
Housing Vacancies and Homeownership (CPS/HVS)
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Annual Statistics: 2001

APPENDIX B. SOURCE AND ACCURACY OF ESTIMATES
REDESIGN OF THE CURRENT POPULATION SURVEY/Housing Vacancies and Homeownership
(CPS/HVS)

Major changes related to the Current Population Survey/Housing Vacancies and Homeownership
(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. Revised data are provided in the historical tables for 1993 to
show the effect of this change. Generally, the vacancy rates are only minimally affected, while
the homeownership rate is about one-half of a percentage point lower with the new weighting
procedures.

A second change is that the CPS/HVS has become 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 1994 and later data with earlier data.

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/Housing Vacancy
Survey (CPS/HVS). Characteristics of occupied housing units 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. Beginning in
April 1984, the current design was phased in through a series of changes that were completed in
July 1985. Prior to the redesign, sample cases were selected from the 1970 census frame.

The CPS/HVS sample is spread over 729 sample areas, which represent 1,973
geographic areas in the United States. The metropolitan/nonmetropolitan data shown in this
report reflect 1990 census definitions. The CPS/HVS began a major geographic redesign in
April 1994. The survey gradually replaced sample cases selected from the 1980 census over a
15-month phase-in period with new sample cases drawn from the 1990 census. The sample
was fully phased in by June 1995. For the transitional period (1995), we have converted the
remaining 1980 sample cases to reflect 1990 metropolitan/nonmetropolitan definitions.
For 1996 data and beyond, the data will reflect 1990 definitions.

In 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.

Of the 60,000 housing units both occupied and vacant contained in the CPS sample,
approximately 51,000 are occupied and eligible for interview each month; of this number,
3,200 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 51,000 occupied units, there are also about 9,000 sample units in an average
month which are visited but are found vacant or otherwise not to be interviewed. About half of
the 9,000 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 1990 census vacant counts.
A second adjustment inflates these results based on the CPS coverage of occupied units by
geographic areas.

Data shown in all tables (except table 2) on vacancy rates and tenure of occupied units
for 2001 are from the CPS and are averaged over the 12 months of the year. The data
concerning the distribution of characteristics for occupied housing units, shown in table 2, 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 1999 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
60,700 housing units both occupied and vacant contained in the AHS sample, 52,600 were
interviewed and 5,800 were classified as "noninterview" for various reasons. In addition, 2,300
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 1999.

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 Vacancies and Homeownership. 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, 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.
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
CPS/HVS appear in the 1985 and earlier reports of this series.

Prior to 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 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 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
nonsampling 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 decennial 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 has a homeowner vacancy rate of 1.7 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 CENSUS OF HOUSING DATA

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.

COMPARABILITY WITH EARLIER DATA

As stated earlier in this report, beginning in 1994 new weighting procedures based on
the 1990 decennial census were implemented. In addidition, the survey data collection
procedures became totally computerized. Caution should be used when comparing current data
with unrevised data prior to 1994.

In 1989, new edit procedures were implemented in the Current Population
Survey/Housing Vacancies and Homeownership (CPS/HVS). These new procedures were used to allocate
cases that would have been classified as "not reported" under previous procedures.

In 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 year-round vacant mobile
homes increases the vacancy rate significantly in some cases. All of the 1989 data in this report
have been updated to include year-round vacant mobile homes. Caution should be used when
comparing unrevised vacancy data prior to 1990 to data for later years.

In addition to the above mentioned design and estimation changes, caution should be
used in comparing data for 1980 and beyond in this report with data from 1979 and earlier
years. Starting in 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 (QHS) 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 1979 and previous
years, as published in Housing Vacancies reports, series H-111. Furthermore, unrevised data
prior to 1990 are not completely comparable to 1990 data and beyond, due to the inclusion of
year-round vacant mobile homes, beginning in 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.

The revised 1979 vacancy estimates are higher than the original 1979 estimates. The
increase in vacancy rates was not the result of locating additional vacant units, but reflects the
increase in sample size and refinements in the estimation procedure. It is safe to assume that
prior to the implementation of these new procedures (1955 through 1978) HVS produced
underestimates of vacant units. Earlier reports in this series give more complete descriptions of
the original CPS sample, the QHS sample, and estimation procedures.

CAUTION IN USING VACANCY RATES FOR CHARACTERISTICS
IN TABLE 2

Vacancy rates in table 2 are based in part on forecasts of occupied housing units. These
forecasts are periodically revised to incorporate more recent data and improved forecasting
procedures. For 2001 and 2000, data shown on table 2, these forecasts are based on the 1999
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 1987 has shown that estimates for these
characteristics have been underestimated by approximately 28 percent. The estimates
beginning in 1987 are adjusted to reflect this. This revision has an effect on other categories
(especially the percentage occupied) in addition to seasonal vacant units in the distributions
shown in tables 7.

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 nonsampling. The accuracy of a survey
result depends on both types of errors, but the full extent of the nonsampling 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 nonsampling 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.)

NONSAMPLING 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 given in the following 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 1.6 standard errors below the estimate to 1.6
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 MA's versus the vacancy rate outside MA's. 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 -1.6 and +1.6, 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 -1.6 or larger than +1.6, 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 1.6 times the standard error of the difference.

Comparisons of characteristics of vacancies for 1990 (which include year-round vacant
mobile homes as part of the year-round vacant inventory for the first time) with previous
unrevised years reveal significant differences in some cases. Thus caution should be used when
comparing current data with previous unrevised data prior to 1990.

ILLUSTRATION OF THE USE OF TABLES OF STANDARD ERRORS

Standard errors are used to: 1) measure the accuracy of the survey estimates, and 2)
draw inferences from the survey data. For example, Table B-1 of this report shows that the
percent of for-rent units outside MAs for 2000 is estimated to be 2.4 percent. Table B-1 also
shows the standard error of this estimate to be approximately 0.1 percentage points.
Consequently, the 90-percent confidence interval as shown by these data is from 2.2 to 2.6; i.e.,
the interval 2.4 +/- (1.6 x 0.1) percentage points. Thus, one can say with about 90-percent
confidence that the average percent of for-rent units derived from all possible samples is
included in this confidence interval. Statements about differences are made only when the 90-
percent confidence interval on the estimated difference does not include zero. The 90-percent
confidence intervals are shown in the text 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.

ILLUSTRATION OF THE COMPUTATION OF THE STANDARD ERROR OF A
DIFFERENCE

Table B-1 shows the rental vacancy rate for units in the South is 11.1 percent and 6.2 percent in the
West. Thus, the apparent difference between the two rates is 4.9 percent. The standard error of 11.1 percent
and the standard error of 6.2 percent are both 0.2 as shown in table B-1. Therefore, the standard error of the
estimated difference of 4.9 percent is about 0.3 percent.

----------------
|
0.3 = \|(0.2)2 + (0.2)2

Consequently, the 90 percent confidence interval for the 4.9 difference is from 4.4 to 5.4 percent; i.e., the
interval 4.9 + (1.6 x 0.3) percentage points. Thus, one can say with about 90 percent confidence that this
interval includes the actual value that would have been obtained by averaging the results from all possible
samples of this type. Thus, we can conclude with 90 percent confidence that the rental vacancy rate in the South
is higher than the rate in the West.

Go to Housing Vacancies and Homeownership Annual Statistics: 2001

Contact Bob Callis or Linda Cavanaugh at (301)763-3199 or visit ask.census.gov for further information on the Housing Vacancy Survey.

Source: U.S. Census Bureau, Housing and Household Economic Statistics Division

Last Revised: December 02, 2004

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