Nonforeign Area Cost-of-Living Allowance; General Population Rental Equivalence Survey Report, 43228-43249 [06-6568]
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Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices
United States Free Trade Agreement
(‘‘the CAFTA–DR’’). Chapter 9 of the
CAFTA–DR sets forth certain
obligations with respect to government
procurement of goods and services, as
specified in Annex 9.1.2(b)(i) of the
CAFTA–DR. On August 2, 2005, the
President signed into law the
Dominican Republic-Central AmericaUnited States Free Trade Agreement
Implementation Act (‘‘the CAFTA–DR
Act’’) (Pub. L. 109–53, 119 Stat. 462) (19
U.S.C. 4001 note). In section 101(a) of
the CAFTA–DR Act, the Congress
approved the CAFTA–DR. The CAFTA–
DR entered into force on July 1, 2006,
for Guatemala.
Section 1–201 of Executive Order
12260 of December 31, 1980 (46 FR
1653) delegates the functions of the
President under Sections 301 and 302 of
the Trade Agreements Act of 1979 (‘‘the
Trade Agreements Act’’) (19 U.S.C.
2511, 2512) to the United States Trade
Representative.
Now, therefore, I, Susan C. Schwab,
United States Trade Representative, in
conformity with the provisions of
Sections 301 and 302 of the Trade
Agreements Act, and Executive Order
12260, and in order to carry out U.S.
obligations under Chapter 9 of the
CAFTA–DR, do hereby determine that:
1. Guatemala is a country, other than
a major industrialized country, which,
pursuant to the CAFTA–DR, will
provide appropriate reciprocal
competitive government procurement
opportunities to United States products
and suppliers of such products. In
accordance with Section 301(b)(3) of the
Trade Agreements Act, Guatemala is so
designated for purposes of Section
301(a) of the Trade Agreements Act.
2. With respect to eligible products of
Guatemala (i.e., goods and services
covered by the Schedules of the United
States in Annex 9.1.2(b)(i) of the
CAFTA–DR) and suppliers of such
products, the application of any law,
regulation, procedure, or practice
regarding government procurement that
would, if applied to such products and
suppliers, result in treatment less
favorable than accorded—
(A) to United States products and
suppliers of such products; or
(B) to eligible products of another
foreign country or instrumentality
which is a party to the Agreement on
Government Procurement referred to in
section 101(d)(17) of the Uruguay
Round Agreements Act (19 U.S.C.
3511(d)(17)) and suppliers of such
products, shall be waived.
With respect to Guatemala, this
waiver shall be applied by all entities
listed in the Schedule of the United
States to Section A of Annex 9.1.2(b)(i)
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and in List A of Section C of Annex
9.1.2(b)(i) of the CAFTA–DR.
3. The designation in paragraph 1 and
the waiver in paragraph 2 are subject to
modification or withdrawal by the
United States Trade Representative.
Dated: July 25, 2006.
Susan C. Schwab,
United States Trade Representative.
[FR Doc. E6–12222 Filed 7–28–06; 8:45 am]
BILLING CODE 3190–W6–P
OFFICE OF PERSONNEL
MANAGEMENT
Nonforeign Area Cost-of-Living
Allowance; General Population Rental
Equivalence Survey Report
Office of Personnel
Management.
ACTION: Notice.
AGENCY:
SUMMARY: This notice publishes the
‘‘Nonforeign Area General Population
Rental Equivalence Survey Report.’’ The
General Population Rental Equivalence
Survey (GPRES) was a special research
project in which the Office of Personnel
Management (OPM) collected data on
homeowner estimates of the rental value
of their homes and market rents in the
nonforeign area cost-of-living allowance
(COLA) areas and in the Washington,
DC area. OPM conducted GPRES to
determine whether rental survey data
collected in the COLA surveys should
be adjusted to account for homeowner
shelter costs. Based on the GPRES
results, OPM has determined that no
adjustment is appropriate. OPM is
publishing this report to inform
interested parties of the research results
and provide an opportunity for
comment.
Comments on this report must be
received on or before September 29,
2006.
DATES:
Send or deliver comments
to Jerome D. Mikowicz, Acting Deputy
Associate Director for Pay and
Performance Policy, Strategic Human
Resources Policy Division, Office of
Personnel Management, Room 7H31,
1900 E Street NW., Washington, DC
20415–8200; fax: (202) 606–4264; or email: COLA@opm.gov.
FOR FURTHER INFORMATION CONTACT:
Donald L. Paquin, (202) 606–2838; fax:
(202) 606–4264; or e-mail:
COLA@opm.gov.
ADDRESSES:
The Office
of Personnel Management (OPM)
conducted the General Population
Rental Equivalence Survey (GPRES) to
determine whether OPM should adjust
SUPPLEMENTARY INFORMATION:
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the rent indexes it computes from data
collected in the nonforeign area cost-ofliving allowance (COLA) surveys. The
Federal Government pays COLAs to
certain white collar Federal and U.S.
Postal Service employees in Alaska,
Hawaii, Guam and the Northern
Mariana Islands, Puerto Rico, and the
U.S. Virgin Islands. As provided by
subpart B of title 5, Code of Federal
Regulations, OPM conducts living-cost
surveys to set COLA rates.
One of the items OPM surveys during
the COLA surveys is market rents for
detached houses, duplexes and
triplexes, town and row houses, and
apartments. We use rental data to
estimate the relative price of shelter for
both homeowners and renters between
the COLA areas and the Washington, DC
area. (For an example, see the 2004
Pacific COLA survey report published at
70 FR 44989–45023.) As applied to
homeowners, this approach is called
‘‘rental equivalence’’ because it
estimates the shelter value of owned
homes rather than surveying
homeowner costs directly.
OPM adopted the rental equivalence
approach pursuant to the settlement in
Caraballo, et al. v. United States, No.
1997–0027 (D.V.I), August 17, 2000. The
settlement provides for several
significant changes in the COLA
methodology, including the use of rental
equivalence. The settlement also
established the Survey Implementation
Committee (SIC), composed of seven
plaintiffs’ representatives and two OPM
representatives, and the Technical
Advisory Committee (TAC), composed
of three economists with expertise in
living-cost analysis. The TAC advises
the SIC and OPM on living-cost issues.
The SIC and the TAC agreed OPM could
use, on an interim basis, market rents
collected in the COLA surveys to
estimate homeowner costs. The TAC
noted, however, that the relative price of
shelter for homeowners could differ
compared with the relative price of
market rents between the COLA areas
and the DC area. If this were the case,
it would be appropriate for OPM to
adjust COLA survey market rent indexes
before applying them to homeowners.
Therefore, OPM conducted a special
research project, i.e., GPRES, to collect
information on market rents and
homeowner estimates of the rental value
of their homes in the COLA areas and
in the Washington, DC area. The SIC
and the TAC were involved heavily in
the design of the survey, and the TAC
analyzed the survey results. The TAC
also compared GPRES results with the
results of the 1998 Federal Employee
Housing and Living Patterns Survey
(FEHLPS), which Joel Popkin and
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Company conducted as part of the
research leading to the Caraballo
settlement.
Using the GPRES results, the TAC
found that no adjustment to the COLA
survey market rents was appropriate
because there were no statistically
significant differences between
homeowner estimated rents and market
rents in the COLA areas compared with
the DC area. The TAC found essentially
the same results using FEHLPS.
Therefore, the TAC recommended no
rental equivalence adjustment be made.
However, the TAC noted some
differences between GPRES results and
FEHLPS results and speculated these
differences could reflect trends in
relative rent prices/rental price
estimates. Therefore, the TAC
recommended OPM consider
conducting additional GPRES-type
surveys if OPM were to adopt a rental
equivalence adjustment. Because OPM
agrees that no rental equivalence
adjustment is warranted, we do not plan
to conduct additional GPRES-type
surveys at this time.
Office of Personnel Management.
Linda M. Springer,
Director.
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Nonforeign Area General Population
Rental Equivalence Survey Report
TABLE OF CONTENTS
1. Introduction.
2. Purpose of GPRES.
2.1 Rental Equivalence and Rents.
2.2 Caraballo Settlement and Rental
Equivalence.
3. Planning GPRES.
3.1 Consultation with the SIC and TAC.
3.2 Survey Instrument, Sampling
Methodology, and Sample Size.
4. Conducting the Survey.
4.1 Survey Period.
4.2 Efforts To Ensure Quality Participation.
4.3 Survey Complications.
4.3.1 Home Size.
4.3.2 Prevalence of Subsidized Housing in
Some Areas.
5. Survey Results and Response Rates.
5.1 GPRES Survey Results and Response
Rates.
5.2. FEHLPS Survey Results and Response
Rates.
6. Survey Analyses
6.1 Homeowner Factors: Comparison of
Owner Rent Estimates and Market Rents.
6.2 Regional Comparisons.
6.3 COLA Survey Area Comparisons.
7. Summary and Conclusions.
List of Appendices
A. GPRES Survey Questionnaire.
B. GPRES Sample Size.
C. GPRES Data Collection Guidelines.
D. GPRES Number of Responses and
Response Rates.
E. FEHLPS Samples Size, Responses, and
Response Rates.
F. FEHLPS Survey Questionnaire—Housing
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Portion.
G. GPRES SAS Regression Results—Regional
Analyses.
H. FEHLPS SAS Regression Results—
Regional Analyses.
I. GPRES SAS Regression Results—Survey
Area Analyses.
J. FEHLPS SAS Regression Results—Survey
Area Analyses.
1. Introduction
This report provides the results of the
General Population Rental Equivalence
Survey (GPRES), which Westat,
Incorporated, conducted for OPM in the
winter of 2004/2005. In addition, the
report provides for comparison
purposes the results of the 1998 Federal
Employee Housing and Living Patterns
Survey (FEHLPS), which Joel Popkin
and Company conducted for plaintiffs’
representatives and Government
representatives who were working
collaboratively to resolve long-contested
issues in the nonforeign area cost-ofliving allowance (COLA) program. The
collaborative work lead to the
settlement of Caraballo, et al. v. United
States, No. 1997–0027 (D.V.I.), August
17, 2000, and to major changes in the
nonforeign area cost-of-living allowance
(COLA) program. Therefore, although
this report is principally about GPRES,
it also covers the FEHLPS as it applies
to rental equivalence analyses.
The report describes how OPM
planned and prepared for the conduct of
GPRES. In planning the survey, OPM
consulted closely with the Survey
Implementation Committee (SIC) and
the Technical Advisory Committee
(TAC), both established pursuant to the
Caraballo settlement. The SIC has seven
members—five plaintiffs’
representatives from the COLA areas
and two OPM representatives. The TAC
has three members—economists who
have expertise in living-cost
measurement. The TAC performs
research for and advises the members of
the SIC.
The purpose of GPRES was two-fold.
First, it was to determine whether there
are statistically significant ‘‘homeowner
factors’’ (HFs) that reflect the difference
between homeowners’ estimates of the
rental value of their homes compared
with market rents, holding rental unit
characteristics constant. (The HF is the
estimated rental value of owned homes
divided by the market rent for homes of
equivalent observed quality and
quantity.) Second, GPRES was to
determine whether HFs varied between
the COLA areas and the Washington, DC
area to a statistically significant degree.
If so, OPM could use the results to
adjust the market rents it collects during
the COLA surveys to reflect homeowner
shelter costs.
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FEHLPS was used to look at the same
two questions. The purpose of FEHLPS
was to collect a wide range of
information on Federal employees—
much more than housing data. However,
among the data FEHLPS collected were
homeowner estimates of the rental value
of their homes, so it was possible to use
the survey to compute HFs and to
examine whether these varied to a
statistically significant degree between
the COLA areas and the Washington, DC
area. The scope of FEHLPS was more
limited than GPRES. It had
approximately a third fewer housing
observations and was limited to Federal
employees—a subset of the general
population.
Comparing GPRES and FEHLPS
results was very informative. This report
describes those comparisons and why,
based on the results and comparisons,
no adjustment to rental indexes to
account for homeowner shelter costs
appears warranted at this time.
2. Purpose of GPRES
2.1 Rental Equivalence and Rents
There are two commonly accepted
approaches for measuring the shelter
value of owned homes. One is the usercost approach. The other is rental
equivalence. In simplistic terms, user
costs are the costs of owning and
maintaining a home minus the annual
discounted expected capital gains that
the owner will realize when he or she
sells the home. Rental equivalence is
what an owned home would rent for if
it were available for rent in the rental
market.
Rental equivalence is a well-known
approach and is used by the Bureau of
Labor Statistics (BLS) in the
computation of the Consumer Price
Index. Instead of measuring the change
in owner user costs, which tend to be
volatile, BLS attributes the change in
market rents to homeowner shelter
costs. This approach is supported by
research that BLS conducted in the
1990’s. Economists advising the
plaintiffs’ and Government
representatives prior to the Caraballo
settlement recommended that OPM
adopt a similar approach for the COLA
program, and the Caraballo settlement
and OPM regulations adopted pursuant
to the settlement prescribe that OPM use
a rental equivalence approach to
estimate the ‘‘price’’ of homeowner
shelter.
Economic theory suggests that
homeowners’’ estimates of the rental
value of their homes will on average be
higher than market rents for housing
with equivalent observed characteristics
(i.e., of equivalent observed quantity
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and quality). (See Akerlof, George A.,
1970. ‘‘The Market for ‘Lemons’: Quality
Uncertainty and the Market
Mechanism,’’ The Quarterly Journal of
Economics, MIT Press, vol. 84(3), pages
488–500.) Imperfect market knowledge
on the part of potential renters’ and
homeowners’ awareness of unobserved
amenities of their homes cause owner
rent estimates to be higher than market
rents. In other words, the HF should be
greater than one. The size of the HF,
however, could vary between one or
more COLA areas and the Washington,
DC area if owned homes in some areas
have more unobserved amenities than
owned homes in other areas.
Other factors could also affect owner
rent estimates of the rental value of their
homes, such as the owner’s limited
knowledge of local rental markets.
Although some owners might have an
excellent knowledge of rental markets
and the rental value of their homes,
most owners have little reason to pay
much attention to the rental market, and
their estimates might well be less
accurate. In fact, GPRES results suggest
that homeowners often relied on their
mortgage payments to estimate the
rental value of their homes, and
mortgage payments are not necessarily
correlated with market rents.
Although homeowner estimates may
be somewhat inaccurate, the expectation
is that the inaccurate estimates would
be distributed normally in any area—
some too high and some too low. Once
again, it is possible that the effect might
not be constant across all areas. Owners
might overestimate in areas where home
values are rising rapidly, even though
market rents were trailing. On the other
hand, owners might estimate more
accurately in areas with a higher
proportion of transient population
because owners might have a greater
opportunity to acquire rental market
knowledge if homes near to them
become available for rent. Variation in
the accuracy of owner estimates among
areas would make it difficult to compare
differences between owner estimates
and market rents from one area to the
next.
