# Report on Winter 1994 Surveys Used To Determine Cost-of-Living Allowances in Alaska; Notice OFFICE OF PERSONNEL MANAGEMENT

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URL: https://www.frixlaw.com/law-library/documents/fr%3A94-21119

## Record

- **Collection:** Federal Register
- **Document type:** Uncategorized Document
- **Published:** August 31, 1994

## Text

SUMMARY: This notice publishes the ``Report to OPM on Living Costs in
Alaska and in the Washington, DC, Area, June 1994,'' prepared by
Runzheimer International under Government contract OPM-90-0705.

DATES: Comments must be received on or before October 31, 1994.

ADDRESSES: Send or deliver comments to Allan G. Hearne, Methodology
Development Branch, Office of Compensation Policy, Personnel Systems
and Oversight Group, Office of Personnel Management, room 6H31, 1900 E
Street NW., Washington, DC 20415.

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 Alaska and in the Washington DC
Area, June 1994,'' produced by Runzheimer International under contract
with OPM. This report explains in detail the methodologies,
calculations, and findings of the winter 1994 living-cost surveys
conducted in Alaska and in the Washington, DC area.
The report presents only the results of the winter 1994 surveys. It
does not cover the summer 1993 living-cost surveys conducted in Hawaii,
Puerto Rico, Guam, and the U.S. Virgin Islands. The results of the
summer 1993 surveys were published in the Federal Register on May 26,
1994. Reporting the summer and winter living-cost surveys separately
allows OPM to adjust COLA rates where warranted in a more timely
manner.
Based on the winter 1994 living-cost surveys, Runzheimer computed
index values of relative living costs in allowance areas using an index
scale where the living costs in the Washington, DC area equal 100. (See
the Executive Summary of the June 1994 Runzheimer report accompanying
this notice.) 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), prohibits reductions in COLA rates through
December 31, 1995. Therefore, OPM is not proposing any adjustments to
the COLA rates in Alaska at this time.

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

Report to OPM on Living Costs in Alaska and in the Washington, DC, Area

June 1994

Table of Contents

Executive Summary
1. Introduction
1.1 Report Objectives
1.2 Changes in This Year's Survey
1.3 Pricing Period
1.4 Living Cost Components
2. Overall Mode
2.1 Measurement of Living-Cost Differences
2.1.1 Target Population: Federal Employees
2.1.2 Determination of Expenditure Patterns
2.1.2.1 Source of Expenditure Data
2.1.2.2 Income Level Adjustments
2.1.2.3 Family Size Considerations
2.1.2.4 Analysis of the 1988 Consumer Expenditure Survey
2.2 General Formulae and Applications
2.3 Data Collection Process
2.3.1 In-house Research Staff
2.3.2 Field Researchers--``Research Associates''
2.3.3 On-site Visits by Runzheimer Research Personnel
2.4 Editing and Quality Control Procedures
2.5 Pricing Survey in Nome, Alaska
2.6 Surveying the Washington, D.C., Area
3. Consumption Goods & Services
3.1 Component Overview
3.2 Marketbasket Research
3.2.1 Expenditure Research--Category Weightings
3.2.2 Expenditure Research--Subcategory and Item Weightings
3.3 Marketbasket Item Specifications
3.3.1 Exchange and Commissary Expenditure Research
3.4 Goods & Services Data Collection Procedures
3.4.1 Data Collection Materials
3.4.2 Outlet Selection
3.5 Inclusion of Sales and Excise Taxes
3.6 Goods & Services Survey Results
4. Housing
4.1 Component Overview
4.2 Housing Model
4.2.1 Expenditure Research
4.2.2 Development of Housing Profiles
4.2.3 Living Community Selection
4.2.4 Identification and Quantification of 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 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
4.4.1.1 Data Trimming
4.4.1.2 Special Considerations
4.4.2 Rental Data Analysis
4.4.2.1 Data Trimming and Special Analyses
4.4.3 Analysis of Housing-Related Expenses
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
5.3 Public Transportation Methodology
5.4 Transportation Survey Results
6. Miscellaneous Expenses
6.1 Component Overview
6.2 Miscellaneous Expense Model
6.2.1 Expenditure Research
6.2.2 Miscellaneous Expense Methodology
6.3 Miscellaneous Expense Data Collection Procedures
6.4 Miscellaneous Expense Survey Results
7. Final Results
7.1 Total Comparative Cost Indexes
7.2 General Comments
7.3 Recommendations

Appendix

Appendix 1 Consumer Expenditure Survey (CES)
Appendix 2 Marketbasket Descriptions
Appendix 3 Pricing Changes: Goods & Services/Miscellaneous Expense/
Housing Related
Appendix 4 Consumption Goods & Services Analysis
Appendix 5 Nonforeign Area Cost-of-Living Allowances Price Survey
Data and Background Survey Data Collection Procedures
Appendix 6 1993/1994 OPM Living Community Selection
Appendix 7 Housing Cost Analysis
Appendix 8 Housing Analysis
Appendix 9A Analysis of Home Sales Data
Appendix 9B Analysis of Rental Data
Appendix 10 Private Transportation Cost Analysis
Appendix 11 Transportation Analysis
Appendix 12 Miscellaneous Expense Analysis
Appendix 13 Federal Employment Weights Within A Single Allowance
Area
Appendix 14 Component Expenditure Amounts & Total Comparative Cost
Indexes

Executive Summary

This report culminates the fifth living-cost comparison study
undertaken by Runzheimer International for the Office of Personnel
Management (OPM) under contract OPM-90-0705. The contract requires
Runzheimer to:

(1) survey living costs in 4 cost-of-living allowance (COLA) areas and
the Washington, D.C., area, and
(2) compare living costs between the areas and the D.C. area.

To determine living costs in the identified areas and build this
report, Runzheimer researched over 1,000 outlets and gathered more than
6,000 price quotes.
This report presents the results of the living-cost surveys
conducted during the winter of 1994. The results of the summer 1993
surveys were presented in a report provided to OPM earlier this year.
To ease interpretation of the research results, we display the
outcome of the comparisons as living-cost indexes in the table below.
In addition, the table shows living-cost indexes for federal employees
who have unlimited access to commissary and exchange facilities because
of their employment. The index for the Washington, D.C., area (not
shown) is 100.00 because it is, by definition, the reference area.

Final Cost Comparison Indexes
------------------------------------------------------------------------
Local Commissary
Allowance area pricing & exchange
------------------------------------------------------------------------
Anchorage, Alaska............................. 103.94 101.32
Fairbanks, Alaska............................. 106.03 103.41
Juneau, Alaska................................ 108.10 NA
Other Areas in Alaska*........................ 127.56 NA
------------------------------------------------------------------------
* As represented by Nome, AK.
NA = Not Applicable

One of the changes OPM requested this year was to separate the
reporting of the summer and winter living-cost surveys. The purpose of
this change was to allow OPM to adjust COLA where warranted in a more
timely manner. Other changes included:
A moving average approach to introduce new federal
employment weights,
A new methodology for collecting and analyzing automotive
maintenance cost, and
Minor changes in pricing sources for certain items to
refine the comparisons of D.C. and allowance area prices.
We discuss these and other adjustments in appropriate sections
throughout this report.
In addition, to monitor, fine-tune, and maintain effective control
of the data-gathering efforts in Alaska, Runzheimer sent a full-time
research professional to Alaska to visit retail outlets, Runzheimer
research associates, housing data sources, and living communities.

Report to OPM on Living Costs in Alaska and in the Washington, DC, Area

1. Introduction

1.1 Report Objectives
This comprehensive report culminates data-gathering and research
work undertaken in Winter 1994 as required by Task 2 of contract OPM-
90-0705 between the Office of Personnel Management (OPM) and Runzheimer
International. The report details the results of Runzheimer
International's surveys of over 1,000 outlets to obtain more than 6,000
price quotes and the analyses of the data.
In 1990, in fulfillment of Task 1 of the contract, Runzheimer
worked with OPM to design a model for estimating comparative living
costs between the allowance areas and the Washington, D.C., area. Task
2 of the contract required that Runzheimer apply the model by
conducting living-cost surveys, analyzing the results, and developing
living-cost comparative indexes. On February 26, 1991, OPM published
that model and the results of the first surveys conducted under the
model in the Federal Register. On December 10, 1992, OPM published in
the Federal Register the second report, which covered the summer 1991
and winter 1992 surveys. On August 30, 1993, OPM published in the
Federal Register the next report that covered the summer 1992 and
winter 1993 surveys; and on May 26, 1994, OPM published the results of
the summer 1993 surveys.
This report provides only the results of the winter 1994 surveys.
This change was made at OPM's request. Separating the summer 1993 and
winter 1994 surveys allowed OPM to adjust COLA rates where warranted in
a more timely manner.
The analyses establish the comparative cost differences between the
listed allowance areas and the Washington, D.C., area:

1. Anchorage, Alaska
2. Fairbanks, Alaska
3. Juneau, Alaska
4. Other Areas in Alaska (as represented by Nome, Alaska)

By law, Washington, D.C., is the base or ``reference'' area for the
nonforeign area COLA program.
Task 2 of the OPM contract also required Runzheimer International
to calculate comparative living costs in the areas listed below and the
Washington, D.C., area for federal civilian employees who have access
to military commissaries and post exchanges.

1. Anchorage, AK
2. Fairbanks, AK

Under OPM regulations, federal civilian employees who have
unlimited access to commissaries and post exchanges due to their
employment by the government may receive a different allowance rate
than other federal employees. This regulation does not apply to federal
employees who have limited access or unlimited access for other
reasons--e.g., being married to active or retired military personnel.
1.2 Changes in This Year's Survey
Runzheimer and OPM made several changes to the survey and analyses.
These changes included:
Reporting the results of the summer and winter surveys
separately,
Using a moving average approach to introduce new federal
employment weights,
Updating appliance models or replacing one make with
another where a previous brand was difficult to find,
Employing a new methodology for determining automobile
maintenance costs,
Surveying only the cash price at branded gas stations
unless only non-branded stations are available, and
More accurately defining the distinguishing differences
between family dining and fine dining.
Runzheimer has continued to include catalog sales in its survey.
Since the Sears catalogs have been discontinued, Runzheimer has
researched hundreds of catalogs to determine which are most
appropriate. Runzheimer researchers found that most catalogs have
uniform shipping charges. Only catalogs that sell merchandise in the
allowance areas and Washington, D.C. area were used.
Appendix 3 identifies Goods & Services, Miscellaneous Expense, and
Housing Related pricing changes. Current housing data can be found in
Appendix 9A and Appendix 9B. Other changes are discussed where
applicable in the report.
1.3 Pricing Period
Runzheimer collected price data for the Alaska allowance areas
(and, again, the Washington, D.C., area) in February 1994. As with the
previous surveys, however, our research associates collected price data
for items dependent upon the pricing of other items slightly later
(i.e., in March and April 1994).
To ensure consistent seasonal catalog pricing, Runzheimer used
fall/winter catalogs for the Alaska areas.
1.4 Living Cost Components
In accordance with federal regulations, expense components
Runzheimer costed to develop analyses, comparisons, and the report
were:

1. Housing and Housing Related Expenses
2. Transportation
3. Consumption Goods & Services
4. Miscellaneous Expenses

Runzheimer factored sales, excise and property taxes into the
analysis where applicable. However, in keeping with previous reports,
we did not factor federal, state and local income taxes into the
analysis. Because income taxes significantly affect living costs,
Runzheimer and OPM are researching the issue of including income taxes
in future surveys.
Educational opportunities vary significantly among locations in
terms of availability, quality, and other factors. Runzheimer analysts
and OPM officials agree that, without additional information, attempts
to measure cost differences in education in the selected areas would be
highly subjective and would not add to the integrity of the model.
Therefore, education expense is not included in the model or surveys.

