Nonforeign Area Cost-of-Living Allowance; General Population Rental Equivalence Survey Report, 43228-43249 [06-6568]

Download as PDF sroberts on PROD1PC70 with NOTICES 43228 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) VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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: PO 00000 Frm 00135 Fmt 4703 Sfmt 4703 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 E:\FR\FM\31JYN1.SGM 31JYN1 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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. sroberts on PROD1PC70 with NOTICES 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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. PO 00000 Frm 00136 Fmt 4703 Sfmt 4703 43229 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 E:\FR\FM\31JYN1.SGM 31JYN1 sroberts on PROD1PC70 with NOTICES 43230 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 ‘‘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 PO 00000 Frm 00137 Fmt 4703 Sfmt 4703 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 E:\FR\FM\31JYN1.SGM 31JYN1 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices sroberts on PROD1PC70 with NOTICES 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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 PO 00000 Frm 00138 Fmt 4703 Sfmt 4703 43231 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 E:\FR\FM\31JYN1.SGM 31JYN1 43232 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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 PO 00000 Frm 00139 Fmt 4703 Sfmt 4703 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 E:\FR\FM\31JYN1.SGM 31JYN1 43233 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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 PO 00000 Frm 00140 Fmt 4703 Sfmt 4703 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. E:\FR\FM\31JYN1.SGM 31JYN1 43234 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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 PO 00000 Frm 00141 Fmt 4703 Sfmt 4703 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. E:\FR\FM\31JYN1.SGM 31JYN1 43235 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 ................................................................................................................................. VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00142 Fmt 4703 Sfmt 4703 E:\FR\FM\31JYN1.SGM 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 .................. 43236 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 the rent? How about . . . PO 00000 Frm 00143 Fmt 4703 Sfmt 4703 E:\FR\FM\31JYN1.SGM 31JYN1 1 1 1 1 NO REF 2 2 2 2 ¥7 ¥7 ¥7 ¥7 Don’t know ¥8 ¥8 ¥8 ¥8 43237 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 sroberts on PROD1PC70 with NOTICES 8ca 8cb 8cc 8cd 8ce 8cf VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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 PO 00000 Frm 00144 Fmt 4703 Sfmt 4703 Don’t know REF 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 E:\FR\FM\31JYN1.SGM 31JYN1 43238 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 +/- VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 $500 in annual rent with 90 percent confidence level, and the ‘‘Target’’ set was the sample size for estimating rent or rental PO 00000 Frm 00145 Fmt 4703 Sfmt 4703 equivalence at the same margin of error at the 95 percent confidence level. E:\FR\FM\31JYN1.SGM 31JYN1 43239 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 sroberts on PROD1PC70 with NOTICES Survey area Anchorage ........................................................................................................ Fairbanks ......................................................................................................... Juneau ............................................................................................................. Rest of AK ....................................................................................................... Honolulu County .............................................................................................. Hawaii County .................................................................................................. Kauai County ................................................................................................... VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00146 Fmt 4703 Sfmt 4703 Sample size 7,549 1,625 814 2,413 16,073 728 332 E:\FR\FM\31JYN1.SGM 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 43240 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 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 sroberts on PROD1PC70 with NOTICES BILLING CODE 6325–39–P VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00147 Fmt 4703 Sfmt 4703 E:\FR\FM\31JYN1.SGM 31JYN1 Responses Response rate (percent) VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00148 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 43241 EN31JY06.007</GPH> sroberts on PROD1PC70 with NOTICES Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices VerDate Aug<31>2005 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00149 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 EN31JY06.008</GPH> sroberts on PROD1PC70 with NOTICES 43242 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00150 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 43243 EN31JY06.009</GPH> sroberts on PROD1PC70 with NOTICES Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices VerDate Aug<31>2005 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00151 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 EN31JY06.010</GPH> sroberts on PROD1PC70 with NOTICES 43244 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00152 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 43245 EN31JY06.011</GPH> sroberts on PROD1PC70 with NOTICES Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices VerDate Aug<31>2005 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00153 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 EN31JY06.012</GPH> sroberts on PROD1PC70 with NOTICES 43246 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00154 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 43247 EN31JY06.013</GPH> sroberts on PROD1PC70 with NOTICES Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices VerDate Aug<31>2005 Federal Register / Vol. 71, No. 146 / Monday, July 31, 2006 / Notices 17:34 Jul 28, 2006 Jkt 208001 PO 00000 Frm 00155 Fmt 4703 Sfmt 4725 E:\FR\FM\31JYN1.SGM 31JYN1 EN31JY06.014</GPH> sroberts on PROD1PC70 with NOTICES 43248 [FR Doc. 06–6568 Filed 7–28–06; 8:45 am] BILLING CODE 6325–39–C sroberts on PROD1PC70 with NOTICES 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 VerDate Aug<31>2005 17:34 Jul 28, 2006 Jkt 208001 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). PO 00000 Frm 00156 Fmt 4703 Sfmt 4703 43249 (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. E:\FR\FM\31JYN1.SGM 31JYN1 EN31JY06.015</GPH> 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]


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OFFICE OF PERSONNEL MANAGEMENT


Nonforeign Area Cost-of-Living Allowance; General Population 
Rental Equivalence Survey Report

AGENCY: Office of Personnel Management.

ACTION: Notice.

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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
-------------------------------
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