10.4.1 Assumptions

Table 10.5 Assumptions Used for Generating National Impacts

ETA Annual Energy Outlook 1999 to the year 2020 Fuel Price and extrapolated to the year 2030

Water Price

Discount Rate and the Year of the NPV

Start Year for New Standards

Marginal: $2.49 per 1000 gallons

Discounted to the year 1999 (in 1997$) at 7 percent

(real)

2004

Annual Real Change in Water & Sewer Cost (water

price escalator)

Manufacturing Cost

Total Mark up on Manufacturer Costs

Energy Consumption Data

Clothes Washer Shipments

Percent Horizontal-Axis Washers

2.96 percent

Shipment-weighted average of the most likely (cost

estimate for each manufacturer from AHAM data)

Obtained from Manufacturing Impact Analysis

AHAM data

Assumed same for standards and base case (inelastic to

price and energy savings)

6.25 percent in 1998, with the relative market share of

less efficient machines decreasing 0.5 percent each

year

Primary Energy Conversion Factors AEO99

Using these assumptions, we highlight output in key areas below.

10.4.2 Base Case Shipments

The results of the shipments model are used to establish a base case shipment forecast. The

base case forecast is shown in section describing the shipments model.

10.4.3 National Energy Savings and Net Present Value from Possible Standards

The national energy savings and net present value results from the NES spreadsheet are

shown in Tables 10.6 and 10.7. More detailed results are also available in Appendix N. Results are

cumulative to 2030 and are shown as absolute energy and water savings and as the discounted value

of these savings in dollar terms. Table 10.6 compares an upper and lower bound of consumer price

sensitivity. The lower consumer price sensitivity case occurs if income is a factor in clothes washer

purchases, while the higher consumer price response assumes that price is the primary explanatory

variable for historical trends, and that the highest sensitivity consistent with historical data best

represents future behavior. Specifically the lower bound is defined as price/income elasticity =

medium; upper bound is defined as having a high price elasticity; all other parameters in the

NES/Shipment spreadsheet are set at reference, medium or average.

10-15

EE-RM-PET-100 COMMENT 88
The tables in this chapter use input values based on RECS93 and AEO 1999 data. After this

analysis was completed, the next issue of RECS and AEO data became available -- RECS97 and

AEO2000. Results based on these data are provided in Appendix R. The most recent results do not

vary significantly from the results based on RECS 93 and AEO2000.

Table 10.6 Range of Energy Savings and NPV for Each Standard Level

Trial

Standard

Level

MEF Efficiency

Improvement

over the Base

Case

Energy Savings

Quads

Water Savings

trillion gallons

Net Present Value

(NPV)

(billion 1997$)

Bound lower upper lower upper lower upper

1 1.021 20% 2.13 2.15 0.54 0.54 3.68 3.70

2 1.089 25% 4.08 4.06 9.17 9.14 14.40 14.32

4 1.257 35% 6.09 5.94 13.15 12.86 16.98 16.80

5 1.362 40% 6.13 5.98 13.15 12.85 16.83 16.66

6 1.634 50% 7.70 7.36 11.09 10.63 10.46 11.18

3 l.04in2004

1.26 in 2007

5.61 5.48 11.80 11.50 15.42 15.25

Table 10.7 Reference Case - All Parameters Set to Medium or Average

Trial

Standard

Level

MEF Efficiency

Improvement over

the Base Case

Energy Savings

Quads

Water Savings

trillion gallons

Net Present Value

(NPV)

(billion 1997$)

1 1.021 20% 2.12 0.53 3.66

2 1.089 25% 4.04 9.09 14.29

4 1.257 35% 5.99 12.94 16.88

5 1.362 40% 6.03 12.94 16.73

6 1.634 50% 7.53 10.85 10.79

3 1.04 in 2004

1.26 in 2007

5.52 11.59 15.30

Table 10.7 shows the energy savings, water savings and net present value for different

standard levels and the negotiated two-tier standard.