2. Overall Model

2.1 Measurement of Living-Cost Differences
The most common and most 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
relative cost differences, combining them according to their importance
in terms of consumer expenditures. Runzheimer applied this methodology
to compare living costs in each of the allowance areas with living
costs in the Washington, D.C., area.
To move from this basic concept to computing comparative living
costs between each allowance area and the Washington, D.C., area,
Runzheimer followed five main processes or steps:

Step 1 Identify the segment of the population for which this analysis
is being targeted (i.e., the target population).
Step 2 Determine how these people spend their money.
Step 3 Select items to represent the expense categories for which
these people spend their money.
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.
2.1.1 Target Population: Federal Employees
Runzheimer's living-cost model measures living-cost differences for
non-military federal employees having annual base salaries between
$10,000 and $80,000, the salary range of the 1990 General Schedule of
the Federal Government. Because living-cost differences may vary
depending on an employee's income level, Runzheimer designed its
analytical model to identify living costs at three income levels.
In its first report to OPM, Runzheimer used the salary distribution
of all General Schedule employees as of March 31, 1990, which OPM
supplied, to determine the income levels that most accurately represent
the federal employee population. After analyzing the array of salary
data, Runzheimer picked the midpoints of the lower, middle and upper
thirds of the distribution as its three income levels ($18,000, $28,400
and $45,200 respectively).
Runzheimer applied the same income levels for this report as it did
for the first. In previous reports, Runzheimer recommended that OPM
consider introducing changes in income levels and weights on a gradual
basis. OPM agreed, and this year OPM introduced new Federal employment
weights that are based on a moving average. OPM has informed Runzheimer
that OPM plans to introduce other changes, such as new representative
income levels and Consumer Expenditure Survey (CES) weights, in future
surveys.
Runzheimer uses Federal employment weights in the model in two
ways: (1) to combine survey data from multiple survey areas within a
single allowance area and (2) to combine relative living costs by
income level within each allowance area into a single index for the
area (as required by section 591.205(c) of title 5, Code of Federal
Regulations).
OPM's moving average allows the gradual introduction of new
employment distribution data over time. The weights are based on a
three-year average of GS employment. Each year, the latest GS
employment data will be added to the three-year average, the oldest
data will be deleted, and a new three-year average will be computed.
This will keep the weights current while mitigating any fluctuations
due to short-term changes in Federal employment.
In this first application of the moving average, OPM is departing
slightly from the process described above in that the three employment
distributions used are for the periods of 1990, 1992, and 1993. The
1990 rather than the 1991 employment is used because the model
previously used 1990 data only. (See Appendix 13.)
2.1.2 Determination of Expenditure Patterns
2.1.2.1 Source of Expenditure Data
Conforming with last year's process, Runzheimer used the ``prepub''
statistical reports from the 1988 CES dated February 13, 1990 (see
Appendix 1) as the basis for weighing expenditure patterns.
2.1.2.2 Income Level Adjustments
Because the CES reflected 1988 expenditure levels, Runzheimer
reduced the three 1990 incomes back to 1988 levels before beginning the
expenditure analysis. To calculate estimated 1988 income levels,
Runzheimer used the average percentage salary increases of federal
employees for the two-year period in question as supplied by OPM
officials (4.1% increase 1988-89 and 3.6% increase 1989-90, resulting
in a 7.85% two-year increase). This adjustment reduced the 1990 income
levels to estimated 1988 levels of $16,700, $26,300, and $41,900.
2.1.2.3 Family Size Considerations
A family size of 2.6 was inherent in the weighing scheme Runzheimer
employed to price all allowance areas. Derived from CES research, the
number represented an average for the nation.
2.1.2.4 Analysis of the 1988 Consumer Expenditure Survey
From the 1988 CES, Runzheimer used the statistical report entitled
``Table 2. Income before Taxes,'' which listed average expenditures for
families earning similar incomes, organized into eight income ranges.
Runzheimer analyzed these data to develop typical spending patterns for
the three income profiles identified in 2.1.2.2. (The table below
displays the results of the analysis.)
Seven income ranges encompassed the salary range of the General
Schedule:

$10,000 to $14,999
$15,000 to $19,999
$20,000 to $29,999
$30,000 to $39,999
$40,000 to $49,999
$50,000 and over
All respondents combined

The 1988 CES grouped 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).
Drawing on this survey of expenditure data, Runzheimer sorted the
item groupings into the four main cost components specified in the OPM
regulations: Consumption Goods & Services, Transportation, Housing, and
Miscellaneous Expenses. Runzheimer observed that families in the lower
income ranges spent more of their money, as a percentage of total
expenses, on goods and services and housing than families in higher
income ranges. Also, families spent approximately the same percentage
of their total expenses on transportation, regardless of income.
Consequently, the Miscellaneous Expense component which includes such
things as medical-care expenses, contributions, gifts to non-family
members, pension funds, long-term savings and investments, and life
insurance premiums--increased as a percentage of total expenses as
income increased.
To develop accurate and defensible weighing patterns for the three
income levels, Runzheimer performed linear regression analysis on the
selected 1988 CES data. Listed below are the results of Runzheimer's
analysis for the income ranges listed on the preceding page:

Component Expenses Expressed as a Percentage of Total Expenses
----------------------------------------------------------------------------------------------------------------
Income level Income level Goods & Housing Transportation Misc. Total
1991 1988 (Est.) services (percent) (percent) (percent) (percent)
----------------------------------------------------------------------------------------------------------------
$18,000......... $16,700 39.59 24.35 20.76 15.30 100.00
28,400.......... 26,300 39.15 23.48 20.33 17.04 100.00
45,200.......... 41,900 38.74 22.66 19.94 18.66 100.00
----------------------------------------------------------------------------------------------------------------
AARunzheimer further sorted Goods & Services into ten categories and used linear regression techniques to
provide accurate ratios of renters to homeowners at each income level. Statistics on these component groupings
appear later in this report.

2.2 General Formulae and Applications
An ``index'' is a mathematical way to compare one price (or set of
data) with another. For example, if a price index for a can of green
beans is 110, that means that a can of green beans costs 10% more in
the pricing area (i.e., allowance area) than in the reference area
(i.e., the Washington, D.C., area).
Runzheimer computed indexes for hundreds of items. To combine these
indexes, Runzheimer applied weights from the CES that reflected the
relative amount consumers normally spend on the 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 canned green beans than on apples.
Runzheimer employed an indexing methodology known as Laspeyres to
derive total cost indexes for each of three income levels and for each
costed location. As applied to living-cost research, the Laspeyres
index reflects the expenditure patterns of the people in the reference
area (i.e., the Washington, D.C., area) to weight the prices. Because
detailed CES data by income level are not published for the Washington,
D.C., area, Runzheimer used nationwide CES data to compute weights.
Consequently, Runzheimer did not technically apply the Laspeyres index
methodology in its pure form. Nevertheless, Runzheimer firmly believes
that this nuance does not invalidate the price comparisons presented in
this report.
As described in the example above and in greater detail in sections
3.2 and 6.2, Runzheimer applied the Laspeyres methodology to compute
price indexes for the Goods & Services and the Miscellaneous Expenses
components, respectively. For the Transportation and the Housing
components, Runzheimer used a combination of a cost-build-up approach
and the Laspeyres methodology to compute component indexes.
In conformance with section 591.205(c), title 5, Code of Federal
Regulations, Runzheimer followed a five-step process to derive the
overall total indexes for each allowance area. First, Runzheimer used
the CES data and the income ranges described in section 2.1.2.4 above
to derive the amount of money consumers typically spend on each
component at each income level. These amounts appear in the table below
and in Appendix 14.

Typical Consumer Expenditures by Income Level and Component
----------------------------------------------------------------------------------------------------------------
Goods &
Income level services Own/rent Transportation Misc. Total
----------------------------------------------------------------------------------------------------------------
Lower........................... $7,126 $4,383 $3,737 $2,754 $18,000
Middle.......................... 11,119 6,668 5,774 4,839 28,400
Upper........................... 17,510 10,242 9,013 8,434 45,200
----------------------------------------------------------------------------------------------------------------
Note: Values may not total because of rounding.

Second, for each allowance area, Runzheimer multiplied the 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), we produced two sets of total relative costs--one for
owners and another for renters.
Third, for each allowance area and income level, Runzheimer
combined the total relative costs for owners and renters using the
proportion of owners and renters as identified in the CES to weigh the
costs. (See section 4.2.1.) This produced an overall, average, relative
living cost at each income level in each allowance area.
Fourth, for each allowance area, the overall, average relative
costs by income level were combined using federal employment weights
based on the employment at each income level in the allowance area.
Applying the same allowance-area employment weights, Runzheimer
computed an overall, average cost for the reference area.
The last step was to divide the overall, average relative cost for
the allowance area by the overall, average cost for the reference area
to produce the final index. (See Appendix 14 for the calculations for
each index.)
2.3 Data Collection Process
As noted earlier, Runzheimer obtained price information on over
6,000 items from over 1,000 outlets. To accomplish this important
research effort, we selected the most efficient and effective
information-gathering approaches possible. This section describes the
various approaches.
2.3.1 In-house Research Staff
Runzheimer research personnel at its corporate headquarters in
Rochester, Wisconsin, 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;
Contacted professionals in the real estate business in
each of the costed locations to obtain general information as well as
specific rental rates and home market values;
Conducted pricing surveys on site and by telephone for
many items;
Served as a liaison for field researchers;
Performed hundreds of quality control checks in
conformance with editing rules communicated by Runzheimer to OPM once
the data had been collected (these checks often involved verification
of the survey data through telephone calls as well as comparing current
data-gathering results with those from the 1992-1993 survey); and
Analyzed and computed the category, component and total
comparative cost indexes.
2.3.2 Field Researchers--``Research Associates''
Collection of most price data was best accomplished through
personal visits to retail outlets (e.g., grocery, clothing,
automobiles). For these activities, Runzheimer hired residents of each
allowance area as independent contractors (``research associates'').
For years, when measuring living costs for its clients, Runzheimer has
applied this approach to data collection in over 80 countries
worldwide.
To avoid any real or perceived conflicts of interest, Runzheimer
did not hire persons as research associates who were either employees
of the Federal Government, or who had immediate family who were
employees of the Federal Government.
2.3.3 On-site Visits by Runzheimer Research Personnel
Full-time Runzheimer research professionals travelled to selected
allowance areas to supervise data-collection activities and perform
various quality-control checks on the data as necessary. Each such
visit occurred during the pricing period.
The researchers visited living communities within the allowance
areas to look at housing accommodations personally and to talk with
local real estate professionals. They also visited numerous retail
outlets to verify item quality, selection and price levels in general.
In addition, these researchers met with Runzheimer's research
associate(s) to answer any data-collection questions and to provide any
additional training and instruction as necessary.
2.4 Editing and Quality Control Procedures
Runzheimer's experience in measuring living-cost differences
enabled us to establish editing and quality-control procedures at all
stages of collecting and analyzing data. All data provided by research
associates were manually reviewed by analysts prior to being entered
into Runzheimer's computer system. Data elements were subsequently
checked through software programs.
Federal regulations in section 591.205(b)(1)(i), title 5, Code of
Federal Regulations, state that, ``Whenever possible, exact brands and
models are priced in each location.'' Every effort was made to satisfy
this objective. (See section 3.3 for a discussion of brand and model
selection.) Nevertheless, in a number of the allowance areas, the exact
brands and models were either not readily available or not available at
all. In these instances, editing decisions and substitutions were
needed.
Runzheimer defines ``editing'' as the removal and/or replacement of
a price quote based on consistent and logical criteria. In all areas,
Runzheimer was concerned that items of lesser (or greater) quality than
the item specified might inadvertently be included in the analysis and
bias the results. Therefore, any price quote that varied significantly
from other price quotes for the item was flagged, verified, and, if
necessary, eliminated from the analysis.
Removing an item from a location analysis causes redistribution of
its weight to other items in its subcategory (or category when no
subcategory exists). Consequently, whenever possible, Runzheimer
avoided removing an unpriced item from a location analysis. When the
review process revealed a missing price for an item, Runzheimer
resurveyed to obtain a price wherever possible.
2.5 Pricing Surveys in Nome, Alaska
There are four allowance areas in Alaska: Anchorage, Fairbanks,
Juneau, and the Rest of the State of Alaska. As was done in previous
surveys, Runzheimer surveyed living costs in Nome, Alaska to represent
living costs in the Rest of the State of Alaska allowance area.
OPM selected Nome for survey beginning with the 1991/1992 surveys.
According to OPM, Federal civilian employment in Alaska is concentrated
in the three main cities, and Federal employment outside these three
cities is not concentrated in any particular town or region.
OPM believed that living-cost surveys in multiple places outside
the major cities would not be practical. Therefore, Nome was chosen
because of its remote location, relative population size, and relative
number of Federal civilian employees in that area.
2.6 Surveying the Washington, D.C., Area
OPM defined the Washington, D.C., area in the federal regulations
as the Washington DC-MD-VA Metropolitan Statistical Area. Because
federal employees who work in this area reside in Virginia, in
Maryland, and in the District of Columbia, Runzheimer selected retail
outlets and living communities from all three. Runzheimer's model gave
equal weight to the average prices in each geographic area.
Because of the size and diversity of the Washington, D.C., area,
Runzheimer conducted substantially more pricing surveys there than in
other areas. For the Goods & Services component, Runzheimer generally
surveyed to obtain six times as many price quotes in the Washington,
D.C., area as in the typical allowance area. For the Housing,
Transportation and Miscellaneous Expense components, data collection
was generally triple that of the typical allowance area.

3. Consumption Goods & Services

3.1 Component Overview
Based on the CES data, the Goods & Services component consists of
ten categories of family expense:

Food at Home
Food Away from Home
Tobacco
Alcohol
Furnishings & Household Operations
Clothing
Domestic Services
Professional Services
Personal Care
Recreation

To aid in quality control and analysis of future pricings,
Runzheimer further subdivided four of the largest categories--food at
home, furnishings and household operations, clothing, and recreation--
into subcategories. Specific examples of products and services from
these four subdivided categories can be found below. These examples
only represent a minor portion of the total number of items (products
and services) Runzheimer priced within each subdivided category. (See
Appendix 2 for a complete description of all marketbasket items.)

Examples of Subcategories and Items Surveyed In the Four Major Goods &
Services Categories

Goods & services
category
Subcategories and Items Surveyed (Examples)

------------------------------------------------------------------------
Food at Home.... Meats Cereals & Breads Groceries.
Pork Chops Cookies Coffee.
Whole Chicken Spaghetti Ketchup.
Ground Beef Cake Margarine.
Dairy Fruits & ................
Vegetables
Milk Apples ................
Cheddar Cheese Frozen Peas ................
................. Fresh Oranges ................
Furnishings and Services Furniture Misc. Household
Household Eqpt.
Operations.
Appliance Repair Living Room Chair Hammer.
Supplies Major Appliances Electric Drill.
Toilet Tissue Kitchen Range Show Blower.
Laundry Soap Refrigerator ................
Household Housewares & ................
Textiles Small Appliance
Bath Towel Two-slice Toaster ................
Clothing........ Men's and Boy's Infant's
Boy's Jeans Disposable ................
Diapers
Man's Jeans Footwear ................
Man's Parka Man's Shoes ................
Women's and Apparel Products ................
Girl's and Services
Woman's Slacks Coin Laundry ................
Girl's Blouse ................. ................
Girl's Jeans ................. ................
Recreation...... Fees and TV, Radio and Entertainment.
Admissions Eqpt.
Bowling Video Rental All Terrain
Vehicle.
Downhill Skiing Pets Board Game.
................. Pet Food Reading.
................. ................. Magazine.

