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 second quarter 2006 are from the CPS/HVS and are averaged 
for the three months, April, May, and June 2006. 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 First 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 First 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 
to 1.645 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:  Second 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.....................       2.9        0.1       -0.1        0.1
 Inside Metropolitan Statistical Areas.. 3.1        0.1       -0.1        0.1
 Outside Metropolitan Statistical Areas. 2.2        0.2         -         0.2

 Northeast........................       2.3        0.1        0.2        0.2
 Midwest..........................       3.6        0.2        0.1        0.2
 South............................       3.2        0.2       -0.2        0.2
 West.............................       2.3        0.2       -0.3        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.....................       1.4        (z)         0.3       0.1
 Inside Metropolitan Statistical Areas.. 1.4        0.1         0.3       0.1
 Outside Metropolitan Statistical Areas. 1.2        0.1         0.1       0.1

 Northeast........................       1.0        0.1         0.2       0.1
 Midwest..........................       1.5        0.1         0.2       0.1
 South............................       1.6        0.1         0.3       0.1
 West.............................       1.2        0.1         0.4       0.1

(z) Less than 0.05.       - Represents zero.
\1 Represents difference in second quarter 2006 and second 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 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.