Table 10.8 summarizes the energy and water savings from the negotiated rule, and also

provides an estimate of the present value of the incremental equipment cost.

10-16

EE-RM-PET-100 COMMENT 88
Table 10.8 NES Results: oronosed rule (MEF = 1.04 @ 2004 & MEF=1.26 @2007)

Cost and Net Present Values

Discounted from 2004 at 7% real to 1997 (in billion 1997$)

Total Energy & Water Savings 27.16

Net equipment Cost 11.86

Net Present Benefit 15.30

Benefit/Cost Ratio 2.3%

Table 10.9 details the cumulative energy and water savings at different years. The energy

savings are also broken down by fuel type and illustrate how most of the savings is for electricity

with major savings also in Gas consumption. The impact of the standard on Oil and LPG use is

significantly smaller that the savings for Electricity and Gas.

Table 10.9 Efficiency Level: Enerv and Water Savings (oronosed rule)

Energy Saving in Quads Water Saving

Total Elec Gas Oil LPG (Trillion gals)

From 2004 to 2010 0.39 0.23 0.14 0.01 0.01 0.60

to 2020 2.51 1.47 0.93 0.06 0.05 4.97

to 2030 5.52 3.23 2.05 0.14 0.10 11.59

Figure 10.1 illustrates the typical pattern of national savings and costs resulting from

standards over time. The heavy line running just below the energy and water savings bars indicates

the undiscounted net national consumer impact of standards overtime. Figure 10.1 shows the nature

of net savings for the proposed rule relative to the baseline. This figure also illustrates that for the

proposed two-tier standard most of the savings take place after the second tier becomes effective.

Alternate standard levels would yield different values.

2000 2005 2010 2015 2020 2025 2030

8.00 E:cJPrice Change

Energy & Water Saving

6.00 -Net Saving

IN

4.00

2.00

0.00

uuuu IiU LI Ii U

-2.0 0

-4.00

Figure 10.1 Annual Cost and Savings for the Proposed Clothes Washer

Rule

10-17

EE-RM-PET-100 COMMENT 88
10.5 USER INSTRUCTIONS FOR NES/SHIPMENTS SPREADSHEET

The clothes washer national energy savings (NES) and shipments spreadsheet is used to

calculate the national energy, water and dollar savings from a clothes washer efficiency standard as

well as to estimate future clothes washer shipments. The spreadsheet includes a clothes washer

shipment model that uses clothes washer stock accounting together with a consumer decision model

to forecast future shipments and sales. The consumer decision model includes probability functions

that describe decisions regarding purchases, clothes washer repair, and breakdown information. The

decision probabilities are used together with the accounting of purchases and stocks to forecast future

clothes washer shipments under a variety of potential efficiency standards scenarios. The NES model

uses input from the shipments model regarding washer purchases and compares the energy use

between a baseline scenario and the various standards scenarios.

The 'Welcome NES' and 'Welcome Ship' worksheets act as the main user interfaces for NES

and shipment forecast calculations respectively. When the user clicks on the 'Welcome NES' or

'Welcome Ship' tab, a user interface appears. For the NES scenario, this can be run for different

standard levels and scenarios for energy price projection, start year, discount rate, annual h-axis

market share increase, and water escalation rate. This worksheet also has a Reset Base Case button

that allows the user to set the base case scenario. Similarly for the shipments forecast, different

manufacturer price mark-ups, macro-economic explanatory variables, and consumer decision

elasticities can be selected by the user.

10.5.1 BASIC OPERATING INSTRUCTIONS

Once you have downloaded the NES/Shipments integrated spreadsheet file from the web,

open the file using Excel. At the bottom, click on the tab for the 'Welcome NES' or 'Welcome Ship'

worksheet. The 'Welcome NES' worksheet will display two tables: Energy and Water Savings, and

Cost and Net Present Values. Also included is a chart Cost and Savings of Clothes Washer

Standard. Use Excel's commands at the top, View/Zoom, to change the size of the display to make

it fit your monitor.