From its ten categories of expense (which include the four
subdivided categories above), Runzheimer selected a marketbasket of
items on which to base its goods and services analysis. A
``marketbasket'' is a selected group of products and services that
represent hundreds or even thousands of other items. Pricing every item
available to consumers in a given locale would be unnecessary,
inefficient, and probably impossible.
Runzheimer selected typically purchased items and weighted these
according to their relative importance in terms of consumer expenditure
patterns. Each marketbasket item represented a specific group of
related expense items. Using CES data, we determined the relative
importance (weight) of each item. We compared the average price of each
marketbasket item in each allowance area with the average price in the
Washington, D.C., area. The price differences (expressed as indexes)
were aggregated based on the item, subcategory and category weightings,
resulting in a total Goods & Services component index at each income
level.
In 1991, OPM directed Runzheimer to include catalog pricing
(including applicable shipping costs) to reflect this common purchasing
option in allowance areas. OPM identified items to survey based on
comments received on the 1990 survey. Runzheimer identified items to
survey that were either unavailable or difficult to find in each
allowance area. Together, OPM and Runzheimer agreed to survey eight
marketbasket items by catalog.
In each allowance area Runzheimer generally requested three price
quotes for each item (and sometimes more than three) from the local
economy--one from each of three different outlets.
3.2 Marketbasket Research
3.2.1 Expenditure Research--Category Weightings
Runzheimer tabulated the expense data from the 1988 Consumer
Expenditure Survey according to the ten categories of goods and
services. As in the component analysis, Runzheimer used the expense
data from the seven most appropriate income ranges as input into a
linear regression analysis. From that analysis, Runzheimer calculated
the category weightings for each income level as listed below:

Category Weightings Expressed as a Percentage
------------------------------------------------------------------------
Category Lower Middle Upper
------------------------------------------------------------------------
Food at Home..................... 25.52 22.38 19.35
Food Away from Home.............. 15.95 16.09 16.23
Tobacco.......................... 3.13 2.54 1.96
Alcohol.......................... 2.92 2.79 2.67
Furnishings & Hsld. Op........... 14.35 15.95 17.49
Clothing......................... 14.24 14.93 15.59
Domestic Service................. 1.78 1.79 1.81
Professional Services............ 5.77 5.84 5.91
Personal Care.................... 3.57 3.47 3.38
Recreation....................... 12.77 14.22 15.61
--------------------------------------
Totals..................... 100.00 100.00 100.00
------------------------------------------------------------------------

3.2.2 Expenditure Research--Subcategory and Item Weightings
Runzheimer also drew upon the expense data from the 1988 CES to
determine proper subcategory and item weightings and to identify
marketbasket items. Logical groupings of family expenditures provided
the basis for subcategory and item weights. Unlike category weightings,
which vary by income level, subcategory and item weightings are
computed from national aggregate expenditures only (i.e., all three
income levels used the same set of subcategory and item weightings) as
this approach is most common in similar private sector cost-of-living
analyses.
Runzheimer's expenditure research process included procedures to
ensure that no marketbasket item had an overwhelmingly large or
insignificantly small item weighing.
3.3 Marketbasket Item Specifications
From each logical expense grouping, Runzheimer selected one or more
marketbasket items to represent all items in the grouping. When
selecting specific items for the marketbasket, Runzheimer worked to
satisfy these three criteria:
Items should be readily available in all locations if
possible or should be items of local significance (e.g., snow blower).
Item price levels should logically represent the price
levels of unselected items in the ``logical grouping.''
Items should have the same or nearly the same application
in all locations.
Appendix 2 lists Runzheimer's marketbasket items. Once an item was
selected, Runzheimer's research analysts identified the specific brand
and/or model/size of each item available in all (or most) locations.
For some items, this involved contacting manufacturers, trade
associations, retail establishments, etc. For other items, isolating
specifications was quite straight forward because of their nature
(e.g., bread, sirloin steak, nonprescription pain reliever). Appendix 3
identifies changes in the current items selected for pricing in the
Goods & Services, Miscellaneous Expense, and Housing Related
categories, along with explanation for the changes.
3.3.1 Exchange and Commissary Expenditure Research
Runzheimer used the same marketbasket items to price commissaries
and exchanges as were used for the local pricings. We obtained one
price quote for each marketbasket item surveyed in these facilities.
Runzheimer did not assume that people with access to military
facilities made all purchases in these facilities. Instead, we used
OPM's 1980 Living Pattern Survey of federal employees to determine the
percentage of purchases that families typically make in military
facilities versus local outlets. These percentages were used to
aggregate the local and commissary/exchange prices into one set of
appropriate, blended prices. (The blended prices were compared to the
local prices in the Washington, D.C., area just as each allowance
area's local prices were.)

Percentages of Purchases Made at PX/Commissaries
------------------------------------------------------------------------
Allowance Area
Category -------------------------
Fairbanks Anchorage
------------------------------------------------------------------------
Food at Home.................................. 61.3 66.2
Food Away..................................... 0.0 0.0
Tobacco....................................... 81.0 71.0
Alcohol....................................... 53.0 47.0
Furn. & Hsld. Op.............................. 46.2 44.3
Clothing...................................... 17.3 18.3
Domestic Service.............................. 0.0 0.0
Professional Services......................... 0.0 0.0
Personal Care................................. 59.5 36.0
Recreation.................................... 49.7 33.7
------------------------------------------------------------------------

3.4 Goods & Services Data Collection Procedures
3.4.1 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).
Runzheimer collected data with OMB-approved data collection
materials (see Appendix 5). All Runzheimer-developed worksheets
conformed to the OMB-approved materials.
3.4.2 Outlet Selection
Proper outlet selection is crucial to measuring living-cost
differences accurately because misjudgment can seriously affect survey
results. Runzheimer paid particular attention to choosing appropriate
outlets, focusing on three key guidelines to ensure proper outlet
selection.
First, for areas that had numerous outlets from which to choose,
Runzheimer identified targets in several different geographic areas.
For example, in the Washington, D.C., area, Runzheimer selected outlets
in and around six different geographic areas: that is, two areas in
Virginia, two in Maryland and two in the District of Columbia.
Runzheimer's second guideline was that for any one marketbasket
item, all outlets be similar in type. For example, Runzheimer surveyed
two of the three food items in full-service grocery stores and the
third food item in a warehouse-type grocery store in all locations
where such stores are found. Gathering prices from all warehouse-type
stores in one location and all full-service grocery stores in another
would have distorted price comparisons.
The last guideline involved the diversity of outlets in
Runzheimer's sample. We believe that pricing different items in
different types of outlets more accurately portrays living-cost
differences. For example, for efficiency, Runzheimer could have priced
all clothing items in department stores. However, to incorporate price
levels at other types of outlets that sell clothing items, whenever
possible, Runzheimer surveyed some items in men's and women's clothing
stores, some items in department stores, other items in shoe stores and
still other items in discount department stores.
Runzheimer's research analysts selected outlets on the basis of:
Personal experience of Runzheimer on-site research
associates and travelling researchers;
Informal telephone interviews with knowledgeable residents
in each area;
Yellow pages sections of area telephone books;
Area chambers of commerce and information bureaus; and
Experience gained from other surveys conducted by
Runzheimer.
With new businesses constantly appearing (and old ones
disappearing), outlet selection will be an ongoing process. Also, one
can expect a portion of outlets to refuse to participate every year.
Therefore, updating Runzheimer's outlet sample is a necessary and
important part of each pricing survey.
An example of refining outlet selection for this year's survey is
the attention paid to defining the distinguishing differences between
restaurants categorized as appropriate for family dining and those
appropriate for fine dining. OPM developed a matrix which defined such
characteristics as menu selections, atmosphere, table setting, seating,
reservations, and AAA rating. This allowed Runzheimer researchers to
compare apples to apples between the allowance areas and the Washington
D.C. area. Also, OPM established guidelines directing Runzheimer to
survey 100% family restaurants for breakfast, roughly 75% for lunch,
and roughly 66% for dinner.
3.5 Inclusion of Sales and Excise Taxes
For all items subject to sales tax, the appropriate amount of tax
was added prior to analysis. Runzheimer gathered applicable information
on taxes by contacting appropriate sources of information in the
allowance areas. Runzheimer also drew upon 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/Borough of Juneau.
3.6 Goods & Services Survey Results
In section 2.2 of this report, Runzheimer presented a detailed
explanation of the economic model used to analyze the price data. As it
applies to Goods & Services, the approach involved comparing the
average prices of marketbasket items in each allowance area with those
in the Washington, D.C., area. The resulting price ratios were
aggregated into subcategory and then category indexes using the
expenditure weightings derived from the 1988 CES.
In the area of professional services (accountant and legal fees),
Runzheimer and OPM noted the existence of a relatively few extreme
values that were either exceptionally low or high cost. In situations
such as this, statisticians frequently use the median or trim the data
in some manner to enhance reliability. Consequently, Runzheimer
recommended that the observations be ranked from low to high and that
the top and bottom 20% of the observations be ``trimmed'' (i.e.
eliminated) from the data before averages or trends were calculated.
(Data were not trimmed if there were fewer than five observations.) OPM
agreed. These procedures reduce the influence of anomalies and make
survey results more stable from one year to the next.
Appendix 4 contains tables showing the ten category indexes, the
three weighing patterns, and the three total consumption Goods &
Services indexes for each allowance area. The Washington, D.C., area
does not require a table because it is, by definition, ``the reference
location'' where all category and component indexes equal 100.

4. Housing

4.1 Component Overview
The Housing component consists of expenses related to owning or
renting a dwelling. These include:
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, Runzheimer measured annual
housing costs under the two main housing categories: ownership and
rental.
4.2 Housing Model
4.2.1 Expenditure Research
Section 2.1.2.4 describes how Runzheimer analyzed the 1988 CES to
identify the portion of expenses attributable to each of the four
components. Runzheimer also used this survey to determine the national
average ratio of families who own, as opposed to rent, their
residences. Using the expense data from the seven most appropriate
income ranges as input into a linear regression analysis, Runzheimer
calculated own and rent weights:

Own/Rent Weightings
------------------------------------------------------------------------
Income levels
-----------------------------------------------
Category Lower Middle Upper
(percent) (percent) (percent)
------------------------------------------------------------------------
Homeowner*.............. 37.10 46.91 62.86
Renter.................. 62.90 53.09 37.14
Totals............ 100.00 100.00 100.00
------------------------------------------------------------------------
*With mortgage.

Runzheimer excluded expenditure data for homeowning families
without a mortgage because they were not typical of homeowners in the
base area or in the allowance areas with the largest concentrations of
federal employees.
The 1988 CES was also used to identify which home-maintenance items
to price and to establish the relative importance of those items.
4.2.2 Development of Housing Profiles
To compare housing costs accurately in all locations, Runzheimer
constructed a model to measure housing costs under six different
circumstances; that is, we identified six typical housing profiles and
matched these profiles to three income levels, as shown in the table
below. Runzheimer and OPM agreed that at least one criterion for the
owner profile should be the square footage of the home and at least one
criterion for the renter profile should be the number of bedrooms in
the rental unit. The profiles for homeowners and renters are:

Housing Profiles
------------------------------------------------------------------------
Income level Renter profile Owner profile
------------------------------------------------------------------------
Lower.................. 3-1-1 600* sq. ft. apt. 4-2-1 900 sq. ft.
Condo or detached
house.
Middle................. 4-2-1 900 sq. ft. apt.. 5-3-1.5 1,300 sq. ft.
detached house.**
Upper.................. 4-2-2 or 5-3-2 1,100 7-3-2 1,700 sq. ft.
sq. ft. townhouse or detached house.
detached house.
------------------------------------------------------------------------
*Defined as ``Total rooms--Bedrooms--Baths and representative size.''
Total rooms excludes bathrooms, hallways, entrance areas, and closets
but includes bedrooms, living room, family room, kitchen, formal
dining room, and den/study. The representative size is roughly the
midpoint size for the range of housing surveyed at the income level.
**Row houses may be used in Northeast Washington, D.C., where the
availability of single family detached homes is limited.

