Report on Winter 1995 Surveys Used to Determine Cost-of-Living Allowances in Alaska

Summary

This notice publishes the ``Report To OPM On Living Costs In Anchorage, Fairbanks, Juneau, The Rest Of The State Of Alaska, And In The Washington, DC, Area, November 6, 1995,'' prepared by Jack Faucett Associates under Government contract OPM-94-BP-3816.

Full text

SUMMARY: This notice publishes the ``Report To OPM On Living Costs In 
Anchorage, Fairbanks, Juneau, The Rest Of The State Of Alaska, And In 
The Washington, DC, Area, November 6, 1995,'' prepared by Jack Faucett 
Associates under Government contract OPM-94-BP-3816.

DATES: Comments must be received on or before April 2, 1996.

ADDRESSES: Send or deliver comments to Allan G. Hearne, Salary Systems 
Division, Office of Compensation Policy, Human Resources Systems 
Service, Office of Personnel Management, Room 6H31, 1900 E Street NW., 
Washington, DC 20415, or FAX to (202) 606-4264.

FOR FURTHER INFORMATION CONTACT: Allan G. Hearne, (202) 606-2838.

SUPPLEMENTARY INFORMATION: Sections 591.205(d) and 591.206(c) of title 
5, Code of Federal Regulations, require that nonforeign area cost-of-
living allowance (COLA) survey summaries and calculations be published 
in the Federal Register. Accordingly, OPM is publishing the complete 
``Report To OPM On Living Costs In Anchorage, Fairbanks, Juneau, The 
Rest Of The State Of Alaska, And In The Washington, DC, Area, November 
6, 1995,'' produced by Jack Faucett Associates under contract with OPM. 
This report explains in detail the methodologies, calculations, and 
findings of the winter 1995 living-cost surveys.
    Survey Results. Jack Faucett Associates computed index values of 
relative living costs in the allowance areas using an index scale where 
the living costs in the Washington, DC, area equal 100. (See the 
Executive Summary of the report.) OPM notes that the winter survey 
indices showed that the COLA rate for the Rest of the State of Alaska 
is currently set at the proper level but that the rates authorized for 
all of the other Alaska allowance areas are above levels warranted by 
the indices. However, the Treasury, Postal Service and General 
Government Appropriations Act, 1992 (Pub. L. 102-141), as amended, 
prohibits reductions in COLA rates through December 31, 1998. 
Therefore, OPM is not proposing any adjustments in the COLA rates in 
these allowance areas at this time.

Office of Personnel Management.
James B. King,
Director.

Table of Contents

Executive Summary

1. Introduction
    1.1  Report Objections
    1.2  Changes in This Year's Survey
    1.2.1  Three-Year CES Moving Average
    1.2.2  New Living Communities
    1.2.3  Historical Housing Data
    1.3  Pricing Period
2. The COLA Model
    2.1  Measurement of Living-Cost Differences
    2.2  Step 1: Identifying the Target Population
    2.2.1  Federal Salaries
    2.2.2  Federal Employment Weights
    2.3  Step 2: Estimating How People Spend Their Money
    2.3.1  Consumer Expenditure Survey (CES)
    2.3.2  Expenditure Categories and Components
    2.4  Step 3: Selecting Items and Outlets
    2.4.1  Item Selections--The Market Basket
    2.4.2  Geographic Coverage and Outlet Selection
    2.4.2.1  Geographic Areas
    2.4.2.2  Similarity of Outlets
    2.4.2.3  Catelog Pricing
    2.5  Step 4: Surveying Prices
    2.5.1  In-House Research Staff
    2.5.2  Field Researchers--``Research Associates''
    2.5.3  Data Collection Materials
    2.5.4  Inclusion of Sales and Excise Taxes
    2.5.5  JFA's Onsite Visits
    2.5.6  Special Considerations in Selection Areas
    2.5.6.1  Surveying the Washington, DC Area
    2.6  Step 5: Analyzing Data and Computing Indexes
    2.6.1  General Formulae
    2.6.1.1  Indexes
    2.6.1.2  Item Weights
    2.6.1.3  Category and Component Weights
    2.6.2  Computing the Overall Index
3. Consumption Goods and Services
    3.1  Categories and Category Weights
    3.2  Goods and Services Data Collection--Special Considerations
    3.2.1  Restaurant Pricing
    3.3  Goods and Services Survey Results
4. Housing
    4.1  Component Overview
    4.2  Housing Model
    4.2.1  Expenditure Research
    4.2.2  House Profiles
    4.2.3  Living Community Selection
    4.2.4  Housing-Related Expenses
    4.2.4.1  Utilities
    4.2.4.2  Real Estate Taxes
    4.2.4.3  Owners/Renters Insurance
    4.2.4.4  Home Maintenance
    4.2.4.5  Telephone
    4.3  Housing Data Collection Procedures
    4.3.1  Homeowner Data Collection
    4.3.2  Renter Data Collection
    4.4  Housing Analysis
    4.4.1  Homeowner Data Analysis
    4.4.2  Rental Data Analysis
    4.5  Housing Survey Results
5. Transportation
    5.1  Component Overview
    5.2  Private Transportation Methodology
    5.2.1  Vehicle Selection and Pricing
    5.2.2  Vehicle Trade Cycle
    5.2.3  Fuel Performance and Type
    5.2.3.1  Impact of Temperature upon Fuel Performance
    5.2.3.2  Impact of Road Surface upon Fuel Performance
    5.2.3.3  Impact of Gradient Upon Fuel Performance
    5.2.3.4  Overall Impact upon Fuel Performance
    5.2.4  Vehicle Maintenance
    5.2.5  Tires
    5.2.6  License and Registration Fees, and Miscellaneous Tax
    5.2.7  Depreciation
    5.2.8  Finance Expense
    5.2.9  Vehicle Insurance
    5.2.10  Overall Annual Costs
    5.3  Other Transportation Costs--Air Fares
    5.4  Transportation Component Analyses
6. Miscellaneous Expenses
    6.1  Component Overview
    6.2  Component Weights
    6.3  Component Categories
    6.3.1  Medical Expense Category
    6.3.2  Contributions Category
    6.3.3  Personal Insurance and Retirement Category
    6.4  Miscellaneous Expense Analyses
7. Final Results
    7.1  Total Comparative Cost Indexes