Another factor that might lead to
inaccurate homeowner estimates could
be the pride of ownership. It is
conceivable that home owners
systematically might estimate high
rental values because the owners take
pride in their homes and think they
should be worth more, regardless of any
unobserved amenities. This could
further contribute to the ‘‘noise’’ in the
survey—i.e., undermine the survey’s
ability to reflect higher owner shelter
values attributable to unobserved
amenities. Whether the effect of this
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‘‘pride factor’’ might vary among areas
is speculative.
GPRES was designed to collect
information that could be used to
compare homeowner estimated rents
with market rents. It also obtained
information on many of the
characteristics and amenities of the
respondents’ homes to allow the
comparison of estimated rents and
market rents while holding observed
quality and quantity constant.
2.2 Caraballo Settlement and Rental
Equivalence
As stated in the previous section,
pursuant to the Caraballo settlement
OPM adopted a rental equivalence
approach to measure the shelter value of
owner-occupied housing. Appendix A
of the stipulation for settlement
provides 26 ‘‘Safe Harbor Principles’’
(SHPs) concerning the operation of the
COLA program. One of the key
principles, SHP–18, describes how OPM
will measure the relative cost of shelter:
18. Hedonic Housing Model and Rental
Equivalence: Shelter price relatives will be
estimated for owners and renters from the
triennial regional sample. The sample for the
region will be pooled with the comparison
sample from the base area and price relatives
for the COLA areas will be estimated using
hedonic regression models to adjust for
quality differences.
Discussion: OPM will adopt a rentalequivalence approach to estimate shelter
costs and a hedonic regression approach to
compare housing of similar quality. To
identify the living communities to be
surveyed, OPM will use the results of the
1992/93 employees survey, JPC’s [Joel Popkin
and Company] survey, and/or other
appropriate information. How the housing
data will be collected is not known or
stipulated. OPM may survey Federal
employees, collect the data on its own or
through a contractor, enter into an
interagency agreement with another Federal
agency (e.g., the Department of Interior), or
use some other appropriate approach.
OPM adopted this principle when it
published final regulations at 67 FR
22339. Section 591.219 of title 5, Code
of Federal Regulations, prescribes how
OPM will compute shelter price indexes
based on rental and rental equivalence
prices and/or estimates. As noted in
Section 2.1, rental equivalence
compares the shelter value (rental value)
of owned homes rather than total owner
costs because the latter are influenced
by capital gains (i.e., the investment
value of a home). Most living-cost
surveys do not compare how consumers
invest their money.
In the COLA surveys, OPM surveys
market rents in each of the COLA areas
and in the Washington, DC area,
obtaining over 80 characteristics of the
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rental units for use in the hedonic
regression equations. (A hedonic
regression is a statistical technique,
specifically a form of multiple linear
regression. For an explanation of how
OPM applies these regressions, see
‘‘2004 Nonforeign Area Cost-of-Living
Allowance Survey Report: Pacific and
Washington, DC Areas,’’ published at 70
FR 44989.) The SIC and the TAC agreed
that OPM could use market rents as an
estimate for rental equivalence until the
issue of rental equivalence could be
explored more fully through a GPREStype survey.
GPRES explored two questions. The
first question was whether the rental
value of owned homes in the COLA and
DC areas differed to a statistically
significant degree from market rents in
the same area holding observed quality
and quantity constant. To do this, the
TAC computed homeowner factors, as
described in Section 6.1. The second
question was whether the COLA area
homeowner factors differed to a
statistically significant degree compared
with the DC area homeowner factor. If
the homeowner factors were
significantly different, it might be
appropriate for OPM to make a rental
equivalence adjustment to account for
homeowner shelter costs. As it turned
out, no adjustment was appropriate
because we did not find statistically
significant differences between the
COLA and DC areas.
3. Planning GPRES
3.1 Consultation With the SIC and
TAC
OPM worked closely with the SIC and
TAC to plan and develop GPRES. In
August 2001, OPM provided the SIC
and TAC with a rough draft of a survey
questionnaire that could be used with
homeowners and renters to obtain and
compare information about estimated
rental values and market rents. The SIC
and TAC subsequently met on several
occasions to refine the questionnaire
and begin planning GPRES. The goal
was to design a survey that was
sufficiently brief as to encourage renters
and owners to participate but
sufficiently detailed so that OPM could
compare market rents and rental
equivalence estimates for comparable
housing. By early 2002, the SIC and
TAC had developed such a
questionnaire. Later that year, at the
request of the SIC and TAC, the
Caraballo trustee entered into a contract
with Joel Popkin and Company (JPC) to
review draft plans for GPRES, review
current literature regarding rental
equivalence, and to make
recommendations to the SIC and TAC
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concerning GPRES. JPC’s research
emphasized the importance of
conducting GPRES. The SIC and TAC
reviewed JPC’s findings, incorporated
them as appropriate in the survey, and
recommended that OPM proceed with
the conduct of GPRES. This OPM did.
OPM continued to consult with the
SIC and TAC as it finalized plans for
GPRES and kept them apprised during
the conduct of GPRES. The TAC
analyzed GPRES results, and OPM and
the TAC discussed those results with
the SIC.
3.2 Survey Instrument, Sampling
Methodology, and Sample Size
In the fall of 2002, OPM contracted
with Westat, Inc., a statistical research
firm, to review JPC’s research, propose
a survey methodology, develop a survey
instrument, and recommend sample
sizes and sampling strategies for GPRES.
In terms of a survey methodology,
Westat recommended the use of
Computer Assisted Telephone
Interviews (CATIs). This approach
appeared to offer the probability of
greater response rates at reasonable cost
compared with other approaches, such
as mail-out questionnaires. Appendix A
shows the GPRES questionnaire that
Westat developed as modified by OPM.
To develop sample sizes, Westat used
the results of FEHLPS and OPM’s 2002
Caribbean and DC area COLA rental
survey, applying standard sample size
calculations. (See Cochran, W.G.,
Sampling Techniques: third edition,
New York: John Wiley & Sons, Inc.,
1977) Westat used FEHLPS to estimate
the standard deviation of homeowner
estimated rents for each COLA area and
the Washington, DC area. Westat also
used the results of the survey to
estimate the standard deviation of
market rents by area, except for the
Caribbean and DC areas. For these areas,
Westat used the results of the 2002
COLA survey because that survey had
more observations and covered the
general population, not just Federal
employees. From the surveys, Westat
developed sample sizes for owner and
renters for the COLA areas and the
Washington, DC area. Westat developed
two sets each for owners and renters.
One set was the sample size necessary
for estimating rent or rental equivalence
within a margin of error of +/¥ $500 in
annual rent with 90 percent confidence
level, and the other was the sample size
for estimating rent or rental equivalence
at the same margin of error at the 95
percent confidence level. Subsequent to
the 2003 Alaska COLA survey, OPM
modified the renter sample sizes for the
Alaska and DC areas based on the
additional rental data that OPM had
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collected in these areas. Appendix B
shows the sample sizes Westat
recommended, as modified by OPM.
Within each area, OPM limited the
geographic scope of GPRES to the zip
code areas in which OPM collected
rental data in the annual COLA surveys.
In the Washington, DC area, OPM
further allocated the sample among the
District of Columbia and the Counties of
Montgomery, MD; Prince Georges, MD;
Arlington, VA; Fairfax, VA; and Prince
William, VA; and the independent cities
therein, based on the relative numbers
of owners and renters within these areas
as reflected by the 2000 Census.
OPM obtained approval for GPRES
from the Office of Management and
Budget (OMB) as required by 5 CFR Part
1320, and OMB assigned GPRES an
information collection number. Federal
surveys and other information
collections that Federal agencies
conduct are covered by the Paperwork
Reduction Act (44 U.S.C. 3501 et seq.).
Participation in GPRES was voluntary,
and any identifying information
regarding the respondents is protected
under the Privacy Act (5 U.S.C. 552a)
and the Freedom of Information Act (5
U.S.C. 552).
4. Conducting the Survey
4.1 Survey Period
In the fall of 2004, OPM awarded a
second contract to Westat to conduct
GPRES. Using CATI, Westat began
collecting data in October 2004 and
finished in March 2005. Although
Westat started data collection in some
areas before others, Westat essentially
collected data in all of the areas
throughout this entire time period.
Westat provided OPM with interim
deliverables throughout the survey so
that OPM and the TAC could begin
testing analyses prior to receiving the
final deliverable. Westat provided the
final deliverable in early April 2005.
4.2 Efforts to Ensure Quality
Participation
Westat used commercially available
lists of phone numbers and addresses of
owners and renters for the Washington,
DC area and all of the COLA areas,
except Guam, Puerto Rico, and the U.S.
Virgin Islands for which such lists were
unavailable. Using the sampling strategy
described in Section 3.2, Westat drew
the sample using commercial data bases
where available. Westat then mailed
letters to the prospective respondents
informing them of the survey and asking
for their cooperation. The letter was
prepared by OPM on OPM letterhead
and signed by Donald J. Winstead, who
at that time was OPM’s Deputy
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Associate Director for Pay and
Performance Policy, Strategic Human
Resources Policy Division. For those
areas where commercial mailing/phone
lists were unavailable, Westat was
unable to mail advance letters; and
Westat used simple random sampling to
select potential participants.
At the beginning of each telephone
interview, Westat surveyors explained
the purpose of the survey, that the
survey was voluntary, and provided the
respondent the OMB-provided
information collection number. Westat
made certain that the respondent was a
knowledgeable adult who could answer
questions relating to the housing unit. If
the adult was not available, Westat
made arrangements to call back at a
more convenient time to conduct the
interview. The complete interview took
approximately 8 minutes.
It was critically important that GPRES
collect accurate information from
persons who either owned their own
homes or rented homes at current
market rents. To this end, some GPRES
questions were designed to eliminate
respondents who did not meet these
criteria. For example, Westat
discontinued the survey if the
respondent lived in rent-subsidized or
rent-controlled housing, occupied
military housing, or rented from
relatives or other persons at rates other
than market rates. Likewise, Westat
discontinued the survey if the
respondent was renting a room in a
home or was living in a mobile home or
similar lodging.
In addition, OPM identified for
Westat several ‘‘threshold’’ questions
that were critical to the survey and
instructed Westat to discontinue the
survey if the respondent could not or
would not answer these questions. For
example, if the respondent did not
know or refused to answer how many
bathrooms or bedrooms were in the
home, Westat was instructed to
discontinue the survey. The
questionnaire in Appendix A shows the
threshold questions. They are identified
by the interview instruction ‘‘GO TO
END.’’ Similarly, OPM provided Westat
with guidelines to help ensure that
respondents did not provide frivolous
responses or occupied housing so
atypical as to be outside the scope of the
survey. Appendix C shows the
Guidelines that Westat used to help
identify frivolous and highly atypical
responses.
4.3 Survey Complications
Westat encountered two unexpected
complications in conducting GPRES.
One involved the respondent’s lack of
knowledge concerning home size. The
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other involved an unexpectedly high
proportion of the population in certain
areas residing in subsidized or rentcontrolled housing.
4.3.1
Home Size
One problem that Westat encountered
was that respondents often did not
know and could not estimate or guess
the number of square feet in their home.
As shown in Appendix A, OPM had
identified this as a critical threshold
question; and as shown in Appendix C,
OPM provided guidelines concerning
acceptable data. Westat noted that
invalidating these responses was
increasing the non-response rate and the
cost of the survey. Westat suggested that
OPM reconsider whether home size
should be a threshold question and/or
subject to the guidelines.
OPM discussed the issue with the
TAC. The TAC was not surprised and
noted that BLS, the Bureau of the
Census, and other housing surveys
encountered the same problem and
dropped home size as a question in their
surveys. The TAC suggested that OPM
use room count and a limited number of
other characteristics to impute home
size for respondents who were
unknowledgeable or provided atypical
responses. OPM tested this approach
using the rental data it had collected in
the COLA surveys and found it feasible.
Therefore, OPM informed Westat to
continue survey interviews even when
respondents did not know and could
not estimate home size and instructed
Westat not to apply guidelines to flag
atypical responses. OPM and the TAC
later tested whether to use imputed
home sizes but decided against it
because the imputation process had a
systematic error in estimating the size of
relatively small and relatively large
homes.
sroberts on PROD1PC70 with NOTICES
4.3.2 Prevalence of Subsidized
Housing in Some Areas
Westat also discovered difficulties
obtaining the desired sample of renters
in certain areas because an
unexpectedly large portion of the renter
population appear to occupy subsidized
or rent-controlled housing. This was
most noticeable in Guam, Puerto Rico,
and the U.S. Virgin Islands (USVI), as
well as in the District of Columbia.
Under the contract, OPM paid Westat on
a price-per-completed-survey-response
basis. When Westat began encountering
unexpectedly high respondent
invalidation rates, Westat informed
OPM that it would not be able to
provide the desired sample sizes in
certain areas because the company had
reached the breakeven point at which
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further data collection would not be
profitable.
Therefore, OPM modified the price
schedule in the contract to ensure that
Westat could obtain at least the
‘‘minimum’’ sample size shown in
Appendix B in all areas. As shown in
Appendix D, Westat exceeded this level
in several areas, but it was unable to
obtain the minimum number of renter
samples in Guam and Puerto Rico.
5. Survey Results and Response Rates
5.1 GPRES Survey Results and
Response Rates
Appendix D shows the number of
renter and owner observations that
Westat obtained by area. Except in
Guam and Puerto Rico, Westat obtained
a sample that equaled or exceeded the
sample size necessary for estimating
rent or rental equivalence within a
margin of error of +/-$500 in annual rent
with a 90 percent confidence level. In
all, Westat obtained 6,170 observations.
To do this, Westat made more than
152,000 phone calls. Therefore, one
simplistic measure of the response rate
might be 4 percent (i.e., 6,170 divided
by 152,000). Many of those calls,
however, particularly in the areas for
which commercial phone list data as
described in Section 4.2 were
unavailable, were screening calls to
businesses, facsimile machines, and
other non-residential phone numbers.
Also, many of the residential
respondents (e.g., those occupying rentcontrolled or subsidized housing) were
not eligible to be part of the survey
universe. Therefore, another and
perhaps more meaningful way to look at
the response rate is to compare the
number of respondents with the total
number of those who were determined,
after the screening questions, to be part
of the survey universe. According to
Westat, a total of 23,662 respondents
passed the screening questions. Using
this as a basis, the response rate was
26.1 percent (i.e., 6,170 divided by
23,662). This does not, however,
include respondents who become
ineligible in the ‘‘extended interview,’’
i.e., the main part of the interview that
followed the screening questions.
Taking this into consideration, the
overall GPRES response rate according
to Westat was 28 percent. Appendix D
shows this type of response rate for each
COLA area and the for Washington, DC
area.
5.2 FEHLPS Survey Results and
Response Rates
JPC conducted FEHLPS in
cooperation with OPM in 1998. It was
a survey of a sample of non-U.S. Postal
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Service Federal employees in the COLA
areas and in the Washington, DC area.