4.2.3 Living Community Selection
Runzheimer surveyed the same living communities for the Winter 1994
survey as it did for the winter survey portion of the 1992/1993 study.
To gather data, our researchers contacted real estate brokers,
residential appraisers and other knowledgeable real estate
professionals in each area to obtain information on the predominant
age(s), size(s) and type(s) of housing in various communities and
housing subdivisions. When available and appropriate, Runzheimer
identified at least six communities (two at each income level) in each
allowance area. However, this goal was not achievable in some of the
smaller allowance areas. For the Washington, D.C., area, Runzheimer
selected nine communities (three at each income level) in which to
gather renter and homeowner data.
A table of living communities used for pricing can be found in
Appendix 6.
4.2.4 Identification and Quantification of Housing-Related Expenses
From the 1988 CES, Runzheimer identified and categorized housing-
related expense items into one of five groups:
utilities,
real estate taxes,
owners/renters insurance,
maintenance, and
telephone.
4.2.4.1 Utilities
For this study, Runzheimer classified electric, heat (oil or gas),
water and sewer as utilities. Although most utility companies had ready
access to current charges per unit of consumption and average
consumption patterns for all households, very few (if any) separated
consumption patterns by number of family members in a household or by
size/type of accommodation.
Runzheimer focused on average annual consumption experience per
household, gathering this information from utility companies serving
each allowance area and the Washington, D.C., area. Combining this
consumption data with current utility rates, Runzheimer computed
average annual utility costs for each of electric, gas or oil
(whichever Runzheimer found to be more widely used, if used at all),
water and sewer. Runzheimer then assigned this average consumption
pattern to the homeowner profile at the middle income level.
Because some utility costs vary by size of house and yard,
Runzheimer calculated a multiplier consistent with the standard home
sizes to arrive at utility rates for the other five profiles. The table
below shows the standard sizes and utility factors for each profile.
The standard sizes roughly equate to the reference size of each
profile. The formula to calculate each multiplier was:

Multiplier = 1 + (.5 x (Standard square feet--1300)/1300)

The resulting utility multipliers are:

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

4.2.4.2 Real Estate Taxes
For this study, Runzheimer contacted the city assessor in each
allowance area to obtain real estate tax information on the selected
living communities. Real estate tax formulas were obtained for most
living communities. Actual or representative tax amount paid were
obtained in other communities.
4.2.4.3 Owners/Renters Insurance
As it did for previous surveys, Runzheimer undertook to gather
insurance-rate information for the allowance areas for both renter and
owner profiles. These rates represent coverage for structure and
contents for homeowners but contents only for renters.
Previous research conducted by Runzheimer, at the request of OPM,
found that insurance coverage for disasters, such as floods and
earthquakes, is not prevalent in the allowance areas; consequently,
Runzheimer, with the concurrence of OPM, does not consider these
additional riders. (See Report to OPM on Living Costs in Selected
NonForeign Areas and in the Washington-D.C., Area, June 1992 at 57 FR
58556). Runzheimer notes, however, that OPM is reviewing the results of
the Federal Employee Housing and Living Patterns Survey as they apply
to this issue.
4.2.4.4 Maintenance
Many factors were involved in measuring the cost of maintaining a
home, including area climate, architecture and building materials, and
the cost of maintenance materials and labor. As it did for the previous
survey, Runzheimer priced such household maintenance commodities as
fire extinguisher, bathroom caulking and kitchen faucet. Pest control
service was priced in every allowance area except Nome, Alaska, where
local sources indicated it wasn't necessary.
Runzheimer developed maintenance costs based on the cost of
maintenance materials and labor rates in each area. Runzheimer's
approach to maintenance was the same as the approach to goods and
services, as explained below.
Runzheimer used expenditure data from the 1988 CES to identify the
national average home-maintenance expense, the maintenance items to
survey, and the appropriate item weighing. Because most, if not all,
maintenance items were included in rent, maintenance costs were not
added in the three renter profiles.
To compute home-maintenance cost differences between each allowance
area and the Washington, D.C., area for the homeowner profiles,
Runzheimer obtained prices for selected building materials and labor
rates for maintenance work. For each area, Runzheimer computed the
relative cost (i.e., an index) for each maintenance item compared to
the cost of that item in the D.C. area. As with Goods & Services, the
results of the nationwide CES were used to weight these maintenance
indexes into an overall index for each area.
To combine maintenance indexes with the other homeowner costs,
which were expressed in dollar amounts, Runzheimer converted the
indexes to dollars. To do this, Runzheimer multiplied the maintenance
cost index for each area by the CES nationwide average maintenance cost
and assigned that cost to the middle-income homeowner profile.
Logically, maintenance costs for larger homes would be greater than
costs for middle-sized homes, while costs for smaller homes would be
less. Therefore, in this study, Runzheimer applied the same homeowner
multipliers used in the utilities model for the lower and upper income
profiles (.85 and 1.15 respectively) to recognize differences in
maintenance costs due to house size.
4.2.4.5 Telephone
Telephone expenses consisted of local service charges, possible
additional charges for local calls, and charges for long distance
calls. To measure estimated expenses for local service and local calls,
where available, Runzheimer surveyed the cost of touch-tone service
with unlimited calling.
To estimate long distance charges in all areas, Runzheimer 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).
Runzheimer 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 8:00
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 was done in previous years, Runzheimer collected housing
information from a variety of sources. Also as in previous years,
Runzheimer research personnel traveled to profiled communities in the
allowance areas to observe first hand the comparability of homes in one
area versus another and the appropriateness of individual housing units
for the profiled income level.
In previous surveys, OPM required several additional steps to
increase the quantity and quality of housing data collected. These
extra steps were again taken this year and included purchasing data
from additional real estate listing services, making greater use of
assessor's records when other data were not available, and contacting
more real estate professionals to obtain additional home sales, rental
data, and market trend information.
4.3.1 Homeowner Data Collection
In the homeowner data-gathering phase, Runzheimer obtained sale
prices of homes (called ``comparable sales'') in the area that matched
the housing profiles. In the communities that were identified (see
section 4.2.3), Runzheimer tried to obtain all the comparable sales
during the 6-month period prior to the date of the survey. For the
winter surveys, the pricing period was July 1993 through February 1994.
As was done last year, Runzheimer contacted knowledgeable and
helpful real estate professionals in each location and/or used real
estate sales data and listing services. The amount of data obtained
depended on the number of home sales in the community and the
availability of square footage and other information. This in turn
depended on the size of the community, the economic conditions, the
quality and quantity of the realty data available, and the willingness
and ability of local realty professionals and assessor offices to
provide data. If the comparable sales data obtained from the first data
sources were insufficient, Runzheimer contacted additional data sources
in the area to attempt to secure more sales data, if practical.
4.3.2 Renter Data Collection
In some cases, the same realtors and brokers who assisted in our
profiling phase were very active in the rental markets as well. When
this occurred, Runzheimer obtained current rental rates and fees for
our profiled apartments, townhouses and houses from these sources.
Runzheimer also contacted rental management firms that operated
apartment complexes matching the profile specifications. In large
metropolitan areas, such as the Washington, DC, area where rental
complexes abound, our housing analysts conducted telephone surveys to
obtain current rental information.
Rental data were obtained from a variety of sources, e.g., brokers,
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.
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. Because OPM has no information on how federal employees
who rent generally secure their lodgings, OPM requested that Runzheimer
apply equal weights to the broker and non-broker data to compute the
overall average rental rate for the area and income level. (See
Appendix 9B.)
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. For each income profile
in each allowance area and the Washington, DC, area, Runzheimer
computed that average price per square foot for the comparables.
Runzheimer used this value times the reference square footage for the
profile to determine the average home value for the profile.
4.4.1.1 Data Trimming
OPM requested that Runzheimer continue to apply the special
procedures developed during the 1992/1993 surveys. In 1992/1993, based
on experience from the previous home-pricing surveys, OPM modified the
living-cost model as it applied to the analysis of housing data. The
modifications allow the use of housing costs trend data as well as
current housing costs in the analysis of owner and renter living costs.
These analyses are consistent with section 591.205(b)(3) of title 5,
Code of Federal Regulations, and result in improved housing data
results.
One of the modifications involves ``trimming'' the observations. In
past surveys, Runzheimer and OPM noted that a relatively few extreme
values (values that were either exceptionally low or high cost) could
have a significant influence on the average housing costs observed at
an income level within an area. Including these extreme values had the
potential to cause results to vary erratically from one year to the
next.
In situations such as this, statisticians frequently use the median
or trim the data in some manner to reduce its volatility. The use of
the median home value was not desirable because some areas had
relatively sparse data at one or more income levels. This could make
the median unstable from one year to the next.
In the 1992/1993 surveys, Runzheimer recommended, and OPM agreed,
that the observations be ranked from low to high on the basis of the
cost per square foot and that the top and bottom 20 percent of the
observations be ``trimmed'' (i.e., eliminated) from the sample before
averages or trends were calculated. (Data were not trimmed if there
were fewer than five observations.) These procedures reduce the
influence of home sales anomalies and make survey results more stable
from one year to the next.
4.4.1.2 Special Considerations
The new procedures also involved analyzing data in a more thorough
and integrated manner. The procedures required analyzing the current
housing survey data, analyzing the trends observed when these data were
compared with the previous survey's data, and comparing these trends
with the views obtained from real estate professionals in the area. How
and which data were used depended on the quality and quantity of data
collected and how the trends observed agreed among income levels and
with the views of local real estate professionals. These procedures are
discussed below.
Runzheimer sought to gather all of the appropriate comparable sales
data available in each area. As a minimum, Runzheimer sought to obtain
10 realtor sales per community per income level or 20 per income level
per area. In many areas, the sales data exceeded the minimum.
If the minimum number could not be obtained or if highly divergent
trend data were observed among income levels in the area or as compared
with the views of local real estate professionals, additional analyses
were performed. These analyses were:
1. If the current data were significantly better than the previous
data (e.g., greater in quantity or more consistent), the current data
were used to the extent practical.
2. If at least three observations at each income level were
available, and the previous data were better than the current data or
the previous and current data were of equivalent quality, the change
(i.e., trend) in the average price was used to update the previous
data. This was done using one of the following procedures, depending on
the situation:
a. If data problems occurred at one income level only, the average
rate of change at the other two income levels was used to adjust the
previous prices for the affected income level.
b. If data problems occurred in two income levels, the rate of
change observed at the non-problem income level was used to adjust the
previous prices for the two affected income levels.
c. If data problems occurred at all income levels, the average rate
of change observed at all three income levels was used to adjust the
previous prices at all income levels.
3. If fewer than three observations were available at any income
level and/or the data quality was questionable at all levels, all three
levels of current and previous survey data were merged. These data were
then analyzed by applying the procedures described in section 4.4.1
above to each set of merged data, and the average cost per square foot
was computed for each set of data and compared to estimate the overall
change in the area. This overall change was applied to the previous
average costs by income level to determine the current costs at each
income level for the area.
The areas for which these procedures were applied and the
calculations used are found in Appendix 9A.
4.4.2 Rental Data Analysis
Runzheimer assigned each rental quote data point to a single income
level, based on these criteria:
Assign one bedroom apartments to the lower income level.
Assign two bedroom apartments to the middle income level.
Assign townhouses and detached houses with a minimum of
two bedrooms to the upper income level.
4.4.2.1 Data Trimming and Special Analyses
In the analysis of rental data, Runzheimer applied the same
procedures used to trim the home sales data (see section 4.4.1.1)
except that data were ranked on the basis of monthly rental rates, not
cost per square foot. Also, as with home sales analyses, special
analyses were applied to rental data when the data were sparse or
highly divergent trends were observed among income levels. These
analyses were the same as those applied to home sales data (see section
4.4.1.2) except that if data were merged, overall estimates were based
on monthly rental rates, not the cost per square foot. (See Appendix 9B
for these analyses.)
4.4.3 Analysis of Housing-Related Expenses
Because section 4.2.4 covers the identification and quantification
of housing-related expenses, these topics are not repeated here.
However, it should be noted that Runzheimer incorporated home sale
prices from this study into the calculations of real estate taxes and
homeowner's insurance, which depend upon the value of the home.
4.5 Housing Survey Results
In the above sections, Runzheimer describes how it measured the
costs for maintenance, insurance, utilities, real estate taxes, rents,
and homeowner mortgages. Appendix 7 shows the cost of each of these
items, for renters and homeowners separately, in each allowance area
and in the Washington, DC, area.
Appendix 8 compares the total cost of these items in each allowance
area with the total cost of the same items 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 14 to derive the total, overall index for owners
and renters. (Refer to section 2.2 for a discussion of the general
formulae and how the component indexes are combined.)

5. Transportation

5.1 Component Overview
The Transportation component consisted of expenses related to
private and public transportation. The private transportation category
contained expenses related to owning and operating a vehicle in each
area. The public transportation category focused on the cost of air
fares from each location to a common point within the contiguous 48
states.
As was done in previous surveys, Runzheimer used national average
expenditure data to combine the private and public transportation
relative cost differences between each allowance area and the
Washington, DC, area to arrive at a total Transportation component
index.
5.2 Private Transportation Methodology
Runzheimer determined that an accurate and reasonable approach to
measure transportation costs was to select and analyze three commonly
driven vehicles (a domestic auto, an import auto and a utility vehicle)
in all areas.
New vehicles were the basis for developing the transportation-cost
calculations. Although Runzheimer could have developed costs from the
premise that ``identical'' used vehicles would be purchased from auto
dealers in each location, Runzheimer believed that costing new vehicles
reduced the potential for inconsistencies due to value judgements
concerning used vehicles.
5.2.1 Vehicle Selection and Pricing
As mentioned above, Runzheimer selected and priced a domestic auto,
an import auto, and a utility vehicle as the basic vehicle types to
cost in all locations. We based our selection of these vehicle types on
their popularity in the United States as demonstrated by owner
registration data.
To select a specific make and model within each vehicle type,
Runzheimer identified the top-selling models in each car class. For
these models, Runzheimer's research associates collected new vehicle
prices.
At each auto dealership in the sample, Runzheimer recorded the
suggested retail prices of the three vehicles plus any additional
charges, such as shipping, excise tax, dealer prep, and additional
dealer markup. Runzheimer used the suggested retail prices (not
negotiated prices) in the analysis. Runzheimer also included
documentation fees as part of the new-vehicle costs in Alaskan
locations. Contacted dealerships explained that a documentation fee is
charged on a new-car purchase to cover paperwork costs.
Runzheimer did not include a fee for the Washington, D.C., area
because dealers in those areas do not typically charge a documentation
fee.
The three vehicles selected for analysis were:

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

Runzheimer priced 1994 models.
All vehicles were equipped with standard options, such as automatic
transmission, AM/FM stereo radio and air conditioning. As done in the
1992/1993 survey, at OPM's request, Runzheimer also priced snow tires,
engine-block heaters, and heavy-duty batteries in all of the Alaskan
locations.
Car dealers in the Washington, D.C., area did not recommend vehicle
rustproofing. However, it was suggested or recommended in allowance
areas. Therefore, we included rustproofing as an add-on in all
allowance areas, but not in the Washington, D.C., area.
5.2.2 Vehicle Trade Cycle
Calculating the cost to own and operate a vehicle requires that two
important factors be determined: miles driven and time period of
ownership. 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 either in months or years, and the total number of
miles driven in that time period (e.g., four-year, 60,000-mile trade
cycle). This information is required to compute annual costs related to
fuel, oil, tires, maintenance and depreciation.
Conforming with previous living-cost reports, Runzheimer used a
four-year 60,000-mile trade cycle in all areas based upon the following
information:
The Internal Revenue Service has used this trade cycle for
many years 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.
U.S. Department of Energy statistics for 1988 show that
the U.S. average for number of vehicle miles driven was: 18,595 per
household and 10,246 miles per vehicle.
Runzheimer has been unable to find conclusive statistics on average
annual miles driven per vehicle in any allowance area. In 1991,
Runzheimer contacted car dealers to obtain their observations on
average odometer mileage on trade-in vehicles and informally asked
other residents of each area for their opinions.
From the opinions gathered, we concluded that, in most cases, the
average annual miles driven in allowance locations appeared to be less
than or equal to 15,000. In the Washington, D.C., area, the opinions of
those contacted indicated an average annual mileage of 15,000 or more.
Therefore, without definitive statistics to prove otherwise, Runzheimer
set a standard used in all reports to date of 15,000 miles per year,
which results in a four-year, 60,000-mile trade cycle.
5.2.3 Fuel Performance and Type
To establish average fuel-performance ratings, Runzheimer selected
the ``city driving'' figures published by the Environmental Protection
Agency (EPA). Runzheimer chose the ``city'' instead of ``highway''
figures because all locations contained considerable stop-and-go
driving conditions. All vehicles included in this study used regular
unleaded fuel. Except in Alaska, Runzheimer obtained self-service cash
prices and substituted full-service when self-service was not
available. At OPM's request, Runzheimer priced gasoline at the full-
service pump in Alaska.
As in its second report to OPM, Runzheimer has included in its
analysis a number of fuel-performance factors; specifically,
temperature, road surface, and gradient. Based on our research of these
three factors, Runzheimer analysts developed fuel-performance
adjustment percentages in each allowance area.
5.2.3.1 Impact of Temperature Upon Fuel Performance
Runzheimer consulted two published sources to develop its
adjustment percentages for this fuel-efficiency factor: Passenger Car
Fuel Economy: EPA and Road and The Weather Almanac (Ruffner & Blair).
Miles-per-gallon performance varies by ambient temperature. The lower
the temperature, the fewer miles-per-gallon achieved and vice versa. In
the EPA study, the temperature at which no adjustments to fuel
performance occur is 77 deg.F. Below that temperature, miles-per-gallon
achieved drops; above 77 deg., miles-per-gallon achieved improves. To
measure the effect temperature has on miles-per-gallon for each
allowance area, Runzheimer researched average monthly temperatures as
reported in The Weather Almanac.
In each location and for each month, Runzheimer assigned the
appropriate shortfall factor from the EPA study based on the average
monthly temperature for each given location. For example, if the
average monthly temperature was 35 deg., the shortfall factor in miles-
per-gallon would be 0.876. After assigning factors to each month,
Runzheimer averaged the twelve factors for each location. The results
of these calculations are shown in section 5.2.3.4.
5.2.3.2 Impact of Road Surface Upon Fuel Performance
For its analysis, Runzheimer assumed that federally controlled
roadways are typically composed of concrete and/or high-load asphalt
and that locally controlled roadways are typically composed of low-load
asphalt. EPA's research indicates that cars are generally more fuel-
efficient on the firmer, high-load surfaces than on the softer, low-
load surfaces.
Although traffic patterns and road usage certainly vary among
areas, Runzheimer could find no relevant studies of these issues.
Therefore, Runzheimer assumed that federally controlled roadways
generally support twice the traffic of or are used at least twice as
much as locally controlled roadways.
In each allowance area, Runzheimer researched the total mileage
falling into either the federal or local categories. For example,
Alaska contains 5,512 miles of federally controlled roads and 7,120
miles of locally controlled roads. The usage assumption allowed
Runzheimer to increase federal road mileage by a factor of two.
Runzheimer applied the average low-load asphalt factor (which
reflects dry, wet, and snowy conditions) to the local mileage
percentage and the average concrete and/or high-load asphalt factor to
the federal mileage percentage to create a weighted average factor for
each area. These weighted factors for Alaska ranged from 0.94 to 0.97.
The Washington, D.C., area was assigned a factor of 1.00 on the premise
that the vast majority of traffic in that area travels on dry, high-
load surfaces. (See section 5.2.3.4 for application of this factor in
estimating overall miles-per-gallon.)
5.2.3.3 Impact of Gradient Upon Fuel Performance
Runzheimer consulted EPA's Passenger Car Fuel Economy: EPA and Road
to determine the effect of local topography (i.e., gradient) upon fuel
efficiency. EPA provides mileage factors based upon various gradients
ranging from less than 0.5% (essentially flat) to greater than 6%
(steep).
Runzheimer reviewed the topographic features of each area and found
a wide range of road conditions. However, Runzheimer was unable to find
information on the types of terrain drivers typically encounter in each
area or the number of miles drivers travel in each type of terrain.
Lacking such information, Runzheimer assumed that drivers in the
allowance areas generally travel roads having approximately the same
gradients that are found on average in the United States. Applying the
information from EPA's research, Runzheimer computed a fuel-performance
factor of 0.981 for this type of driving. This factor was assigned to
each allowance area. Runzheimer assigned a factor of 1.00 to the
Washington, D.C., area on the premise that the vast majority of traffic
in that area travels on major freeways and highways that are relatively
flat. (See section 5.2.3.4 for application of this factor in estimating
overall fuel efficiency.)
5.2.3.4 Overall Impact Upon Fuel Performance
Runzheimer applied the results of the analyses described above to
``localize'' or make geographically sensitive adjustments to the EPA
average ratings and establish reasonable fuel-performance ratings for
each allowance area.
In the table below, the factor 1.00 means that no adjustment to EPA
fuel performance is appropriate. A factor of less than 1.00 means that
the estimated gasoline mileage in the area is less than the EPA
average. For example, the total adjustment factor for Fairbanks/Nome is
0.80. This means that the estimated gasoline mileage in Fairbanks and
Nome is 80% of the EPA estimated average. Note that the adjustment
factor for the Washington, D.C., area (0.94) indicates that average
gasoline mileage in that area is below the EPA estimate also.

Summary of Fuel-Performance Adjustments
------------------------------------------------------------------------
Road
Location Temperature surface Gradient Total
------------------------------------------------------------------------
Anchorage........... 0.88 0.96 0.98 0.83
Fairbanks/Nome...... 0.85 0.96 0.98 0.80
Juneau.............. 0.89 0.96 0.98 0.84
Washington, D.C..... 0.94 1.00 1.00 0.94
------------------------------------------------------------------------
Note: These adjustments compound. That is, the Total adjustment is the
result of multiplying the three individual factors together for each
location/area.

5.2.4 Vehicle Maintenance
With OPM's concurrence, Runzheimer selected the five most common
maintenance service/repair jobs performed on vehicles as the basis for
vehicle maintenance analysis:
tune-up,
oil change,
automatic transmission fluid change,
flush/fill coolant, and
muffler installation.
Automobile manufacturers' recommended maintenance schedules were
used to determine the frequency of performing each of these maintenance
jobs. Maintenance schedules vary, depending on the driving conditions
typically encountered. Consistent with the assumptions used for fuel
economy and tire mileage, Runzheimer assumed that driving conditions in
the allowance areas were generally severe and used the maintenance
schedules that reflected that kind of driving. For the D.C. area,
Runzheimer assumed that driving conditions were normal and used the
maintenance schedules that reflected that kind of driving.
The recommended frequency of performing each of these jobs was
combined with the prices charged by local dealers and service stations
to compute an estimated annual maintenance expense.
For Alaska, Runzheimer included constant velocity (CV) joint boots
as well. Runzheimer's research of CV joint boot replacement revealed
varying replacement cycles between Alaskan allowance areas: Anchorage--
every 45,000 miles (3 years), Fairbanks--every 15,000 miles (1 year),
Juneau--every 45,000 miles (3 years) and Nome--every 30,000 miles (2
years). The cost of replacement for all three vehicle types has been
factored into the indexes based upon the life cycle of the replacement.
For example, 100% of the cost was included for Fairbanks because
research indicated annual replacement was the norm. Only 50% of the
cost was included for Nome where research indicated bi-annual
replacement.
5.2.5 Tires
Research previously conducted by Runzheimer for OPM (see the June
1992 report) revealed that various factors (e.g., road quality/state of
repair, road composition) caused tread life (the average number of
miles a tire is expected to last) to be less in allowance areas than in
the Washington, D.C., area. Based on these findings (some of which were
quantitative), Runzheimer based tire expenses on a 40,000-mile tread-
life in allowance areas, and a 55,000-mile tread-life in the
Washington, D.C., area.
Runzheimer's research also indicated that four extra snow tires,
with studs, would be required for all three vehicles in Anchorage,
Fairbanks, and Juneau. For Nome, Runzheimer's research revealed that
mud and snow tires would be appropriate for the S10 Blazer but not the
other two vehicles because all-season radials were reported to be the
norm. (Most of the driving in Nome occurs within a very confined area).
Therefore, as with the previous survey, Runzheimer surveyed the cost of
extra wheels, extra tires, and installing studs for all vehicles in
Anchorage, Fairbanks, and Juneau and the additional cost of mud and
snow tires for the S10 Blazer in Nome.
5.2.6 License and Registration Fees, and Miscellaneous Tax
Runzheimer obtained information regarding appropriate license and
registration fees, and miscellaneous taxes (i.e., personal property tax
and motor vehicle registration tax) from each area. One-time fees and
miscellaneous taxes were divided equally over each vehicle's four-year
trade cycle. Sales and excise taxes were included in the purchase price
of each vehicle (see section 5.2.7.). Ongoing fees and taxes were
included as part of the annual costs.
5.2.7 Depreciation
From Runzheimer's experience, the single largest annual expense
related to owning and operating newer vehicles is vehicle depreciation,
the lost value of the vehicle as it ages and is driven. To calculate
average annual depreciation, Runzheimer divides the difference between
the purchase price and the residual value by the number of years the
vehicle is owned.
In the depreciation equation, Runzheimer used suggested retail
prices, plus any additional charges, such as shipping, excise tax,
dealer prep, and additional dealer markup. (Runzheimer did not believe
that negotiated prices could be collected on an equitable basis.) As
discussed earlier, the trade cycle was determined to be four years,
60,000 miles. Runzheimer research indicated that residual values were
the same in all areas except Fairbanks and Nome. This research effort
is explained below.
Runzheimer is aware that several firms and associations track and
publish weekly or monthly used-car and used-truck wholesale auction
prices. Some firms even publish projections of the future value of
today's new vehicles. Most publications provide several residual values
for each vehicle, depending on its condition at the time of trade-in
(e.g., clean, average, rough). Several common publications of this type
are Black Book, Kelley Blue Book, Automotive Market Report, and NADA
(National Automobile Dealers Association). Unfortunately, these sources
only track prices for vehicles sold in the contiguous 48 states and
then publish broad-based average residual values for each vehicle.
To get specific information from sources knowledgeable about the
used vehicle markets in allowance areas, Runzheimer contacted auto
dealers and financial institutions in these areas. Most of the sources
with whom Runzheimer spoke said that they used the above-mentioned
publications as guides, just as dealers and financial institutions
across the United States used them.
Except for Fairbanks and Nome, Runzheimer found no conclusive
evidence that used vehicles in allowance areas were (on average) worth
more or less than used vehicles in the Washington, D.C., area.
Therefore, we reported the same used vehicle prices in all areas
(except Fairbanks and Nome). An appropriate and logical source for
these values was the October 1993 issue of Black Book Official Finance/
Lease Guide for 1994 vehicles. For Fairbanks and Nome, Runzheimer used
90% of the Black Book projected residual values to reflect rougher
conditions.
It should be noted for clarification that identical residual values
did not translate into identical depreciation amounts in all locations.
Depreciation amounts were higher in allowance areas than in the
Washington, D.C., area because new vehicle prices in all allowance
areas were higher.
5.2.8 Finance Expense
Runzheimer included the average annual cost of financing a vehicle
in the total cost of private transportation. Runzheimer surveyed banks
in all areas for their auto-loan interest rates, using a 48-month loan
length with 80% financing as the basis in all locations.
5.2.9 Vehicle Insurance
Runzheimer measured the cost of auto insurance in each location. To
determine the type of coverage to price, Runzheimer contacted insurance
agents in each area to obtain information on the typical policy. Listed
below are the most common coverages, limits, and deductibles for the
surveyed living-cost areas.