List of Appendices

Appendix 1: Publication in the Federal Register of Results of 
Nonforeign Area Living-Cost Surveys: 1990--1994
Appendix 2: Federal Employment Weights
Appendix 3: Consumer Expenditure Surveys (CES) Item Weights
Appendix 4: CES Category and Component Weights
Appendix 5: Item Descriptions
Appendix 6: Pricing Changes
Appendix 7: OMB-Approved Survey Materials
Appendix 8: Consumption Goods and Services Analysis
Appendix 9: OPM Living Community List
Appendix 10: Historical Home Market Values and Interest Rates
Appendix 11: Historical Housing Data
Appendix 12: Rental Data Analyses
Appendix 13: Housing Cost Analysis
Appendix 14: Housing Analysis
Appendix 15: Private Transportation Cost Analysis
Appendix 16: Air Fares and Other Transportation Expenses Cost 
Analysis
Appendix 17: Transportation Analysis
Appendix 18: Miscellaneous Expense Analysis
Appendix 19: Final Indexes

Executive Summary

    This report provides the results of the winter 1995 living-cost 
surveys and compares living costs in Alaska nonforeign cost-of-living 
allowance (COLA) areas relative to the Washington, DC area.
    The surveys and analyses were conducted by Jack Faucett Associates 
(JFA), an economics consulting firm located in Bethesda, Maryland, and 
its subcontractor, Runzheimer International, a Wisconsin-based firm, 
specializing in the collection and analysis of cost-of-living 
information. The study was conducted for the Office of Personnel 
Management (OPM) under contract OPM-94-BP-3816. The contract requires 
JFA to:
    (1) Survey living costs in four allowance areas and in the 
Washington, DC area, and
    (2) Compare living costs between the allowance areas and the DC 
area.
    For this study, JFA and Runzheimer researched more than 1,000 
outlets and gathered more than 5,500 prices on more than 200 items 
representing typical consumer purchases. These prices were then 
combined using consumer expenditure information developed by the Bureau 
of Labor Statistics. The final result of the study is a series of 
living-cost indexes, shown in the table below, which show the living-
costs in each of the allowance areas relative to the Washington, DC 
area. The index for the DC area (not shown) is 100.00 because it is, by 
definition, the reference area.

                Table E-1.--Final Cost Comparison Indexes               
------------------------------------------------------------------------
                        Allowance area                            Index 
------------------------------------------------------------------------
Anchorage, Alaska.............................................    105.14
Fairbanks, Alaska.............................................    108.64
Juneau, Alaska................................................    108.33
The rest of the State of Alaska...............................    126.19
------------------------------------------------------------------------

    OPM implemented a number of improvements for the winter 1995 
survey. These improvements included:

--Using a moving average to introduce new weights based on the results 
of the Bureau of Labor Statistics' Consumer Expenditure Surveys;
--Using new representative income levels based on the 1994 distribution 
of salaries of Federal employess in the allowance areas;
--Selecting new living communities based on the results of the 1992 
Federal Employee Housing and Living Patterns Survey;
--Incorporating historical housing data to reflect both newly purchased 
and previously purchased homes;
--Using the median home value in place of trimming and trend analyses 
used in previous surveys; and
--Using the Goods and Services index to reflect relative expenditures 
for cash contributions.

    These changes as well as the data collection and analysis 
procedures already employed in the survey are discussed in the various 
sections of this report.

1. Introduction

1.1  Report Objectives

    This comprehensive report culminates data collection and research 
work undertaken in winter 1995 as required by Tasks 1 and 2 of contract 
OPM-94-BP-3816 between the Office of Personnel Management (OPM) and 
Jack Faucett Associates (JFA). This report only provides the results of 
the winter 1995 surveys. A listing of earlier reports that provided the 
results of previous surveys is shown in Appendix 1.
    The analyses show the comparative living-cost differences between 
the Washington, DC area and the following allowance areas:

1. City of Anchorage, Alaska
2. City of Fairbanks, Alaska
3. City of Juneau, Alaska
4. The rest of the State of Alaska

    By law, Washington, DC is the base of ``reference'' area for the 
nonforeign area cost-of-living allowance (COLA) program.

1.2  Changes in This Year's Survey

    One of the obvious changes this year was OPM's selection of a new 
contractor for living-cost surveys and analyses: JFA. JFA subcontracted 
a substantial portion of the work to Runzheimer International, OPM's 
previous contractor for the COLA program.
    OPM directed JFA to make several changes to the survey and 
analyses. Some of the key changes this year included:

--Using a moving average to introduce new weights based on the results 
of the Bureau of Labor Statistics' Consumer Expenditure Surveys (CES);
--Using new representative incomes based on the 1994 distribution of 
salaries of Federal employees in the allowance areas;
--Selecting new living communities based on the results of the 1992 
Federal Employee Housing and Living Patterns Survey;
--Incorporating historical housing data to reflect both newly purchased 
and previously purchased units;
--Using the median home value in place of trimming and trend analyses 
used in previous surveys; and
--Using the Goods and Services index to reflect relative expenditures 
for cash contributions.

    Three of these changes are discussed further below. The other 
changes are discussed where applicable in the report.
1.2.1  Three-Year CES Moving Average
    One change was the introduction of a three-year moving average of 
CES data in calculating the weights used to combine price indexes. In 
prior years, expenditure weights were based on the 1988 CES, and OPM 
wanted to use more current CES information.
    Rather than simply replacing the 1988 CES data with the most recent 
(1992) CES data, OPM implemented a system that would allow the gradual 
introduction of new CES data over time, thereby reducing the impact 
that short-term changes in CES might have on the living-cost indexes. 
In future surveys, OPM plans to include current CES information and 
drop the oldest CES data to maintain a three-year moving average. 
Appendices 3 and 4 show the CES data used in this study.
1.2.2  New Living Communities
    Another change was the selection of new living communities based on 
the results of the 1992 Federal Employee Housing and Living Patterns 
Survey. In that survey, employees were asked to provide their 
residential zip codes. OPM used this information to refine community 
selection.
    Two types of changes were made. In areas with relatively large 
concentrations of Federal employees and sufficient housing data, OPM 
selected communities to reflect the areas where Federal employees 
typically lived.
    The updated list of communities is provided in Appendix 9. These 
are the communities in which house sales and rental rates were 
collected. The communities were also used to determine the normal 
shopping radius and the outlets at which price were collected.
1.2.3  Historical Housing Data
    A third change was the incorporation of historical housing data to 
reflect not only the prices paid for recent home purchases but also for 
homes purchased in prior years. Appendix 10 shows the home market 
values, interest rates, and annual principal and interest payments for 
each area by year and income level. Appendix 11 shows how the principal 
and interest payments were combined using weights based on the percent 
of Federal employees presumed to have purchased their homes in each 
given year. The weights were derived from the results of the 1992 
Federal Employee Housing and Living Patterns Survey. 1.3  Pricing Period

    The prices were collected in the allowance areas and in the 
Washington, DC area in February 1995. As with the previous surveys, the 
prices of some items--those dependent upon the pricing of other items--
were collected slightly later (i.e., in March and April 1995) In 
addition, individual item prices not meeting OPM's quality control 
procedures were resurveyed in April and used to verify or replace the 
original prices.
    As done in previous surveys, JFA included some catalog sales in its 
survey. Only catalogs that sell merchandise in both the allowance areas 
and the Washington, D.C. area, were used. To ensure consistent seasonal 
catalog pricing, JFA used winter catalogs for the catalog items 
surveyed.