JPC selected a sample size of
approximately 15,800, of which 11,478
were to be drawn from the COLA areas
and 4,324 were to come from the
Washington, DC area. The sample was
drawn from OPM’s Central Personnel
Data File (CPDF), which is essentially a
census of non-Postal Federal employees.
According to the CPDF, there were
approximately 44,027 non-Postal
Federal employees in 1998 in the COLA
areas and 258,304 in the DC area.
JPC collected 5,662 responses from
the COLA areas, which makes the
average response rate for those areas
49.3 percent. JPC collected 1,081
responses from the Washington, DC
area, which makes the DC area response
rate 25 percent. Appendix E shows the
FEHLPS sample sizes, responses, and
response rates by COLA area and for the
Washington, DC area. Not all of the
respondents provided usable housing
data. Therefore, the TAC could use only
4,275 FEHLPS observations in its
analyses.
The survey was a ‘‘mail out’’ survey,
delivered to employees at their
worksite. Agencies were encouraged to
grant employees time at work to
complete the survey. FEHLPS covered
numerous topics, including
transportation and travel, K–12 private
education, college education, medical
costs, and housing. Appendix F shows
the housing related portion of the
survey.
6. Survey Analyses
The TAC performed most of the
analyses of the GPRES results, with
OPM’s support and oversight. OPM also
contracted with JPC to review the
GPRES results and analyses. JPC
concurred with the TAC’s analyses,
findings, and recommendations.
6.1 Homeowner Factors: Comparison
of Owner Rent Estimates and Market
Rents
As discussed in Section 2, one
purpose for conducting GPRES was to
compare owner estimates of the rental
value of their homes with market rents
for comparable housing in terms of
quality and quantity. The goal was to
express mathematically the relationship
of rents and rent estimates within each
COLA area and the Washington, DC
area. The second purpose was to
examine whether those relationships
varied significantly between the COLA
areas and the Washington, DC area.
The TAC computed homeowner
factors (HFs) to express the relationship
of homeowner rent estimates and
market rents in and among the COLA
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areas and the Washington, DC area. The
HF is the estimated rental value of
owned homes divided by the market
rent for homes of equivalent observed
quality and quantity. To compute the
HF, the TAC used hedonic regressions
to hold quality and quantity constant.
The TAC used two distinctly different
approaches to analyze HFs. One
approach involved comparing HFs by
COLA region with the DC area HF. The
other involved estimating HFs for each
COLA survey area and comparing these
with the DC area HF. The results of the
two approaches were quite different but
lead to the same conclusion.
6.2. Regional Comparisons
The COLA areas are divided into
three regions—the Alaska, Pacific, and
Caribbean regions. The Alaska region is
composed of the Anchorage, Fairbanks,
and Juneau COLA survey areas. The
Pacific region is composed of the
Honolulu County; Hilo and Kailua
Kona, Hawaii County; Kauai County;
Maui County; and Guam COLA survey
areas. The Caribbean region is
composed of the Puerto Rico; St. Croix,
USVI, and St. Thomas/St. John, USVI,
COLA survey areas.
The TAC noted that there were
virtually no previous studies to serve as
a guide on how to analyze HFs by area
and compare them between areas. The
TAC believed if there were systematic
differences in HFs across areas, the TAC
would need as many observations as
possible to identify these relationships.
Pooling the data by region allowed the
use of all of the survey observations
(GPRES or FEHLPS) at one time.
The TAC applied semi-logarithmic
hedonic regressions to compute rental
equivalence indexes and market rent
indexes for the COLA regions relative to
the Washington, DC area, holding
quantity and quality of housing
constant. The dependent variable of the
regression was the logarithm of rent.
Appendix G shows the SAS GPRES
regression results that the TAC used.
(SAS is a proprietary statistical analysis
computer software package.) The
independent variables for the GPRES
regression are listed below:
Type of dwelling (e.g., detached house,
townhouse, apartment),
Whether the unit had central air
conditioning,
Number of baths,
Number of bedrooms,
Number of baths crossed with type of
dwelling, and
Tenure (i.e., owned or rented) by the
COLA region or DC area in which unit
is located.
The parameter of interest in this
regression was tenure by COLA region
and the results are shown in the table
below. The HF is shown in column (1).
(The logarithmic form of the HFs and
standard errors and t values are shown
in columns (2) through (4).) An HF of
1.223 for Alaska means that homeowner
estimates of the rental value of their
homes are on average 22.3 percent
higher than market rents holding
observed quality and quantity of the
housing unit characteristics constant.
The critical values of ‘‘t’’ at the 5
percent and 1 percent levels are 1.96
and 2.58 respectively. In other words,
HFs with t-values equal to or greater
than 2.58 are significant at a 99 percent
confidence level or higher.
TABLE 1.—GPRES HOMEOWNER FACTORS BY REGION
HF
Alaska ................................................................................................................................
Pacific ................................................................................................................................
Caribbean ..........................................................................................................................
Washington, DC Area ........................................................................................................
The TAC also computed homeowner
factors on a regional basis using the
results of FEHLPS. Again, the
dependent variable was the log of rent,
Logarithmic HF
Standard
error
t-value
(1)
COLA region
(2)
(3)
(4)
1.223
1.171
1.117
1.153
but the independent variables were
somewhat different than those used in
the GPRES analyses. Appendix H shows
the TAC’s regression results using the
0.201
0.158
0.111
0.142
0.027
0.018
0.023
0.031
7.50
8.74
4.94
4.62
FEHLPS data. The homeowner factors
are shown in Table 2, below:
TABLE 2.—FEHLPS HOMEOWNER FACTORS BY REGION
HF
sroberts on PROD1PC70 with NOTICES
Alaska ................................................................................................................................
Pacific ................................................................................................................................
Caribbean ..........................................................................................................................
Washington, DC Area ........................................................................................................
The HFs from both surveys are
statistically significant and greater than
1 when the results are analyzed on a
regional basis. HFs greater than one is
what economic theory would predict.
The key question is whether there are
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Logarithmic HF
Standard
error
t-value
(1)
COLA region
(2)
(3)
(4)
1.274
1.092
1.168
1.254
statistically significant differences
between the HFs for the COLA regions
compared with the DC area HF. To do
this, the TAC again used a t-test where
the standard error is the difference
between HFs calculated from a
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0.242
0.088
0.155
0.226
0.0301
0.0195
0.0326
0.0479
8.03
4.49
4.75
4.71
covariance matrix of the regression
coefficients on owners and renters.
Tables 3 and 4 below show the results
for GPRES and FEHLPS respectively.
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TABLE 3.—GPRES TEST OF DIFFERENCE BETWEEN REGIONAL HFS AND DC AREA HF
COLA region HF
divided by DC
Logarithmic COLA
region HF
Standard
error
t-value
(1)
COLA region
(2)
(3)
(4)
0.0375
0.0328
0.0353
1.58
0.49
¥0.85
Alaska ............................................................................................................
Pacific ............................................................................................................
Caribbean ......................................................................................................
1.061
1.016
0.970
0.0595
0.0161
¥0.0301
TABLE 4.—FEHLPS TEST OF DIFFERENCE BETWEEN REGIONAL HFS AND DC AREA HF
COLA region HF
divided by DC
Area HF
COLA region
Alaska ............................................................................................................
Pacific ............................................................................................................
Caribbean ......................................................................................................
As shown in Table 3, the TAC found,
based on the GPRES results, the
differences between the COLA region
HFs and the DC area HF were not
statistically significant. Similarly, as
shown in Table 4, the TAC found, based
on the FEHLPS results, there was no
statistically significant difference
between the COLA region HFs and the
DC area HF. Therefore, no adjustment to
the COLA survey rental index was
appropriate to account for homeowner
shelter values (rental equivalence).
Although analyses of both surveys
found no statistically significant
differences between the COLA and DC
area HFs, the TAC also noted the
significant differences between the
GPRES results compared with the
FEHLPS results. For example, GPRES
showed the Pacific region HF was
Logarithmic COLA
region HF ¥DC
Area HF
1.016
0.871
0.932
slightly higher than the DC area HF, but
FEHLPS show the Pacific region HF to
be somewhat lower than the DC area
HF. Unless Federal employees were
atypical of the general population with
regard to market rents and homeowner
estimates, it appeared that the HFs
changed substantially over the 6-year
interval between FEHLPS and GPRES.
The TAC found the apparent lack of
stability over time troubling.
6.3 COLA Survey Area Comparisons
The second approach the TAC used to
analyze GPRES and FEHLPS results was
to compute HFs by COLA survey area
and compare these with the DC HF. The
advantage of this approach was more
consistency with the COLA program,
which sets COLA rates by COLA area,
not COLA region. It also allowed the
0.0161
¥0.1379
¥0.0705
Standard
error
0.0548
0.0500
0.0560
t-value
0.29
¥2.76
¥1.26
HFs to be computed separately for each
area, using different equations as
appropriate. The disadvantage was that
each regression used far less data than
in the regional analyses.
To compute HFs for each of the COLA
survey areas, the TAC pooled the survey
data by region and computed HFs for
each of the COLA survey areas within
the region. Appendix I has an example
of the SAS regression results for one of
the survey areas—the Pacific region—
using GPRES. Appendix J has an
example of the SAS regression results
for one of the survey areas—the
Caribbean region—using FEHLPS. Table
5 shows the HFs by area and their
relationship to the DC HF using GPRES.
Table 6 shows the same results using
FEHLPS.
TABLE 5.—GPRES HFS BY COLA SURVEY AREA
HF
sroberts on PROD1PC70 with NOTICES
Anchorage ..........................................................................................................................
Fairbanks ...........................................................................................................................
Juneau ...............................................................................................................................
Honolulu .............................................................................................................................
Hilo .....................................................................................................................................
Kailua Kona .......................................................................................................................
Kauai ..................................................................................................................................
Maui ...................................................................................................................................
Guam .................................................................................................................................
Puerto Rico ........................................................................................................................
St. Croix .............................................................................................................................
St. Thomas/St. John ..........................................................................................................
DC Area .............................................................................................................................
Unlike the COLA region analyses, the
GPRES results in Table 5 show that the
HFs are less than 1 in half of the COLA
survey areas. This is contrary to what
economic theory would predict. In
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Logarithmic HF
Standard
error
t ratio
(1)
Survey area
(2)
(3)
(4)
1.025
0.958
0.935
1.061
0.986
0.957
0.930
1.013
0.997
1.002
1.141
1.124
1.110
0.0250
¥0.0434
¥0.0667
0.0588
¥0.0141
¥0.0440
¥0.0728
0.0134
¥0.0030
0.0018
0.1321
0.1166
0.1040
0.0354
0.0416
0.0392
0.0321
0.0499
0.0546
0.0396
0.0355
0.0351
0.0495
0.0395
0.0442
0.0415
0.70
¥1.04
¥1.70
1.81
¥0.28
¥0.81
¥1.84
0.38
¥0.09
0.04
3.35
2.64
2.51
addition, 10 of the 13 COLA survey area
HFs are not statistically significant at a
95 percent confidence level. By
comparison, the results using FEHLPS
are quite different. (See Table 6.) All of
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the HFs are greater than 1, which
conforms with economic theory, and
only four of the HFs are not significant
at a 95 percent confidence level.
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TABLE 6.—FEHLPS HFS BY COLA SURVEY AREA
HF
Anchorage ..........................................................................................................................
Fairbanks ...........................................................................................................................
Juneau ...............................................................................................................................
Honolulu .............................................................................................................................
Hawaii County ....................................................................................................................
Kauai ..................................................................................................................................
Maui ...................................................................................................................................
Guam .................................................................................................................................
Puerto Rico ........................................................................................................................
St. Croix .............................................................................................................................
St. Thomas/St. John ..........................................................................................................
DC Area .............................................................................................................................
As with the regional analysis, the key
question is whether the COLA survey
area HFs are statistically significantly
different from the DC area HF. The TAC
used the same approach it used to
produce Tables 3 and 4 in the region
analyses. As shown in Table 7, the
GPRES results indicate that the HFs in
the COLA survey areas are lower than
the DC area HF except in the USVI. The
Logarithmic HF
Standard
error
t ratio
(1)
Survey area
(2)
(3)
(4)
1.278
1.011
1.222
1.120
1.011
1.083
1.176
1.168
1.208
1.045
1.468
1.279
t-ratios, however, show that these
results are not significant at the 95
percent confidence level in 8 out of 12
cases. (Keep in mind that 10 of the 13
HFs were not statistically significant at
that level, which further weakens the
statistical validity of the comparison.).
Table 8, which shows the FEHLPS
results, also shows that the COLA
survey area HFs are lower than the DC
0.2451
0.0106
0.2006
0.1130
0.0108
0.0798
0.1618
0.1549
0.1888
0.0440
0.3842
0.2461
0.0397
0.0623
0.0707
0.0240
0.0424
0.0587
0.0495
0.0488
0.0497
0.0784
0.0839
0.0450
6.17
0.17
2.84
4.71
0.25
1.36
3.27
3.17
3.80
0.56
4.58
5.46
area HF, except in St. Thomas/St. John,
USVI. (Note: Unlike GPRES, it was not
possible using FEHLPS data to split
Hawaii County into the Hilo and Kailua
Kona survey areas.) In addition, the
FEHLPS differences are not statistically
significant at a 95 percent confidence
level in 7 out of 13 areas.
TABLE 7.—GPRES TEST OF DIFFERENCE BETWEEN SURVEY AREA HFS AND DC AREA HF
COLA area HF divided by DC area
HF
Logarithmic COLA
area HF¥ DC
area HF
t ratio
(1)
Survey area
(2)
(3)
Anchorage ..............................................................................................................................
Fairbanks ...............................................................................................................................
Juneau ...................................................................................................................................
Honolulu .................................................................................................................................
Hilo .........................................................................................................................................
Kailua Kona ...........................................................................................................................
Kauai ......................................................................................................................................
Maui .......................................................................................................................................
Guam .....................................................................................................................................
Puerto Rico ............................................................................................................................
St. Croix .................................................................................................................................
St. Thomas/St. John ..............................................................................................................
DC Area .................................................................................................................................
0.924
0.863
0.843
0.956
0.889
0.862
0.838
0.913
0.899
0.903
1.028
1.013
1.000
¥0.0790
¥0.1474
¥0.1707
¥0.0452
¥0.1181
¥0.1480
¥0.1768
¥0.0906
¥0.1070
¥0.1022
0.0281
0.0126
0.0
¥1.45
¥2.51
¥2.99
¥0.86
¥1.82
¥2.16
¥3.09
¥1.66
¥1.97
¥1.58
0.49
0.21
TABLE 8.—FEHLPS TEST OF DIFFERENCE BETWEEN SURVEY AREA HFS AND DC AREA HF
COLA area HF
divided by DC
area HF
sroberts on PROD1PC70 with NOTICES
Logarithmic COLA
area HF¥DC
Area HF
t ratio
(1)
Survey area
(2)
(5)
Anchorage ..............................................................................................................................
