2004 Nonforeign Area Cost-of-Living Allowance Survey Report: Pacific and Washington, DC, Areas, 44989-45023 [05-15099]

Agencies

• Office of Personnel Management
• Personnel Management Office

[Federal Register Volume 70, Number 149 (Thursday, August 4, 2005)]
[Notices]
[Pages 44989-45023]
From the Federal Register Online via the Government Printing Office [www.gpo.gov]
[FR Doc No: 05-15099]


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OFFICE OF PERSONNEL MANAGEMENT


2004 Nonforeign Area Cost-of-Living Allowance Survey Report: 
Pacific and Washington, DC, Areas

AGENCY: Office of Personnel Management.

ACTION: Notice.

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SUMMARY: This notice publishes the ``2004 Nonforeign Area Cost-of-
Living Allowance Survey Report: Pacific and Washington, DC, Areas.'' 
The Federal Government uses the results of surveys such as these to set 
cost-of-living allowance (COLA) rates for General Schedule, U.S. Postal 
Service, and certain other Federal employees in Alaska, Hawaii, Guam 
and the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin 
Islands. This report contains the results of the COLA surveys conducted 
by the Office of Personnel Management in Hawaii, Guam, and the 
Washington, DC, area during the spring and summer of 2004.

DATES: Comments on this report must be received on or before October 3, 
2005.

ADDRESSES: Send or deliver comments to Donald J. Winstead, 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: Section 591.229 of title 5, Code of Federal 
Regulations, requires the Office of Personnel Management (OPM) to 
publish nonforeign area cost-of-living allowance (COLA) survey summary 
reports in the Federal Register. We are publishing the complete ``2004 
Nonforeign Area Cost-of-Living Allowance Survey Report: Pacific and 
Washington, DC, Areas'' with this notice. This report contains the 
results of the COLA surveys conducted by OPM

[[Page 44990]]

in Hawaii, Guam, and the Washington, DC, area during the spring and 
summer of 2004.

Survey Results

    Using an index scale with Washington, DC, area living costs equal 
to 100, OPM computed index values of relative prices in the Honolulu 
County, Hawaii County, Kauai County, Maui County, and Guam and the 
Commonwealth of the Northern Mariana Islands (CNMI) COLA areas. Then 
OPM added an adjustment factor of 5.0 to the Honolulu County price 
index, 7.0 to the Hawaii County, Kauai County, and Maui County price 
indexes, and 9.0 to the Guam/CNMI price index and rounded the results 
to the nearest whole percentage point. The results show that the COLA 
rates for Hawaii County, Kauai County, and Maui County should increase 
and that the COLA rates for Honolulu County and Guam/CNMI, which are at 
the statutory maximum (25 percent), should remain unchanged.
    In a proposed rule published with this notice, OPM proposes to 
adjust COLA rates based on the results of the 2004 Pacific surveys. In 
that proposed rule, OPM also proposes to adjust COLA rates for the COLA 
areas in the Caribbean and Alaska based on surveys conducted by OPM in 
2002 and 2003. OPM published the results of these surveys previously. 
(See Appendix 1 for a listing of previously published COLA survey 
reports.)

Office of Personnel Management.
Linda M. Springer,
Director.

2004 Nonforeign Area Cost-of-Living Allowance Survey Report: Pacific 
and Washington, DC, Areas

Table of Contents

Executive Summary
1. Introduction
    1.1 Report Objectives
2. Preparing for the Survey
    2.1 COLA Advisory Committees
    2.2 Pre-Survey Meetings
    2.3 Survey Item Selection
    2.3.1 Special Considerations
    2.4 Outlet Selection
    2.5 Geographic Coverage
3. Conducting the Survey
    3.1 Pricing Period
    3.2 Non-Housing Price Data Collection
    3.2.1 Data Collection Teams
    3.2.2 Data Collection Process
    3.3 Housing (Rental) Price Data Collection
4. Analyzing the Results
    4.1 Data Review
    4.2 Special Price Computations
    4.2.1 K-12 Private Education
    4.2.2 Guam Automobile Insurance
    4.2.3 Health Insurance
    4.2.4 Water Utilities
    4.2.5 Energy Utilities Model
    4.2.6 Rental Data Hedonic Models
    4.3 Averaging Prices by Item and Area
    4.4 Computing Price Indexes
    4.4.1 Geometric Means
    4.4.2 Special Private Education Computations
    4.5 Applying Consumer Expenditure Weights
5. Final Results
6. Post Survey Meetings

List of Appendices

Appendix 1: Publication in the Federal Register of Prior Survey 
Results: 1990-2004
Appendix 2: Estimated DC Area Middle Income Annual Consumer 
Expenditures
Appendix 3: COLA Survey Items and Descriptions
Appendix 4: COLA Rental Survey Data Collection Elements
Appendix 5: Utility Usage and Calculations
Appendix 6: Hedonic Rental Data Equations and Results
Appendix 7: Final Living-Cost Results for COLA Areas

Executive Summary

    The Government pays cost-of-living allowances (COLAs) to Federal 
employees in nonforeign areas in consideration of living costs 
significantly higher than those in the Washington, DC, area. The Office 
of Personnel Management (OPM) conducts living-cost surveys to set the 
COLA rates. The methodology for conducting these surveys is prescribed 
in regulation at subpart B of part 591 of title 5 of the Code of 
Federal Regulations, as modified by the proposed rule that accompanies 
this notice.
    This report provides the results of the COLA surveys conducted by 
OPM in the spring and summer of 2004 in Honolulu County, Hawaii County, 
Kauai County, Maui County, Guam, and the Washington, DC, area. The 
report details OPM's comparison of living costs in these areas with 
living costs in the Washington, DC, area.
    For the surveys, OPM contacted about 1,200 outlets and collected 
approximately 6,000 prices on more than 240 items representing typical 
consumer purchases. OPM then combined the data using consumer 
expenditure information developed by the Bureau of Labor Statistics. 
The final results are a series of living-cost indexes, shown in Table 
1, that compare living costs in the surveyed areas to those in the 
Washington, DC, area. The index for the DC area (not shown) is 100.00 
because it is, by law, the reference area. The living-cost indexes 
shown in Table 1 include the adjustment factor prescribed at 5 CFR 
591.227.