2. The COLA Model

2.1  Measurement of Living-Cost Differences

    A common and widely accepted way to measure living-cost differences 
between and among locations is to select representative items that 
people purchase in these locations and to calculate the respective cost 
differences, combining them according to their importance to each other 
(as measured by relative percentage of expenditures). The COLA model 
applies this methodology to compare the living costs in each of the 
allowance areas with the living costs in Washington, DC area.
    Moving from this basic concept to computing comparative living 
costs between each allowance area and the Washington, DC area involves 
five main steps:
    Step 1: Identify the segment of the population for which the 
analysis is targeted (i.e., the target population).
    Step 2: Estimate how these people spend their money.
    Step 3: Select items to represent the types of expenditures people 
usually make and outlets at which people typically make purchases.
    Step 4: Conduct pricing surveys of the selected items in each area.
    Step 5: Analyze cost ratios for the selected items and aggregate 
them according to the relative importance of each item.

2.2  Step 1: Identifying the Target Population

    The study estimates living-cost differences for nonmilitary Federal 
employees who have annual base salaries between approximately $12,000 
and $87,000, the range of the General Schedule. Because living costs 
may vary depending on an employee's income level, living costs are 
analyzed at three income levels.
2.2.1  Federal Salaries
    To determine the appropriate income levels, OPM analyzed the 1994 
distribution of salaries for all General Schedule employees in all of 
the allowance areas combined. OPM divided this distribution into three 
groups of equal size and identified the median salary in each of the 
groups. These values were then rounded to the nearest $100 to produce 
the three representative income levels of $20,800, $31,500, and 
$48,300.
    The study analyzes living costs at each of these three income 
levels. The results are three sets of estimated expenditures for each 
allowance area and for the Washington, DC area. To combine these 
estimated expenditures into a single overall index for the area, JFA 
used employment weights provided by OPM.
2.2.2  Federal Employment Weights
    As with the income levels, the OPM employment weights were derived 
from the distribution of General Schedule employees by salary level. 
Using the salary parameters identified in the income analysis described 
above, OPM determined the number of General Schedule employees in each 
salary group in each allowance area. Using a moving average similar to 
that used with the CES data (see section 1.2.1), OPM combined these 
data with the same type of information for the previous two years and 
calculated the percent of the General Schedule workforce in each income 
group in each area. These percentages were the weights that JFA used. 
Appendix 2 shows the General Schedule employment distribution and how 
the percentage weights were derived.

2.3  Step 2: Estimating How People Spend Their Money

2.3.1.  Consumer Expenditure Survey (CES)
    Expenditure patterns for employees for all areas, including the 
Washington, D.C. area, are based on national data from the CES. OPM 
obtained from the Bureau of Labor Statistics ``prepublished'' CES 
results for 1988, 1991, 1992. As discussed in section 1.2.1, these 
three years of CES data were combined using a moving average.
    CES data are used in two ways: to identify appropriate items for 
the survey and to derive item, category, and component weights. The 
item weights are not income-sensitive. However, aggregated CES data are 
analyzed by income level to derive category and component weights. 
These weights are income-sensitive. The CES data used in this study are 
shown in Appendix 3 and 4.
    The Bureau of Labor Statistics has advised OPM that 
``prepublished'' CES data may not be statistically significant. To 
OPM's knowledge, however, it is the only source of comprehensive 
consumer expenditure information by income level. Therefore, it is used 
in the model.
2.3.2  Expenditure Categories and Components
    The CES groupings expenses into small, logical families of items. 
For example, the report divided money spent by families on beef into 
four groups: ground beef, roast, steak and other beef. The steak and 
roast groupings were further separated into smaller clusters of items 
(e.g., sirloin and round steak, chuck and round roast).
    Using the CES data, the items were sorted into the four main cost 
components specified in OPM regulations: Consumption Goods and 
Services, Transportation, Housing, and Miscellaneous Expenses. To 
develop weighting patterns for the three income levels, JFA performed 
linear regression analyses on the CES data shown in Appendix 3.\1\ 
These analyses produced estimated expenditures at the three income 
levels identified in section 2.2.1 above. JFA converted these 
expenditures to percentages of total expenditures for the four 
components to produce the values shown in the table below. The values 
were the weights JFA used to combine the expenditures for each of the 
components into an overall value for each income level in each 
allowance area and the Washington, DC area.

    \1\ The midpoint of the moving average of CES data was 1991. 
Therefore, for the purposes of these regressions, OPM provided 
adjusted Federal salaries to reflect 1991 pay rates. OPM used the 
pay increases for 1992 (4.2%), 1993 (3.7%), and 1994 (0.0%) to 
deflate the 1994 salaries. This produced adjusted Federal salaries 
of $19,250, $29,150, and $44,700 for use in the regression 
equations. Table 2-1.--Component Expenses Expressed as a Percentage of Total Expenses                   
----------------------------------------------------------------------------------------------------------------
                                    Income     Goods and                                                        
       Income level 1994          level 1991    services     Housing    Transportation     Misc.        Total   
                                   adjusted    (percent)    (percent)      (percent)     (percent)    (percent) 
----------------------------------------------------------------------------------------------------------------
$20,800........................      $19,250        40.10        25.01          18.93         15.96       100.00
31,500.........................       29,150        39.47        23.98          18.66         17.88       100.00
48,300.........................       44,700        38.87        23.01          18.41         19.71       100.00
----------------------------------------------------------------------------------------------------------------
(Values may not total because of rounding.)                                                                     

    Goods and services items were further sorted into ten categories 
and linear regression techniques were used to estimate expenditures on 
these ten categories by income level. The weights for these categories 
are shown in section 3.1. The same technique was also used to compute 
category weights for the Transportation and Miscellaneous Components 
and to produce ratios of renters to homeowners at each income level.