In the revised NES and shipments analysis, operating costs effect the base case shipments

projection. Because of this, every time a parameter is changed, the base case scenario needs to be

recalculated and saved for comparison with the standard case scenario.

Therefore, the first step in using the NES/Shipments spreadsheet is to set the base case. To

do this you first select the Standard Case Design that you want to use for the base case scenario.

Then you select the Energy Price Projection, Water Escalation Rate, Discount Rate, Start Year, and

the Annual % Increase of H-Axis market share of interest. In addition, if you want to change options

in the shipments model, you need to go to the 'Welcome Ship' worksheet and select the combination

of markup and elasticities of interest. After you make these selections, the spreadsheet will calculate

the shipments and the energy use characteristics of the base case scenario. Next click on the Reset

Base Case button in the 'Welcome NES' worksheet in order to copy the data from the shipment

forecast into the base case worksheet. Then, select the standard scenario that you wish to compare

to the base case, and the spreadsheet will calculate the new forecast of shipments, energy use, and

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EE-RM-PET-100 COMMENT 88
water use. It will also calculate the expenses and savings of the standard scenario in comparison to

the base case that was set.

The following two tables provide the specific spreadsheet locations for several quantities

mentioned in this documentation. Table 10.10 shows the quantities and their locations in the

national energy savings spreadsheet (NES2000-05 1 5-2T.XLS).

Table 10.10 National Energy Saving Quantities and their Locations in the National Energy

Savings Spreadsheet

OUANTITY SHEET COLUMN ROW

National Annual Energy Consumption Base Case or Ship Forecast BX-CM 58-113

National Annual Energy Savings Savings U 11-41

Source conversion factor (src_conv) Energy Inputs AJ-AK 54-84

Stock of clothes washers (STOCKy) Base Case or Ship Forecast DAGa 58-113

Cycles per year (Ilcycie) Energy Inputs V 54-84

Energy per Cycle (UEC) Engineering G-S 35-39

Table 10.11 Net Present Value Quantities and their Locations in the National Energy

Savings Spreadsheet

OUANTITY SHEET COL ROW

Discount factor Savings AG 11-67

Net Present Value (NPV)1' Welcome NES S 12

Present Value of Costs (PVC)C Welcome NES

Savings (Original)

5

AF

11

66

Present Value of Savings (PVSy1 (Copy) NES

(Original) Savings

S

AE

10

66

Net equipment Cost (yearly) Savings AC 15-41

Total Operating Cost Savings (yearly) Savings AD 15-41

a These columns may be hidden. To display them, use the Excel command sequence FormatlColumnftjnhide.

b Referred to in the spreadsheet as "net present benefit."

Referred to in the spreadsheet as "net equipment cost" (discounted).

d Referred to in the spreadsheet as "total energy and water savings" (discounted).

10-19

EE-RM-PET-100 COMMENT 88
REFERENCES

U.S. Department of Energy - Energy Information Administration, Annual Energy Outlook

1999: With Projections Through 2020, December, 1998. Washington, DC. Report No.

DOEIEIA-03 83(99). <http://www.eia.doe.gov/oiaf/aeo99/homepage.html>

2. Title 10, Code of Federal Regulations, Appendixfl to SubpartB or Part 430--Uniform Test

Method for Measuring the Energy Consumption of Automatic and Semi-automatic Clothes - Washers, January 1, 1999, U.S. Office of the Federal Register.

3. Lawrence Berkeley National Laboratory, Draft Report on the Preliminary Engineering

Analysis for Clothes Washers, Appendix D-1, October, 1996. Berkeley, CA. Report to U.S.

Department of Energy, Office of Codes and Standards.

4. Proposed Rulemaking Regarding Energy Conservation Standards for Three Cleaning

Products, Comment No. 40, Docket No. EE-RM-94-403, July 13, 1995.