Fairbanks ...............................................................................................................................
Juneau ...................................................................................................................................
Honolulu .................................................................................................................................
Hawaii County ........................................................................................................................
Kauai ......................................................................................................................................
Maui .......................................................................................................................................
Guam .....................................................................................................................................
Puerto Rico ............................................................................................................................
St. Croix .................................................................................................................................
St. Thomas/St. John ..............................................................................................................
DC Area .................................................................................................................................
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0.999
0.790
0.956
0.875
0.790
0.847
0.919
0.913
0.944
0.817
1.148
1.000
31JYN1
¥0.0010
¥0.2355
¥0.0455
¥0.1331
¥0.2353
¥0.1663
¥0.0843
¥0.0912
¥0.0573
¥0.2021
0.1381
0.0
¥0.02
¥3.06
¥0.54
¥2.61
¥3.80
¥2.25
¥1.26
¥1.37
¥0.85
¥2.23
1.45
..................
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As with the regional analyses, the
TAC found troubling the significant
differences between the GPRES and
FEHLPS results. Once again, the
question was whether there were trends
over the 6-year period between the
surveys that could explain these
differences or the differences were
simply inherent in the populations
surveyed and/or survey techniques
used. The TAC recommended that OPM
not implement any adjustments to the
rental data based on the COLA survey
area analyses without first conducting
additional GPRES-like surveys.
7. Summary and Conclusions
OPM conducted GPRES to determine
whether OPM should adjust rental data
that it collects during its annual COLA
surveys. In these annual surveys, OPM
collects prices on market rents on
various types of housing units. OPM
uses rental data to estimate the relative
price of shelter for both homeowners
and renters between the COLA areas
and the Washington, DC area.
The TAC analyzed the GPRES results
and compared them with similar
analyses using rental data and estimates
from an earlier survey of Federal
employees—FEHLPS. Using regression
analyses, the TAC computed
homeowner estimated rent and market
rent indexes and from these computed
homeowner factors (HFs), which were
homeowner indexes divided by the
market rent indexes for units of
equivalent observed quality and
quantity. Economic theory suggests that
HFs will be greater than 1.
The TAC conducted two significantly
different analyses—one pooled the
COLA region and DC area data and the
other treated each COLA area
separately. The TAC conducted these
analyses using GPRES results and then
using FEHLPS results for comparison.
For both surveys, the regional analyses
showed that the HF were greater than 1
for all areas, which means that
homeowner rent estimates are higher
than market rents, holding observed
housing characteristics constant. This is
as economic theory would predict. But
the TAC also found that for both
surveys, the COLA area HFs did not
differ to a statistically significant degree
compared with the DC area HF.
Therefore, no adjustments to the COLA
survey rent index to account for rental
equivalence are appropriate. In
addition, the differences between the
results using GPRES and those using
FEHLPS raised questions of whether
HFs are changing over time.
The TAC also analyzed the results of
both surveys on a COLA survey area
basis. These analyses showed that the
COLA area HFs were generally less than
1, which is the opposite of the findings
from the regional analyses and what
economic theory would predict. Most of
these HFs were not statistically
significant using GPRES, and many
were not significant using FEHLPS. For
both surveys, the COLA area HFs were
lower than the DC area HF, with the
exception of the USVI HFs, but several
of the COLA area HFs did not differ to
a statistically significant degree from the
DC area HF. As with the regional
analyses, the COLA survey area analyses
indicates that no adjustments to the
COLA survey rent index are
appropriate. In addition, the differences
between the results using GPRES and
those using FEHLPS were even more
extreme and raised more questions of
whether HFs are changing over time.
Based on these analyses, the TAC
recommended that no adjustments be
made in the COLA survey rent index to
account for homeowner shelter costs.
The TAC further recommended that
OPM conduct additional GPRES-like
surveys before considering any such
adjustment. OPM hired JPC to review
the TAC’s analyses. JPC found the
TAC’s analyses to be appropriate and
comprehensive and concurred with the
TAC’s recommendations. Therefore,
OPM will not adjust COLA survey rent
indexes to account for homeowner
shelter costs. OPM does not see a need
to conduct additional GPRES surveys at
this time.
Appendix A—GPRES Survey
Questionnaire
The interviewer must provide the
following information to each respondent:
My name is {INTERVIEWER’S NAME} and I
am calling on behalf of the U.S. Office of
Personnel Management. We are conducting a
study to determine housing costs in your
area. Although the results of the study may
be public, we will not divulge any
information that would allow someone to
identify you or your home.
Your participation is voluntary and very
important to the success of this study. This
study should take approximately 8 minutes.
You may send any comments concerning this
study to the Office of Personnel Management.
[IF NEEDED: The address is office of
Personnel Management, Forms Officer,
Washington, DC 20415–8900]. We invite
comments about how long the study takes
and how this time could be reduced.
The Office of Management and Budget has
approved this study and assigned it a
collection number of 3206–0247. We would
not be able to conduct this study without this
approval. The approval expires 5/31/2007.
1. Do you own or rent your home?
OWN—1 GO TO Q8a
RENT—2 GO TO 2
OTHER (SPECIFY ______)—91 GO TO END
REFUSED—¥7 GO TO END
DON’T KNOW—8 GO TO END
RENTERS ONLY
2. Which of the following best describes your
rental agreement? Would you say . . .
You live in subsidized or rent controlled
housing—1 GO TO END
You live in military housing—2 GO TO
END
You rent from a family member or friend
who does not charge you market rate for
your home—3 GO TO END
You pay the market rate for renting your
home—4
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
3. What is the length of your lease?
YEAR—1
6 MONTHS—2
NO LEASE (e.g., month-to-month)—3
OTHER—91
(SPECIFY)—
REFUSED—¥7
DON’T KNOW—¥8
4a. What is your monthly rent?
$ll,lll MONTHLY RENTAL
AMOUNT
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
4b. Are any utilities included in the rent?
YES—1
NO—2 GO TO Q5
REFUSED—¥7 GO TO Q5
DON’T KNOW—¥8 GO TO Q5
4c. Which of the following utilities are
included in the rent? Does it include
. . .
sroberts on PROD1PC70 with NOTICES
YES
4ca
4cb
4cc
4cd
Water? .................................................................................................................................................
Electric? ...............................................................................................................................................
Gas? ....................................................................................................................................................
Heat? ...................................................................................................................................................
5. Are any of the following included in
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1
1
1
1
NO
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2
2
2
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¥7
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¥7
Don’t
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YES
5a
5b
5c
5d
5e
5f
Maintenance, e.g. faucet/appliance repair? ........................................................................................
Lawn care? ..........................................................................................................................................
Snow removal? ....................................................................................................................................
Trash removal? ....................................................................................................................................
Parking in covered public style garage? .............................................................................................
Furnishings? ........................................................................................................................................
6a. Are pets allowed at your rental unit?
YES—1
NO—2 GO TO 7a
REFUSED—¥7 GO TO 7a
DON’T KNOW—¥8 GO TO 7a
6b. Is there an additional fee for pets?
YES—1
NO—2 GO TO 7a
REFUSED—¥7 GO TO 7a
DON’T KNOW—¥8 GO TO 7a
6c How much is the additional fee?
$llllll AMOUNT OF PET FEE
MONTHLY—1
ANNUALLY—2
ONE-TIME DEPOSIT—3
OTHER (SPECIFY) llllll—91
REFUSED—¥7
DON’T KNOW—¥8
7a. Approximately how long have you rented
at this location?
NOTE: LESS THAN 1 MONTH = 1
MONTH
llllll TIME RENTED AT THIS
ADDRESS MONTHS
llllll TIME RENTED AT THIS
ADDRESS YEARS
REFUSED—¥7
DON’T KNOW—¥8
7b. Would you consider the place that you’re
renting a permanent rental property, that
is, the property is consistently rented
out, or is it a temporary rental, for
example the owner is abroad and intends
to return?.
PERMANENT—1 GO TO 11a
TEMPORARY—2 GO TO 11a
REFUSED—¥7 GO TO 11a
DON’T KNOW—¥8 GO TO 11a
OWNERS ONLY
8a. If you were to rent your home on a long
term basis, not as a vacation rental, what
do you think your home would rent for
per month? We are not asking you
whether you want to rent it, only to
NOTE: ALL RESPONDENTS WILL BE ASKED ABOUT EACH REASON
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8cb
8cc
8cd
8ce
8cf
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One-family detached house—1 GO TO
Q12a
Duplex or triplex—2 GO TO Q12a
Townhouse or rowhouse—3 GO TO Q12a
Apartment—4 GO TO Q11b
Rented room in a house—5 GO TO END
Trailer, or—6 GO TO END
Somewhere else?—91 GO TO END
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
11b. Would you say that your home is . . .
An apartment in a home—1
An apartment in a building without an
elevator or—2
An apartment in a building with an
elevator—3
REFUSED—¥7
DON’T KNOW—¥8
12a. Approximately how many square feet of
living space do you have?
l,lllll LIVING SPACE IN SQUARE
FEET GO TO NOTE 1
REFUSED—¥7 GO TO 12b
DON’T KNOW—¥8 GO TO 12b
12b. Would you estimate that your living
space is
Less than 250 square feet,—1 GO TO END
250 to less than 500 square feet,—2 SEE
PROGRAMMER NOTE, ABOVE
500 to 1,000 square feet,—3 GO TO NOTE 1
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2
2
2
2
2
2
¥7
¥7
¥7
¥7
¥7
¥7
¥8
¥8
¥8
¥8
¥8
¥8
estimate what it might rent for if it were
for rent.
$llllll MONTHLY RENTAL
AMOUNT—SKIP TO 8c
REFUSED—¥7 GO TO 8b
DON’T KNOW—¥8 GO TO 8b
8b. Would you estimate that your home
would rent for . . .
Less than $200 per month—1 GO TO END
$201 to $500 per month—2 GO TO 8c
$501 to $1,000 per month—3 GO TO 8c
$1,001 to $1,500 per month—4 GO TO 8c
$1,501 to $2,000 per month—5 GO TO 8c
$2,001 to $2,500 per month—6 GO TO 8c
$2,501 to $3,000 per month—7 GO TO 8c
$3,001 to $6000 per month—or 8 GO TO
8c
Over $6000 per month?—9 GO TO END
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
8c. How did you arrive at the rental amount?
Was it based on . . .
YES
Other neighborhood rentals? ............................................................................................
Rental ads in newspapers, etc? .......................................................................................
Realtor or property manager advide? ..............................................................................
Previous experience renting this home? ..........................................................................
Cost incurred, for example, receiving enough to cover your mortgage? .........................
Something else? (Specify):llllll .........................................................................
9a. How long ago did you rent it?
llllll TIME SINCE RENTED
MONTHS
llllll TIME SINCE RENTED
YEARS
REFUSED—¥7
DON’T KNOW—¥8
9b. How much rent did you charge?
$llllll PER
9b.1 MONTH—1
WEEK—2
YEAR—3
REFUSED—¥7
DON’T KNOW—¥8
10a. What is the approximate monthly
mortgage payment on your home?
$llllll MORTGAGE PAYMENT
REFUSED—¥7
DON’T KNOW—¥8
10b. Given current market conditions in your
area, at what price would your home
sell?
$llllllll
REFUSED—¥7
DON’T KNOW—¥8
OWNERS AND RENTERS
11a. Which one of the following best
describes where you currently live? Do
you live in a . . .
1
1
1
1
1
1
NO
NO
1
1
1
1
1
1
2
2
2
2
2
2
REF
Don’t
know
¥7
¥7
¥7
¥7
¥7
¥7
¥8
¥8
¥8
¥8
¥8
¥8
GO
GO
GO
GO
GO
GO
TO
TO
TO
TO
TO
TO
10a
10a
10a
9a
10a
10a
1,001 to 1,500 square feet,—4 GO TO NOTE
1
1,501 to 2,000 square feet,—5 GO TO NOTE
1
2,001 to 2,500 square feet,—6 GO TO NOTE
1
2,501 to 3,000 square feet,—7 GO TO NOTE
1
3,001 to less than 6,000 square feet, or—8 GO
TO NOTE 1
Over 6,000 square feet,—9 GO TO NOTE 1
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
13. What is the lot size of your property?
ll,llll.ll PROPERTY LOT SIZE
13.1 ACRES—1
SQUARE FEET—2
REFUSED—¥7
DON’T KNOW—¥8
14. Does your home have an exceptional
view, for example, overlooking a body of
water or a city skyline?
YES—1
NO—2
REFUSED—¥7
DON’T KNOW—¥8
15a. How old is your home?
LESS THAN 1 YEAR = 1 YEAR
llll TIME IN YEARS
REFUSED—¥7
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DON’T KNOW—¥8
15b. How many years has it been since it was
remodeled/renovated?
LESS THAN 1 YEAR = 1 YEAR
llll TIME IN YEARS
NOT REMODELED/RENOVATED—N
REFUSED—¥7
DON’T KNOW—¥8
16a. Do you live in a studio or efficiency
apartment?
YES—1 GO TO 17A.
NO—2 GO TO 16
REFUSED—¥7 GO TO 16
DON’T KNOW—¥8 GO TO 16
16. Please tell us how many bedrooms you
have?
l NUMBER OF BEDROOMS
REFUSED—¥7 GO TO END
DON’T KNOW—¥8 GO TO END
17a. How many full bathrooms are in your
home?
ll NUMBER OF FULL BATHS
REFUSED—¥7 } GO TO END
DON’T KNOW—¥8 } GO TO END
17b. How many 1⁄2 bathrooms are in your
home?
ll NUMBER OF HALF BATHS
REFUSED—¥7 } GO TO END
DON’T KNOW—¥8 } GO TO END
18. Excluding the bedrooms and bathrooms
you just mentioned, how many other
rooms are there? (Note: Closets and
hallways are not rooms.)
ll NUMBER OF OTHER ROOMS
REFUSED—¥7
DON’T KNOW—¥8
19. Do you have a security system or live in
a gated or guarded community?
YES—1
NO—2
REFUSED—¥7
DON’T KNOW—¥8
20a. Do you have air conditioning?
YES—1
NO—2 GO TO Q21a
REFUSED—¥7 GO TO Q21a
DON’T KNOW—¥8 GO TO Q21a
20b. Is it central air or individual room units?
CENTRAL AIR—1
ROOM UNIT—2
BOTH—3
REFUSED—¥7
DON’T KNOW—¥8
21a. How do you mainly heat your home?
SPACE HEATERS [electric or kerosene]—
1
WALL UNIT [gas, electric]—2
BASEBOARD [electric, hot water]—3
CENTRAL HEAT [forced air]—4
NONE—5 GO TO Q22
OTHER—91
(SPECIFY)— llllllllllllll
REFUSED—¥7 GO TO Q22 lllllll
DON’T KNOW—¥8 GO TO Q22 lllll
21b. What type of fuel does it use?