2.4  Step 3: Selecting Items and Outlets

2.4.1  Item Selections--The Market Basket
    As noted above, CES items were grouped into ``clusters'' of 
expenses to determine which items to survey. These clusters were chosen 
so that no market basket item would have overwhelmingly large or 
insignificantly small item weight.
    For each of these clusters, a set of items to price was identified. 
Collectively, these items are called a ``market basket.'' Because it 
would have been impractical to survey all of the thousands of items 
consumers might buy, the market basket contains representative items, 
such as cheddar cheese, that represents itself and the many other 
related items that consumers purchase (e.g., Edam, Gouda, Jack, Swiss, 
et cetera). JFA's market basket had more than 200 items ranging from 
table salt to new cars to home purchases.
    The items selected were representative of other similar items, 
commonly purchased, and readily available in all areas. For example, a 
10.5-ounce can of Campbell's vegetable soup was selected for the survey 
because it is representative of canned and packaged soups, is a 
commonly-purchased brand, and is found in all areas. Whenever 
practical, the item description included the exact brand, model, type, 
and size, so that exactly the same items could be priced in all areas 
if possible. Appendix 5 provides a list of the items surveyed and their 
descriptions.
    Changes to the item list and descriptions are an important aspect 
of the COLA survey. These changes are necessary to improve the survey 
and keep the items' descriptions current. For this survey, JFA changed 
several of the items or descriptions. The changes and the reasons for 
each are listed in Appendix 6.
2.4.2  Geographic Coverage and Outlet Selection
    Just as it was important to select commonly-purchased items and 
survey the same items in all areas, it was important to select outlets 
frequented by consumers and find equivalent outlets in all areas. This 
involved deciding which geographic areas to survey and which outlets to 
survey within these geographic areas.
2.4.2.1  Geographic Areas
    For some areas, the choice of which area(s) to survey was obvious. 
In Nome, for example, the whole city is surveyed because Nome is a 
relatively small city and Federal employees live throughout the city.
    For other areas, specific communities had to be identified. To do 
this, OPM used the results of the 1992 Federal Employee Housing and 
Living Patterns Survey. Among other things, that survey obtained 
information on where Federal employees lived. OPM used this information 
to select the communities in which housing costs would be priced. JFA 
then identified outlets within a normal shopping radius of these 
housing communities.
2.4.2.2  Similarity of Outlets
    Whenever possible, JFA selected popular outlets that were 
comparable to outlets in all areas. For example, JFA surveyed the price 
of grocery items at supermarkets in all areas because most people 
purchase their groceries at such stories and because supermarkets are 
found in all areas.\2\ The selection of comparable outlets was 
particularly important because comparing the prices of items purchased 
at dissimilar outlets would be inappropriate (e.g., comparing the price 
of a box of cereal at a supermarket with one sold at a convenience 
store).

    \2\ In the Washington, DC, area, JFA surveyed groceries at two 
kinds of supermarkets (i.e., full-service supermarkets and 
``warehouse-type'' supermarkets) because both types of grocery 
stores are common in this area. JFA did not survey ``warehouse-
type'' grocery stores in any other area because they are relatively 
uncommon and not frequented by most Federal employees.
---------------------------------------------------------------------------

    Although major supermarkets, department stores, and discount stores 
represented a sizable portions of the survey, JFA also selected outlets 
to represent the diversity of consumer shopping. For example, JFA could 
have used department stores for pricing all clothing items surveyed. 
This would not have reflected, however, the range of consumer choices. 
Therefore, JFA also priced some clothing items in men's and women's 
clothing stores, other clothing items in department stores, others in 
shoe stores, and still others in discount stores. For each item, the 
same type of outlet (e.g., clothing store, discount store, department 
store) was selected in each area whenever possible.
2.4.2.3  Catalog Pricing
    A limited amount of catalog pricing was included in the survey to 
reflect this common purchasing option. Eight item prices were surveyed 
by catalog. OPM selected these items based on comments it received from 
Federal employees. Catalog pricing also allowed the comparison of 
comparable items that would have been difficult to price otherwise. Of 
course, all catalog prices included any charges for shipping and 
handling and all applicable taxes.

2.5  Step 4: Surveying Prices

    As noted earlier, JFA obtained approximately 5,500 prices on more 
than 200 items from 1,000 outlets. In each survey area, JFA attempted 
to get at least three price quotes for each item, with certain 
exceptions. For example, essentially all of the available home sales 
and rental data meeting the specifications were obtained. For other 
items, such as utilities and real estate tax rates, only one quote was 
obtained in each area because these items have uniform rates within an 
area. Because the Washington, DC area has six survey communities, JFA 
attempted to get at least 18 price quotes for most items in this area. To accomplish this, JFA used various information-gathering 
approaches. These are described below.
2.5.1  In-House Research Staff
    JFA's research personnel, and those of Runzheimer, its 
subcontractor, played a major role in all data-collection activities. 
These professionals:

--Contacted manufacturers, trade associations, governmental agencies, 
and retail establishments to ensure that suitable items were selected 
and priced at common types of outlets;
--Contacted real estate professionals in each survey area to obtain 
general information as well as specific rental rates and home market 
values;
--Conducted pricing surveys, onsite and by telephone;
--Served as a liaison for field researchers who collected price 
information onsite;
--Performed hundreds of quality control checks, often verifying survey 
data through telephone calls and comparing current data-gathering 
results with those from earlier surveys; and
--Analyzed and computed the item, category, component, and total 
comparative cost indexes.
2.5.2  Field Researchers--``Research Associates''
    Most of the price data were collected onsite by Research Associates 
(RA's). The RA's were independent contractors, hired by JFA to visit 
retail outlets in each area and collect prices. All of these RA's were 
residents of the area. To avoid any real or perceived conflicts of 
interest, JFA refrained from hiring research associates who were either 
employees of the Federal government or who had immediate family who 
were employees of the Federal government.
2.5.3  Data Collection Materials
    The living-cost surveys conform with the provisions of the 
Paperwork Reduction Act and are approved by the Office of Management 
and Budget (OMB). The OMB-approved survey collection materials are 
found in Appendix 7. All JFA-developed worksheets or other survey 
materials conformed with those approved by OMB.
2.5.4  Inclusion of Sales and Excise Taxes
    For all items subject to sales and/or excise tax, the appropriate 
amount of tax was added prior to analysis. JFA gathered applicable 
information on taxes by contacting appropriate sources of information 
in the allowance areas and the Washington, DC area. JFA also used 
appropriate tax publications, such as the State of Maryland's Sales and 
Use Tax Laws and Regulations and the ``Uniform Sales Tax'' (Ordinance 
Section 69.05) of the City and Borough of Juneau.
2.5.5  JFA's Onsite Visits
    Full-time JFA research professionals traveled to each allowance 
area to supervise data collection activities and perform various 
quality control checks as necessary. These visits all occurred during 
the pricing period so that these professionals could answer any of the 
RA's data collection questions or provide additional training and 
instruction if necessary.
    The researchers visited living communities within the allowance 
areas to look at housing and to talk with local real estate 
professionals. They also visited numerous retail outlets to verify that 
comparable items were being priced at comparable outlets. In addition, 
they obtained general information about the local economy.
2.5.6  Special Considerations in Selected Areas
2.5.6.1  Surveying the Washington, DC Area
    As noted earlier, JFA attempted to get more price quotes in the DC 
area than in the allowance areas because of the size and diversity of 
the Washington metropolitan area. For the purposes of the COLA surveys, 
the DC area was divided into six survey areas: two in the District of 
Columbia, two in Maryland, and two in Virginia. The specific areas 
surveyed were within a normal shopping radius of the housing 
communities identified in Appendix 9. Survey data from each of the six 
DC survey areas were combined using equal weights.