Lawrence Berkeley National Laboratory, Revised Draft Report on Consumer Research for

Clothes Washers. Comment No.85. Docket No. EE-RM-94-403, April 3, 1998. Berkeley,

CA. <http://www.eren.doe.gov/buildings/codes_standards/notices/notcOO 1 2/index.htm>

10-20

EE-RM-PET-100 COMMENT 88
CHAPTER 11. MANUFACTURER IMPACT ANALYSIS

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TABLE OF CONTENTS

11.1 MANUFACTURER IMPACT ANALYSIS METHODOLOGY 11-1

11.1.1 Phase 1: Industry Profile 11-1

11.1.2 Phase 2: Preliminary Industry Cash Flow Analysis 11-2

11.1.3 Phase 3: Sub-Group Impact Analysis 11-2

11.1.4 Small Manufacturer Sub-Group 11-3

11.2 INPUTS TO THE GRIM 11-4

11.2.1 Overview of GRIM Spreadsheet 11-4

11.2.2 Financial Inputs to the GRJIrvI 11-6

11.2.2.1 Tax Rate 11-7

11.2.2.2 WorkingCapital 11-7

11.2.2.3 Selling, General and Administration (SG&A) 11-8

11.2.2.4 Research and Development (R&D) 11-8

11.2.2.5 Depreciation 11-9

11.2.2.6 CapitalExpenditures 11-10

11.2.2.7 Cost of CapitallDiscount Rate 11-10

11.2.3 GRIM Shipments 11-15

11.2.3.1 Impact of New Energy-Efficiency Standards for Clothes

Washers on Export Sales 11-24

11.2.4 Manufacturing Costs 11-25

11.2.4.1 Baseline Industry Cost Structure 11-25

11.3 IMPACTS ON CASH FLOW 11-27

11.3.1 Base Case NPV 11-27

11.3.2 StandardCaseNPV 11-28

11.3.2.1 Impact of Standards on Manufacturer Prices and Profit

Margins 11-28

11.3.2.2 Impact of New Energy-Efficiency Standards on Manufacturing

Costs 11-29

11.3.2.3 Definition of Business Scenarios 11-3 1

11.3.2.4 "No Consolidation" Scenario 11-3 1

11.3.2.5 Consolidation Scenario 11-34

11.4 IMPACT ON CLOTHES DRYER BUSINESS 11-36

11.4.1 Dryer Employment Impacts 11-39

11.5 CLOTHES WASHER REPAIR INDUSTRY ANALYSIS 11-41

11.5.1 KeyAssumptions 11-41

11.5.2 Impact of New Energy Efficiency Standards on the Repair Industry 11-42

11.6 IMPACTS ON MANUFACTURING CAPACITY 11-45

11.6.1 Manufacturing Facilities 11-45

11.6.2 The Impact of New Energy Efficiency Standards on the Production

Facility Mix 11-45

11-i

EE-RM-PET-100 COMMENT 88
11.6.3 The Impact of New Energy Efficiency Standards on Capacity Utilization and