             Table 1.--Final Living-Cost Comparison Indexes
------------------------------------------------------------------------
                        Allowance area                            Index
------------------------------------------------------------------------
Honolulu County, HI...........................................    127.78
Hawaii County, HI.............................................    119.11
Kauai County, HI..............................................    130.58
Maui County, HI...............................................    134.49
Guam/CNMI.....................................................    127.65
------------------------------------------------------------------------

1. Introduction

1.1 Report Objectives
    This report provides the results of the 2004 (i.e., ``Pacific'') 
nonforeign area cost-of-living allowance (COLA) surveys conducted by 
the Office of Personnel Management (OPM) in the spring and summer of 
2004. (Appendix 1 lists prior survey reports and their publication 
dates.) In addition to providing these results, this report describes 
how OPM prepared for and conducted the survey and how it analyzed the 
results. The results show comparative living-cost differences between 
the Pacific areas, i.e., Honolulu County, Hawaii County, Kauai County, 
Maui County, and Guam, and the Washington, DC, area. By law, 
Washington, DC, is the base or ``reference'' area for the COLA program.

2. Preparing for the Survey

2.1 COLA Advisory Committees
    Before the Pacific surveys, OPM established COLA Advisory 
Committees (CACs) in Honolulu, the Hawaii County areas of Hilo and 
Kailua Kona, Kauai, Maui, and Guam. The settlement of Caraballo, et al. 
v. United States, No. 1997-0027 (D.V.I.), August 17, 2000, provides for 
employee involvement in the administration of the COLA program. In the 
Pacific surveys, as in the 2002 surveys in the Caribbean and the 2003 
surveys in Alaska, OPM found it valuable to involve employee and agency 
representatives in planning and conducting the surveys and reviewing 
the survey results.
    Each CAC is composed of approximately 12 agency and employee 
representatives from the survey area and 2 representatives from OPM. 
The functions of the CACs include the following:

--Advising and assisting OPM in planning COLA surveys;
--Providing or arranging for data collection observers during COLA 
surveys;
--Advising and assisting OPM in reviewing survey data;
--Advising OPM on its COLA program administration, including survey 
methodology;
--Assisting OPM in disseminating information to affected employees

[[Page 44991]]

about the surveys and the COLA program; and
--Advising OPM on special situations or conditions, such as hurricanes 
and earthquakes, as they relate to OPM's authority to conduct interim 
surveys or implement some other change in response to conditions caused 
by a natural disaster or similar emergency.
2.2 Pre-Survey Meetings
    To help OPM prepare for the COLA surveys, the CACs held 3-day 
meetings in Honolulu, Hilo, Kailua Kona, Kauai, Maui, and Guam. These 
were joint meetings of the CAC, Survey Implementation Committee (SIC), 
and Technical Advisory Committee (TAC). The SIC and the TAC were 
established pursuant to the Caraballo settlement. The SIC advises and 
assists OPM in the implementation of the new COLA methodology to which 
the parties agreed. The SIC consists of five plaintiffs' 
representatives from the COLA areas and two OPM representatives. The 
TAC consists of three economists who have expertise in living-cost 
measurement. The TAC performs research for and advises the SIC.
    The CACs, SIC, and TAC reviewed the preliminary outlet and item 
lists developed by OPM for the surveys. The committee members 
researched the outlets and availability and appropriateness of the 
items in each area and made recommendations to OPM concerning the 
survey. OPM incorporated these recommendations into its survey design.
    OPM found the work of the CACs, SIC, and TAC to be extremely 
helpful and informative. The SIC and TAC's knowledge of the Caraballo 
settlement, the new COLA methodology, and the economic concepts 
underlying that methodology, combined with the CACs' knowledge of the 
local area, the popularity of items and outlets, and other information 
about the COLA area, were invaluable in helping OPM plan the survey. 
These joint CAC, SIC, and TAC meetings were particularly important 
because, under the Caraballo settlement, the SIC and TAC dissolve on 
December 31, 2005.
2.3 Survey Item Selection
    As described in Sections 2.1 and 2.2, OPM consulted with the CACs, 
SIC, and TAC as it selected survey items. OPM identified items to 
reflect a wide array of items consumers typically purchase. To 
determine what consumers purchase, OPM used the Bureau of Labor 
Statistics (BLS) 2000 Consumer Expenditure Survey (CES). OPM aggregated 
CES expenditures into the following nine major expenditure groups 
(MEGs):

--Food,
--Shelter and Utilities,
--Household Furnishings and Supplies,
--Apparel,
--Transportation,
--Medical,
--Recreation,
--Education and Communication, and
--Miscellaneous

    OPM further subdivided each MEG into primary expenditure groups 
(PEGs). In all, there were 45 PEGs. For example, OPM subdivided Food 
into the following nine PEGs:

--Cereals and Bakery Products;
--Meats, Poultry, Fish, and Eggs;
--Dairy Products;
--Fresh Fruits and Vegetables;
--Processed Foods;
--Other Food at Home;
--Nonalcoholic Beverages;
--Food Away from Home; and
--Alcoholic Beverages.

    To select survey items, OPM chose a sufficient number of items to 
represent each PEG and reduce overall price index variability. To do 
this, OPM applied the following guidelines: Each survey item should 
be--

--Relatively important (i.e., represent a fairly large expenditure) 
within the PEG;
--Relatively easy to find in both COLA and DC areas;
--Relatively common, i.e., what people typically buy;
--Relatively stable over time, e.g., not a fad item; and
--Subject to similar supply and demand functions.

    In all, OPM selected over 240 non-housing items to survey. Appendix 
2 shows how OPM organized the CES data into MEGs and PEGs, identifies 
the Detailed Expenditure Categories (DECs) for which OPM chose survey 
items, and shows estimated DC area middle income annual consumer 
expenditures for each DEC and higher level of aggregations.
    Appendix 3 lists the non-housing items surveyed by OPM and their 
descriptions. Each of these items is specifically described with an 
exact brand, model, type, and size whenever practical. Thus, OPM priced 
exactly the same items or the same quality and quantity of items in 
both the COLA and DC areas. For example, OPM priced a 10.5-ounce can of 
Campbell's Vegetable Soup in both the COLA and DC areas because it is 
typical of canned soups, and consumers commonly purchase it.
2.3.1 Special Considerations
    Health Insurance: It was not practical to compare the prices of 
exactly the same quality and quantity of health insurance between the 
COLA and Washington, DC, areas because the same array of plans is not 
offered in each area, and a significant proportion of Federal employees 
in both the COLA and DC areas subscribe to plans that are not available 
nationwide. To compare the employee health benefits premiums of these 
often highly different plans, OPM would have to adjust for differences 
in benefits and coverage. Research conducted by the parties prior to 
the Caraballo settlement indicated that this would not be feasible.
    Therefore, OPM used the non-Postal Service employee's share of the 
Federal Employees Health Benefits premiums by plan for each plan 
offered in each area and obtained from OPM's Central Personnel Data 
File (CPDF) the number of white-collar Federal employees enrolled in 
each plan. As described in Section 4.2.3 below, OPM used these data to 
compute the average ``price'' of health insurance for Federal employees 
in the COLA and DC areas.
    Housing: For housing items, OPM surveyed rental rates for specific 
kinds or classes of housing and collected detailed information about 
each housing unit. OPM surveyed the following classes of housing:

--Four bedroom, single family unit, not to exceed 3200 square feet;
--Three bedroom, single family unit, not to exceed 2600 square feet;
--Two bedroom, single family unit, not to exceed 2200 square feet;
--Three bedroom apartment unit, not to exceed 2000 square feet;
--Two bedroom apartment unit, not to exceed 1800 square feet; and
--One bedroom apartment unit, not to exceed 1400 square feet

    Appendix 4 lists the types of detailed information collected by 
OPM. OPM did not collect homeowner data, such as mortgage payments, 
maintenance expenses, or insurance. Under the Caraballo settlement, the 
parties agreed to adopt a rental equivalence approach similar to the 
one BLS uses for the Consumer Price Index. Rental equivalence compares 
the shelter value (rental value) of owned homes, rather than total 
owner costs, because the latter are influenced by the investment value 
of the home (i.e., influenced by what homeowners hope to realize as a 
profit when they sell their homes). As a rule, living-cost surveys do 
not compare how consumers invest their money.
    In the 2004 survey, OPM surveyed rents and used that as a surrogate 
for rental equivalence. In late 2004 and 2005, OPM conducted special 
research, the General Population Rental

[[Page 44992]]

Equivalence Survey (GPRES), to obtain additional rent and rental 
equivalence information to determine whether the approach OPM uses is 
appropriate. Preliminary analyses of GPRES results support OPM's 
current approach, but those analyses continue. OPM will publish the 
GPRES results in a Federal Register notice at a later date.
    Although OPM surveyed rental rates for the same classes of housing 
in each area, the type, style, size, quality, and other characteristics 
of each unit varied within each area and between the COLA and DC areas. 
As described in Section 4.2.6, OPM used hedonic regression analyses to 
hold these characteristics constant between the COLA and Washington, 
DC, area to make rental price comparisons.
2.4 Outlet Selection
    Just as it is important to select commonly-purchased items and 
survey the same items in both the DC area and COLA areas, it is 
important to select outlets frequented by consumers and find comparable 
outlets in both the COLA and DC areas. To identify comparable outlets, 
OPM categorized outlets by type (e.g., grocery store, convenience 
store, discount store, hardware store, auto dealer, and catalog 
outlet). For example, OPM surveyed grocery items at supermarkets in all 
areas because most people purchase their groceries at such stores and 
because supermarkets exist in nearly all areas. Selecting comparable 
outlets is particularly important because of the significant price 
variations that may occur between dissimilar outlets (e.g., comparing 
the price of milk at a supermarket with the price of milk at a 
convenience store).
    OPM used the above classification criteria and existing data 
sources, including previous COLA surveys, phone books, and various 
business listings, to develop initial outlet lists for the survey. OPM 
provided these lists to the CACs, SIC, and TAC and consulted with them 
on outlet selection. The committees helped OPM refine the outlet lists 
and identify other/additional outlets where local consumers generally 
purchase the items OPM planned to survey.
    OPM also priced some items by catalog; when it did, it priced the 
same items by catalog in the COLA areas and in DC areas for comparative 
purposes. To ensure consistent catalog pricing, OPM used only current 
catalogs for all catalog survey items. OPM priced 12 items by catalog 
in the Pacific and DC areas. All catalog prices included any charges 
for shipping and handling and all applicable taxes.
    In all, OPM surveyed prices from approximately 1,200 outlets. In 
the COLA survey areas, described below, OPM attempted to survey three 
popular outlets of each type, to the extent practical. For some outlet 
types, such as local phone service, there were not three outlets. In 
some areas, there were not a sufficient number of businesses to find 
three outlets of each particular type. In the Washington, DC, area, OPM 
attempted to survey nine popular outlets of each type, three in each of 
the DC survey areas described in Table 3.
2.5 Geographic Coverage
    Table 3 shows the Pacific COLA and DC survey area boundaries.

               Table 3.--Survey and Data Collection Areas
------------------------------------------------------------------------
COLA areas and reference areas                 Survey area
------------------------------------------------------------------------
Honolulu County...............  City and County of Honolulu.
Hawaii County.................  Hilo area, Kailua Kona/Waimea area.
Kauai County..................  Kauai Island.
Maui County...................  Maui Island.
Guam/CNMI.....................  Guam.
Washington, DC-DC.............  District of Columbia.
Washington, DC-MD.............  Montgomery County and Prince Georges
                                 County.
Washington, DC-VA.............  Arlington County, Fairfax County, Prince
                                 William County, City of Alexandria,
                                 City of Fairfax, City of Falls Church,
                                 City of Manassas, and City of Manassas
                                 Park.
------------------------------------------------------------------------
Note: For selected items, such as golf and air travel, these survey
  areas include additional geographic locations beyond these
  jurisdictions.

    OPM collected non-housing prices in outlets throughout the Pacific 
areas described in Table 3. To collect housing (i.e., rental) data, OPM 
contracted with Delta-21 Resources, Incorporated, a research 
organization with expertise in housing and rental data collection. 
Delta-21 surveyed rental rates in locations within these areas. In 
selecting the locations and sample sizes within these areas, OPM used 
tables from the 2000 census that showed the number of Federal employees 
and housing units by zip code.
    To collect data in the DC area, OPM divided the area into three 
survey areas, as shown in Table 3. OPM collected non-housing prices in 
outlets throughout this area. OPM surveyed certain items, including 
golf, in areas beyond the counties and cities shown in Table 3. OPM 
also surveyed the cost of air travel from Ronald Reagan Washington 
National Airport, Washington Dulles International Airport, and 
Baltimore/Washington International Airport (BWI) and surveyed the price 
of a 5-mile taxi ride originating at these airports. Both Dulles and 
BWI are outside the counties and cities shown in Table 3. Nevertheless, 
DC area residents commonly use both of these airports.
    Delta-21 surveyed rental rates throughout the DC area. As with the 
Pacific COLA areas, OPM used Census data to select specific locations 
and sample sizes within the DC area, and Delta-21 collected data 
accordingly within these locations.