2.6  Step 5: Analyzing Data and Computing Indexes

2.6.1  General Formulae
2.6.1.1  Indexes
    Nonforeign area COLAs are derived from the living-cost indexes. 
These indexes are mathematical comparisons of living costs in the 
allowance areas compared with living costs in the Washington, DC area.
    At the most fundamental level, an index is a way to state the 
difference between two prices (or sets of prices). For example, if a 
can of green beans costs $1.00 in the allowance area and 80 cents in 
the DC area, green beans are 25 percent more expensive in the allowance 
area than in DC. That difference can also be stated as a price index of 
125.
2.6.1.2  Item Weights
    JFA computed indexes for hundreds of items. To combine these 
indexes, JFA used weights derived from the CES. These weights reflected 
the relative amount consumers normally spend on different items. For 
example, the price of a can of green beans has a lower weight than the 
price of a pound of apples because, according to the CES, people 
generally spend less on green beans than on apples.
    The COLA model uses a fixed-weight indexing methodology. This means 
that the same expenditure weights are used in the reference area (i.e., 
the DC area) and in the allowance areas. The weights used are based on 
the expenditure patterns of consumers nationwide as reported by the 
CES. This is the only source, of which OPM is aware, that provides 
expenditure information by income level.
2.6.1.3  Category and Component Weights
    As described in section 2.3.2, JFA also computed income sensitive 
category and component weights. This allowed the combination of item 
prices in a manner that reflected the different spending patterns of 
people at different income levels. How this was accomplished, differed 
among the components.
    For the Goods and Services and Miscellaneous Expense components, 
JFA simply combined indexes within each category using the CES weights 
to derive an overall index for the category. The category indexes were 
then combined into an overall component index using the income-
sensitive category weights described above.
    For the Transportation and Housing Components, JFA used the above 
approach in combination with a cost-build-up approach. For example, for 
each area the annual cost of owning and operating an automobile was 
computed by taking individual prices (e.g., automobile financing, 
insurance, gas and oil, and maintenance) and computing an overall 
dollar cost for each area. These costs were compared with those in the 
DC area to compute the Private Transportation Category index. This 
index was then combined with the Other Transportation Category index 
using income sensitive category weights to compute an overall 
Transportation Component index for each area.
2.6.2  Computing the Overall Index
    The item, category, and component indexes were combined using the 
process prescribed in Section 591.205(c), title 5, Code of Federal Regulations. That is a five-step 
process that involves converting the indexes to dollar values and 
weighting these, combining them, and comparing them to compute a final 
weighted-average index. The process is described below.
    First, JFA used the CES data and the income ranges described in 
section 2.2.1 to determine the quantity of money consumers typically 
spend on each component at each income level. These amounts appear in 
the table below and in Appendix 19. They were derived by taking the 
component weights shown in Table 2-1 times the representative income 
levels described in section 2.2.1.

                     Table 2-2.--Typical Consumer Expenditures by Income Level and Component                    
----------------------------------------------------------------------------------------------------------------
                                               Goods and                                                        
                Income level                    services     Own/rent   Transportation     Misc.        Total   
----------------------------------------------------------------------------------------------------------------
Lower.......................................       $8,341       $5,202         $3,938        $3,320      $20,800
Middle......................................       12,433        7,555          5,879         5,634       31,500
Upper.......................................       18,775       11,114          8,892         9,520       48,300
----------------------------------------------------------------------------------------------------------------
(Note: Values may not total because of rounding.)                                                               

    Second, for each allowance area, JFA multiplied the dollar values 
above by the component indexes for the allowance area. Because the 
housing component consisted of two indexes (one for owners and another 
for renters), two sets of total relative costs were produced--one for 
owners and another for renters.
    Third, for each allowance area and income level, JFA combined the 
total relative costs for owners and renters using as weights the 
proportion of owners and renters as identified in the CES. (See section 
4.2.1.) This produced an overall expenditure dollar amount for each 
income level in each allowance area.
    Fourth, JFA computed a single overall average expenditure for each 
allowance area by combining the income level expenditures and using the 
allowance area General Schedule employment distribution as weights. 
This produced a single overall dollar expenditure value for the 
allowance area. Using the same General Schedule employment weights, JFA 
also computed a single overall dollar expenditure value for the DC 
area.
    The final step was to divide the overall average dollar expenditure 
for the allowance area by the overall average dollar expenditure for 
the DC area to compute a final index. These indexes are shown in the 
last section of this report and in Appendix 19.

3. Consumption Goods and Services

3.1  Categories and Category Weights

    Based on the CES data, JFA identified ten categories of expenses 
within the Goods and Services Component. Using linear regression 
analyses and the CES data, JFA identified the portion of total Goods 
and Services expenditures that the typical consumer spends in each 
category at various income levels. The categories and the relative 
expenditures are shown in the table below:

   Table 3-1.--Category Weights Expressed as a Percentage of Goods and  
                  Services Expenditures by Income Level                 
------------------------------------------------------------------------
                                               Income levels            
             Category             --------------------------------------
                                      Lower        Middle       Upper   
------------------------------------------------------------------------
Food at Home.....................        26.40        23.49        20.65
Food Away from Home..............        14.42        14.73        15.04
Tobacco..........................         3.15         2.59         2.05
Alcohol..........................         2.77         2.73         2.69
Furnishings and Hsld. Op.........        14.71        15.79        16.85
Clothing.........................        13.97        14.65        15.30
Domestic Service.................         1.76         1.90         2.04
Professional Services............         6.48         6.65         6.82
Personal Care....................         3.62         3.52         3.43
Recreation.......................        12.72        13.94        15.14
                                  --------------------------------------
      Totals.....................       100.00       100.00       100.00
------------------------------------------------------------------------
(Note: Values may not total because of rounding.)                       