Bodily Injury--$100,000/$300,000
Property Damage--$50,000
Medical--$5,000
Uninsured Motorist--$100,000/$300,000
Comprehensive--$100 Deductible
Collision--$250 Deductible

In all areas, Runzheimer attempted to identify the most ``popular''
automobile insurance companies by analyzing market-share reports
compiled by an industry rating bureau. The policy described above was
then priced again this year for each location. Two or three price
quotes were obtained for each area and averaged together to produce the
final number for this component in each allowance area.
5.3 Public Transportation Methodology
As was done last year, Runzheimer surveyed the cost of air fares as
they relate to recreational travel. Runzheimer priced the lowest
available round-trip air fare from each allowance area and the
Washington, D.C., area to Los Angeles, California. Los Angeles was
selected because it is a common point approximately equidistant from
most of the allowance areas and the Washington, D.C., area. The cost of
the trip from each allowance area to Los Angeles was compared with the
cost of the trip from the Washington, D.C., area to Los Angeles to
compute the public transportation category indexes. (See Appendix 11.)
5.4 Transportation Survey Results
Runzheimer measured the costs for fuel, maintenance and oil, tires,
licensing, taxes, depreciation, finance, and insurance for three types
of automobiles in each allowance area and in the Washington, D.C., area
to determine typical private transportation costs. Appendix 10 shows
the cost of each of these items in each area.
Runzheimer also measured the cost of recreational air travel from
each allowance area and from the Washington, D.C., area to a common
point within the contiguous 48 states. Appendix 11 shows the cost of
these air fares and their relationship to the cost for the Washington,
D.C., area.
Appendix 11 compares the total cost of the private transportation
items for each vehicle in each allowance area with the total cost of
the same items in the Washington, D.C., area. Appendix 11 also shows
how the private and public transportation indexes were combined using
expenditure weights derived from the CES data to produce final
transportation indexes.
The final transportation indexes are used in Appendix 14 to derive
the total overall index. (Refer to section 2.2 for a discussion of the
general formulae and how the component indexes are combined.)

6. Miscellaneous Expenses

6.1 Component Overview
The Miscellaneous Expense component consists primarily of four
unrelated groups of expenses:
medical care,
contributions (including gifts to non-family members),
personal insurance, and
savings and investments (including pensions).
Runzheimer believes that certain miscellaneous expense items should
not affect living-cost measures between locations. For example,
Runzheimer considers charitable contributions a personal choice, so we
include this expenditure as a constant amount in all locations. Based
on research into all of the expenses of this component, Runzheimer also
regards expenses related to personal insurance, savings and
investments, and pensions as constants, for reasons discussed in
section 6.2.2.
To measure the miscellaneous expenses, Runzheimer constructed a
pricing methodology similar to the one used in the Goods & Services
component. Runzheimer selected representative items for medical care,
priced them in all areas, and then computed a Miscellaneous Expense
component index based on the relative importance of costed items and
categories held constant.
6.2 Miscellaneous Expense Model
6.2.1 Expenditure Research
From the 1988 CES, Runzheimer tabulated the miscellaneous expense
data into logical expense groupings and then determined the appropriate
item weighing. The table on the following page lists the categories
that Runzheimer selected to price and their weights:

Miscellaneous Expense Categories & Weights
------------------------------------------------------------------------
Income Level
-----------------------------------------------
Categories Lower Middle Upper
(percent) (percent) (percent)
------------------------------------------------------------------------
Medical Care............ 43.41 31.56 22.40
Contributions (including
gifts)*................ 12.38 14.90 16.85
Personal Insurance &
Pensions*.............. 44.21 53.54 60.75
Totals............ 100.00 100.00 100.00
------------------------------------------------------------------------
*Held constant.

6.2.2 Miscellaneous Expense Methodology
As stated in section 2.2, Runzheimer used the Laspeyres indexing
methodology to compute the Miscellaneous Expense component index. For
groups of items held constant, the model assumed a price ratio between
the allowance area and the Washington, D.C., area equal to 100.00%.
Runzheimer defined personal insurance and pensions as the portion
of a family's budget that was targeted for long-term financial
security. This is consistent with the definitions used by the CES, the
results of which are used as weights in the COLA model. In the CES,
money stored in a savings or investment vehicle for future expenditures
(of goods and services, housing, or transportation) is accounted for in
the other component weightings.
In section 6.1, we noted that expenses related to personal
insurance were held constant for all locations. This was based on
information received from life insurance companies and OPM officials.
The life insurance companies contacted indicated that policies written
(and premiums charged) to persons within the United States and its
territories did not vary due to location. Runzheimer's research and
discussions with OPM officials also indicated that, in general, federal
employees in all areas received similar or identical benefits
packages--any variations were due to personal preference. Therefore,
Runzheimer believed, and OPM concurred, that holding these types of
expenses constant was appropriate.
6.3 Miscellaneous Expense Data Collection Procedures
Medical care items were surveyed consistent with the approach used
in the Goods & Services component. For quality-control purposes,
Runzheimer used its in-house research staff to conduct much of this
survey.
The following medical-care items were priced in each allowance area
and in the Washington, D.C., area:
nonprescription pain reliever
prescription drugs
vision check
dental service
doctor visit
hospital room
health insurance
Runzheimer computed a Medical Care subcategory price index for each
item in each allowance area by comparing each local average price with
the Washington, D.C., area average prices. These indexes were combined
using weights derived from the CES to compute a Medical Care
subcategory index for each allowance area.
6.4 Miscellaneous Expense Survey Results
Appendix 12 contains the results of our data collection and index
calculations. As the appendix shows, the relative costs of the majority
of the items in the Miscellaneous Expense Component are based on
surveyed prices. Therefore, the Miscellaneous Component index reflects
living-cost differences among areas. The cost of only two items--life
insurance/pensions and contributions--does not differ among areas.
Although these two items together have a significant weight, one should
keep in mind that the Miscellaneous Component has the smallest weight
of the four components.
Section 2.2 describes how the Miscellaneous Expense component
indexes are combined with the other component indexes to derive the
final index for each area.

7. Final Results

7.1 Total Comparative Cost Indexes
The total comparative cost indexes appear below. Appendix 14 shows
how each index was derived from the component indexes.

Final Cost Comparison Indexes
------------------------------------------------------------------------
Local Commissary
Allowance area pricing & exchange
------------------------------------------------------------------------
Anchorage, Alaska................................ 103.94 101.32
Fairbanks, Alaska................................ 106.03 103.41
Juneau, Alaska................................... 108.10 NA
Other Areas in Alaska*........................... 127.56 NA
------------------------------------------------------------------------
*As represented by Nome, AK.
NA = Not Applicable.

7.2 General Comments
Runzheimer's primary goal throughout its work on each study has
been to bring fairness and accuracy to the results. The scope of this
multi-year engagement has become more comprehensive by virtue of
special research projects, seasonal pricings, expanded marketbasket
pricings and other efforts. Runzheimer believes that living-cost
research is a dynamic process, not a static one, and that fresh
research and analysis will enhance further the quality of the survey
and the findings. Moreover, we believe that planned, ongoing
interaction with OPM will aid the process and improve accuracy.
7.3 Recommendations
As noted earlier in this report, Runzheimer and OPM are researching
the issue of including income taxes in the living-cost surveys and
analyses. We believe that the research will show that income taxes
represent a significant portion of living expenses--a portion that
varies from one area to the next.
As also noted in the report, Runzheimer recognizes that it applied
the same salary levels and CES data this year as it did in the 1990
surveys. We commend OPM for introducing new federal employment weights
and urge OPM to continue with its plans to introduce gradually new CES
data and salary levels in future surveys.