3. Conducting the Survey

3.1 Pricing Period
    OPM collected data from early March through May 2004. OPM collected 
non-housing price data concurrently in the Pacific areas in March and 
collected the bulk of the DC area data in April and May. Delta-21 
collected rental data sequentially in Guam, Kauai, Kailua Kona/Waimea, 
Hilo, Maui, Honolulu County, and in the Washington, DC, area beginning 
on June 21, 2004, and ending on August 30, 2004.
3.2 Non-Housing Price Data Collection
3.2.1 Data Collection Teams
    In both the COLA and Washington, DC, areas, OPM central office 
staff collected non-housing price data. In the COLA areas, data 
collection observers designated by the local CAC

[[Page 44993]]

accompanied the OPM data collectors. Data collection observers were 
extremely helpful to OPM and the survey process by advising and 
assisting the data collectors in contacting outlets, matching items, 
and selecting substitutes. The observers also advised OPM on other 
living-cost and compensation issues relating to their areas. OPM did 
not use data collection observers in the Washington, DC, area, but OPM 
made the collected data available to the CACs.
3.2.2 Data Collection Process
    The data collector/observer teams obtained most of the data by 
visiting stores, auto dealers, and other outlets. The teams also priced 
items, such as insurance, tax preparation fees, bank interest, and 
private education tuition, by telephone. As noted in Section 2.4, OPM 
surveyed some items via catalog, including all shipping costs and any 
applicable taxes in the price. OPM also collected other data, such as 
sales tax rates and airline fares, from Web sites on the Internet.
    For all items subject to sales and/or excise taxes, OPM added the 
appropriate amount of tax to the price for computing COLA rates. For 
the Hawaii areas, OPM added 4.166 percent to account for the Hawaii 
general excise tax on businesses. In the DC area, sales tax rates 
varied by city, and some sales tax rates also varied by item, such as 
restaurant meals, within a location. Guam currently has no general 
sales or business tax that is passed on to the consumer separately at 
the time of sale.
    The data collectors collected the price of the item at the time of 
the visit to the outlet. Therefore, with certain exceptions, the data 
collectors collected the sale price, if the item was on sale, and OPM 
used that sale price in the COLA calculations. The exceptions include 
coupon prices, going-out-of-business prices, clearance prices, and 
area-wide distress sales, which OPM does not use because they are 
atypical and/or seasonal. OPM also does not collect automobile ``sale'' 
or negotiated prices. Instead, OPM obtains the sticker (i.e., non-
negotiated) price for the model and specified options. The prices are 
the manufacturer's suggested retail price (including options), 
destination charges, additional shipping charges, appropriate dealer-
added items or options, dealer mark-up, and taxes, including sales tax 
and licensing and title fees.
3.3 Housing (Rental) Price Data Collection
    As noted in Section 2.5, OPM contracted for the collection of 
rental data with Delta-21, which collected data in the Pacific areas 
and in the DC area. These data included rental prices, comprehensive 
information about the size and type of dwelling, number and types of 
rooms, amenities, and other important aspects of the dwelling that 
might influence the rental price. Appendix 4 lists the data elements 
collected by the contractor.
    The contractor identified units for rent from various sources, 
including rental property managers, realtor brokers, listing services, 
newspaper ads, grocery store bulletin boards, and casual drive-by 
observation. The contractor then visited each rental unit, took a 
photograph of the unit, made a sketch of the floor plan based on 
exterior dimensions and shape, and noted the unit's longitude and 
latitude coordinates for mapping purposes and so that OPM could 
correlate the unit with census tract information from the Bureau of the 
Census. OPM made the rental data available to the CACs, including the 
photographs, sketches, and maps.

4. Analyzing the Results

4.1 Data Review
    During and after the data collection process, the data collectors 
reviewed the data for errors and omissions. This involved reviewing the 
data item-by-item and comparing prices across outlets within an area to 
spot data entry errors, mismatches, and other mistakes.
    After all of the data had been collected in both the COLA areas and 
the Washington, DC, area, OPM staff again reviewed the data by item 
across all of the areas. One purpose was to spot errors not previously 
detected, but the principal reason was to look at substitute items.
    A substitute is an item that is similar but does not exactly match 
the description of the specified survey item. For example, one of the 
items OPM specified was a 20-pound bag of Iams dry dog food. The data 
collectors in the Pacific areas, however, discovered that some stores 
did not carry the 20-pound bag. Therefore, the data collectors priced 
an 8-pound bag instead. OPM then priced the same sized bag in the DC 
area and used the substitute price information for this item.
4.2 Special Price Computations
    After completing its data review, OPM had to make special price 
computations for five survey items: K-12 private education, Federal 
Employees Health Benefits premiums, water utilities, energy utility 
prices, and rental prices. For each of these, OPM used special 
processes to calculate appropriate values for each survey area.
4.2.1 K-12 Private Education
    One of the items OPM surveyed is the average annual tuition for 
private education, grades K-12, in each area. Generally, tuition rates 
varied by grade level, so OPM computed an overall average tuition 
``price'' for each school surveyed by averaging the tuition rates 
grade-by-grade. Section 4.4.2 below describes the additional special 
adjustments OPM applied to these ``prices'' in the price comparison 
process.
4.2.2 Guam Automobile Insurance
    OPM also surveyed the cost of automobile insurance. In each area, 
OPM surveyed the annual premium for the Chrysler, Ford, and Toyota 
automobiles specified in the survey. OPM collected the premiums for 
$100,000/$300,000 bodily injury; $25,000 property damage; $15,000 
medical or $50,000 personal injury; $100,000/$300,000 uninsured 
motorist; $100 comprehensive deductible; and $250 collision deductible 
level of coverage. (See Appendix 3 for the complete item description.) 
OPM was able to obtain premiums for this level of coverage in all areas 
except Guam.
    In Guam, insurance companies offered the same level of coverage for 
everything except medical and uninsured motorist coverage, for which 
they offered significantly lower levels of coverage. Therefore, OPM 
estimated the price of a policy in Guam as if the insurance companies 
offered the same levels of coverage found in the Washington, DC, area.
    To do this, OPM computed average prices for the portion of the 
policies that were the same in both Guam and in the Washington, DC, 
area. Because only two of the three companies surveyed provided detail 
at that level in their price quotes, OPM could do this only for those 
two companies, although it adjusted the premiums for the third company 
as described in the next paragraph. OPM then computed price indexes for 
these partial insurance polices for Guam relative to the Washington, 
DC, area. Next, OPM multiplied the surveyed prices in Guam for the 
medical and uninsured motorist coverage by those indexes to derive 
higher estimated prices for the higher level of coverage. OPM then re-
totaled the Guam premiums for the two companies using the higher prices 
for uninsured motorist and medical coverage.
    To adjust the price of the premiums for the third insurance 
company, OPM