GAS [Includes LP/ Propane]—1
ELECTRIC—2
OIL—3
OTHER—91
(SPECIFY)— llllllllllllll
REFUSED—¥7
DON’T KNOW—¥8
22. What type of water system do you have?
Is your water provided via* * *
Municipal water system,—1
Well,—2
Cistern, or—3
Something else?—91
(SPECIFY)— llllllllllllll
REFUSED—¥7
DON’T KNOW—¥8
23. Do you have a garage? By this I mean
your own garage, not a large public style
parking garage.
YES—1
NO—2
REFUSED—¥7
DON’T KNOW—¥8
24. Do you have a carport?
YES—1
NO—2
REFUSED—¥7
DON’T KNOW—¥8
25a. Do you work outside of the home either
full or part time?
YES—1
NO—2 GO TO 26
REFUSED—¥7 GO TO 26
DON’T KNOW—¥8 GO TO 26
25b. What is the one-way distance, in miles,
from your home to your work?
LESS THAN ONE MILE—1
1–5 MILES—2
6–10 MILES—3
11–15 MILES—4
16–20 MILES—5
21–25 MILES—6
26–30 MILES—7
MORE THAN 30 MILES—8
REFUSED—¥7
DON’T KNOW—¥8
26. Do you or a member of your household
work for the Federal Government?
YES—1
NO—2
REFUSED—¥7
DON’T KNOW—¥8
27. What is your zip code?
ŸŸŸŸŸZIP CODE—
REFUSED—¥7
DON’T KNOW—¥8
END.
Appendix B—GPRES Sample Sizes
‘‘Target’’ Quantity
‘‘Minimum’’
Quantity
Geographic area
Owner
quantity
Total
quantity
Renter
quantity
Owner
quantity
A: District of Columbia ........................................................
B: Montgomery Co., MD .....................................................
C: Prince Geo. Co., MD ......................................................
D: Arlington Co., VA ............................................................
E: Fairfax Co., VA ...............................................................
F: Prince William Co., VA ...................................................
G: Anchorage, AK ...............................................................
H: Fairbanks, AK .................................................................
I: Juneau, AK ......................................................................
J: Honolulu County, HI ........................................................
K: Hilo Area, HI ...................................................................
L: Kailua Kona Area, HI ......................................................
M: Kauai County, HI ............................................................
N: Maui County, HI .............................................................
O: Guam ..............................................................................
P: Puerto Rico .....................................................................
Q: St. Croix, USVI ...............................................................
R: St. Thomas, USVI ..........................................................
T: St. John, USVI ................................................................
105
72
78
35
82
20
239
122
174
412
112
85
187
237
278
256
185
219
17
43
88
75
16
108
7
182
126
114
279
107
69
155
246
246
361
295
234
25
148
160
153
51
190
27
421
248
288
691
219
154
342
483
524
617
480
462
42
151
103
112
50
116
28
342
174
249
587
159
121
268
337
396
365
264
312
25
61
126
107
23
155
9
260
179
162
398
153
98
221
352
351
515
422
346
35
212
229
219
73
271
37
602
353
411
985
312
219
489
689
747
880
686
658
61
Totals ....................................................................................
sroberts on PROD1PC70 with NOTICES
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Area
Renter
quantity
2,915
2,776
5,700
4,159
3,973
8,133
Note: The ‘‘Minimum’’ set was the sample
size necessary for estimating rent or rental
equivalence within a margin of error of +/-
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$500 in annual rent with 90 percent
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the sample size for estimating rent or rental
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equivalence at the same margin of error at the
95 percent confidence level.
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Appendix C—Guidelines for Possible
Flags to Identify Potentially Spurious or
Highly Atypical Responses
Responses outside the range are assumed
to be spurious and/or highly atypical and are
not acceptable.
4a. Monthly Rent .........................................................................................................................
6c. Typical Pet fees ......................................................................................................................
7a. Time at this address ..............................................................................................................
8a. Rental equivalence .................................................................................................................
9a. Time since last rented ...........................................................................................................
9b. Rent charged ..........................................................................................................................
10a. Mortgage payment ................................................................................................................
10b. Market Price .........................................................................................................................
12a. Home square footage ............................................................................................................
13. Lot size ...................................................................................................................................
15a. Age in years ..........................................................................................................................
15b. Years since remodeled ........................................................................................................
16. Bedrooms ................................................................................................................................
17a. Full baths ..............................................................................................................................
17b. Half baths .............................................................................................................................
18. Other rooms ...........................................................................................................................
$200 to $5000.
Suggest this field not be flagged.
Suggest this field not be flagged.
$200 to $6000.
Suggest this field not be flagged.
$200 to $5000.
$0 to $6000.
$10,000 to $1,000,000.
Apartments: 250 to 3000; Houses: 500 to 6000.
One-Family Detached House: Greater than
home square footage and 5 acres or less. All
other homes: Suggest this field not be
flagged.
0 to 200.
0 to 50.
Apartments: 0 to 4; All others: 1 to 8.
1 to the number of bedrooms plus 1.
0 to the number of bedrooms minus 1.
Apartments: 1 to 5; All other: 2 to 8.
Appendix D—General Population Rental
Equivalence Survey—Final Response Rates
Screener
Extended
Respondents
Refusals
Area
#Wrkd
A—DC ..................
B—Mont Co ..........
C—PG Co ............
D—Arlington .........
E—Fairfax .............
F—PW ..................
G—Anchorage ......
H—Fairbanks ........
I—Juneau .............
J—Honolulu ..........
K—Hilo .................
L—Kona ................
M—Kauai ..............
N—Maui ................
O—Guam .............
Puerto Rico ...........
Q-St. Croix ............
R-St. Thomas .......
T-St. John .............
820
858
795
320
1,016
178
4,054
1,436
12,878
10,563
2,953
9,454
14,862
11,239
20,791
39,613
10,004
7,020
3,672
152,526
Ineligible
Eligible
Response
(percent)
Refusals
Response
(percent)
Ineligible
231
302
247
148
365
69
1,640
444
2,638
5,313
1,382
2,857
7,064
4,660
1,249
14,127
1,405
611
1,304
46,056
3
3
3
3
2
4
70
47
351
16
57
19
263
23
2
1
1
5
0
873
360
371
331
101
431
50
1,159
644
2,236
2,579
900
1,133
1,934
1,806
1,387
4,660
1,772
1,181
627
23,662
61
55
57
41
54
44
43
61
50
33
41
29
24
28
53
25
56
66
32
35
72
77
63
25
77
5
208
90
315
427
167
238
310
429
136
477
392
418
352
4,278
80
79
81
75
82
90
82
86
86
83
81
79
84
76
90
90
78
65
44
82
122
95
80
20
109
15
454
282
1,597
1,445
505
723
1,243
894
781
3,718
662
238
231
13,214
Hsehlds
594
676
581
252
798
123
2,869
1,135
5,225
7,908
2,339
4,009
9,261
6,489
2,638
18,788
3,178
1,797
1,931
70,591
Total
166
199
188
56
245
30
497
272
324
707
228
172
381
483
470
465
718
525
44
6,170
Owners
Renters
Combined*
(percent)
61
126
109
21
155
10
248
150
163
288
123
87
210
246
247
363
533
278
27
3,445
105
73
79
35
90
20
249
122
161
419
105
85
171
237
223
102
185
247
17
2,725
49
44
47
31
45
40
35
52
43
27
33
23
20
21
47
22
43
43
14
28
* Combined response rate.
Appendix E—1998 Federal Employee
Housing and Living Patterns Survey
Sample Size, Responses, and Response
Rates
Number of
non-postal federal employees
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Survey area
Anchorage ........................................................................................................
Fairbanks .........................................................................................................
Juneau .............................................................................................................
Rest of AK .......................................................................................................
Honolulu County ..............................................................................................
Hawaii County ..................................................................................................
Kauai County ...................................................................................................
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Sample size
7,549
1,625
814
2,413
16,073
728
332
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1,379
519
412
524
3,768
577
332
31JYN1
Responses
748
320
248
336
1,923
378
182
Response rate
(percent)
54.2
61.7
60.2
64.1
51.0
65.5
54.8
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Survey area
Number of
non-postal federal employees
Sample size
Maui County .....................................................................................................
Guam ...............................................................................................................
Puerto Rico ......................................................................................................
U.S. Virgin Islands ...........................................................................................
St. Croix ...........................................................................................................
St. Thomas/St. John ........................................................................................
COLA Areas Subtotal ......................................................................................
Washington DC Area .......................................................................................
471
2,026
11,195
801
........................
........................
44,027
258,304
471
820
1,875
801
........................
........................
11,478
4,324
216
338
629
344
155
184
5,662
1,081
45.9
41.2
33.5
42.9
........................
........................
49.3
25.0
Total ...................................................................................................
302,331
15,802
6,743
42.7
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Response rate
(percent)
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BILLING CODE 6325–39–C
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RAILROAD RETIREMENT BOARD
Summary of Proposal(s):
Agency Forms Submitted for OMB
Review
Summary: In accordance with the
Paperwork Reduction Act of 1995 (44
U.S.C. Chapter 35), the Railroad
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Retirement Board (RRB) has submitted
the following proposal(s) for the
collection of information to the Office of
Management and Budget for review and
approval.
(1) Collection title: Employer
Reporting.
(2) Form(s) submitted: AA–12,
G–88A.1, G–88A.2, BA–6a, BA–6a
(Internet), BA–6a (E-mail).
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(3) OMB Number: 3220–0005.
(4) Expiration date of current OMB
clearance: 9/30/2006.
(5) Type of request: Revision of a
currently approved collection.
(6) Respondents: Business or other
for-profit, Individuals or Households.
(7) Estimated annual number of
respondents: 495.
(8) Total annual responses: 1,958.
(9) Total annual reporting hours: 418.
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Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices
Agencies
[Federal Register Volume 71, Number 146 (Monday, July 31, 2006)]
[Notices]
[Pages 43228-43249]
From the Federal Register Online via the Government Printing Office [www.gpo.gov]
[FR Doc No: 06-6568]
=======================================================================
-----------------------------------------------------------------------
OFFICE OF PERSONNEL MANAGEMENT
Nonforeign Area Cost-of-Living Allowance; General Population
Rental Equivalence Survey Report
AGENCY: Office of Personnel Management.
ACTION: Notice.
-----------------------------------------------------------------------
SUMMARY: This notice publishes the ``Nonforeign Area General Population
Rental Equivalence Survey Report.'' The General Population Rental
Equivalence Survey (GPRES) was a special research project in which the
Office of Personnel Management (OPM) collected data on homeowner
estimates of the rental value of their homes and market rents in the
nonforeign area cost-of-living allowance (COLA) areas and in the
Washington, DC area. OPM conducted GPRES to determine whether rental
survey data collected in the COLA surveys should be adjusted to account
for homeowner shelter costs. Based on the GPRES results, OPM has
determined that no adjustment is appropriate. OPM is publishing this
report to inform interested parties of the research results and provide
an opportunity for comment.
DATES: Comments on this report must be received on or before September
29, 2006.
ADDRESSES: Send or deliver comments to Jerome D. Mikowicz, Acting
Deputy Associate Director for Pay and Performance Policy, Strategic
Human Resources Policy Division, Office of Personnel Management, Room
7H31, 1900 E Street NW., Washington, DC 20415-8200; fax: (202) 606-
4264; or e-mail: COLA@opm.gov.
FOR FURTHER INFORMATION CONTACT: Donald L. Paquin, (202) 606-2838; fax:
(202) 606-4264; or e-mail: COLA@opm.gov.
SUPPLEMENTARY INFORMATION: The Office of Personnel Management (OPM)
conducted the General Population Rental Equivalence Survey (GPRES) to
determine whether OPM should adjust the rent indexes it computes from
data collected in the nonforeign area cost-of-living allowance (COLA)
surveys. The Federal Government pays COLAs to certain white collar
Federal and U.S. Postal Service employees in Alaska, Hawaii, Guam and
the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands.
As provided by subpart B of title 5, Code of Federal Regulations, OPM
conducts living-cost surveys to set COLA rates.
One of the items OPM surveys during the COLA surveys is market
rents for detached houses, duplexes and triplexes, town and row houses,
and apartments. We use rental data to estimate the relative price of
shelter for both homeowners and renters between the COLA areas and the
Washington, DC area. (For an example, see the 2004 Pacific COLA survey
report published at 70 FR 44989-45023.) As applied to homeowners, this
approach is called ``rental equivalence'' because it estimates the
shelter value of owned homes rather than surveying homeowner costs
directly.
OPM adopted the rental equivalence approach pursuant to the
settlement in Caraballo, et al. v. United States, No. 1997-0027
(D.V.I), August 17, 2000. The settlement provides for several
significant changes in the COLA methodology, including the use of
rental equivalence. The settlement also established the Survey
Implementation Committee (SIC), composed of seven plaintiffs'
representatives and two OPM representatives, and the Technical Advisory
Committee (TAC), composed of three economists with expertise in living-
cost analysis. The TAC advises the SIC and OPM on living-cost issues.
The SIC and the TAC agreed OPM could use, on an interim basis, market
rents collected in the COLA surveys to estimate homeowner costs. The
TAC noted, however, that the relative price of shelter for homeowners
could differ compared with the relative price of market rents between
the COLA areas and the DC area. If this were the case, it would be
appropriate for OPM to adjust COLA survey market rent indexes before
applying them to homeowners.
Therefore, OPM conducted a special research project, i.e., GPRES,
to collect information on market rents and homeowner estimates of the
rental value of their homes in the COLA areas and in the Washington, DC
area. The SIC and the TAC were involved heavily in the design of the
survey, and the TAC analyzed the survey results. The TAC also compared
GPRES results with the results of the 1998 Federal Employee Housing and
Living Patterns Survey (FEHLPS), which Joel Popkin and
[[Page 43229]]
Company conducted as part of the research leading to the Caraballo
settlement.
Using the GPRES results, the TAC found that no adjustment to the
COLA survey market rents was appropriate because there were no
statistically significant differences between homeowner estimated rents
and market rents in the COLA areas compared with the DC area. The TAC
found essentially the same results using FEHLPS. Therefore, the TAC
recommended no rental equivalence adjustment be made. However, the TAC
noted some differences between GPRES results and FEHLPS results and
speculated these differences could reflect trends in relative rent
prices/rental price estimates. Therefore, the TAC recommended OPM
consider conducting additional GPRES-type surveys if OPM were to adopt
a rental equivalence adjustment. Because OPM agrees that no rental
equivalence adjustment is warranted, we do not plan to conduct
additional GPRES-type surveys at this time.
Office of Personnel Management.
Linda M. Springer,
Director.
