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) are
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 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 data for 1994 and later
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 (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.  Beginning in April 1994, the current
design was phased in through a series of changes that were completed in July 1995.  

     The CPS/HVS sample is selected from a frame based on the 1990 census and is spread over 754
sample areas, which represent 2,007 geographic areas in the United States.  Due to the new sample drawn
from the 1990 census, metropolitan/nonmetropolitan data published in 1995 and later are not directly
comparable to data for 1994 and earlier.

     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.  
     Of the 60,000 housing units both occupied and vacant contained in the CPS sample, approximately
51,000 are 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, there are also about 9,000 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 9,000 are vacant and interviewed for 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 3) on vacancy rates and tenure of occupied units for the fourth
quarter 1997 are from the CPS/HVS and are averaged for the 3 months, October, November, and December
1997.  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 1995 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 59,500 housing units both
occupied and vacant contained in the AHS sample, 51,700 were interviewed and 4,200 were classified as
"noninterview" for various reasons.  In addition, 3,600 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 1995.  


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 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.  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. 


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 addidition, 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 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 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
third quarter 1997, table 3 is based on data from the 1995 AHS.  The 1996 data shown in table 3 have been
revised to reflect this change.

     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 1.6 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 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 -1.6 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 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 
 
     Standard errors are used to: 1) measure the accuracy of the survey estimates, and 2) draw inferences
from the survey data.  For example, Table 10 of this report shows that 2.6 percent of all housing units are
vacant and available for rent.  Table A-1 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 2.4 to
2.8; i.e., the interval 2.6 + (1.6 x 0.1) percentage points.  Thus, one can say with about 90-percent confidence
that the average rental vacancy rate 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.