[[Page 44994]]

first computed an adjustment factor that reflected the overall price 
increases for the other two companies. OPM then multiplied the price of 
the premiums at the third company by this factor to increase the prices 
of the policies for that company. The final result was a set of 
automobile insurance prices for all three companies that reflected the 
same level of coverage in both Guam and the Washington, DC, area to the 
extent practical.
4.2.3 Health Insurance
    As noted in Section 2.3.1, OPM surveyed the non-Postal employees' 
premium for the various Federal Employees Health Benefits (FEHB) plans 
offered in each survey area. Using enrollment information from OPM's 
CPDF, OPM computed two weighted average premium costs--one for self-
only coverage and another for family coverage--for white-collar Federal 
employees in each of the COLA areas and the Washington, DC, area. As 
shown in Table 4, OPM then computed an overall weighted average premium 
for each survey area by applying the number of white-collar Federal 
employees nationwide enrolled in self-only and family plans. OPM used 
these overall weighted average premiums as ``prices'' in the price 
averaging process described in Section 4.3 below.

                     Table 4.--2003 Average FEHB Premiums for Full-Time Permanent Employees
                                          [Non-postal employees' share]
----------------------------------------------------------------------------------------------------------------
                                                                                     Bi-weekly        Annual
                                                                      Family         weighted        weighted
                    Location                       Self  premium      premium         average         average
                                                                                      premium         premium
----------------------------------------------------------------------------------------------------------------
Honolulu County.................................          $36.22          $80.14          $62.72       $1,636.32
Hawaii County...................................           35.48           79.13           61.82        1,612.84
Kauai County....................................           35.34           80.53           62.61        1,633.45
Maui County.....................................           36.30           80.60           63.03        1,644.41
Guam/CNMI.......................................           39.77          102.42           77.57        2,023.75
DC Area.........................................           45.20           93.96           79.93        2,085.32
Nationwide Enrollment...........................         615,389         936,075
Enrollment Percentage...........................          39.67%          60.33%
----------------------------------------------------------------------------------------------------------------

4.2.4 Water Utilities
    OPM surveyed water utility rates in each of the COLA and 
Washington, DC, survey areas. To compute the ``price'' of water 
utilities, OPM assumed that the average monthly water consumption in 
each area was 7,600 gallons. This is consistent with the consumption 
amount OPM used in the previous COLA survey. OPM used this quantity 
along with the rates charged to compute the average monthly water 
utility cost by survey area. OPM used these average monthly costs as 
``prices'' in the price averaging process described in Section 4.3 
below.
4.2.5 Energy Utilities Model collected from local utility companies and 
suppliers in the COLA and DC survey areas the price of various energy 
utilities used for lighting, cooking, cooling, and other household 
needs. OPM then used the results of a heating and cooling engineering 
model to determine how many kilowatt hours of electricity, cubic feet 
of gas, and/or gallons of fuel oil are needed to maintain a specific 
model home at a constant ambient temperature of 72 degrees in each 
area. The engineering model uses local home construction information 
and climatic data from the National Oceanic and Atmospheric 
Administration and also includes the amount of electricity needed to 
run standard household appliances and lighting. For each survey area, 
OPM calculated the cost to heat and cool the model home using the 
different heating fuels and electricity for lighting and appliances. 
Although some homes use additional energy sources, such as wood, coal, 
kerosene, and solar energy, OPM did not price or include these in the 
calculations because, based on the results of the 2000 census, 
relatively few homes use these as primary energy sources.
    For the Pacific areas, OPM surveyed the price of electricity to 
compute home energy costs because the 2000 census indicated that 
electricity is the primary energy source in more than 95 percent of the 
homes in Hawaii and Guam. In the DC area, OPM surveyed the costs of all 
three fuels (gas, oil, and electricity). OPM used percentages based on 
the usage of the different fuels in each survey area to compute a 
weighted average utility fuel cost for the area. Appendix 5 shows the 
energy requirements, relative usage percentages, and total costs by 
area. OPM used these total costs as the ``price'' of utilities in the 
COLA rate calculations.
4.2.6 Rental Data Hedonic Models
    As discussed in Sections 2.5 and 3.3, OPM hired a contractor to 
collect rental data, including rents and the characteristics of each 
rental unit. At the recommendation of the TAC, OPM associated these 
rental data with census tract information published by the Bureau of 
the Census. The TAC recommended the use of census tracts, which are 
relatively small geographically, because they may be good surrogates 
for neighborhoods. The TAC believes census tract characteristics, such 
as the percentage of school age children, should reflect the character 
and quality of the neighborhoods in which the rental units are found.
    As prescribed by OPM regulations and working closely with the TAC, 
OPM used hedonic regression analysis, which is a type of multiple 
linear regression analysis, to compare rents in the COLA areas with 
rents in the DC area. Multiple linear regression is used to determine 
how the dependent variable (in this case

[[Page 44995]]

rent) is influenced by the independent variables (in this case the 
characteristics of the rental unit). OPM found that only some of the 
housing characteristics collected by Delta-21 were statistically 
meaningful in determining what influenced rent in the Pacific and DC 
areas. OPM tested various approaches using different characteristics 
and shared the results with the TAC. The TAC recommended one specific 
approach, which OPM adopted. This equation used the independent 
variables listed below, although some of the variables were ``crossed'' 
(i.e., used interactively) with other variables:

Age of unit (i.e., number of years since built or extensively 
remodeled);
Age squared;
Air conditioning (yes/no);
Clothes dryer (yes/no);
Exceptional view (yes/no);
External condition (above average/average or below);
Furnished (yes/no);
Garage (yes/no);
Landlord provides electricity (yes/no);
Neighborhood condition (above average/average or below);
Number of square feet;
Number of square feet squared;
Number of bedrooms;
Number of bathrooms;
Percent school age children in census tract;
Percent with BA degree or higher in census tract;
Percent with BA degree squared;
Recreation facilities (yes/no);
Security devices or services (yes/no);
Unit Type (house/townhouse, duplex/triplex, high rise apartment, other 
apartment); and
Survey area (Honolulu County, Hilo, Kailua Kona/Waimea, Kauai, Maui, 
Guam, or the DC area).