Nonforeign Area General Population Rental Equivalence Survey Report
TABLE OF CONTENTS
1. Introduction.
2. Purpose of GPRES.
2.1 Rental Equivalence and Rents.
2.2 Caraballo Settlement and Rental Equivalence.
3. Planning GPRES.
3.1 Consultation with the SIC and TAC.
3.2 Survey Instrument, Sampling Methodology, and Sample Size.
4. Conducting the Survey.
4.1 Survey Period.
4.2 Efforts To Ensure Quality Participation.
4.3 Survey Complications.
4.3.1 Home Size.
4.3.2 Prevalence of Subsidized Housing in Some Areas.
5. Survey Results and Response Rates.
5.1 GPRES Survey Results and Response Rates.
5.2. FEHLPS Survey Results and Response Rates.
6. Survey Analyses
6.1 Homeowner Factors: Comparison of Owner Rent Estimates and
Market Rents.
6.2 Regional Comparisons.
6.3 COLA Survey Area Comparisons.
7. Summary and Conclusions.
List of Appendices
A. GPRES Survey Questionnaire.
B. GPRES Sample Size.
C. GPRES Data Collection Guidelines.
D. GPRES Number of Responses and Response Rates.
E. FEHLPS Samples Size, Responses, and Response Rates.
F. FEHLPS Survey Questionnaire--Housing Portion.
G. GPRES SAS Regression Results--Regional Analyses.
H. FEHLPS SAS Regression Results--Regional Analyses.
I. GPRES SAS Regression Results--Survey Area Analyses.
J. FEHLPS SAS Regression Results--Survey Area Analyses.
1. Introduction
This report provides the results of the General Population Rental
Equivalence Survey (GPRES), which Westat, Incorporated, conducted for
OPM in the winter of 2004/2005. In addition, the report provides for
comparison purposes the results of the 1998 Federal Employee Housing
and Living Patterns Survey (FEHLPS), which Joel Popkin and Company
conducted for plaintiffs' representatives and Government
representatives who were working collaboratively to resolve long-
contested issues in the nonforeign area cost-of-living allowance (COLA)
program. The collaborative work lead to the settlement of Caraballo, et
al. v. United States, No. 1997-0027 (D.V.I.), August 17, 2000, and to
major changes in the nonforeign area cost-of-living allowance (COLA)
program. Therefore, although this report is principally about GPRES, it
also covers the FEHLPS as it applies to rental equivalence analyses.
The report describes how OPM planned and prepared for the conduct
of GPRES. In planning the survey, OPM consulted closely with the Survey
Implementation Committee (SIC) and the Technical Advisory Committee
(TAC), both established pursuant to the Caraballo settlement. The SIC
has seven members--five plaintiffs' representatives from the COLA areas
and two OPM representatives. The TAC has three members--economists who
have expertise in living-cost measurement. The TAC performs research
for and advises the members of the SIC.
The purpose of GPRES was two-fold. First, it was to determine
whether there are statistically significant ``homeowner factors'' (HFs)
that reflect the difference between homeowners' estimates of the rental
value of their homes compared with market rents, holding rental unit
characteristics constant. (The HF is the estimated rental value of
owned homes divided by the market rent for homes of equivalent observed
quality and quantity.) Second, GPRES was to determine whether HFs
varied between the COLA areas and the Washington, DC area to a
statistically significant degree. If so, OPM could use the results to
adjust the market rents it collects during the COLA surveys to reflect
homeowner shelter costs.
FEHLPS was used to look at the same two questions. The purpose of
FEHLPS was to collect a wide range of information on Federal
employees--much more than housing data. However, among the data FEHLPS
collected were homeowner estimates of the rental value of their homes,
so it was possible to use the survey to compute HFs and to examine
whether these varied to a statistically significant degree between the
COLA areas and the Washington, DC area. The scope of FEHLPS was more
limited than GPRES. It had approximately a third fewer housing
observations and was limited to Federal employees--a subset of the
general population.
Comparing GPRES and FEHLPS results was very informative. This
report describes those comparisons and why, based on the results and
comparisons, no adjustment to rental indexes to account for homeowner
shelter costs appears warranted at this time.
2. Purpose of GPRES
2.1 Rental Equivalence and Rents
There are two commonly accepted approaches for measuring the
shelter value of owned homes. One is the user-cost approach. The other
is rental equivalence. In simplistic terms, user costs are the costs of
owning and maintaining a home minus the annual discounted expected
capital gains that the owner will realize when he or she sells the
home. Rental equivalence is what an owned home would rent for if it
were available for rent in the rental market.
Rental equivalence is a well-known approach and is used by the
Bureau of Labor Statistics (BLS) in the computation of the Consumer
Price Index. Instead of measuring the change in owner user costs, which
tend to be volatile, BLS attributes the change in market rents to
homeowner shelter costs. This approach is supported by research that
BLS conducted in the 1990's. Economists advising the plaintiffs' and
Government representatives prior to the Caraballo settlement
recommended that OPM adopt a similar approach for the COLA program, and
the Caraballo settlement and OPM regulations adopted pursuant to the
settlement prescribe that OPM use a rental equivalence approach to
estimate the ``price'' of homeowner shelter.
Economic theory suggests that homeowners'' estimates of the rental
value of their homes will on average be higher than market rents for
housing with equivalent observed characteristics (i.e., of equivalent
observed quantity
[[Page 43230]]
and quality). (See Akerlof, George A., 1970. ``The Market for `Lemons':
Quality Uncertainty and the Market Mechanism,'' The Quarterly Journal
of Economics, MIT Press, vol. 84(3), pages 488-500.) Imperfect market
knowledge on the part of potential renters' and homeowners' awareness
of unobserved amenities of their homes cause owner rent estimates to be
higher than market rents. In other words, the HF should be greater than
one. The size of the HF, however, could vary between one or more COLA
areas and the Washington, DC area if owned homes in some areas have
more unobserved amenities than owned homes in other areas.
Other factors could also affect owner rent estimates of the rental
value of their homes, such as the owner's limited knowledge of local
rental markets. Although some owners might have an excellent knowledge
of rental markets and the rental value of their homes, most owners have
little reason to pay much attention to the rental market, and their
estimates might well be less accurate. In fact, GPRES results suggest
that homeowners often relied on their mortgage payments to estimate the
rental value of their homes, and mortgage payments are not necessarily
correlated with market rents.
Although homeowner estimates may be somewhat inaccurate, the
expectation is that the inaccurate estimates would be distributed
normally in any area--some too high and some too low. Once again, it is
possible that the effect might not be constant across all areas. Owners
might overestimate in areas where home values are rising rapidly, even
though market rents were trailing. On the other hand, owners might
estimate more accurately in areas with a higher proportion of transient
population because owners might have a greater opportunity to acquire
rental market knowledge if homes near to them become available for
rent. Variation in the accuracy of owner estimates among areas would
make it difficult to compare differences between owner estimates and
market rents from one area to the next.
Another factor that might lead to inaccurate homeowner estimates
could be the pride of ownership. It is conceivable that home owners
systematically might estimate high rental values because the owners
take pride in their homes and think they should be worth more,
regardless of any unobserved amenities. This could further contribute
to the ``noise'' in the survey--i.e., undermine the survey's ability to
reflect higher owner shelter values attributable to unobserved
amenities. Whether the effect of this ``pride factor'' might vary among
areas is speculative.
GPRES was designed to collect information that could be used to
compare homeowner estimated rents with market rents. It also obtained
information on many of the characteristics and amenities of the
respondents' homes to allow the comparison of estimated rents and
market rents while holding observed quality and quantity constant.
2.2 Caraballo Settlement and Rental Equivalence
As stated in the previous section, pursuant to the Caraballo
settlement OPM adopted a rental equivalence approach to measure the
shelter value of owner-occupied housing. Appendix A of the stipulation
for settlement provides 26 ``Safe Harbor Principles'' (SHPs) concerning
the operation of the COLA program. One of the key principles, SHP-18,
describes how OPM will measure the relative cost of shelter:
18. Hedonic Housing Model and Rental Equivalence: Shelter price
relatives will be estimated for owners and renters from the
triennial regional sample. The sample for the region will be pooled
with the comparison sample from the base area and price relatives
for the COLA areas will be estimated using hedonic regression models
to adjust for quality differences.
Discussion: OPM will adopt a rental-equivalence approach to
estimate shelter costs and a hedonic regression approach to compare
housing of similar quality. To identify the living communities to be
surveyed, OPM will use the results of the 1992/93 employees survey,
JPC's [Joel Popkin and Company] survey, and/or other appropriate
information. How the housing data will be collected is not known or
stipulated. OPM may survey Federal employees, collect the data on
its own or through a contractor, enter into an interagency agreement
with another Federal agency (e.g., the Department of Interior), or
use some other appropriate approach.
OPM adopted this principle when it published final regulations at
67 FR 22339. Section 591.219 of title 5, Code of Federal Regulations,
prescribes how OPM will compute shelter price indexes based on rental
and rental equivalence prices and/or estimates. As noted in Section
2.1, rental equivalence compares the shelter value (rental value) of
owned homes rather than total owner costs because the latter are
influenced by capital gains (i.e., the investment value of a home).
Most living-cost surveys do not compare how consumers invest their
money.
In the COLA surveys, OPM surveys market rents in each of the COLA
areas and in the Washington, DC area, obtaining over 80 characteristics
of the rental units for use in the hedonic regression equations. (A
hedonic regression is a statistical technique, specifically a form of
multiple linear regression. For an explanation of how OPM applies these
regressions, see ``2004 Nonforeign Area Cost-of-Living Allowance Survey
Report: Pacific and Washington, DC Areas,'' published at 70 FR 44989.)
The SIC and the TAC agreed that OPM could use market rents as an
estimate for rental equivalence until the issue of rental equivalence
could be explored more fully through a GPRES-type survey.
GPRES explored two questions. The first question was whether the
rental value of owned homes in the COLA and DC areas differed to a
statistically significant degree from market rents in the same area
holding observed quality and quantity constant. To do this, the TAC
computed homeowner factors, as described in Section 6.1. The second
question was whether the COLA area homeowner factors differed to a
statistically significant degree compared with the DC area homeowner
factor. If the homeowner factors were significantly different, it might
be appropriate for OPM to make a rental equivalence adjustment to
account for homeowner shelter costs. As it turned out, no adjustment
was appropriate because we did not find statistically significant
differences between the COLA and DC areas.
3. Planning GPRES
3.1 Consultation With the SIC and TAC
OPM worked closely with the SIC and TAC to plan and develop GPRES.
In August 2001, OPM provided the SIC and TAC with a rough draft of a
survey questionnaire that could be used with homeowners and renters to
obtain and compare information about estimated rental values and market
rents. The SIC and TAC subsequently met on several occasions to refine
the questionnaire and begin planning GPRES. The goal was to design a
survey that was sufficiently brief as to encourage renters and owners
to participate but sufficiently detailed so that OPM could compare
market rents and rental equivalence estimates for comparable housing.
By early 2002, the SIC and TAC had developed such a questionnaire.
Later that year, at the request of the SIC and TAC, the Caraballo
trustee entered into a contract with Joel Popkin and Company (JPC) to
review draft plans for GPRES, review current literature regarding
rental equivalence, and to make recommendations to the SIC and TAC
[[Page 43231]]
concerning GPRES. JPC's research emphasized the importance of
conducting GPRES. The SIC and TAC reviewed JPC's findings, incorporated
them as appropriate in the survey, and recommended that OPM proceed
with the conduct of GPRES. This OPM did.
OPM continued to consult with the SIC and TAC as it finalized plans
for GPRES and kept them apprised during the conduct of GPRES. The TAC
analyzed GPRES results, and OPM and the TAC discussed those results
with the SIC.
3.2 Survey Instrument, Sampling Methodology, and Sample Size
In the fall of 2002, OPM contracted with Westat, Inc., a
statistical research firm, to review JPC's research, propose a survey
methodology, develop a survey instrument, and recommend sample sizes
and sampling strategies for GPRES. In terms of a survey methodology,
Westat recommended the use of Computer Assisted Telephone Interviews
(CATIs). This approach appeared to offer the probability of greater
response rates at reasonable cost compared with other approaches, such
as mail-out questionnaires. Appendix A shows the GPRES questionnaire
that Westat developed as modified by OPM.
To develop sample sizes, Westat used the results of FEHLPS and
OPM's 2002 Caribbean and DC area COLA rental survey, applying standard
sample size calculations. (See Cochran, W.G., Sampling Techniques:
third edition, New York: John Wiley & Sons, Inc., 1977) Westat used
FEHLPS to estimate the standard deviation of homeowner estimated rents
for each COLA area and the Washington, DC area. Westat also used the
results of the survey to estimate the standard deviation of market
rents by area, except for the Caribbean and DC areas. For these areas,
Westat used the results of the 2002 COLA survey because that survey had
more observations and covered the general population, not just Federal
employees. From the surveys, Westat developed sample sizes for owner
and renters for the COLA areas and the Washington, DC area. Westat
developed two sets each for owners and renters. One set was the sample
size necessary for estimating rent or rental equivalence within a
margin of error of +/- $500 in annual rent with 90 percent confidence
level, and the other was the sample size for estimating rent or rental
equivalence at the same margin of error at the 95 percent confidence
level. Subsequent to the 2003 Alaska COLA survey, OPM modified the
renter sample sizes for the Alaska and DC areas based on the additional
rental data that OPM had collected in these areas. Appendix B shows the
sample sizes Westat recommended, as modified by OPM.
Within each area, OPM limited the geographic scope of GPRES to the
zip code areas in which OPM collected rental data in the annual COLA
surveys. In the Washington, DC area, OPM further allocated the sample
among the District of Columbia and the Counties of Montgomery, MD;
Prince Georges, MD; Arlington, VA; Fairfax, VA; and Prince William, VA;
and the independent cities therein, based on the relative numbers of
owners and renters within these areas as reflected by the 2000 Census.
OPM obtained approval for GPRES from the Office of Management and
Budget (OMB) as required by 5 CFR Part 1320, and OMB assigned GPRES an
information collection number. Federal surveys and other information
collections that Federal agencies conduct are covered by the Paperwork
Reduction Act (44 U.S.C. 3501 et seq.). Participation in GPRES was
voluntary, and any identifying information regarding the respondents is
protected under the Privacy Act (5 U.S.C. 552a) and the Freedom of
Information Act (5 U.S.C. 552).
4. Conducting the Survey
4.1 Survey Period
In the fall of 2004, OPM awarded a second contract to Westat to
conduct GPRES. Using CATI, Westat began collecting data in October 2004
and finished in March 2005. Although Westat started data collection in
some areas before others, Westat essentially collected data in all of
the areas throughout this entire time period. Westat provided OPM with
interim deliverables throughout the survey so that OPM and the TAC
could begin testing analyses prior to receiving the final deliverable.
Westat provided the final deliverable in early April 2005.