Manufacturing Assets Levels at Domestic Production Facilities ......... 11-47

11.6.3.1 Assumption 1: Capital Structure (% of Revenue) Remains

Unchanged .......................................... 11-48

11.6.3.2 Assumption 2: The Per Unit Clothes Washer Capital

Requirements Are Unchanged ........................... 11-49

11.7 IMPACT OF THE EFFECTIVE DATE ON NEW STANDARD .............. 11-50

11.7.1 The Impact of a Delay in the Effective Date on Cash Flow .............. 11-51

11.7.1.1 Discounting ......................................... 11-5 1

11.7.1.2 Ordinary Capital Expenditures Assumption ................ 11-51

11.7.1.3 R&D Assumption ..................................... 11-52

11.7.2 The Impact of a Delay in Effective Date on Dryer and Clothes Washer

Repair Businesses ............................................. 11-53

11.8 IMPACT ON SMALL MANUFACTURERS .............................. 11-53

11.8.1 Introduction .................................................. 11-53

11.8.2 Small Manufacturer Modeling Approach ........................... 11-55

11.8.2.1 Price Assumption ..................................... 11-55

11.8.2.2 Shipments Assumption ................................ 11-56

11.8.2.3 Product Conversion Cost Assumption ..................... 11-56

11.8.2.4 Capital Investment Assumption .......................... 1 1-56

11.8.2.5 Summary of Key Assumptions .......................... 11-57

11.8.3 SummaryofResults ............................................ 11-58

11.8.4 Other Impacts ................................................. 11-59

11.9 EMPLOYMENT IMPACTS ........................................... 11-59

11.9.1 Impact on Workforce Skills Required Under New Energy Efficiency

Standards .................................................... 11-63

11.10 CUMULATIVE REGULATORY BURDEN .............................. 11-63

11.10.1 Regulations on Other Products Produced by Clothes Washer

Manufacturers ............................................. 11-63

11.10.2 Other Regulations .......................................... 11-66

11.11 IMPACTONSUPPLIERS ............................................ 11-66

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LIST OF TABLES

Table 11.1 Average Income Tax Rates 11-7

Table 11.2 Average Working Capital as a Percentage of Revenues 11-8

Table 11.3 Average SG&A Expense as a Percentage of Revenues 11-8

Table 11.4 Average R&D Costs as a Percentage of Revenues 11-9

Table 11.5 Average Depreciation Expense as a Percentage of Revenue 11-9

Table 11.6 Average Capital Expenditures as a Percentage of Revenues 11-10

Table 11.7 CostofDebtandDebtRatio 11-11

Table 11.8 Average Rates of Return (1990-96) and Risk Premiums (1926-94) on

Some Securities (figures in percent per year) 11-13

1 1-u

EE-RM-PET-100 COMMENT 88
Table 11.9 Average Beta Values for Two Appliance Manufacturers ............... 11-14

Table 11.10 Comparison of Financial Data .................................... 11-15

Table 11.11 Clothes Washer Shipment Forecasts for the Base Case and Standard Case

(High Price Elasticity Shipment Scenario) .......................... 11-16

Table 11.12 Clothes Washer Shipment Forecasts for the Base Case and Standard Case

(Medium Price Elasticity Shipment Scenario) ........................ 11-18

Table 11.13 Clothes Washer Shipment Forecasts for the Base and Standard Case

(Medium Price/Income Elasticity Shipment Scenario) ................. 11-20

Table 11.14 Percentage Decreases in Shipments ................................ 11-23

Table 11.15 Annual Shipments of Clothes Washers from 1990 through 1996 (million) . 11-24

Table 11.16 Calculation of Calibration Factor for GRIM Shipment Forecast ......... 11-25

Table 11.17 Industry Average Baseline Cost Structure ........................... 11-27

Table 11.18 Industry Cash Flow Results for the "No Consolidation" Scenario - High

Price Elasticity ................................................ 11-32

Table 11.19 Industry Cash Flow Results for the "No Consolidation" Scenario - Medium

Price Elasticity ................................................ 11-32

Table 11.20 Industry Cash Flow Results for the "No Consolidation" Scenario - Medium

Price/Income Elasticity ......................................... 11-33

Table 11.21 Industry Cash Flow Results for the "Industry Consolidation" Scenario -

High Price Elasticity ........................................... 11-34

Table 11.22 Industry Cash Flow Results for the "Industry Consolidation" Scenario -

Medium Price Elasticity ......................................... 11-35

Table 11.23 Industry Cash Flow Results for the "Industry Consolidation" Scenario -

Medium Price/Income Elasticity .................................. 11-35

Table 11.24 Shipment-weighted Manufacturer Price of Dryers from 1990

through 1996 ................................................. 11-36

Table 11.25 Cost and Financial Information Used in the Dryer GRIM ............... 11-37