    As is common in this type of analysis and as was done in the 
research leading to the Caraballo settlement, OPM used semi-logarithmic 
regressions. The regression produces parameter estimates for each 
independent variable, including survey area. When the regression uses 
the Washington, DC, area as the base, the regression produces parameter 
estimates for each of the COLA survey areas: Honolulu County, Hilo 
area, Kailua Kona/Waimea area, Kauai County, Maui County, and Guam. The 
exponent of the survey area parameter estimate (i.e., after the 
estimate is converted from natural logarithms) multiplied by 100 
(following the convention used to express indexes) is the survey area's 
rent index. This index reflects the difference in rents for the COLA 
survey area relative to the Washington, DC, area, while (in effect) 
holding other significant housing characteristics constant.
    As it had with the 2002 and 2003 Caribbean and Alaska rental survey 
analyses, the TAC recommended a technical adjustment in the above 
calculations to correct for a slight bias caused by the use of 
logarithms. The exponent of the average of the logarithms of a series 
of numbers is always less than the average of the numbers. Therefore, 
at the TAC's recommendation, OPM added one-half of the standard 
deviation of the survey area parameter estimate before converting from 
natural logarithms. (See Arthur Goldberger, ``Best Linear Unbiased 
Prediction in the Generalized Linear Regression Model,'' Journal of the 
American Statistical Association, 1962.) Table 6 shows the resulting 
rent indexes. OPM used these indexes as ``prices'' in the price 
averaging process described in Section 4.3.

                         Table 6.--Rent Indexes
------------------------------------------------------------------------
                                                                  Rent
                             Area                                index
------------------------------------------------------------------------
Honolulu County..............................................    132.21
Hilo Area....................................................     81.19
Kailua Kona\Waimea Area......................................    106.75
Kauai County.................................................    117.61
Maui County..................................................    127.62
Guam.........................................................     89.52
Washington, DC, Area.........................................   *100.00
------------------------------------------------------------------------
\*\ By definition, the index of the base area is always 100.00

    Appendix 6 shows the regression equation in SAS code and the 
regression results. (SAS is a proprietary statistical analysis computer 
software package.)
4.3 Averaging Prices by Item and Area
    After OPM collected, reviewed, and made special adjustments in the 
data (as required), OPM averaged the prices for each item by COLA 
survey area. For example, OPM priced a bag of sugar at three different 
grocery stores in Honolulu County and averaged these prices to compute 
a single average price for sugar in Honolulu. If OPM collected more 
than one price for a particular matched item within the same outlet 
(e.g., priced equivalent brands), OPM used the lowest price by item and 
outlet to compute the average. (The concept is that if the item and 
brands are equivalent, consumers will choose the one with the lowest 
price.) OPM repeated this item-by-item averaging process for each area.
    For Washington, DC, area prices, OPM first averaged prices within 
each of the three DC survey areas described in Section 2.5. Then OPM 
computed a simple average of the three DC area survey averages to 
derive a single DC area average price for each survey item.
4.4 Computing Price Indexes
    Next, OPM computed a price index for each of the items found in 
both the COLA survey area and in the Washington, DC, area. To do this, 
OPM divided the COLA survey area average price by the DC area average 
price and, following the convention used to express indexes, multiplied 
this by 100. For the vast majority of survey items, OPM next applied 
consumer expenditure weights. For a few items, however, OPM first 
applied special processes as described in Sections 4.4.1 and 4.4.2 
below.
4.4.1 Geometric Means
    As described in Section 2.3, OPM selected survey items to represent 
selected detailed expenditure categories (DECs). Generally, OPM 
surveyed only one item per DEC, but in a few cases, OPM surveyed 
multiple items at a single DEC. In these cases, OPM computed the 
geometric mean of the price indexes to derive a single price index for 
the DEC. (A geometric mean is the nth root of the product of n 
different numbers and is often used in price index computations.) For 
example, OPM surveyed two prescription drugs--Amoxicillin and Nexium. 
These two different prescription drugs represent a single DEC called 
``prescription drugs.'' To derive a single price index for the DEC, OPM 
computed the geometric mean of the price index for Amoxicillin and the 
price index for Nexium.
4.4.2 Special Private Education Computations
    As noted in Section 4.2.1, OPM surveyed K-12 private education in 
the COLA and DC areas and computed an average tuition ``price'' that 
reflected all grade levels. Because not everyone sends children to 
private school, OPM made an additional special adjustment for K-12 
education by applying ``use factors.'' These use factors reflect the 
relative extent to which Federal employees make use of private 
education in the COLA and DC areas. For example, Table 8 shows a use 
factor of 2.0302 for Honolulu County. OPM computed this by dividing 
26.86 percent (the percentage of Federal employees in Honolulu County 
with at least 1 child in a private school) by 13.23 percent (the 
percentage of DC area Federal employees with at least 1 child in a 
private school). OPM obtained the percentages from the results of the 
1992/93 Federal Employee Housing and Living Patterns Survey, which is 
the

[[Page 44996]]

most current comprehensive data available. Table 8 below shows the use 
factors and the adjusted price indexes for each COLA survey area.

                         Table 8.--Summary of Private Education Use Factors and Indexes
----------------------------------------------------------------------------------------------------------------
                                                       Employees w/children                              Price
                                                        in private schools        Use        Price     index w/
                  COLA survey area                   ------------------------   factor       index        use
                                                      Local area    DC area                             factor
----------------------------------------------------------------------------------------------------------------
Honolulu County.....................................       26.86       13.23      2.0302       77.01      156.34
Hilo Area *.........................................       18.94       13.23      1.4316       36.20       51.82
Kailua Kona[bs]Waimea *............       18.94       13.23      1.4316       74.49      106.65
Kauai County........................................       22.46       13.23      1.6977       47.50       80.64
Maui County.........................................       20.39       13.23      1.5412       58.09       89.53
Guam................................................       42.26       13.23      3.1943       48.03     153.41
----------------------------------------------------------------------------------------------------------------
* Use factor data available only for Hawaii County.