Appendix 1.--Consumer Expenditure Survey (CES)
[By Income Before Taxes: Average annual expenditures and characteristics of all consumer units, Consumer
Expenditure Survey 1988, Feb. 13, 1990]
----------------------------------------------------------------------------------------------------------------
June 7, 1990
------------------------------------------------------------------------------------------
Item Total
complete $10,000 to $15,000 to $20,000 to $30,000 to $40,000 to $50,000 and
reporting $14,999 $19,999 $29,999 $39,999 $49,999 over
----------------------------------------------------------------------------------------------------------------
Number of consumer
units (in thousands) 81354 9433 8219 14586 10901 7198 12209
Number of sample
interviews.......... 30900 3500 3107 5496 4119 2849 4983
Consumer unit
characteristics:
Income before
taxes\1\.......... $28540 $12320 $17373 $24591 $34375 $44331 $74234
Income after
taxes\1\.......... 26149 11892 16345 22963 31660 40100 66345
Average number of
persons in
consumer unit..... 2.6 2.2 2.5 2.7 2.9 3.2 3.1
Age of reference
person............ 46.9 50.1 46.5 44.7 43.2 42.3 45.3
Average number in
consumer unit:
Earners.......... 1.4 0.9 1.2 1.5 1.8 2.0 2.1
Vehicles......... 2.0 1.4 1.9 2.2 2.6 2.7 3.1
Children under 18 0.7 0.6 0.7 0.7 0.9 1.0 0.8
Persons 65 and
over............ 0.3 0.5 0.4 0.3 0.2 0.1 0.1
Percent
distribution:
Male............. 66 57 64 71 78 82 87
Female........... 34 43 36 29 22 18 13
Homeowner with
mortgage........ 38 15 26 36 52 64 76
Homeowner without
mortgage........ 24 32 26 25 18 14 14
Renter........... 39 53 47 39 30 21 11
Black............ 11 12 10 10 5 6 4
White and other.. 89 88 90 90 95 94 96
Elementary (1-8). 11 17 12 8 5 2 3
High school (9-
12)............. 44 51 54 48 42 40 24
College.......... 44 31 34 44 53 58 73
Never attended
and other....... 1 1 1 0 0 0 0
At least one
vehicle owned..... 86 84 91 95 96 97 97
Average annual
expenditures........ 26389.07 16788.64 19558.35 24896.36 31659.60 37562.00 52320.19
Food............... 3804.39 2777.33 3194.53 3765.02 4587.49 5281.61 6296.11
Food at home..... 2176.94 1809.23 1954.49 2174.01 2556.74 2906.55 3109.86
*Cereals and
bakery products. 317.03 266.20 274.62 320.55 375.38 417.06 450.19
*Cereals and
cereal
products.... 111.15 101.45 100.46 111.31 134.59 145.71 138.66
*Flour..... 4.83 6.43 4.59 4.99 5.06 4.15 4.17
*Prepared
flour
mixes..... 9.88 9.30 9.21 10.32 11.92 14.72 12.18
*Ready-to-
eat and
cooked
cereals... 73.49 65.38 65.31 72.80 89.56 98.06 92.85
*Rice...... 7.98 8.00 6.06 7.95 9.66 9.48 10.14
*Pasta,
cornmeal
and other
cereals... 14.97 12.33 15.29 15.24 18.39 19.30 19.34
*Bakery
products.... 205.88 164.75 174.16 209.23 240.80 271.35 311.53
*Bread..... 65.72 58.48 61.24 68.58 72.19 78.50 86.03
*White
bread... 35.48 32.79 33.61 38.12 39.98 39.46 42.54
*Bread,
other
than
white... 30.24 25.69 27.63 30.46 32.21 39.05 43.49
*Crackers
and
cookies... 51.76 41.43 42.92 53.39 60.40 75.75 77.18
*Cookies. 32.19 24.30 27.98 33.01 35.93 47.99 49.96
*Crackers 19.57 17.13 14.94 20.38 24.46 27.76 27.21
*Frozen and
refrigerat
ed bakery
products.. 13.55 10.10 10.54 13.12 15.29 17.64 24.89
*Other
bakery
products.. 74.84 54.74 59.46 74.14 92.92 99.46 123.44
*Biscuits
and
rolls... 26.62 18.31 20.95 27.08 30.87 38.69 45.14
*Cakes
and
cupcakes 20.31 13.30 15.37 21.50 26.94 26.92 31.29
*Bread
and
cracker
products 2.82 2.70 2.40 2.36 3.73 4.07 4.89
*Sweetrol
ls,
coffee
cakes,
doughnut
s....... 19.60 15.04 15.68 18.44 23.22 23.31 33.90
*Pies,
tarts,
turnover
s....... 5.48 5.38 5.07 4.76 8.16 6.48 8.22
*Meats,
poultry, fish
and eggs...... 560.01 477.38 555.07 541.91 635.94 699.55 812.35
*Beef........ 183.66 152.35 204.56 185.96 215.42 225.57 263.75
*Ground
beef...... 79.09 71.32 84.22 79.31 96.47 91.12 101.79
*Roast..... 33.40 28.09 34.54 34.19 35.85 40.13 50.81
*Chuck
roast... 13.23 11.36 14.43 13.12 16.66 14.71 17.87
*Round
roast... 9.13 7.79 10.19 8.42 8.80 15.67 13.71
*Other
roast... 11.04 8.93 9.92 12.65 10.38 9.75 19.23
*Steak..... 59.01 41.47 71.43 61.32 70.25 77.08 93.67
*Round
steak... 11.62 11.60 16.74 13.83 12.33 11.66 13.85
*Sirloin
steak... 12.96 8.51 11.79 12.72 14.53 20.48 24.43
*Other
steak... 34.42 21.36 42.90 34.77 43.40 44.94 55.39
*Other beef 12.17 11.47 14.37 11.14 12.84 17.24 17.48
*Pork........ 114.19 104.51 108.16 108.24 132.60 131.31 157.61
*Bacon..... 20.23 24.20 17.46 18.44 23.15 18.48 25.09
*Pork chops 27.10 19.23 28.84 25.14 36.30 28.37 34.33
*Ham....... 27.43 25.79 27.94 28.11 31.54 35.35 39.08
*Ham, not
canned.. 24.47 21.68 25.11 26.25 28.62 29.58 36.43
*Canned
ham..... 2.96 4.10 2.83 1.86 2.92 5.77 2.65
*Sausage... 16.60 14.09 17.07 13.98 17.67 22.46 23.28
*Other pork 22.83 21.21 16.84 22.58 23.95 26.65 35.83
*Other meats. 83.61 71.60 75.48 79.96 98.98 113.62 118.21
*Frankfurte
rs........ 17.37 15.97 17.17 17.77 19.56 21.76 22.58
*Lunch
meats
(cold
cuts)..... 58.88 49.13 49.48 56.28 71.83 80.88 86.21
*Bologna,
liverwur
st,
salami.. 19.11 17.97 16.54 19.36 22.06 23.99 25.51
*Other
lunchmea
ts...... 39.78 31.16 32.94 36.92 49.77 56.89 60.70
*Lamb,
organ
meats and
others.... 7.36 6.51 8.93 5.91 7.58 10.98 9.42
*Lamb and
organ
meats... 6.17 5.97 5.33 4.82 7.57 8.63 8.50
*Mutton,
goat and
game.... 1.19 0.54 3.60 1.10 0.01 2.36 0.92
*Poultry..... 85.49 69.40 81.53 82.16 85.67 111.40 133.20
*Fresh and
frozen
chickens.. 66.41 55.25 66.61 65.26 66.71 81.88 96.35
*Fresh
whole
chicken. 17.24 17.03 17.44 20.11 14.32 16.24 23.38
*Fresh
and
frozen
chicken
parts... 49.17 38.22 49.18 45.15 52.39 65.64 72.97
*Other
poultry,
incl whole
frzn
chickens.. 19.98 14.15 14.91 16.91 18.96 29.52 36.85
*Fish and
seafood..... 65.24 50.44 57.57 56.89 74.24 86.03 109.89
*Canned
fish and
seafood... 17.95 14.01 15.77 16.67 23.21 21.96 26.53
*Fresh and
frozen
shellfish. 14.98 5.89 17.35 14.09 15.81 18.33 32.78
*Fresh and
frozen
finfish... 32.31 30.53 24.45 26.13 35.23 45.74 50.59
*Eggs........ 27.83 29.08 27.68 28.69 29.02 31.61 29.68
*Dairy products 277.91 237.49 246.39 287.05 337.97 365.06 383.11
*Fresh milk
and cream... 134.41 132.08 125.44 135.91 160.12 158.15 168.53
*Whole milk 52.12 58.46 57.48 57.54 55.58 44.53 55.37
*Other milk
and cream. 82.29 73.61 67.97 78.37 104.54 113.61 113.17
*Other dairy
products.... 143.50 105.41 120.95 151.15 177.85 206.92 214.57
*Butter.... 8.89 8.28 8.17 8.63 9.20 12.22 13.04
*Cheese.... 79.01 54.41 69.16 83.03 98.98 111.72 119.08
*Ice cream
and
related
products.. 41.68 31.02 33.95 46.55 53.10 60.05 61.85
*Miscellane
ous dairy
products.. 13.93 11.70 9.67 12.93 16.57 22.93 20.60
*Fruits and
vegetables.... 376.38 327.70 335.02 366.35 441.76 487.04 526.17
*Fresh fruits 120.98 102.64 104.99 116.33 148.47 156.62 172.21
*Apples.... 21.57 16.83 17.80 21.56 26.58 28.77 29.44
*Bananas... 20.65 19.42 19.04 21.64 24.06 22.66 27.22
*Oranges... 10.98 9.36 9.43 9.37 15.38 16.47 14.72
*Other
fresh
fruits.... 67.78 57.02 58.71 63.75 82.45 88.72 100.83
*Fresh
vegetables.. 110.67 101.90 100.87 106.30 124.19 123.40 158.76
*Potatoes.. 16.61 13.93 17.56 15.59 19.18 20.55 22.24
*Lettuce... 13.73 11.36 11.61 12.80 16.85 16.95 20.85
*Tomatoes.. 14.87 13.49 14.08 14.64 17.94 16.43 19.74
*Other
fresh
vegetables 65.47 63.12 57.63 63.28 70.21 69.47 95.93
*Processed
fruits...... 86.81 75.04 80.64 82.22 98.04 126.19 121.27
*Frozen
fruits and
fruit
juices.... 19.59 17.95 18.61 18.42 22.98 32.00 28.71
*Frozen
orange
juice... 14.43 13.60 13.91 14.55 14.89 21.97 20.88
*Other
frozen
fruits
and
juices.. 5.16 4.35 4.70 3.87 8.10 10.03 7.83
*Canned and
dried
fruits.... 21.22 18.05 18.46 20.85 24.80 32.50 26.30
*Fresh,
canned or
bottled
fruit
juices.... 46.00 39.04 43.58 42.95 50.26 61.68 66.26
*Processed
vegetables.. 57.92 48.13 48.52 61.49 71.05 80.82 73.92
*Frozen
vegetables 21.30 13.63 16.57 23.19 27.40 32.62 31.07
*Canned and
dried
vegetables
and juices 36.62 34.50 31.95 38.30 43.65 48.21 42.85
*Canned
beans... 6.64 5.41 6.00 6.98 7.85 9.98 7.27
*Canned
corn.... 4.21 2.91 3.86 4.70 4.31 6.10 4.37
*Other
canned
and
dried
veg., &
juices.. 25.77 26.17 22.09 26.62 31.49 32.12 31.21
*Other food at
home.......... 645.61 500.46 543.39 658.15 765.69 937.83 938.05
*Sugar and
other sweets 80.66 65.44 64.53 82.49 97.73 122.23 111.61
*Candy and
chewing
gum....... 45.41 32.09 31.13 46.37 55.74 75.32 71.53
*Sugar..... 17.07 18.57 17.60 17.61 18.27 17.57 16.01
*Artificial
sweetners. 2.36 1.56 2.44 2.90 1.78 3.70 2.68
*Jams,
preserves,
other
sweets.... 15.82 13.22 13.36 15.62 21.94 25.64 21.39
*Fats and
oils........ 56.65 48.51 45.63 59.62 69.18 76.24 70.54
*Margerine. 11.96 10.65 9.89 12.19 14.51 15.78 15.49
*Other
fats,
oils, and
salad
dressing.. 31.66 26.57 26.33 32.32 37.90 45.04 38.58
*Nondairy
cream and
imitation
milk...... 4.49 4.53 3.64 4.91 4.72 5.00 4.89
*Peanut
butter.... 8.54 6.75 5.77 10.20 12.05 10.42 11.57
*Miscellaneou
s foods..... 272.98 209.21 230.18 278.73 325.17 410.76 393.38
*Frozen
prepared
foods..... 46.13 34.31 44.35 47.46 54.87 69.97 66.80
*Frozen
meals... 16.75 14.44 19.43 16.05 23.09 21.11 23.97
*Other
frozen
prepared
foods... 29.39 19.87 24.92 31.41 31.78 48.86 42.82
*Canned and
packaged
soups..... 21.41 17.65 16.96 21.06 24.10 35.62 28.50
*Potato
chips,
nuts, and
other
snacks.... 59.78 41.00 37.67 64.36 71.49 95.82 100.20
*Potato
chips
and
other
snacks.. 46.79 30.06 31.54 53.75 55.18 74.06 77.26
*Nuts.... 12.99 10.94 6.13 10.61 16.31 21.76 22.94
*Condiments
and
seasonings 61.52 49.20 56.11 58.41 77.90 82.89 92.16
*Salt,
spices,
other
seasonin
gs...... 12.31 10.17 11.24 11.99 14.15 14.15 20.09
*Olives,
pickles,
relishes 7.62 5.36 8.73 7.01 9.48 10.54 10.59
*Sauces
and
gravies. 31.62 25.10 26.76 29.73 42.60 43.35 46.87
*Baking
needs
and
misc.
products 9.97 8.58 9.38 9.67 11.67 14.85 14.61
*Other
canned/pac
kaged
prepared
foods..... 84.14 67.05 75.08 87.44 96.82 126.46 105.73
*Salads
and
desserts 13.23 11.82 12.59 11.96 17.20 18.07 18.37
*Baby
food.... 16.25 10.38 15.03 16.91 19.52 26.99 12.93
*Miscella
neous
prepared
foods... 54.66 44.85 47.47 58.57 60.10 81.41 74.43
*Nonalcoholic
beverages... 204.37 164.51 186.49 210.29 233.06 283.11 287.11
*Cola...... 92.19 66.57 88.15 99.91 101.86 140.51 123.90
*Other
carbonated
drinks.... 32.62 23.55 29.15 28.70 40.86 43.90 53.99
*Coffee.... 40.93 38.84 38.48 38.15 43.16 47.73 54.95
*Roasted
coffee.. 25.27 22.96 23.27 24.63 26.36 31.15 34.98
*Instant
and
freeze
dried
coffee.. 15.66 15.87 15.21 13.52 16.81 16.58 19.98
*Non-
carbonated
fruit
flavored
drinks.... 16.30 12.30 11.92 21.28 20.62 24.65 21.32
*Tea....... 11.18 10.67 8.25 11.36 13.49 15.33 13.42
*Other non-
alcoholic
beverages. 11.15 12.58 10.54 10.90 13.08 10.98 19.52
Food prepared
by cu on out
of town
trips....... 30.94 12.80 16.56 27.01 40.55 45.49 75.42
Food away from
home............ 1627.45 968.10 1240.03 1591.02 2030.75 2375.06 3186.24
*Meals at
restaurants,
carry-outs &
other......... 1275.77 799.32 1039.21 1294.24 1591.66 1870.30 2351.22
*Lunch....... 499.88 277.04 407.25 514.76 619.15 709.45 956.78
*Dinner...... 549.30 339.39 440.28 550.06 662.77 822.65 1057.00
*Snacks and
non
alcoholic
beverage.... 142.56 105.40 121.94 145.83 190.00 225.33 207.78
*Breakfast
and brunch.. 84.04 77.48 69.75 83.59 119.74 112.87 129.66
Board
(including at
school)....... 43.62 6.74 7.89 27.65 36.46 39.33 153.00
Catered affairs 41.27 7.39 5.78 34.97 50.79 47.01 142.76
Food on out of
town trips.... 195.31 93.30 115.14 165.61 254.20 300.02 451.05
School lunches. 42.24 20.43 26.30 41.51 67.39 84.77 70.55
Meals as pay... 29.24 40.92 45.71 27.04 30.27 33.64 17.65
Alcoholic beverages 281.70 182.87 235.22 290.56 343.77 352.96 506.47
*At home......... 148.36 107.27 126.68 152.37 189.69 178.29 246.36
*Beer and ale.. 89.05 72.34 77.77 95.86 108.21 102.60 126.68
*Whiskey....... 12.73 12.89 5.93 13.17 16.76 13.43 21.68
*Wine.......... 32.15 13.69 26.16 31.70 40.94 46.88 70.20
*Other
alcoholic
beverages..... 14.43 8.35 16.82 11.65 23.78 15.38 27.80
