 
homeowner vacancy rate of 2.1 percent, while the CPS/HVS had a vacancy rate of approximately 1.7 
percent for the first half of 1990. For occupied housing, the April 1990 census produced a 
homeownership rate of 64.2 percent, while for the first half of 1990 the CPS/HVS produced a rate 
of 63.9 percent. These differences illustrate that, for these characteristics as well as others, 
caution should be used when making comparisons between the 1990 census and the CPS/HVS. Further 
research has shown that the CPS/HVS and the 2000 census produced significant differences for 
vacancy characteristics. The rental vacancy rate from the April 2000 census was 6.8 percent, 
whereas the CPS/HVS reported the rental vacancy rate of 7.9 percent for the first half of 2000. 
The April 2000 census had a homeowner vacancy rate of 1.7 percent, while the CPS/HVS had a 
vacancy rate of approximately 1.5 percent for the first half of 2000. For occupied housing, the 
April 2000 census produced a homeownership rate of 66.2 percent, while for the first half of 2000, 
the CPS/HVS produced a rate of 67.2 percent. These differences illustrate that, for these 
characteristics as well as others, caution should be used when making comparisons between the 2000 
census and the CPS/HVS. 

COMPARABILITY WITH EARLIER DATA 

As stated earlier in this report, beginning with the first quarter 1994 new weighting procedures 
based on the 1990 decennial census were implemented. In addition, the survey data collection 
procedures became totally computerized. Caution should be used when comparing current data with 
unrevised data prior to 1994. In the fourth quarter 1989, new edit procedures were implemented in 
the Current Population Survey/Housing Vacancy Survey (CPS/HVS). These new procedures were used to 
allocate cases that would have been classified as "not reported" under previous procedures. In the 
first quarter 1990, year-round vacant mobile homes were included for the first time as part of the 
year-round vacant count of housing units. This change was made to make the composition of the 
housing unit inventory for the CPS/HVS similar to the decennial census and other surveys, which 
count all mobile homes as housing units when occupied or vacant (available for occupancy on the 
site). Research has shown that the inclusion of vacant mobile homes increased the vacancy rate 
significantly in some cases. We have revised 1989 data in this report to reflect all changes. 
Caution should be used when comparing data from 1990 or later with unrevised data prior to 1990. 
In addition to the design and estimation changes mentioned in the previous section, caution should 
be used in comparing data for 1980 and beyond in this report with data from 1979 and earlier years. 
Starting with the first quarter 1980, several changes were implemented in the survey to improve the 
reliability of the data presented. These included adding a supplemental sample, refining the 
estimation procedures, and changing the source of occupied characteristics from the Quarterly 
Housing Survey to the AHS. Although the above mentioned changes resulted in more reliable estimates, 
data for 1980 and later in this report are not completely comparable to data for the fourth quarter 
1979 and previous quarters, as published in Housing Vacancies reports, series H-111, Nos. 1 to 79-Q4. 
Furthermore, unrevised data prior to 1990 were not completely comparable to 1990 data and beyond, 
due to the inclusion of year-round vacant mobile homes, beginning in the first quarter 1990. Thus, 
particular caution should be observed in drawing conclusions about trends that extend from before 
1980 to 1980 and beyond, and also trends from before 1990 to 1990 and later. For comparative 
purposes, 1979 data in this report were revised to incorporate all changes made in 1980, and 1989 
data were revised to incorporate all changes made in 1990. Unrevised 1989 and 1979 data are 
provided to show the magnitude of the various changes. 

VACANCY RATES FOR CHARACTERISTICS IN TABLE 3 

Vacancy rates in table 3 are based in part on forecasts of occupied housing units. These forecasts 
are periodically revised to incorporate more recent data and improved forecasting procedures. 
Beginning in the first quarter 2003, table 3 is based on data from the 2001 AHS. Beginning in 2005, 
first quarter 2004 data is based on data from the 2003 AHS.

For the occupied unit forecasts for the monthly rent categories, we update the AHS data quarterly 
to reflect the rise in the cost of renting through the use of the residential rent index, and the 
latest available asking rent data for newly constructed rental units.