4.5 Applying Consumer Expenditure Weights
    Next, OPM applied consumer expenditure weights to aggregate price 
indexes by expenditure group. As noted in Section 2.3, OPM used the 
results of the BLS Consumer Expenditure Survey to estimate the amounts 
middle income level consumers in the DC area spend on various items. 
Using expenditure weights, OPM combined the price indexes according to 
their relative importance. For example, shelter is the most important 
expenditure in terms of the COLA survey and represents about 30 percent 
of total consumer expenditures. On the other hand, the purchase of 
newspapers at newsstands represents less than 1/10th of 1 percent of 
total expenditures.
    Beginning at the lowest level of expenditure aggregation (e.g., 
sub-PEG), OPM computed the relative importance of each survey item 
within the level of aggregation, multiplied the price index times its 
expenditure percentage, and summed the cross products for all of the 
items within the level of aggregation to compute a weighted price index 
for that level. OPM repeated this process at each higher level of 
aggregation (e.g., PEG and MEG). Appendix 7 shows these calculations 
for each COLA survey area at the PEG and MEG level.
    The above process resulted in an overall price index for each of 
the Pacific COLA areas (shown in Appendix 7), but not for Hawaii 
County, which has two separate COLA survey areas. To compute an overall 
price index for Hawaii County, OPM computed weights based on the number 
of General Schedule (GS) and equivalent Federal employees stationed on 
the Hilo side of the island compared with the number stationed on the 
Kailua Kona/Waimea side of the island. OPM then multiplied each of the 
MEG indexes for Hilo and Kailua Kona by their respective GS employment 
weights and summed the cross products to produce an overall price index 
for Hawaii County. (See Appendix 7.) Table 9 shows the weights OPM 
used.

        Table 9.--Hilo and Kailua Kona/Waimea Employment Weights
------------------------------------------------------------------------
                                                       GS        Weight
                       Area                        employment  (percent)
------------------------------------------------------------------------
Hilo Area........................................        511       66.7
Kailua Kona/Waimea Area..........................        255       33.3
Total............................................        766      100.0
------------------------------------------------------------------------

5. Final Results

    To compute the overall living-cost index, OPM added to the price 
index a non-price adjustment factor. The parties in Caraballo 
negotiated these factors to reflect differences in living costs that 
might not be captured by the surveys, and OPM adopted these factors in 
regulation as part of the new methodology. The factor for Honolulu 
County is five index points. The factor for all other COLA areas in 
Hawaii is seven index points. The factor for Guam/CNMI is nine index 
points. The resulting living-cost indexes are shown in Table 10.

             Table 10.--Final Living-Cost Comparison Indexes
------------------------------------------------------------------------
                        Allowance area                            Index
------------------------------------------------------------------------
Honolulu County, HI...........................................    127.78
Hawaii County, HI.............................................    119.11
Kauai County, HI..............................................    130.58
Maui County, HI...............................................    134.49
Guam/CNMI.....................................................    127.65
------------------------------------------------------------------------

6. Post Survey Meetings

    In December 2004, the CACs, SIC, and TAC held 1-day joint meetings 
in Honolulu, Hilo, Kailua Kona, Kauai, Maui, and Guam to review the 
survey results. OPM provided the committee members with various reports 
showing all the data collected by OPM, examples of how OPM reviewed 
these data, the data OPM used in its analyses, and the results at the 
PEG and MEG level, as shown in Appendix 7. Members of the TAC explained 
how the rental data were analyzed and how OPM used expenditure weights 
to combine price indexes to reflect overall living costs.
    Subsequent to these meetings, the Hilo CAC provided extensive 
comments on the Hilo 2004 rental data. OPM found these comments to be 
very helpful and made changes as appropriate in the rental data. The 
Hilo CAC also recommended merging all of the COLA areas in the State of 
Hawaii into a single COLA area. The Kona CAC, on the other hand, 
recommended that OPM establish a separate COLA area for the Kailua 
Kona/Waimea area. OPM reviewed these recommendations and determined 
that Hawaii County should remain a single COLA area for now. OPM will 
reconsider the definitions of the COLA areas in Hawaii after the next 
Pacific survey, which will be conducted in 2007.

Appendix 1--Publication in the Federal Register of Prior Survey 
Results: 1990--2003

------------------------------------------------------------------------
           Citation                             Contents
------------------------------------------------------------------------
69 FR 12002...................  Report on 2003 living-cost surveys
                                 conducted in Alaska.
69 FR 6020....................  Report on 2002 living-cost surveys
                                 conducted in Puerto Rico and the U.S.
                                 Virgin Islands.

[[Page 44997]]

 
65 FR 44103...................  Report on 1998 living-cost surveys
                                 conducted in Alaska, Hawaii, Guam,
                                 Puerto Rico, and the U.S. Virgin
                                 Islands.
63 FR 56432...................  Report on 1997 living-cost surveys
                                 conducted in Alaska, Hawaii, Guam,
                                 Puerto Rico, and the U.S. Virgin
                                 Islands.
62 FR 14190...................  Report on 1996 living-cost surveys
                                 conducted in Alaska, Hawaii, Guam,
                                 Puerto Rico, and the U.S. Virgin
                                 Islands.
61 FR 4070....................  Report on winter 1995 living-cost
                                 surveys conducted in Alaska.
60 FR 61332...................  Report on summer 1994 living-cost
                                 surveys conducted in Hawaii, Guam,
                                 Puerto Rico, and the U.S. Virgin
                                 Islands.
59 FR 45066...................  Report on winter 1994 living-cost
                                 surveys conducted in Alaska.
58 FR 45558...................  Report on summer 1992 and winter 1993
                                 living-cost surveys conducted in
                                 Alaska, Hawaii, Guam, Puerto Rico, and
                                 the U.S. Virgin Islands.
58 FR 27316...................  Report on summer 1993 living-cost
                                 surveys conducted in Hawaii, Guam,
                                 Puerto Rico, and the U.S. Virgin
                                 Islands.
57 FR 58556...................  Report on summer 1991 and winter 1992
                                 living-cost surveys conducted in
                                 Alaska, Hawaii, Guam, Puerto Rico, and
                                 the U.S. Virgin Islands.
56 FR 7902....................  Report on summer 1990 living-cost
                                 surveys conducted in Alaska, Hawaii,
                                 Guam, Puerto Rico, and the U.S. Virgin
                                 Islands.
------------------------------------------------------------------------

Appendix 2.--Estimated DC Area Middle Income Annual Consumer 
Expenditures

    (Asterisks show Detailed Expenditure Categories (DECs) for which 
OPM surveyed items.)