3.2  Goods and Services Data Collection--Special Considerations

3.2.1  Restaurant Pricing
    To ensure comparison of prices at comparable restaurants among 
areas, OPM asked JFA to survey only three restaurant chains: Dennys, 
Sizzler, and Pizza Hut (or their equivalents). This allowed for the 
comparison of meal prices at a comparable mix of restaurants in all 
areas.

3.3  Goods and Services Survey Results

    Section 2.6 of this report provides a detailed explanation of the 
economic model used to analyze the price data. As it applies to Goods 
and Services, the approach involved comparing the average prices of 
market basket items in each allowance area with those in the 
Washington, DC area. The resulting price ratios were aggregated into 
subcategory and then category indexes using the moving-average 
expenditure weights derived from the CES data.
    Appendix 8 shows for each allowance area ten category indexes, the 
weights used at each of the three income levels, and the overall Goods 
and Services indexes. The Washington, DC area is not shown because it 
is, by definition, the reference area. Therefore, the DC indexes are 
100. 4. Housing

4.1  Component Overview

    The Housing component consists of expenses related to owning or 
renting a dwelling. These are--

--Mortgage or rent payments,
--Utilities,
--Real estate taxes,
--Homeowner's or renter's insurance,
--Home maintenance, and
--Telephone.

    At each of the three income levels, JFA measured separately the 
annual housing costs for homeowners and renters. The results were then 
combined using as weights the percentages of owners and renters 
reported by the CES.

4.2  Housing Model

4.2.1  Expenditure Research
    The CES was used to determine the national average ratio of 
families who own, as opposed to renting, their residences. Using the 
expense data by income range as input into a linear regression 
analysis, JFA calculated the owner and rent weights shown below. JFA 
excluded expenditure data for home owning families without a mortgage 
because they were not typical of homeowners in the base area or in the 
allowance areas.

                    Table 4-1.--Owner/Renter Weights                    
------------------------------------------------------------------------
                                               Income levels            
                                  --------------------------------------
             Category                 Lower        Middle       Upper   
                                    (percent)    (percent)    (percent) 
------------------------------------------------------------------------
Homeowner with mortgage..........        38.41        47.46        61.67
Renter...........................        61.59        52.54        38.33
                                  --------------------------------------
      Totals.....................       100.00       100.00       100.00
------------------------------------------------------------------------

    The CES data were also used to identify which home-maintenance 
items to price and to establish the relative importance of those items.
4.2.2  Housing Profiles
    To compare housing costs in all locations, six typical housing 
profiles are used and are assigned to the three income levels, as shown 
in the table below. OPM requested that at least one criterion for the 
owner profile be the square footage of the home and at least one 
criterion for the renter profile be the number of bedrooms in the 
rental unit.

                                          Table 4-2.--Housing Profiles                                          
----------------------------------------------------------------------------------------------------------------
            Income level                         Renter profile                         Owner profile           
----------------------------------------------------------------------------------------------------------------
Lower..............................  3 rooms, 1 BR, 1 bath, 600 sq. ft.     4 rooms, 2 BR, 1 bath, 900 sq. ft.  
                                      apartment.                             condo or detached house.           
Middle.............................  4 rooms, 2 BR, 1 bath, 900 sq. ft.     5 rooms, 3 BR, 1 bath, 1,300 sq. ft.
                                      apartment.                             detached house (rowhouse in NE DC).
Upper..............................  4 rooms, 2 BR, 2 baths, 1,100 sq. ft.  7 rooms, 3 BR, 2 baths, 1,700 sq.   
                                      townhouse or detached house.           ft. detached house.                
----------------------------------------------------------------------------------------------------------------

    The home sizes stated above are the representative sizes used for 
certain calculations in the model. They are not, however, the only size 
surveyed for each profile. For rentals, JFA obtained rental rates on 
any unit, regardless of its size, that otherwise met the profile 
characteristics. For home sales, JFA obtained the prices of homes 
within size range and otherwise meeting the profile specifications. The 
size ranges are shown below:

                     Table 4-3.--Home Sizes Surveyed                    
------------------------------------------------------------------------
           Income level                             Range               
------------------------------------------------------------------------
Lower.............................  600 to 1,200 sq. ft.                
Middle............................  1,000 to 1,600 sq. ft.              
Upper.............................  1,400 to 2,300 sq. ft.              
------------------------------------------------------------------------

    It should be noted that although the size ranges overlap, no home 
sale observation could be used at more than one income level. 
Application of the other criteria (i.e., number and type of rooms) 
ensured that each observation was assigned to the appropriate income 
level even though its size was common to two income levels.
4.2.3  Living Community Selection
    As discussed briefly in sections 1.2.2 and 2.4.2.1, OPM identified 
the living communities to be surveyed based on the results of the 1992 
Federal Employee Housing and Living Patterns Survey. This resulted in 
many survey community changes in both the allowance areas and in the 
Washington, DC area. The communities surveyed are identified in 
Appendix 9.
    As with previous surveys, nine homeowner and nine renter 
communities were identified for the Washington, DC area--one for each 
income level in each of the three areas (DC, Maryland, and Virginia). 
In the allowance areas, up to three homeowner and three renter 
communities were identified--one for each income level.
    The three-community owner/renter goal was not achievable in many of 
allowance areas due to the relatively few home sales and rental 
opportunities in these areas. In such areas, OPM directed JFA to 
collect prices for the entire survey area or allowance area rather than 
in specific communities. This was done in Fairbanks, Juneau, and Nome. 
In these areas, all home sales and/or rental rates meeting the housing 
profile characteristics for the particular income group were included 
in the analysis.
4.2.4  Housing-Related Expenses
    Based on the CES data, housing-related expense items are 
categorized into one of five groups in the COLA model. These groups 
are--

--Utilities,
--Real estate taxes,
--Owners/renters insurance,
--Maintenance, and
--Telephone.
4.2.4.1  Utilities
    Electricity, oil, gas, water, and sewer are the utilities used in 
the model. Most utility companies are able to provide current charges per unit of 
consumption and average consumption patterns for all households. The 
companies were not, however, able to provide separate consumption 
patterns by the size or type of housing.
    Because many utility costs vary by size of house, a factor is 
needed to derive the utility rates at each of the home profiles. The 
table below shows the standard square foot sizes and utility factors 
used for each home profile. The factors are calculated by assuming that 
utility use increases or decreases at half the rate that square footage 
increases or decreases.