Table 11.26 Standard Case NPV for Dryer Business - High Price Elasticity Scenario

Efficiency Improvement ......................................... 11-38

Table 11.27 Standard Case NPV for Dryer Business - Medium Price Elasticity Scenario

Efficiency Improvement ......................................... 11-3 8

Table 11.28 Standard Case NPV for Dryer Business - Medium Price/Income Elasticity

Scenario ..................................................... 11-39

Table 11.29 Repair Industry Revenue Assumptions ............................. 11-44

Table 11.30 Net Present Value of OEM Repair Revenues ($ Millions) .............. 11-44

Table 11.31 Manufacturer Implied Impact of New Efficiency Standards on Production

Facility Mix .................................................. 11-46

Table 11.32 Clothes Washer Industry Property, Plant and Equipment Forecasts for the

Baseline and Trial Standard Level 4 (35 percent Efficiency Improvement) . 11-48

Table 11.33 Estimate of Industry Stranded Assets (Assuming Industry Maintains

Current Cost Structure) ($million) ................................ 11-49

Table 11.34 Estimate of Industry Stranded Assets (Assuming Industry Maintains

Current Value of Plant, Property and Equipment) ($million) ............ 11-50

Table 11.35 Stranded Assets as a percent of Pre-standard Assets .................. 11-52

1 1-ui

EE-RM-PET-100 COMMENT 88
Table 11.36 Standards-Related Design & Marketing Expenditures ................. 11-53

Table 11.37 Base Year Shipments ........................................... 11-56

Table 11.38 Change in Value of Small Manufacturers, Results for the "No

Consolidation" Scenario - High Price Elasticity Scenario (%) ........... 11-58

Table 11.39 Change in Value of Small Manufacturers, Results for the "No

Consolidation" Scenario - Medium Price Elasticity Scenario (%) ........ 11-58

Table 11.40 Change in Value of Small Manufacturers, Results for the "No

Consolidation" Scenario - Medium Price/Income Elasticity Scenario (%) . . 11-58

Table 11.41 "Worst Case" Manufacturer Implied Impact of New Energy Efficiency

Standards on Employment Levels resulting from Plant Closures* 11-60

Table 11.42 Expected Incremental Labor Costs at Various Efficiency Levels ......... 11-61

Table 11.43 Future Regulations Affecting Appliance Manufacturers ................ 11-64

Table 11.44 Market Shares of Major Clothes Washer Manufacturers in Other Products

Faced with Future Regulations ................................... 11-64

Table 11.45 Estimated Impacts of Approaching Regulations on Clothes Washer

Manufacturers ................................................ 11-65

Table 11.46 Average Breakup of Raw Materials and Component Costs in U.S

Manufactured Clothes Washers (as % of Total Materials Cost) .......... 11-66

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LIST OF FIGURES

Figure 11.1 Using GRIM to Conduct the Cash Flow Analysis 11-5

Figure 11.2 Clothes Washer Shipment Forecasts for Base Case and the Negotiated

Standard Level 11-22

Figure 11.3 Implied Impact of Decline in Washer Shipments on Clothes Dryer

Employment Levels 11-40

Figure 11.4 Estimated Number of Clothes Washer Repairs (High Price Elasticity

Shipment Scenario) 11-43

Figure 11.5 Predicted Impact on U.S. Clothes Washer Industry Employment Levels 11-62

11 -iv

EE-RM-PET-100 COMMENT 88
CHAPTER 11. MANUFACTURER IMPACT ANALYSIS

11.1 MANUFACTURER IMPACT ANALYSIS METHODOLOGY

In determining whether a standard is economically justified, the Secretary of Energy is

statutorily required to consider "the economic impact of the standard on the manufacturers and on

the consumers of the products subject to such a standard.a The legislation also calls for an

assessment of the impact of any lessening of competition as determined in writing by the Attorney

General. The purpose of the Manufacturer Impact Analysis (MIA) is to provide information that can

be used to evaluate these impacts. The MIA estimates the financial impact of standards on

manufacturers and reports impacts on employment and manufacturing capacity.