----------------------------------------------------------------------------------------------------------------
       Level                   Code                                         Category name           Expenditures
----------------------------------------------------------------------------------------------------------------
1.................  TOTALEXP..................  .................  Total Expenditure..............    $50,478.63
2.................  FOODTOTL..................  MEG..............    Food                               6,295.89
3.................  CERBAKRY..................  PEG..............    Cereals and bakery products..        469.08
4.................  CEREAL....................  .................     Cereals and cereal products.        166.15
5.................  010110....................  .................      Flour......................          9.36
5.................  010120....................  .................      Prepared flour mixes.......         15.24
5.................  010210....................  .................      Ready-to-eat and cooked             92.05
                                                                        cereals*.
5.................  010310....................  .................      Rice*......................         20.51
5.................  010320....................  .................      Pasta, cornmeal and other           28.98
                                                                        cereal products*.
4.................  BAKERY....................  .................     Bakery products.............        302.94
5.................  BREAD.....................  .................      Bread......................         86.62
6.................  020110....................  .................       White bread*..............         36.93
6.................  020210....................  .................       Bread, other than white*..         49.69
5.................  CRAKCOOK..................  .................      Crackers and cookies.......         69.88
6.................  020510....................  .................       Cookies*..................         45.17
6.................  020610....................  .................       Crackers..................         24.70
5.................  020810....................  .................      Frozen and refrigerated             23.52
                                                                        bakery products*.
5.................  OTHBAKRY..................  .................      Other bakery products......        122.92
6.................  020310....................  .................       Biscuits and rolls*.......         41.87
6.................  020410....................  .................       Cakes and cupcakes*.......         38.56
6.................  020620....................  .................       Bread and cracker products          3.34
6.................  020710....................  .................       Sweetrolls, coffee cakes,          28.98
                                                                         doughnuts.
6.................  020820....................  .................       Pies, tarts, turnovers....         10.17
3.................  ANIMAL....................  PEG..............    Meats, poultry, fish, and            763.51
                                                                      eggs.
4.................  BEEF......................  .................     Beef........................        191.96
5.................  030110....................  .................      Ground beef*...............         74.89
5.................  ROAST.....................  .................      Roast......................         32.98
6.................  030210....................  .................       Chuck roast*..............          9.82
6.................  030310....................  .................       Round roast*..............          7.66
6.................  030410....................  .................       Other roast...............         15.51
5.................  STEAK.....................  .................      Steak......................         70.41
6.................  030510....................  .................       Round steak*..............         11.50
6.................  030610....................  .................       Sirloin steak*............         21.63
6.................  030710....................  .................       Other steak...............         37.29
5.................  030810....................  .................      Other beef.................         13.67
4.................  PORK......................  .................     Pork........................        117.76
5.................  040110....................  .................      Bacon*.....................         19.09
5.................  040210....................  .................      Pork chops*................         27.43
5.................  HAM.......................  .................      Ham........................         27.97
6.................  040310....................  .................       Ham, not canned*..........         26.30
6.................  040610....................  .................       Canned ham*...............          1.67
5.................  040510....................  .................      Sausage....................         19.55
5.................  040410....................  .................      Other pork.................         23.72
4.................  OTHRMEAT..................  .................     Other meats.................         92.84
5.................  050110....................  .................      Frankfurters*..............         19.84
5.................  LNCHMEAT..................  .................      Lunch meats (cold cuts)....         62.16
6.................  050210....................  .................       Bologna, liverwurst,               16.80
                                                                         salami*.
6.................  050310....................  .................       Other lunchmeats..........         45.37
5.................  LAMBOTHR..................  .................      Lamb, organ meats and               10.84
                                                                        others.
6.................  050410....................  .................       Lamb and organ meats......          5.95
6.................  050900....................  .................       Mutton, goat and game.....          4.89

[[Page 44998]]

 
4.................  POULTRY...................  .................     Poultry.....................        158.21
5.................  CHICKEN...................  .................    Fresh and frozen chickens            125.84
6.................  060110....................  .................      Fresh and frozen whole              34.20
                                                                        chicken*.
6.................  060210....................  .................       Fresh and frozen chicken           91.63
                                                                         parts*.
5.................  060310....................  .................      Other poultry..............         32.37
4.................  FISHSEA...................  .................     Fish and seafood............        168.07
5.................  070110....................  .................      Canned fish and seafood*...         23.42
5.................  070230....................  .................      Fresh fish and shellfish*..         99.54
5.................  070240....................  .................      Frozen fish and shellfish*.         45.11
4.................  080110....................  .................     Eggs........................         34.67
3.................  DAIRY.....................  PEG..............    Dairy products...............        348.56
4.................  MILKCRM...................  .................     Fresh milk and cream........        128.13
5.................  090110....................  .................      Fresh milk, all types*.....        115.34
5.................  090210....................  .................      Cream......................         12.78
4.................  OTHDAIRY..................  .................     Other dairy products........        220.43
5.................  100110....................  .................      Butter.....................         19.44
5.................  100210....................  .................      Cheese*....................        105.53
5.................  100410....................  .................      Ice cream and related               64.36
                                                                        products*.
5.................  100510....................  .................      Miscellaneous dairy                 31.10
                                                                        products.
3.................  FRUITVEG..................  PEG..............    Fruits and vegetables........        385.44
4.................  FRSHFRUT..................  .................     Fresh fruits................        194.98
5.................  110110....................  .................      Apples*....................         36.70
5.................  110210....................  .................      Bananas*...................         33.87
5.................  110310....................  .................      Oranges*...................         19.74
5.................  110510....................  .................      Citrus fruits, excluding            15.47
                                                                        oranges.
5.................  110410....................  .................      Other fresh fruits.........         89.20
4.................  FRESHVEG..................  .................     Fresh vegetables............        190.46
5.................  120110....................  .................      Potatoes*..................         35.89
5.................  120210....................  .................      Lettuce*...................         24.14
5.................  120310....................  .................      Tomatoes*..................         36.87
5.................  120410....................  .................      Other fresh vegetables.....         93.56
3.................  PROCFOOD..................  PEG..............    Processed Foods..............        778.76
4.................  PROCFRUT..................  .................     Processed fruits............        136.45
5.................  FRZNFRUT..................  .................      Frozen fruits and fruit             14.23
                                                                        juices.
6.................  130110....................  .................       Frozen orange juice*......          7.17
6.................  130121....................  .................       Frozen fruits.............          3.39
6.................  130122....................  .................       Frozen fruit juices.......          3.67
5.................  130310....................  .................      Canned fruits*.............         17.39
5.................  130320....................  .................      Dried fruit................          6.56
5.................  130211....................  ....