4.2 Efforts to Ensure Quality Participation
Westat used commercially available lists of phone numbers and
addresses of owners and renters for the Washington, DC area and all of
the COLA areas, except Guam, Puerto Rico, and the U.S. Virgin Islands
for which such lists were unavailable. Using the sampling strategy
described in Section 3.2, Westat drew the sample using commercial data
bases where available. Westat then mailed letters to the prospective
respondents informing them of the survey and asking for their
cooperation. The letter was prepared by OPM on OPM letterhead and
signed by Donald J. Winstead, who at that time was OPM's Deputy
Associate Director for Pay and Performance Policy, Strategic Human
Resources Policy Division. For those areas where commercial mailing/
phone lists were unavailable, Westat was unable to mail advance
letters; and Westat used simple random sampling to select potential
participants.
At the beginning of each telephone interview, Westat surveyors
explained the purpose of the survey, that the survey was voluntary, and
provided the respondent the OMB-provided information collection number.
Westat made certain that the respondent was a knowledgeable adult who
could answer questions relating to the housing unit. If the adult was
not available, Westat made arrangements to call back at a more
convenient time to conduct the interview. The complete interview took
approximately 8 minutes.
It was critically important that GPRES collect accurate information
from persons who either owned their own homes or rented homes at
current market rents. To this end, some GPRES questions were designed
to eliminate respondents who did not meet these criteria. For example,
Westat discontinued the survey if the respondent lived in rent-
subsidized or rent-controlled housing, occupied military housing, or
rented from relatives or other persons at rates other than market
rates. Likewise, Westat discontinued the survey if the respondent was
renting a room in a home or was living in a mobile home or similar
lodging.
In addition, OPM identified for Westat several ``threshold''
questions that were critical to the survey and instructed Westat to
discontinue the survey if the respondent could not or would not answer
these questions. For example, if the respondent did not know or refused
to answer how many bathrooms or bedrooms were in the home, Westat was
instructed to discontinue the survey. The questionnaire in Appendix A
shows the threshold questions. They are identified by the interview
instruction ``GO TO END.'' Similarly, OPM provided Westat with
guidelines to help ensure that respondents did not provide frivolous
responses or occupied housing so atypical as to be outside the scope of
the survey. Appendix C shows the Guidelines that Westat used to help
identify frivolous and highly atypical responses.
4.3 Survey Complications
Westat encountered two unexpected complications in conducting
GPRES. One involved the respondent's lack of knowledge concerning home
size. The
[[Page 43232]]
other involved an unexpectedly high proportion of the population in
certain areas residing in subsidized or rent-controlled housing.
4.3.1 Home Size
One problem that Westat encountered was that respondents often did
not know and could not estimate or guess the number of square feet in
their home. As shown in Appendix A, OPM had identified this as a
critical threshold question; and as shown in Appendix C, OPM provided
guidelines concerning acceptable data. Westat noted that invalidating
these responses was increasing the non-response rate and the cost of
the survey. Westat suggested that OPM reconsider whether home size
should be a threshold question and/or subject to the guidelines.
OPM discussed the issue with the TAC. The TAC was not surprised and
noted that BLS, the Bureau of the Census, and other housing surveys
encountered the same problem and dropped home size as a question in
their surveys. The TAC suggested that OPM use room count and a limited
number of other characteristics to impute home size for respondents who
were unknowledgeable or provided atypical responses. OPM tested this
approach using the rental data it had collected in the COLA surveys and
found it feasible. Therefore, OPM informed Westat to continue survey
interviews even when respondents did not know and could not estimate
home size and instructed Westat not to apply guidelines to flag
atypical responses. OPM and the TAC later tested whether to use imputed
home sizes but decided against it because the imputation process had a
systematic error in estimating the size of relatively small and
relatively large homes.
4.3.2 Prevalence of Subsidized Housing in Some Areas
Westat also discovered difficulties obtaining the desired sample of
renters in certain areas because an unexpectedly large portion of the
renter population appear to occupy subsidized or rent-controlled
housing. This was most noticeable in Guam, Puerto Rico, and the U.S.
Virgin Islands (USVI), as well as in the District of Columbia. Under
the contract, OPM paid Westat on a price-per-completed-survey-response
basis. When Westat began encountering unexpectedly high respondent
invalidation rates, Westat informed OPM that it would not be able to
provide the desired sample sizes in certain areas because the company
had reached the breakeven point at which further data collection would
not be profitable.
Therefore, OPM modified the price schedule in the contract to
ensure that Westat could obtain at least the ``minimum'' sample size
shown in Appendix B in all areas. As shown in Appendix D, Westat
exceeded this level in several areas, but it was unable to obtain the
minimum number of renter samples in Guam and Puerto Rico.
5. Survey Results and Response Rates
5.1 GPRES Survey Results and Response Rates
Appendix D shows the number of renter and owner observations that
Westat obtained by area. Except in Guam and Puerto Rico, Westat
obtained a sample that equaled or exceeded the sample size necessary
for estimating rent or rental equivalence within a margin of error of
+/-$500 in annual rent with a 90 percent confidence level. In all,
Westat obtained 6,170 observations.
To do this, Westat made more than 152,000 phone calls. Therefore,
one simplistic measure of the response rate might be 4 percent (i.e.,
6,170 divided by 152,000). Many of those calls, however, particularly
in the areas for which commercial phone list data as described in
Section 4.2 were unavailable, were screening calls to businesses,
facsimile machines, and other non-residential phone numbers. Also, many
of the residential respondents (e.g., those occupying rent-controlled
or subsidized housing) were not eligible to be part of the survey
universe. Therefore, another and perhaps more meaningful way to look at
the response rate is to compare the number of respondents with the
total number of those who were determined, after the screening
questions, to be part of the survey universe. According to Westat, a
total of 23,662 respondents passed the screening questions. Using this
as a basis, the response rate was 26.1 percent (i.e., 6,170 divided by
23,662). This does not, however, include respondents who become
ineligible in the ``extended interview,'' i.e., the main part of the
interview that followed the screening questions. Taking this into
consideration, the overall GPRES response rate according to Westat was
28 percent. Appendix D shows this type of response rate for each COLA
area and the for Washington, DC area.
5.2 FEHLPS Survey Results and Response Rates
JPC conducted FEHLPS in cooperation with OPM in 1998. It was a
survey of a sample of non-U.S. Postal Service Federal employees in the
COLA areas and in the Washington, DC area. JPC selected a sample size
of approximately 15,800, of which 11,478 were to be drawn from the COLA
areas and 4,324 were to come from the Washington, DC area. The sample
was drawn from OPM's Central Personnel Data File (CPDF), which is
essentially a census of non-Postal Federal employees. According to the
CPDF, there were approximately 44,027 non-Postal Federal employees in
1998 in the COLA areas and 258,304 in the DC area.
JPC collected 5,662 responses from the COLA areas, which makes the
average response rate for those areas 49.3 percent. JPC collected 1,081
responses from the Washington, DC area, which makes the DC area
response rate 25 percent. Appendix E shows the FEHLPS sample sizes,
responses, and response rates by COLA area and for the Washington, DC
area. Not all of the respondents provided usable housing data.
Therefore, the TAC could use only 4,275 FEHLPS observations in its
analyses.
The survey was a ``mail out'' survey, delivered to employees at
their worksite. Agencies were encouraged to grant employees time at
work to complete the survey. FEHLPS covered numerous topics, including
transportation and travel, K-12 private education, college education,
medical costs, and housing. Appendix F shows the housing related
portion of the survey.
6. Survey Analyses
The TAC performed most of the analyses of the GPRES results, with
OPM's support and oversight. OPM also contracted with JPC to review the
GPRES results and analyses. JPC concurred with the TAC's analyses,
findings, and recommendations.
6.1 Homeowner Factors: Comparison of Owner Rent Estimates and Market
Rents
As discussed in Section 2, one purpose for conducting GPRES was to
compare owner estimates of the rental value of their homes with market
rents for comparable housing in terms of quality and quantity. The goal
was to express mathematically the relationship of rents and rent
estimates within each COLA area and the Washington, DC area. The second
purpose was to examine whether those relationships varied significantly
between the COLA areas and the Washington, DC area.
The TAC computed homeowner factors (HFs) to express the
relationship of homeowner rent estimates and market rents in and among
the COLA
[[Page 43233]]
areas and the Washington, DC area. The HF is the estimated rental value
of owned homes divided by the market rent for homes of equivalent
observed quality and quantity. To compute the HF, the TAC used hedonic
regressions to hold quality and quantity constant.
The TAC used two distinctly different approaches to analyze HFs.
One approach involved comparing HFs by COLA region with the DC area HF.
The other involved estimating HFs for each COLA survey area and
comparing these with the DC area HF. The results of the two approaches
were quite different but lead to the same conclusion.
6.2. Regional Comparisons
The COLA areas are divided into three regions--the Alaska, Pacific,
and Caribbean regions. The Alaska region is composed of the Anchorage,
Fairbanks, and Juneau COLA survey areas. The Pacific region is composed
of the Honolulu County; Hilo and Kailua Kona, Hawaii County; Kauai
County; Maui County; and Guam COLA survey areas. The Caribbean region
is composed of the Puerto Rico; St. Croix, USVI, and St. Thomas/St.
John, USVI, COLA survey areas.
The TAC noted that there were virtually no previous studies to
serve as a guide on how to analyze HFs by area and compare them between
areas. The TAC believed if there were systematic differences in HFs
across areas, the TAC would need as many observations as possible to
identify these relationships. Pooling the data by region allowed the
use of all of the survey observations (GPRES or FEHLPS) at one time.
The TAC applied semi-logarithmic hedonic regressions to compute
rental equivalence indexes and market rent indexes for the COLA regions
relative to the Washington, DC area, holding quantity and quality of
housing constant. The dependent variable of the regression was the
logarithm of rent. Appendix G shows the SAS GPRES regression results
that the TAC used. (SAS is a proprietary statistical analysis computer
software package.) The independent variables for the GPRES regression
are listed below:
Type of dwelling (e.g., detached house, townhouse, apartment),
Whether the unit had central air conditioning,
Number of baths,
Number of bedrooms,
Number of baths crossed with type of dwelling, and
Tenure (i.e., owned or rented) by the COLA region or DC area in which
unit is located.
The parameter of interest in this regression was tenure by COLA
region and the results are shown in the table below. The HF is shown in
column (1). (The logarithmic form of the HFs and standard errors and t
values are shown in columns (2) through (4).) An HF of 1.223 for Alaska
means that homeowner estimates of the rental value of their homes are
on average 22.3 percent higher than market rents holding observed
quality and quantity of the housing unit characteristics constant. The
critical values of ``t'' at the 5 percent and 1 percent levels are 1.96
and 2.58 respectively. In other words, HFs with t-values equal to or
greater than 2.58 are significant at a 99 percent confidence level or
higher.
Table 1.--GPRES Homeowner Factors by Region
----------------------------------------------------------------------------------------------------------------
Standard
COLA region HF Logarithmic HF error t-value
----------------------------------------------------------------------------------------------------------------
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
Alaska...................................................... 1.223 0.201 0.027 7.50
Pacific..................................................... 1.171 0.158 0.018 8.74
Caribbean................................................... 1.117 0.111 0.023 4.94
Washington, DC Area......................................... 1.153 0.142 0.031 4.62
----------------------------------------------------------------------------------------------------------------
The TAC also computed homeowner factors on a regional basis using
the results of FEHLPS. Again, the dependent variable was the log of
rent, but the independent variables were somewhat different than those
used in the GPRES analyses. Appendix H shows the TAC's regression
results using the FEHLPS data. The homeowner factors are shown in Table
2, below:
Table 2.--FEHLPS Homeowner Factors by Region
----------------------------------------------------------------------------------------------------------------
Standard
COLA region HF Logarithmic HF error t-value
----------------------------------------------------------------------------------------------------------------
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
Alaska...................................................... 1.274 0.242 0.0301 8.03
Pacific..................................................... 1.092 0.088 0.0195 4.49
Caribbean................................................... 1.168 0.155 0.0326 4.75
Washington, DC Area......................................... 1.254 0.226 0.0479 4.71
----------------------------------------------------------------------------------------------------------------
The HFs from both surveys are statistically significant and greater
than 1 when the results are analyzed on a regional basis. HFs greater
than one is what economic theory would predict. The key question is
whether there are statistically significant differences between the HFs
for the COLA regions compared with the DC area HF. To do this, the TAC
again used a t-test where the standard error is the difference between
HFs calculated from a covariance matrix of the regression coefficients
on owners and renters. Tables 3 and 4 below show the results for GPRES
and FEHLPS respectively.
[[Page 43234]]
Table 3.--GPRES Test of Difference Between Regional HFs and DC Area HF
----------------------------------------------------------------------------------------------------------------
COLA region HF Logarithmic COLA Standard
COLA region divided by DC region HF error t-value
----------------------------------------------------------------------------------------------------------------
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
Alaska........................................... 1.061 0.0595 0.0375 1.58
Pacific.......................................... 1.016 0.0161 0.0328 0.49
Caribbean........................................ 0.970 -0.0301 0.0353 -0.85
----------------------------------------------------------------------------------------------------------------
Table 4.--FEHLPS Test of Difference Between Regional HFs and DC Area HF
----------------------------------------------------------------------------------------------------------------
COLA region HF Logarithmic COLA
COLA region divided by DC region HF -DC Standard t-value
Area HF Area HF error
----------------------------------------------------------------------------------------------------------------
Alaska........................................... 1.016 0.0161 0.0548 0.29
Pacific.......................................... 0.871 -0.1379 0.0500 -2.76
Caribbean........................................ 0.932 -0.0705 0.0560 -1.26
----------------------------------------------------------------------------------------------------------------
As shown in Table 3, the TAC found, based on the GPRES results, the
differences between the COLA region HFs and the DC area HF were not
statistically significant. Similarly, as shown in Table 4, the TAC
found, based on the FEHLPS results, there was no statistically
significant difference between the COLA region HFs and the DC area HF.
Therefore, no adjustment to the COLA survey rental index was
appropriate to account for homeowner shelter values (rental
equivalence).
Although analyses of both surveys found no statistically
significant differences between the COLA and DC area HFs, the TAC also
noted the significant differences between the GPRES results compared
with the FEHLPS results. For example, GPRES showed the Pacific region
HF was slightly higher than the DC area HF, but FEHLPS show the Pacific
region HF to be somewhat lower than the DC area HF. Unless Federal
employees were atypical of the general population with regard to market
rents and homeowner estimates, it appeared that the HFs changed
substantially over the 6-year interval between FEHLPS and GPRES. The
TAC found the apparent lack of stability over time troubling.
6.3 COLA Survey Area Comparisons
The second approach the TAC used to analyze GPRES and FEHLPS
results was to compute HFs by COLA survey area and compare these with
the DC HF. The advantage of this approach was more consistency with the
COLA program, which sets COLA rates by COLA area, not COLA region. It
also allowed the HFs to be computed separately for each area, using
different equations as appropriate. The disadvantage was that each
regression used far less data than in the regional analyses.