                       Table 4-4.--Utility Factors                      
------------------------------------------------------------------------
                                       Renter profile     Owner profile 
            Income level             -----------------------------------
                                      Sq. ft.   Factor  Sq. ft.   Factor
------------------------------------------------------------------------
Lower...............................      600      .73      900      .85
Middle..............................      900      .85    1,300     1.00
Upper...............................    1,100      .92    1,700     1.15
------------------------------------------------------------------------

    In each area, JFA obtained the price of each of the types of 
utilities noted above. JFA used average annual consumption per 
household information gathered from utility companies serving each area 
to compute average annual utility costs. The above factors were then 
used to adjust the total annual utility costs for each of the various 
housing profiles.
4.2.4.2  Real Estate Taxes
    For this study, JFA contacted the city assessors in each allowance 
area and in the Washington, DC area to obtain real estate tax 
information on the living communities surveyed. Real estate tax 
formulas were obtained for all living communities and applied to the 
home values, for each income level, resulting from the homeowner data 
analysis discussed in section 4.4.1.
4.2.4.3  Owners/Renters Insurance
    Homeowners' insurance rates are gathered for each of the survey 
areas for both renter and owner profiles. For renters, the following 
estimated content values were used: $20,000 at the lower and middle 
income levels and $30,000 at the upper income level.
    For homeowners, the cost of insurance was dependent on the average 
home values calculated as part of this survey. In all areas, it was 
assumed that the structure was equal to 80 percent of the total home 
value.
    Previous research, conducted by Runzheimer International for OPM, 
found that insurance coverage for disasters, such as floods and 
earthquakes, were not widely purchased in the allowance areas. 
Therefore, the COLA model does not include these additional riders. 
(See Report to OPM on Living Costs in Selected NonForeign Areas and in 
the Washington, DC Area, June 1992 at 57 FR 58556).
    A comparison of homeowner insurance data previously collected for 
the Alaska areas with the premiums collected for this survey, showed 
several inconsistencies. For example, premiums for all income levels 
for Anchorage, Fairbanks and Nome were significantly lower, even in 
areas where the home market values had increased. In Juneau, the 
insurance data was significantly higher than premiums collected for the 
previous survey. Because of these inconsistencies and the refusal of 
most outlets contacted to participate in the survey, the insurance data 
collected in the Alaska allowance areas for the previous survey, 
adjusted for inflation, were used for the homeowner and renter 
insurance portion of the housing-related expenses analysis. The 
previously published data in 59 FR 45066 was adjusted by the annual 
rate of change in the Consumer Price Index for All Urban Consumers 
(CPI-U) for homeowner's insurance, 3.3%, and renter's insurance, 3.6%, 
as reported in the Bureau of Labor Statistics' CPI Detailed Report Data 
for July 1995.
4.2.4.4  Home Maintenance
    Estimated home maintenance expense was computed for each of the 
homeowner profiles. Maintenance costs were not added in the three 
renter profiles because most, if not all, maintenance expenses are 
covered by the landlord.
    As done in previous surveys, JFA priced both home maintenance 
services as well as home maintenance commodities, using the CES 
information to identify items to price and the weights associated with 
these items. The maintenance service items priced were interior 
painting, plumbing repair, electrical repair, and pest control. In the 
Nome area, however, pest control was not priced because local sources 
indicated it is not necessary. The maintenance commodities priced were 
bathroom caulking, a kitchen faucet set, an electrical outlet, latex 
interior paint, and a fire extinguisher.
    To compute home maintenance cost differences between each allowance 
area and the Washington, DC area for the homeowner profiles, an index 
was computed for each maintenance item by comparing the allowance area 
price to the DC area price. As with the Goods and Services Component 
items, the CES data were used to weight these maintenance indexes into 
an overall home maintenance index for each area.
    To combine the maintenance indexes with the other homeowner costs, 
which were expressed in dollar amounts, JFA converted the indexes to 
dollars by multiplying the index for each area by the average 
maintenance expense reported in the CES. This cost was assigned to the 
middle-income homeowner profile.
    Logically, maintenance costs for larger homes would generally be 
greater than costs for middle-sized homes, while costs for smaller 
homes would generally be less. Therefore, the same homeowner 
multipliers used in the utilities model for the lower and upper income 
profiles (.85 and 1.15 respectively) are applied to recognize 
differences in maintenance costs due to house size.
4.2.4.5  Telephone
    Telephone expense consisted of local service charges, additional 
charges for local calls (if applicable), and charges for long distance 
calls. To measure estimated expenses for local service and local calls, 
JFA surveyed the cost of touch-tone service with unlimited calling in 
each area.
    To estimate long distance charges in all areas, JFA surveyed the 
cost of three, ten-minute direct dial calls per month to large U.S. 
mainland cities (i.e., Los Angeles, Chicago, and New York City). JFA 
measured the price of a call placed in the survey area at the time of 
day necessary to be received in the respective city at 8 p.m. local 
time. In many areas, this resulted in pricing a combination of daytime 
and evening-rate calls.

4.3  Housing Data Collection Procedures

    As done in previous years, JFA collected housing information mainly 
from real estate professionals, various listing services, and 
advertisements. In addition, JFA personnel traveled to each of the 
surveyed communities to assess the compatibility of the housing 
community with the income level for which the data were used and to 
ensure that homes in these communities were comparable to those in the 
Washington, DC area.
4.3.1  Homeowner Data Collection
    JFA obtained selling prices of homes that matched the housing 
profiles in each living community. JFA obtained as many of these 
selling prices as possible for sales that occurred during the 6-month 
period prior to the date of the survey.
    The amount of data obtained depended on the number of home sales in the community and the availability of square footage and other 
housing profile information. This in turn depended on the size of the 
community, economic conditions, quality and quantity of the realty data 
available, and the willingness and ability of local realty 
professionals and assessor offices to provide data.
    If sales data obtained from the preliminary data sources did not 
meet specified contract minimums, JFA contacted additional data sources 
in the area to attempt to secure more sales data, if practical. In this 
manner, either all were or a sizeable portion of the home sales in each 
area was surveyed.
4.3.2  Renter Data Collection
    Rental data also were obtained from a variety of sources, e.g., 
brokers, rental management firms, property managers, newspaper 
advertisements, and other listings. Analyses of these data revealed 
what appeared to be two separate rental markets: a broker market and a 
non-broker market. Rental rates and estimates provided by brokers 
generally exceeded those obtained from other sources. The methodology 
used to analyze these two data sets is discussed in section 4.4.2.

