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

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 53.69 159.01

Water

softening

service..... 2.81 2.73 0.76 2.19 2.95 4.10 7.63

Household

laundry/dry

cleaning,

sent out

(non-

clothing)

not coin-

operated.... 1.63 1.04 0.41 1.66 2.63 2.53 3.39

Coin-operated

household

laundry/dry

cleaning

(non-cloth). 4.78 5.92 5.63 5.41 4.47 6.09 2.27

Other home

services.... 17.86 4.29 9.02 12.39 13.96 13.96 60.11

Termite/pest

control

products.... 0.20 0.05 0.09 0.09 0.25 0.12 0.21

Moving,

storage,

freight

express..... 26.46 10.87 10.32 23.78 32.08 46.84 56.17

Appliance

repair,

incl.

service

center...... 16.44 9.82 17.88 18.93 20.85 17.46 25.57

Reupholsterin

g/furniture

repair...... 13.85 10.37 5.31 13.68 15.55 11.69 32.30

Repairs/renta

ls of lawn/

garden

equipment

hand/power

tools/other

household

equip....... 5.92 4.16 4.59 4.90 6.20 9.08 13.38

Appliance

rental...... 2.08 4.33 2.47 1.01 1.16 0.52 0.54

Rental of

office

equipment

for non-

business use 0.17 0.02 0.27 0.04 0.01 0.57 0.46

*Repair of

miscellaneou

s household

equipment

and

furnishings. 0.48 0.00 1.32 0.19 0.02 0.94 0.59

Rental and

installation

of

dishwashers,

range hoods,

and garbage

disposals... 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Housekeeping

supplies........ 382.82 286.29 321.58 383.43 451.24 475.45 670.22

Laundry and

cleaning

supplies...... 106.44 80.46 104.37 109.27 131.66 129.47 162.63

*Soaps and

detergents.. 62.10 47.30 60.50 63.11 78.35 77.19 89.28

*Other

laundry

cleaning

products.... 44.33 33.16 43.87 46.16 53.30 52.28 73.35

*Other

household

products...... 157.48 125.55 115.86 149.94 183.61 201.65 316.09

*Cleansing

and toilet

tissue,

paper towels

and napkins. 52.12 42.88 45.37 51.88 64.86 67.41 80.71

*Miscellaneou

s household

products.... 67.89 47.17 44.38 58.26 85.63 108.96 139.90

*Lawn and

garden

supplies.... 37.47 35.50 26.12 39.79 33.12 25.27 95.48

*Postage and

stationery.... 118.89 80.28 101.35 124.23 135.97 144.33 191.50

*Stationery,

stationery

supplies,

giftwrap.... 54.40 30.49 36.05 45.35 55.09 74.49 105.20

*Postage..... 64.49 49.79 65.30 78.88 80.87 69.84 86.30

Housefurnishings

and equipment... 1102.32 552.14 720.38 982.28 1385.76 1612.00 2590.97

Household

textiles...... 97.11 50.30 81.09 96.28 104.56 122.28 220.32

*Bathroom

linens...... 13.69 5.45 19.92 9.71 18.83 13.05 30.80

*Bedroom

linens...... 38.11 28.28 35.77 36.81 33.56 50.47 77.56

*Kitchen and

dining room

linens...... 5.74 4.52 2.63 4.03 6.56 7.12 15.73

Curtains and

draperies... 26.56 5.34 12.12 28.90 26.44 39.44 71.25

Slipcovers,

decorative

pillows..... 1.64 0.68 2.26 1.33 2.64 1.28 3.18

*Sewing

materials

for

slipcovers,

curtains,

other sewing

materials

for home use 10.32 4.80 7.95 14.65 15.39 9.43 19.15

Other linens. 1.05 1.25 0.43 0.84 1.13 1.50 2.65

Furniture...... 319.44 139.36 204.72 261.90 378.37 433.38 861.57

Mattress and

springs..... 41.86 18.62 32.81 39.28 57.01 62.91 93.05

Other bedroom

furniture... 39.75 13.71 29.56 22.88 52.21 62.05 107.77

Sofas........ 65.44 37.30 40.98 58.54 83

This text is long and has been trimmed here. Open the source document for the complete record.