To compute HFs for each of the COLA survey areas, the TAC pooled
the survey data by region and computed HFs for each of the COLA survey
areas within the region. Appendix I has an example of the SAS
regression results for one of the survey areas--the Pacific region--
using GPRES. Appendix J has an example of the SAS regression results
for one of the survey areas--the Caribbean region--using FEHLPS. Table
5 shows the HFs by area and their relationship to the DC HF using
GPRES. Table 6 shows the same results using FEHLPS.
Table 5.--GPRES HFs by COLA Survey Area
----------------------------------------------------------------------------------------------------------------
Standard
Survey area HF Logarithmic HF error t ratio
----------------------------------------------------------------------------------------------------------------
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
Anchorage................................................... 1.025 0.0250 0.0354 0.70
Fairbanks................................................... 0.958 -0.0434 0.0416 -1.04
Juneau...................................................... 0.935 -0.0667 0.0392 -1.70
Honolulu.................................................... 1.061 0.0588 0.0321 1.81
Hilo........................................................ 0.986 -0.0141 0.0499 -0.28
Kailua Kona................................................. 0.957 -0.0440 0.0546 -0.81
Kauai....................................................... 0.930 -0.0728 0.0396 -1.84
Maui........................................................ 1.013 0.0134 0.0355 0.38
Guam........................................................ 0.997 -0.0030 0.0351 -0.09
Puerto Rico................................................. 1.002 0.0018 0.0495 0.04
St. Croix................................................... 1.141 0.1321 0.0395 3.35
St. Thomas/St. John......................................... 1.124 0.1166 0.0442 2.64
DC Area..................................................... 1.110 0.1040 0.0415 2.51
----------------------------------------------------------------------------------------------------------------
Unlike the COLA region analyses, the GPRES results in Table 5 show
that the HFs are less than 1 in half of the COLA survey areas. This is
contrary to what economic theory would predict. In addition, 10 of the
13 COLA survey area HFs are not statistically significant at a 95
percent confidence level. By comparison, the results using FEHLPS are
quite different. (See Table 6.) All of the HFs are greater than 1,
which conforms with economic theory, and only four of the HFs are not
significant at a 95 percent confidence level.
[[Page 43235]]
Table 6.--FEHLPS HFs by COLA Survey Area
----------------------------------------------------------------------------------------------------------------
Standard
Survey area HF Logarithmic HF error t ratio
----------------------------------------------------------------------------------------------------------------
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
Anchorage................................................... 1.278 0.2451 0.0397 6.17
Fairbanks................................................... 1.011 0.0106 0.0623 0.17
Juneau...................................................... 1.222 0.2006 0.0707 2.84
Honolulu.................................................... 1.120 0.1130 0.0240 4.71
Hawaii County............................................... 1.011 0.0108 0.0424 0.25
Kauai....................................................... 1.083 0.0798 0.0587 1.36
Maui........................................................ 1.176 0.1618 0.0495 3.27
Guam........................................................ 1.168 0.1549 0.0488 3.17
Puerto Rico................................................. 1.208 0.1888 0.0497 3.80
St. Croix................................................... 1.045 0.0440 0.0784 0.56
St. Thomas/St. John......................................... 1.468 0.3842 0.0839 4.58
DC Area..................................................... 1.279 0.2461 0.0450 5.46
----------------------------------------------------------------------------------------------------------------
As with the regional analysis, the key question is whether the COLA
survey area HFs are statistically significantly different from the DC
area HF. The TAC used the same approach it used to produce Tables 3 and
4 in the region analyses. As shown in Table 7, the GPRES results
indicate that the HFs in the COLA survey areas are lower than the DC
area HF except in the USVI. The t-ratios, however, show that these
results are not significant at the 95 percent confidence level in 8 out
of 12 cases. (Keep in mind that 10 of the 13 HFs were not statistically
significant at that level, which further weakens the statistical
validity of the comparison.). Table 8, which shows the FEHLPS results,
also shows that the COLA survey area HFs are lower than the DC area HF,
except in St. Thomas/St. John, USVI. (Note: Unlike GPRES, it was not
possible using FEHLPS data to split Hawaii County into the Hilo and
Kailua Kona survey areas.) In addition, the FEHLPS differences are not
statistically significant at a 95 percent confidence level in 7 out of
13 areas.
Table 7.--GPRES Test of Difference Between Survey Area HFs and DC Area HF
----------------------------------------------------------------------------------------------------------------
COLA area HF Logarithmic COLA
Survey area divided by DC area HF- DC area t ratio
area HF HF
----------------------------------------------------------------------------------------------------------------
(1) (2) (3)
----------------------------------------------------------------------------------------------------------------
Anchorage..................................................... 0.924 -0.0790 -1.45
Fairbanks..................................................... 0.863 -0.1474 -2.51
Juneau........................................................ 0.843 -0.1707 -2.99
Honolulu...................................................... 0.956 -0.0452 -0.86
Hilo.......................................................... 0.889 -0.1181 -1.82
Kailua Kona................................................... 0.862 -0.1480 -2.16
Kauai......................................................... 0.838 -0.1768 -3.09
Maui.......................................................... 0.913 -0.0906 -1.66
Guam.......................................................... 0.899 -0.1070 -1.97
Puerto Rico................................................... 0.903 -0.1022 -1.58
St. Croix..................................................... 1.028 0.0281 0.49
St. Thomas/St. John........................................... 1.013 0.0126 0.21
DC Area....................................................... 1.000 0.0
----------------------------------------------------------------------------------------------------------------
Table 8.--FEHLPS Test of Difference Between Survey Area HFs and DC Area HF
----------------------------------------------------------------------------------------------------------------
COLA area HF Logarithmic COLA
Survey area divided by DC area HF-DC Area t ratio
area HF HF
(1) (2) (5)
----------------------------------------------------------------------------------------------------------------
Anchorage..................................................... 0.999 -0.0010 -0.02
Fairbanks..................................................... 0.790 -0.2355 -3.06
Juneau........................................................ 0.956 -0.0455 -0.54
Honolulu...................................................... 0.875 -0.1331 -2.61
Hawaii County................................................. 0.790 -0.2353 -3.80
Kauai......................................................... 0.847 -0.1663 -2.25
Maui.......................................................... 0.919 -0.0843 -1.26
Guam.......................................................... 0.913 -0.0912 -1.37
Puerto Rico................................................... 0.944 -0.0573 -0.85
St. Croix..................................................... 0.817 -0.2021 -2.23
St. Thomas/St. John........................................... 1.148 0.1381 1.45
DC Area....................................................... 1.000 0.0 ..........
----------------------------------------------------------------------------------------------------------------
[[Page 43236]]
As with the regional analyses, the TAC found troubling the
significant differences between the GPRES and FEHLPS results. Once
again, the question was whether there were trends over the 6-year
period between the surveys that could explain these differences or the
differences were simply inherent in the populations surveyed and/or
survey techniques used. The TAC recommended that OPM not implement any
adjustments to the rental data based on the COLA survey area analyses
without first conducting additional GPRES-like surveys.
7. Summary and Conclusions
OPM conducted GPRES to determine whether OPM should adjust rental
data that it collects during its annual COLA surveys. In these annual
surveys, OPM collects prices on market rents on various types of
housing units. OPM uses rental data to estimate the relative price of
shelter for both homeowners and renters between the COLA areas and the
Washington, DC area.
The TAC analyzed the GPRES results and compared them with similar
analyses using rental data and estimates from an earlier survey of
Federal employees--FEHLPS. Using regression analyses, the TAC computed
homeowner estimated rent and market rent indexes and from these
computed homeowner factors (HFs), which were homeowner indexes divided
by the market rent indexes for units of equivalent observed quality and
quantity. Economic theory suggests that HFs will be greater than 1.
The TAC conducted two significantly different analyses--one pooled
the COLA region and DC area data and the other treated each COLA area
separately. The TAC conducted these analyses using GPRES results and
then using FEHLPS results for comparison. For both surveys, the
regional analyses showed that the HF were greater than 1 for all areas,
which means that homeowner rent estimates are higher than market rents,
holding observed housing characteristics constant. This is as economic
theory would predict. But the TAC also found that for both surveys, the
COLA area HFs did not differ to a statistically significant degree
compared with the DC area HF. Therefore, no adjustments to the COLA
survey rent index to account for rental equivalence are appropriate. In
addition, the differences between the results using GPRES and those
using FEHLPS raised questions of whether HFs are changing over time.
The TAC also analyzed the results of both surveys on a COLA survey
area basis. These analyses showed that the COLA area HFs were generally
less than 1, which is the opposite of the findings from the regional
analyses and what economic theory would predict. Most of these HFs were
not statistically significant using GPRES, and many were not
significant using FEHLPS. For both surveys, the COLA area HFs were
lower than the DC area HF, with the exception of the USVI HFs, but
several of the COLA area HFs did not differ to a statistically
significant degree from the DC area HF. As with the regional analyses,
the COLA survey area analyses indicates that no adjustments to the COLA
survey rent index are appropriate. In addition, the differences between
the results using GPRES and those using FEHLPS were even more extreme
and raised more questions of whether HFs are changing over time.
Based on these analyses, the TAC recommended that no adjustments be
made in the COLA survey rent index to account for homeowner shelter
costs. The TAC further recommended that OPM conduct additional GPRES-
like surveys before considering any such adjustment. OPM hired JPC to
review the TAC's analyses. JPC found the TAC's analyses to be
appropriate and comprehensive and concurred with the TAC's
recommendations. Therefore, OPM will not adjust COLA survey rent
indexes to account for homeowner shelter costs. OPM does not see a need
to conduct additional GPRES surveys at this time.
Appendix A--GPRES Survey Questionnaire
The interviewer must provide the following information to each
respondent: My name is {INTERVIEWER'S NAME{time} and I am calling
on behalf of the U.S. Office of Personnel Management. We are
conducting a study to determine housing costs in your area. Although
the results of the study may be public, we will not divulge any
information that would allow someone to identify you or your home.
Your participation is voluntary and very important to the
success of this study. This study should take approximately 8
minutes. You may send any comments concerning this study to the
Office of Personnel Management. [IF NEEDED: The address is office of
Personnel Management, Forms Officer, Washington, DC 20415-8900]. We
invite comments about how long the study takes and how this time
could be reduced.
The Office of Management and Budget has approved this study and
assigned it a collection number of 3206-0247. We would not be able
to conduct this study without this approval. The approval expires 5/
31/2007.
1. Do you own or rent your home?
OWN--1 GO TO Q8a
RENT--2 GO TO 2
OTHER (SPECIFY ------------)--91 GO TO END
REFUSED---7 GO TO END
DON'T KNOW--8 GO TO END
RENTERS ONLY
2. Which of the following best describes your rental agreement?
Would you say . . .
You live in subsidized or rent controlled housing--1 GO TO END
You live in military housing--2 GO TO END
You rent from a family member or friend who does not charge you
market rate for your home--3 GO TO END
You pay the market rate for renting your home--4
REFUSED---7 GO TO END
DON'T KNOW---8 GO TO END
3. What is the length of your lease?
YEAR--1
6 MONTHS--2
NO LEASE (e.g., month-to-month)--3
OTHER--91
(SPECIFY)--
REFUSED---7
DON'T KNOW---8
4a. What is your monthly rent?
$----,------ MONTHLY RENTAL AMOUNT
REFUSED---7 GO TO END
DON'T KNOW---8 GO TO END
4b. Are any utilities included in the rent?
YES--1
NO--2 GO TO Q5
REFUSED---7 GO TO Q5
DON'T KNOW---8 GO TO Q5
4c. Which of the following utilities are included in the rent? Does
it include . . .
------------------------------------------------------------------------
Don't
YES NO REF know
------------------------------------------------------------------------
4ca Water?....................... 1 2 -7 -8
4cb Electric?.................... 1 2 -7 -8
4cc Gas?......................... 1 2 -7 -8
4cd Heat?........................ 1 2 -7 -8
------------------------------------------------------------------------
5. Are any of the following included in the rent? How about . . .
[[Page 43237]]
------------------------------------------------------------------------
Don't
YES NO REF know
------------------------------------------------------------------------
5a Maintenance, e.g. faucet/ 1 2 -7 -8
appliance repair?...........
5b Lawn care?................... 1 2 -7 -8
5c Snow removal?................ 1 2 -7 -8
5d Trash removal?............... 1 2 -7 -8
5e Parking in covered public 1 2 -7 -8
style garage?...............
5f Furnishings?................. 1 2 -7 -8
------------------------------------------------------------------------
6a. Are pets allowed at your rental unit?
YES--1
NO--2 GO TO 7a
REFUSED---7 GO TO 7a
DON'T KNOW---8 GO TO 7a
6b. Is there an additional fee for pets?
YES--1
NO--2 GO TO 7a
REFUSED---7 GO TO 7a
DON'T KNOW---8 GO TO 7a
6c How much is the additional fee?
$------------ AMOUNT OF PET FEE
MONTHLY--1
ANNUALLY--2
ONE-TIME DEPOSIT--3
OTHER (SPECIFY) --------------91
REFUSED---7
DON'T KNOW---8
7a. Approximately how long have you rented at this location?
NOTE: LESS THAN 1 MONTH = 1 MONTH
------------ TIME RENTED AT THIS ADDRESS MONTHS
------------ TIME RENTED AT THIS ADDRESS YEARS
REFUSED---7
DON'T KNOW---8
7b. Would you consider the place that you're renting a permanent
rental property, that is, the property is consistently rented out,
or is it a temporary rental, for example the owner is abroad and
intends to return?.
PERMANENT--1 GO TO 11a
TEMPORARY--2 GO TO 11a
REFUSED---7 GO TO 11a
DON'T KNOW---8 GO TO 11a
OWNERS ONLY
8a. If you were to rent your home on a long term basis, not as a
vacation rental, what do you think your home would rent for per
month? We are not asking you whether you want to rent it, only to
estimate what it might rent for if it were for rent.
$------------ MONTHLY RENTAL AMOUNT--SKIP TO 8c
REFUSED---7 GO TO 8b
DON'T KNOW---8 GO TO 8b
8b. Would you estimate that your home would rent for . . .
Less than $200 per month--1 GO TO END
$201 to $500 per month--2 GO TO 8c
$501 to $1,000 per month--3 GO TO 8c
$1,001 to $1,500 per month--4 GO TO 8c
$1,501 to $2,000 per month--5 GO TO 8c
$2,001 to $2,500 per month--6 GO TO 8c
$2,501 to $3,000 per month--7 GO TO 8c
$3,001 to $6000 per month--or 8 GO TO 8c
Over $6000 per month?--9 GO TO END
REFUSED---7 GO TO END
DON'T KNOW---8 GO TO END
8c. How did you arrive at the rental amount? Was it based on . . .
----------------------------------------------------------------------------------------------------------------
NOTE: ALL RESPONDENTS WILL BE ASKED Don't
ABOUT EACH REASON YES NO REF know
-------------------------------