CAUTION IN USING SEASONAL VACANT DATA 

Analysis of seasonal vacant data prior to the first quarter 1987 has shown that estimates for these 
characteristics have been underestimated by approximately 28 percent. The estimates beginning with 
the first quarter 1987 were adjusted to reflect this.

ACCURACY OF THE ESTIMATES 

Since the CPS/HVS estimates are based on a sample, they may differ somewhat from the figures that 
would have been obtained if a complete census had been taken using the same questionnaires, 
instructions, and enumerators. There are two types of errors possible in an estimate based on a 
sample survey: sampling and non-sampling. The accuracy of a survey result depends on both types of 
errors, but the full extent of the non-sampling error is unknown. Consequently, particular care 
should be exercised in the interpretation of figures based on a relatively small number of cases or 
on small differences between estimates. The standard errors provided for the CPS/HVS estimates 
primarily indicate the magnitude of the sampling error. They also partially measure the effect of 
some non-sampling errors in responses and enumeration; but do not measure any systematic biases in 
the data. (Bias is the difference averaged over all possible samples, between the estimate and the 
desired value.) 

NON-SAMPLING VARIABILITY 

Nonsampling errors can be attributed to many sources, e.g., inability to obtain information about 
all cases in the sample, definitional difficulties, differences in the interpretation of questions, 
inability or unwillingness on the part of respondents to provide correct information, inability to 
recall information, errors made in collection such as recording or coding the data, errors made in 
processing the data, errors made in estimating values for missing data, and failure to represent 
all units with the sample (undercoverage). Undercoverage in the CPS/HVS results from missed housing 
units and misclassifying housing units. Ratio estimation to independent controls, as described 
previously, partially corrects for the bias due to survey undercoverage. However, biases exist in 
the estimates to the extent that missed households have different characteristics than interviewed 
households.

SAMPLING VARIABILITY 

The standard errors shown in the tables are primarily measures of sampling variability, that is, 
of the variations that occurred by chance because a sample rather than the entire population was 
surveyed. The sample estimate and its standard error enable one to construct confidence intervals; 
ranges that would include the average results of all possible samples with a known probability. 
For example, if all possible samples were selected, each of these being surveyed under essentially 
the same general conditions and using the same sample design, and if an estimate and its standard 
error were calculated from each sample, then approximately 90-percent of the intervals from 1.645 
standard errors below the estimate to 1.645 standard errors above the estimate would include the 
average result of all possible samples. The average estimate derived from all possible samples is 
or is not contained in any particular computed interval. However, for a particular sample, one can 
say with specified confidence that the average estimate derived from all possible samples is 
included in the confidence interval. Standard errors may also be used to perform hypothesis testing, 
a procedure for distinguishing between population parameters using sample estimates. The most 
common types of hypotheses appearing in this report are: (1) the population parameters are 
identical, and, (2) the population parameters are different. An example of this would be comparing 
the vacancy rate in MAs versus the vacancy rate outside MAs. Tests may be performed at various
levels of significance, where a level of significance is the probability of concluding that the 
characteristics are different when, in fact, they are identical. To perform the most common test, 
let x and y be sample estimates for two characteristics of interest. Let the standard error on the 
difference x-y be SEDIFF. If the ratio R = (x-y)/SEDIFF is between -1.645 and +1.645, no conclusion 
about the difference between the characteristics is justified at the 0.10 level of significance. If, 
on the other hand, this ratio is smaller than -1.645 or larger than +1.645, the observed difference 
is significant at the 0.10 level. In this event, it is a commonly accepted practice to say that the 
characteristics are different. Of course, sometimes this conclusion will be wrong. When the 
characteristics are, in fact, the same, there is a 10 percent chance of concluding that they are 
different. All statements of comparison in the text have passed a hypothesis test at the 0.10 level 
of significance or better. This means that, for most differences cited in the text, the absolute 
value of the estimated difference between characteristics is greater than or equal to 1.645 times 
the estimated standard error of the difference. Comparisons of characteristics of the vacancies for 
the first quarter 1990, (which include year-round vacant mobile homes as part of the year-round 
vacant housing inventory for the first time) with previous unrevised quarters revealed significant 
differences in some cases. Thus caution should be used when comparing current data with unrevised 
data prior to 1990.