4.4  Housing Analysis

4.4.1  Homeowner Data Analysis
    One of the most important factors relating to the price of a home 
is the number of square feet of living space. In the past, OPM directed 
the contractor to rank housing data high to low and trim equal numbers 
of observations from both ends of the data. The average of the 
remaining values was then used. This year, OPM changed the methodology 
and used the median home value rather than trimming and averaging. The 
median is the middle value in a rank-ordered set of observations. The 
purpose of either approach is to reduce the volatility of the housing 
data from one survey to the next because a relatively few extremely 
high or low home prices could significantly influence average housing 
costs.
    For each income profile in each allowance area and the Washington, 
DC area, JFA computed the median price per square foot for the 
comparables. This value was then multiplied by the reference square 
footage for the profile to determine the average home value for the 
profile.
    Another change that OPM made this year was to ask JFA to use 
historical housing data in addition to data collected this year. These 
data are found in Appendix 10 of this report. The historical data are 
from previous living-cost surveys that were published in the Federal 
Register beginning with the 1990 report. (See Appendix 1 for a listing 
of these publications). The data for the period prior to 1990 were 
published with the results of the 1991-1992 living cost surveys at 57 
FR 58618. All housing values are based on the community selections and 
analytical methodologies used at the time of each respective survey.
    The historical housing data used were estimated annual principal 
plus interest payments by income level in each area. To combine these 
data, OPM supplied JFA with weights that were derived from the 1992 
Federal Employee Housing and Living Patterns Survey. These weights 
reflect the proportion of Federal employee homeowners by year of 
purchase or acquisition in all allowance areas and in the Washington, 
DC area. The historical housing weights and analyses are shown in 
Appendix 11.
4.4.2  Rental Data Analysis
    JFA assigned each rental quote data point to a single income level, 
based on the following criteria:

--One bedroom apartments: Lower Income Level,
--Two bedroom apartments: Middle Income Level, and
--Townhouses and detached houses with a minimum of two bedrooms: Upper 
Income Level.

    As discussed earlier, there were essentially two sources of rental 
information: broker and non-broker sources. In each area, the quantity 
of data obtained from either source-type varied significantly. 
Therefore, analyzing all of the rental data (both broker and non-
broker) together for an area and income level was undesirable.
    Instead, OPM instructed JFA to analyze broker and non-broker data 
separately by income level. As with the housing data analyses, OPM 
changed from the use of trimming and averaging to the use of the 
median. Therefore, for each income level, JFA separately ranked rental 
rates from low to high for broker and non-broker data. The median 
values for broker and non-broker data for each group were determined 
and then averaged to compute a single rental value for each income 
level. Because OPM has no information on how the Federal employees who 
rent generally secure their lodgings, OPM requested that JFA apply 
equal weights to the broker and non-broker data to compute an overall 
average rental rate for the area and income level. The broker and non-
broker medians and final results are shown in Appendix 12.

4.5  Housing Survey Results

    In the above sections, the processes used for determining the costs 
for maintenance, insurance, utilities, real estate taxes, rents, and 
homeowner mortgages were described. Appendix 13 shows the cost of each 
of these items for renters and homeowners in each allowance area and in 
the Washington, DC area.
    Appendix 14 compares the total cost of these items by income level 
in each allowance area with the total cost of the same items by income 
level in the Washington, DC area. Again, there are separate comparisons 
for renters and homeowners.
    The final housing-cost comparisons take the form of indexes that 
are used in Appendix 19 to derive the total, overall index for owners 
and renters. (Refer to Section 2.6 for a discussion of the general 
formulae and how the component indexes are combined.)

5. Transportation

5.1  Component Overview

    The transportation component consists of two categories: Automobile 
Expense and Other Transportation Costs. The Automobile Expense Category 
reflects costs relating to owning and operating a car in each area. The 
Other Transportation Costs Category is represented by the cost of air 
travel from each location to a common point within the contiguous 48 
states.

5.2  Private Transportation Methodology

    As done in previous surveys, JFA analyzed automobile transportation 
costs for three commonly purchased vehicles: a domestic auto, an import 
auto, and a utility vehicle. New car costs were used for these analyses 
because it was believed that pricing used vehicles of equivalent 
quality in each area could introduce inconsistencies because of the 
value judgments that would be required.
5.2.1  Vehicle Selection and Pricing
    The three vehicles selected for analysis were:

Domestic--Ford Taurus GL 4-door sedan 3.0L 6 cyl,
Import--Honda Civic DX 4-door sedan 1.5L 4 cyl, and
Utility--Chevrolet S10 Blazer 4X4 2 door 4.3L 6 cyl.

    These are the same models that were surveyed in previous years and 
were selected based on their popularity in the United States as 
demonstrated by owner registration data.
    For each model car, JFA collected new vehicle prices at dealerships 
in each area and from secondary sources, such as the Kelly Blue Book. All prices were based on the 
manufacturers' suggested retail prices (MSRP) for 1995. (OPM did not 
believe it was feasible to collect information on the negotiated price 
for these vehicles.) All vehicles were equipped with standard options, 
such as automatic transmission, AM/FM stereo radio and air 
conditioning. In Alaska locations, special additional equipment was 
included in new-vehicle prices (e.g., snow tires, engine-block heaters, 
and heavy-duty batteries).
    In addition to the MSRP, the price included additional charges such 
as shipping, dealer preparation, additional dealer markup, excise tax, 
sales tax, and any other one-time taxes or charges. In each Alaska 
allowance area, for example, documentation fees were also included as 
part of the new-vehicle costs.
    Rustproofing was priced in all areas, including the Washington, DC 
area. In previous surveys, the contractor found that auto dealers in 
the DC area did not recommend vehicle rustproofing, although it was a 
commonly suggested option in the allowance areas. This year, the 
information collected suggested that rustproofing was a commonly 
offered option in all areas. Therefore, OPM directed JFA to include the 
cost of rustproofing in the DC area as well as the allowance areas.
5.2.2  Vehicle Trade Cycle
    Calculating the cost of owning and operating a vehicle requires 
knowing the miles driven and how long the car is owned. In the 
automobile industry, these two factors are known collectively as a 
vehicle's ``trade cycle.'' The trade cycle is stated as a length of 
time (in months or years) and the total number of miles driven in that 
time period. This information is used in the model to compute annual 
costs related to fuel, oil, tires, maintenance, and depreciation.
    As with the previous living-cost analyses, JFA used a four-year, 
60,000-mile trade cycle in all areas. This was based upon the following 
information:

--The Internal Revenue Service uses this trade cycle to compute the 
allowable cents-per-mile reimbursement rate for persons who drive their 
personal vehicle for business purposes;
--The four-year time period coincides with the typical length of a 
vehicle loan; and
--U.S. Department of Energy statistics for 1988 show that the annual 
average for number of vehicle miles driven in the United States was 
18,595 per household and 10,246 miles per vehicle.
5.2.3  Fuel Performance and Type
    All vehicles included in this study used regular unleaded fuel. JFA 
surveyed self-service cash prices of unleaded regular gasoline at name-
brand gas stations in the Washington, DC area. In consideration of the 
harsh climate in the Alaska allowance areas, full-service cash prices 
were  

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