Away from home... 133.34 75.61 108.54 138.19 154.08 174.67 260.11
*Beer and ale.. 37.50 20.21 32.77 39.59 40.20 53.06 62.61
*Wine.......... 18.54 12.05 15.72 19.17 18.68 24.52 38.32
*Other
alcoholic
beverages..... 58.12 36.45 50.81 60.89 71.66 67.59 113.53
Alcoholic
beverages
purchased on
trips......... 19.17 6.90 9.24 18.54 23.54 29.50 45.66
Housing............ 8069.13 5495.09 5946.80 7511.85 9260.40 10608.79 15719.12
Shelter.......... 4470.25 3043.10 3139.50 4124.86 5049.86 5901.40 8909.44
Owned dwellings 2554.04 961.15 1151.03 1976.74 2970.57 4060.42 6925.93
Mortgage
interest.... 1560.48 318.45 520.13 1051.78 1925.39 2783.87 4724.67
Mortgage
interest
and
charges... 1560.38 318.45 520.13 1051.78 1925.39 2783.87 4724.01
Prepayment
penalty
charges,
(own home) 0.10 0.00 0.00 0.00 0.0 0.00 0.66
Property
taxes....... 496.08 316.48 301.71 417.03 599.30 643.81 1125.91
Maintenance,
repairs,
insur, other
expenses.... 497.48 326.23 329.20 507.92 445.87 632.74 1075.35
Homeowners
and
related
insurance. 151.74 102.72 105.11 139.48 163.01 200.84 313.16
Fire and
extended
coverage 4.98 3.14 4.17 8.42 3.90 7.28 4.94
Homeowner
s
insuranc
e....... 146.76 99.58 100.94 131.06 159.11 193.56 308.22
Ground rent 26.88 26.40 38.12 35.13 23.98 14.38 12.57
Maintenance
and repair
service... 252.68 166.84 159.60 260.79 187.82 293.13 607.16
Painting
and
papering 52.01 34.57 12.75 55.29 21.09 49.82 144.99
Plumbing
and
water
heating. 23.06 12.17 16.84 22.72 17.23 32.94 55.39
Heat, a/
c,
electric
al work. 42.03 40.31 20.65 28.44 44.68 61.59 90.02
Roofing
and
gutters. 46.96 21.78 51.88 49.75 40.70 55.18 111.23
Other
repair/m
aintenan
ce
service. 78.78 53.15 53.69 101.29 54.90 85.14 164.91
Repair &
replace
hard
surface
flooring 8.14 4.68 2.92 2.46 7.98 6.77 33.94
Repair of
built-in
applican
ces..... 1.68 0.16 0.88 0.85 1.24 1.69 6.68
Maintenance
/repair
commod.... 65.41 28.29 25.78 71.76 70.93 122.37 141.50
Paints,
wallpape
r and
supplies 17.47 6.93 5.76 14.64 18.25 33.17 45.07
Tools and
equipmen
t for
painting
and
wallpape
ring.... 1.88 0.74 0.62 1.57 1.96 3.56 4.84
Plumbing
supplies
and
equipmen
t....... 5.65 2.25 3.48 6.92 6.24 11.04 11.40
Electrica
l
supplies
, heat./
cool.
equip... 3.76 0.62 4.14 3.32 4.94 2.21 10.24
Materials
for hard
surface
floor,
repair
and
replace. 1.85 0.82 0.03 1.32 0.66 5.63 5.85
Material
and
equipmen
t for
roof/gut
ters.... 5.18 3.60 3.34 8.46 4.25 3.31 5.16
Materials
for
plaster,
panel,
siding,
windows,
doors,
screens,
awnings. 11.08 9.36 4.91 12.62 12.57 15.49 23.43
Materials
for
patio,
walk,
fence,
drive,
masonry,
brick,
and
stucco
work.... 2.12 0.28 0.61 6.99 0.71 2.30 3.03
Materials
for
landscap
ing
maintena
nce..... 2.52 0.09 0.00 7.40 2.38 2.17 4.45
Miscellan
eous
supplies
/equipme
nt...... 13.89 3.60 2.89 8.52 18.98 43.49 28.02
Materia
ls for
insula
tion,
other
mainte
nance/
repair 7.87 3.60 2.36 6.16 10.04 14.88 18.16
Materia
ls to
finish
baseme
nt,
remode
l rms
or
build
patios
,
walks,
etc
(maint
.,
rep.,
repl.)
(own
prop). 6.02 0.00 0.53 2.36 8.95 28.61 9.86
Property
management
and
security.. 0.74 1.98 0.53 0.72 0.13 1.95 0.79
Property
Manageme
nt...... 0.64 1.88 0.24 0.60 0.12 1.95 0.62
Managemen
t and
upkeep
serv for
security 0.10 0.10 0.28 0.13 0.01 0.00 0.18
Parking.... 0.04 0.00 0.06 0.03 0.00 0.07 0.17
Rented
dwellings..... 1469.41 1753.31 1777.24 1804.99 1563.71 1248.94 825.42
Rent......... 1428.30 1708.38 1718.30 1762.19 1521.88 1216.05 785.55
Rent as pay.. 17.34 25.29 32.67 15.87 14.30 0.70 9.59
Maintenance,
insurance
and other
expenses.... 23.76 19.63 26.27 26.92 27.53 32.19 30.29
Tenant's
insurance. 8.68 4.34 9.22 9.27 12.89 10.61 10.03
Maintenance
and repair
services.. 9.01 10.32 13.18 11.46 9.64 6.78 12.67
Repair or
maintena
nce
service. 8.62 10.32 13.18 11.46 9.50 5.20 11.94
Materials
for
dwelling
under
construc
tion and
addition
s....... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Repair &
replace
hard
surface
flooring 0.36 0.00 0.00 0.00 0.00 1.58 0.69
Repair of
built-in
applianc
es...... 0.03 0.00 0.00 0.00 0.14 0.00 0.05
Maintenance
and repair
comm...... 6.07 4.97 3.87 6.19 5.00 14.80 7.59
Paint,
wallpape
r, and
supplies 1.19 0.85 1.39 1.12 2.22 1.63 1.10
Tools and
equipmen
t for
painting
and
wallpape
ring.... 0.13 0.09 0.15 0.12 0.24 0.18 0.12
Materials
for
plast.,
panels,
roofing,
gutters,
etc..... 0.68 1.43 0.34 0.94 0.69 0.81 0.56
Materials
for
patio,
walk,
fence,
driveway
,
masonry,
brick &
stucco
work.... 0.02 0.06 0.00 0.01 0.00 0.06 0.02
Plumbing
supplies
and
equipmen
t....... 0.38 0.23 0.53 0.75 0.25 0.20 0.17
Electrica
l
supplies
, heat./
cool.
equip... 0.92 0.10 0.18 0.03 0.11 8.91 0.01
Miscellan
eous
supplies
/equipme
nt...... 1.84 2.07 0.79 2.69 1.08 1.80 3.41
Materia
ls for
insula
tion,
other
mainte
nance
and
repair 0.58 0.51 0.73 0.49 0.56 0.67 0.72
Termite
/pest
contro
l
(cap.
improv
ement)
(rente
r).... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Materia
ls for
additi
ons,
finish
baseme
nts,
remode
ling
rooms. 1.08 1.44 0.07 1.89 0.26 0.24 2.69
Constru
ction
mtls
jobs
not
starte
d..... 0.18 0.12 0.00 0.31 0.26 0.89 0.00
Materials
for hard
surface
flooring 0.14 0.00 0.46 0.26 0.00 0.52 0.00
Materials
for
landscap
e
maintena
nce..... 0.76 0.14 0.03 0.27 0.42 0.68 2.21
Other lodging.. 446.79 328.64 211.23 343.13 515.57 592.04 1158.09
Owned
vacation
homes....... 78.26 147.93 26.59 48.70 89.46 52.59 199.82
Prepayment
penalty
charges
(own vac). 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Mortgage
interest.. 48.65 124.50 5.47 31.06 51.05 23.57 117.74
Property
taxes..... 16.90 12.09 14.93 9.58 21.13 16.99 45.43
Maintenance
,
insurance,
other
expenses.. 12.71 11.34 6.19 8.06 17.28 12.03 36.65
Homeowner
s and
related
insuranc
e....... 3.07 1.77 1.42 2.32 2.69 1.79 10.56
Homeown
ers
insura
nce... 3.04 1.54 1.42 2.32 2.69 1.79 10.51
Fire/ex
tended
covera
ge.... 0.03 0.22 0.00 0.00 0.00 0.00 0.05
Ground
rent.... 3.33 0.90 3.95 1.64 6.88 1.26 9.64
Maintenan
ce/repai
r
services 5.52 8.06 0.71 3.83 6.37 8.30 14.44
Repair/
remode
ling
(servi
ce)... 5.52 8.06 0.71 3.83 6.37 8.30 14.44
Repair
and
replac
e hard
surfac
e
floor. 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Maintenan
ce/repai
r comm.. 0.39 0.61 0.11 0.28 0.11 0.23 0.70
Paints,
wallpa
per,
suppli
es.... 0.08 0.19 0.06 0.00 0.03 0.08 0.29
Tools/e
quipme
nt for
painti
ng and
wallpa
pering 0.01 0.02 0.01 0.00 0.00 0.01 0.03
Materia
ls for
plaste
ring,
panels
,
roofin
g,
gutter
s,
dnspou
ts,
siding
,
wdows,
drs.,
screen
s, and
awning
s..... 0.05 0.00 0.00 0.02 0.00 0.03 0.32
Materia
ls for
patio,
walk,
fence,
drive,
masonr
y,
brick,
stucco 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Plumbin
g
suppli
es/equ
ipment 0.02 0.04 0.00 0.00 0.03 0.07 0.05
Electri
cal
suppli
es,
heat./
cool
equip. 0.01 0.00 0.00 0.01 0.04 0.00 0.00
Miscell
aneous
suppli
es/equ
ipment 0.01 0.00 0.05 0.02 0.00 0.04 0.00
Mater
ials
for
insu
lati
on/o
ther
main
t./r
epai
r... 0.01 0.00 0.05 0.00 0.00 0.04 0.00
Mater
ials
for
fini
shin
g
base
ment
s,
remo
deli
ng
room
s... 0.00 0.00 0.00 0.02 0.00 0.00 0.00
Materia
ls for
hard
surfac
e
floor. 0.20 0.35 0.00 0.23 0.00 0.00 0.00
Materia
ls for
landsc
aping
mainte
nance. 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Property
manageme
nt and
security 0.40 0.00 0.00 0.00 1.23 0.44 1.30
Propert
y
manage
ment.. 0.40 0.00 0.00 0.00 1.23 0.44 1.30
Managem
ent
and
upkeep
servic
e for
securi
ty.... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Parking.. 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Expenses for
other
properties.. 154.47 101.84 74.84 137.28 169.04 223.95 390.55
Housing while
attending
school...... 35.48 3.69 3.44 17.58 30.76 35.15 118.12
Lodging while
out of town. 178.58 75.19 106.36 139.57 226.31 280.35 449.60
Utilities, fuels
and public
services........ 1726.29 1412.79 1542.51 1711.07 1924.68 2089.22 2593.19
Natural gas.... 232.22 212.96 214.65 215.34 246.68 276.67 354.61
Util.--Natura
l gas
(renter).... 50.85 73.43 66.38 52.66 45.66 34.00 19.84
Util.--Natura
l gas (own
home)....... 180.07 139.37 147.88 161.65 200.38 242.17 329.43
Util.--Natura
l gas (own
vac.)....... 1.22 0.16 0.30 0.97 0.49 0.50 5.32
Util.--Natura
l gas
(rented
vac.)....... 0.08 0.00 0.09 0.05 0.15 0.00 0.02
Electricity.... 700.08 578.32 608.01 695.11 801.49 859.67 1048.84
Electricity
(renter).... 169.94 222.94 196.59 197.41 178.88 122.29 74.86
Electricity
(own home).. 524.87 350.24 408.24 493.70 618.75 733.65 957.87
Electricity
(own vac.).. 5.03 4.75 2.86 3.92 3.40 3.70 15.87
Electricity
(rented
vac.)....... 0.25 0.39 0.32 0.09 0.45 0.02 0.25
Fuel oil and
other fuels... 94.02 76.70 81.76 99.42 92.78 114.59 128.02
Fuel oil..... 55.60 38.86 47.89 54.62 53.00 82.53 89.36
Fuel oil
(renter).. 5.21 5.93 6.49 5.91 6.38 3.26 4.78
Fuel oil
(own home) 49.96 32.34 41.40 48.50 46.57 79.27 82.89
Fuel oil
(own vac.) 0.38 0.59 0.00 0.21 0.05 0.00 1.69
Fuel oil
(rented
vac.)..... 0.06 0.00 0.00 0.00 0.00 0.00 0.00
Coal......... 3.50 6.85 0.57 6.20 3.64 5.23 0.33
Coal
(renter).. 0.55 1.20 0.20 0.94 0.98 0.00 0.00
Coal (own
home)..... 2.95 5.66 0.37 5.26 2.66 5.23 0.33
Coal (own
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Coal
(rented
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Bottled gas.. 24.48 22.49 23.52 28.34 23.75 17.90 23.47
Gas,
bottled/ta
nk
(renter).. 3.78 5.78 4.73 2.54 3.06 0.69 2.10
Gas,
bottled/ta
nk (own
home)..... 18.58 15.77 17.30 24.49 19.10 12.94 15.42
Gas,
bottled/ta
nk (own
vac.)..... 2.12 0.93 1.49 1.31 1.59 4.26 5.94
Gas,
bottled/ta
nk (rented
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Wood and
other fuels. 10.43 8.49 9.77 10.26 12.38 8.93 14.87
Wood/other
fuels
(renter).. 1.31 2.07 1.19 1.35 0.64 0.21 1.33
Wood/other
fuels (own
home)..... 9.05 6.42 8.57 8.71 11.74 8.64 13.42
Wood/other
fuels (own
vac.)..... 0.06 0.00 0.00 0.20 0.00 0.08 0.13
Wood/other
fuels
(rented
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Telephone...... 528.79 425.98 507.41 539.06 590.21 601.80 769.38
Water and other
public
services...... 171.19 118.83 130.68 162.14 193.53 236.49 292.34
Water/sewerag
e
maintenance. 131.02 91.41 99.79 124.06 150.67 178.26 222.63
Water/sewer
maintenanc
e (renter) 18.53 20.04 17.05 22.99 18.20 15.51 8.91
Water/sewer
maintenanc
e (own
home)..... 111.57 69.24 82.52 100.46 131.51 161.47 212.17
Water/sewer
maintenanc
e (own
vac.)..... 0.83 1.83 0.22 0.52 0.96 1.29 1.43
Water/sewer
maintenanc
e (rented
vac.)..... 0.09 0.30 0.00 0.08 0.00 0.00 0.13
Trash/garbage
collection.. 38.67 26.89 29.90 37.16 40.93 55.27 65.76
Trash/garb.
collection
(renter).. 5.28 5.02 4.95 7.21 4.98 5.00 2.97
Trash/garb.
collection
(own home) 33.31 21.88 24.79 29.91 35.69 50.26 62.64
Trash/garb.
collection
(own vac.) 0.08 0.00 0.16 0.04 0.25 0.00 0.15
Trash/garb.
collection
(rented
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Septic tank
cleaning.... 1.50 0.52 0.98 0.92 1.94 2.96 3.95
Septic tank
cleaning
(renter).. 0.01 0.00 0.00 0.00 0.10 0.00 0.00
Septic tank
cleaning
(own home) 1.48 0.52 0.98 0.91 1.84 2.96 3.95
Septic tank
cleaning
(own vac.) 0.00 0.00 0.00 0.01 0.00 0.00 0.00
Septic tank
cleaning
(rented
vac.)..... 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Household
operations...... 387.45 200.78 222.83 310.21 448.86 530.72 955.30
Personal
services...... 176.53 82.78 119.28 166.06 275.08 311.41 321.27
Babysitting.. 74.62 42.11 58.03 85.19 133.19 114.65 115.47
Care for
elderly,
invalids,
handicapped,
etc......... 11.66 3.93 0.55 4.58 1.46 0.47 24.66
Day care
centers,
nursery/pres
chools...... 90.25 36.75 60.69 76.28 140.43 196.28 181.13
Other household
expenses...... 210.92 118.00 103.56 144.16 173.78 219.31 634.03
Housekeeping
services.... 67.76 36.72 22.44 28.84 41.53 50.94 269.17
Gardening,
lawn care
service..... 49.60 27.27 22.86 30.40 31.13 53.69 159.

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Source: Frix Law Library, https://www.frixlaw.com/law-library/documents/fr%3A94-21119. Public record. Not legal advice.