Prior to initiating the detailed MIA for the clothes washer rule making, the U.S. Department

of Energy (DOE) prepared an approach document titled "Clothes Washer Manufacturer Impact

Analysis." This document was presented at a public workshop held on December 14-15, 1998. It

was based on the general framework for the MIA presented by the Department at a workshop in

March 1997 and was modified for its application to the clothes washer rule. The approach document

outlined procedural steps and identified issues for consideration.

As proposed in the approach document, the MIA was conducted in three phases. Phase 1,

"Industry Profile," consisted of the preparation of an industry characterization. Phase 2, "Preliminary

Industry Cash Flow," had as its focus the larger industry. In this phase, the Government Regulatory

Impact Model (GRIM) was used to prepare a preliminary industry cash flow analysis. Here, the

Department used publicly available information developed in Phase 1 to adapt the GRIM structure

to facilitate the analysis of new clothes washer standards. In Phase 3, "Sub-Group Impact Analysis,"

the Department discussed fully the results of the Preliminary Industry Cash Flow analysis with each

manufacturer and identified the differing impact of standards on sub-groups of manufacturers.

Phase 3 also entailed documenting additional impacts on employment and manufacturing capacity

through a structured interview process.

11.1.1 Phase 1: Industry Profile

Phase 1 of the MIA consisted in preparing an Industry Profile. Prior to initiating the detailed

impact studies, DOE received input on the present and past structure and market characteristics of

the clothes washer industry. This activity involved both quantitative and qualitative efforts to assess

the industry and products to be analyzed. Issues addressed included manufacturer market shares and

characteristics, trends in the number of firms, the financial situation of manufacturers, and trends in

clothes washer characteristics and markets.

aThe Department of Energy's appliance standards program is conducted pursuant to Title III, Part B of the

Energy Policy and Conservation Act (EPCA). 42 U.S.C. 6291-6309.

11-1

EE-RM-PET-100 COMMENT 88
The industry profile included a top-down cost analysis of the appliance industry that was used

to estimate the disaggregated costs of a baseline clothes washer. The cost structure was used to

derive cost and financial inputs for the GRIM-e.g., material, labor, overhead, depreciation, sales

general & administration (SG&A), and research & development (R&D). The profile was also

instrumental in estimating the manufacturer and retail mark-ups that were used in the Life-Cycle

Cost Analysis.

Publicly-available quantitative data published by the U.S. Bureau of Census with regards to

the clothes washer industry is included in Chapter 3. The chapter includes information on the number

of companies, number of manufacturing establishments, and industry employment, payroll, value

added, cost of materials consumed, capital expenditures, product shipments, and concentration ratios.

The Department also utilized additional sources of information to further characterize the

clothes washer industry. These include company Securities and Exchange Commission (SEC) 10-K

and annual reports, Moody's company data reports, Standard & Poor's (S&P) stock reports, Value

Line industry composites, and Dow Jones Financial Services.

11.1.2 Phase 2: Preliminary Industry Cash Flow Analysis

A change in standards affects the analysis in three distinct ways. Increased levels of standards

will require additional investment, raise production costs, and affect revenue through higher prices

and, possibly, lower quantities sold. To quantify these impacts the Department performed in Phase 2

an industry cash flow analysis using the GRIM.

For the Preliminary Industry Cash Flow Analysis, DOE prepared a list of financial values for

the GRIM industry analysis. These were calculated by studying publicly- available financial

statements of clothes washer manufacturers. A detailed definition of financial inputs and their values

for a "prototypical" clothes washer manufacturer is presented in section 11.2. Values for currently

sold "Base Case" prices were derived from the Bureau of Census's Current Industrial Reports (CIRs).