ILLUSTRATION OF THE USE OF TABLES OF STANDARD ERRORS 

The sample estimate and its standard error enable one to construct a confidence interval. A 
confidence interval is a measure of an estimate's variability. The larger a confidence interval 
is in relation to the size of the estimate, the less reliable the estimate. For example, the 
estimated percent of all housing units vacant and available for rent is 3.0 percent (Table 10) and 
the standard error on the estimate is 0.1 percentage points (Table A-1). Then the 90-percent 
confidence interval is calculated as 3.0 percent + (1.645 x 0.1), or 3.0 percent + 0.2, or from 
2.8 percent to 3.2 percent. If all possible samples were surveyed under essentially the same 
general conditions and the same sample design, and if an estimate and its standard error were 
calculated from each sample, then approximately 90 percent of the intervals from 1.645 standard 
errors below the estimate to1.645 standard errors above the estimate would include the average 
result of all possible samples. 

Standard errors are also used to perform hypothesis testing--a procedure for distinguishing 
between population parameters (whose values are not known) using sample estimates. The most 
common type of hypothesis is that two population parameters are different. These tests may be 
performed at various significance levels. The significance level is the probability of concluding 
that the parameters are different when, in fact, they are the same. For example, to conclude that 
two parameters are different at the 0.10 level of significance, the absolute value of the 
difference between their corresponding sample estimates must be greater than or equal to1.645 
times the estimated standard error of the difference.

The Census Bureau uses 90-percent confidence intervals and 0.10 levels of significance to 
determine statistical validity. The 90-percent confidence intervals are shown in the text 
or in the tables for selected items. The standard errors for other figures in this report are 
given in the tables. In addition to sampling error, the figures in this report, both the 
estimates and their standard errors, are also subject to rounding error. 

Table A-1.  Standard Errors of Percentages in Tables 10 and 11:  Third Quarter 2006




                                             Vacant for-rent units as a
                                             percent of all housing units


                                                                    Standard
Area                                          Standard    Differ-   error on
                                      Rate      error     ence\1   difference


United States.....................       3.0        0.1        (z)        0.1
 Inside Metropolitan 
Statistical Area..................       3.2        0.1        (z)        0.1
 Outside Metropolitan 
Statistical Area..................       2.1        0.2       -0.3        0.2

 Northeast........................       2.6        0.2        0.6        0.2
 Midwest..........................       3.5        0.2       -0.2        0.2
 South............................       3.4        0.2          -        0.2
 West.............................       2.2        0.2       -0.4        0.2



                                             Vacant for-sale-only units as a
                                             percent of all housing units

                                                                    Standard
Area                                          Standard    Differ-   error on
                                      Rate      error     ence\1   difference


United States.....................       1.5        0.1        0.3        0.1
 Inside Metropolitan 
Statistical Areas.................       1.6        0.1        0.4        0.1
 Outside Metropolitan 
Statistical Areas.................       1.4        0.1        0.2        0.1

 Northeast........................       1.0        0.1         0.2       0.1
 Midwest..........................       1.8        0.1         0.2       0.1
 South............................       1.7        0.1         0.4       0.1
 West.............................       1.3        0.1         0.5       0.1

(z) Less than 0.05.       - Represents zero.
\1 Represents difference in third quarter 2006 and third quarter 2005 rates.
  NOTE:  Metropolitan Statistical Area data for 2005 and later are not comparable to 
earlier data.  Beginning in first quarter 2005, the Current Population Survey/Housing 
Vacancy Survey is using the new metropolitan and micropolitan statisitcal definitions 
which were announced by the Office of Management and Budget (OMB) in June 2003, and were 
based on the application of the 2000 standards to Census 2000 data.  OMB announced updates 
as of December 2003, based on application of the 2000 standards to more recent Census
Bureau estimates.  In this report, outside Metropolitan Statistical Areas includes micropolitan 
and non-metropolitan statistical areas.  The December 2003 definitions are available at:
http://www.census.gov/population/www/estimates/metrodef.html and
http://www.census.gov/population/www/estimates/aboutmetro.html.