<b>SOURCE AND ACCURACY OF ESTIMATES</b>

<b>REDESIGN OF THE CURRENT POPULATION SURVEY/Housing Vacancies and Homeownership (CPS/HVS)</b>

     Major changes related to the Current Population Survey/Housing
Vacancy Survey (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.

     Beginning the third 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.


<b>SOURCE OF DATA</b> 
 
     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). 


<b>CPS AND AHS DESIGNS</b> 
 
     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 1999 are from the CPS/HVS and are
averaged for the 3 months, October, November, and December, 1999.  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.  



<b>COMPARABILITY WITH CENSUS OF HOUSING DATA</b> 

     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. 


<b>COMPARABILITY WITH EARLIER DATA</b> 
 
     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.  


<b>VACANCY RATES FOR CHARACTERISTICS IN TABLE 3</b> 
 
     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 1997
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.  


<b>CAUTION IN USING SEASONAL VACANT DATA</b> 

     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.  


<b>ACCURACY OF THE ESTIMATES</b> 
 
     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.) 




<b>NON-SAMPLING VARIABILITY</b> 
 
     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.  


<b>SAMPLING VARIABILITY</b> 
 
     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.
 
<b>ILLUSTRATION OF THE USE OF TABLES OF STANDARD ERRORS</b> 
 
     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 <u>+</u> (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. 


Table A-1.  Standard Errors of Percentages in Tables 10 and 11:  Fourth Quarter




                                  Vacant for-rent units as a 
                                  percent of all housing units


                                                         Standard
Area                               Standard    Differ-   error on
                           Rate      error     ence\1   difference


United States..........       2.6        0.1        (z)        0.1
  Inside MAs...........       2.7        0.1        (z)        0.1
  Outside MAs..........       2.1        0.1         -         0.2

 Northeast.............       1.9        0.1       -0.3        0.2 
 Midwest...............       2.5        0.1        0.2        0.2
 South.................       3.1        0.1        0.2        0.2
 West..................       2.3        0.1       -0.2        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..........       1.0        (z)       -0.1        0.1
  Inside MAs...........       0.9        (z)       -0.1        0.1
  Outside MAs..........       1.3        0.1        0.1        0.1

 Northeast.............       0.9        0.1        0.2        0.1
 Midwest...............       0.7        0.1       -0.3        0.1
 South.................       1.2        0.1       -0.1        0.1
 West..................       1.0        0.1        (z)        0.1

Z Less than 0.05.  - Represents zero.
\1 Represents difference in fourth quarter 1999 and fourth quarter 1998 rates.