Methodology Changes in 2003

Population controls that reflect the results of the 2000 decennial census are used in the CPS/HVS 
estimation process for the first time in the first quarter 2003. This change has a slight effect 
on vacancy and homeownership rates, as described below. As a final additional step in our 
estimation process, the estimates are now 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 will affect the count of all housing units in the sense that both occupied 
and vacant units will be ratio estimated to the new control total. Vacancy rates and homeownership 
rates are 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 are 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 are 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 is 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 are 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 are collected. In the past, there 
was one category to show 1-unit in structure. Now that has been broken into two categories: 
1-unit attached and 1-unit detached.

SOURCE OF DATA 

The estimates presented in this report are based on data obtained from two surveys conducted by 
the Bureau of the Census. Data concerning vacancy rates and tenure of occupied housing units are 
from the monthly sample of the Current Population Survey (CPS). Characteristics of occupied 
housing units in table 3 are 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 is selected from a frame based on the 1990 decennial census and is 
spread over 754 sample areas, which represent 2,007 geographic areas in the United States. 
Beginning in April 2004, the new sample drawn from the 2000 decennial census is phased in over a 
15-month period. From April 2004 to June 2005, the sample will consist of sample units drawn from 
both the 1990 and 2000 decennial censuses. 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 are 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 are adjusted at the state level 
using 2000 census vacant counts. A second adjustment inflates 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 are adjusted to reflect independent housing control totals. This change is 
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 fourth quarter 2005 are from the CPS/HVS and 
are averaged for the three months, October, November, and December 2005. The data concerning the 
distribution of characteristics for occupied housing units, shown in table 3, are obtained 
primarily from the AHS national sample. Distributions of characteristics of occupied housing units 
from the AHS estimates are 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 are used to improve estimates of the rent 
distribution. The 2001 AHS sample is 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 
55,800 housing units both occupied and vacant contained in the AHS sample, 48,300 were interviewed 
and 5,400 were classified as "Type A noninterviews" for various reasons. 2,100 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 2001. 

COMPARABILITY WITH CENSUS OF HOUSING DATA 

Most of the concepts and definitions are the same for items that appear in both the 1980 and 
1990 censuses and the Housing Vacancy Survey. However, there is one minor difference in the 
housing unit definition between the CPS/HVS and the 1980 and 1990 decennial censuses. The 
difference is 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 have 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 is 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 have 
been revised to incorporate all changes made in 1980, and 1989 data have been 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.

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 are 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 estimated difference between characteristics is greater than 1.645 times 
the 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 reveal 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 2.9 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 2.9 percent +/- (1.645 x 0.1), or 2.9 percent +/- 0.2, or 
from 2.7 percent to 3.1 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:  Fourth Quarter 2005




                                             Vacant for-rent units as a
                                             percent of all housing units


                                                                    Standard
Area                                          Standard    Differ-   error on
                                      Rate      error     ence\1   difference


United States.....................        2.9        0.1         NA         NA
 Inside Core-Based Statistical Area       3.0        0.1         NA         NA
Outside Core-Based Statistical Area       2.4        0.2         NA         NA

 Northeast........................        2.2        0.1        (z)        0.2
 Midwest..........................        3.4        0.2        0.1        0.2
 South............................        3.2        0.2       -0.3        0.2
 West.............................        2.4        0.2       -0.1        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.....................        1.3        (z)         NA         NA
 Inside Core-Based Statistical Area       1.2        0.1         NA         NA
Outside Core-Based Statistical Area       1.3        0.1         NA         NA

 Northeast........................        0.9        0.1         0.3       0.1
 Midwest..........................        1.6        0.1         0.1       0.1
 South............................        1.4        0.1         0.1       0.1
 West.............................        1.0        0.1         0.1       0.1

(z) Less than 0.05. - Represents zero.
\1 Represents difference in fourth quarter 2005 and fourth quarter 2004 rates.
  NA Not available.  Core-Based 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.  The December 2003 
definitions are available at http://www.census.gov/population/www/estimates/metrodef.html.