The dollar value of clothes washer shipments from factories is divided by the quantity of clothes

washers shipped to arrive at the per-unit manufacturer price. In order to estimate manufacturing

costs-labor, materials, depreciation/tooling, etc.-from the average manufacturer prices obtained from

the CIRs, a typical clothes washer industry cost structure was developed using publicly-available

information from the Census of Manufacturers (CMs) and from industry statistics obtained from

SEC- 10K reports. Finally, in preparing the Preliminary Industry Cash Flow Analysis, DOE used the

same clothes washer shipment scenarios developed for the National Energy Savings (NES)

spreadsheet.

11.1.3 Phase 3: Sub-Group Impact Analysis

DOE conducted detailed interviews with clothes washer manufacturers representing over 99

percent of domestic clothes washer sales to gain insight into the potential impacts of standards on

their revenues and finances, direct employment, capital assets and industry competitiveness, and to

solicit the information necessary to validate industry cash flows.

11-2

EE-RM-PET-100 COMMENT 88
The interview process played a key role in the MIA, since it allowed manufacturers to

privately express their views on important issues and to provide confidential information needed to

assess financial, employment, and other business impacts. To verify the assumptions used to derive

the Preliminary Industry Cash Flow, an interview guide solicited information on the possible impacts

of new standards on manufacturing costs, product prices, and sales. Each manufacturer was provided

a version of the GRIM that included shipment forecasts at each efficiency level, baseline prices and

costs of the V-axis and H-axis washers, and incremental product costs for all percentiles reported

by AHAM. In preparation for the interview, each manufacturer could, if desired, input its own data

and assumptions to develop its own expected cash flow. Alternatively, manufacturers could select

the percentile values that best represented their costs at different efficiency levels. During the

interviews, DOE discussed with each manufacturer the differences, if any, between the impact of

energy-efficiency standards on their shipments, prices, costs, and associated margins and those

presented in the sample results for the industry as a whole.

The interview guide solicited both qualitative and quantitative information. Supporting

documentation was requested wherever applicable. Interview participants were asked to identify all

confidential information provided verbally or in writing. Approximately two weeks following the

interview, an interview summary was provided to the manufacturers to give them an opportunity to

confirm the accuracy and protect the confidentiality of all the collected information. The

manufacturer interview guide is presented in Appendix 0.

11.1.4 Small Manufacturer Sub-Group

Using industry "average" cost values is not adequate for assessing the variation in impacts

among sub-groups of manufacturers. Comments received following the publication of the

preliminary Technical Support Document indicated that the smaller manufacturers of clothes

washers could be more negatively affected than other manufacturers by any proposed standard. To

assess the potential impacts of possible washer standards on smaller manufacturers, DOE conducted

preliminary interviews with the three smallest clothes washer manufacturers (by market share) and

held discussions on possible approaches to performing the Manufacturer Impact Analysis for small

manufacturers. DOE and the manufacturers discussed how a small-manufacturer GRIM could be

constructed and contrasted with the industry cash flow analysis. Foremost in the discussions were

issues concerning data collection and aggregation and the ensuing confidentiality concerns given the

small group of manufacturers and their unbalanced size.

All of the smaller manufacturers worked with DOE to develop a company-specific GRIM

analysis for their firms. Even within the small manufacturer sub-group, DOE found significant

differences in financial structure among the firms depending on their business models (e.g., OEM

vs. retail emphasis, product market niche). DOE found that from a financial standpoint the common

characteristic of this group, in contrast to the overall industry, was its need to spread fixed costs over

smaller production volumes. During the interviews, small manufacturers demonstrated that several

of the key costs necessary to meet any new regulation are largely independent of the product volume

produced. The most apparent are the costs necessary to design a new product meeting the proposed

11-3

EE-RM-PET-100 COMMENT 88
energy standards. Other costs, such as plant engineering, some tooling, and other capital costs, have

significant portions that are independent of final production volumes.

To assess the "differential" potential impacts of possible washer standards on smaller

manufacturers without revealing individual manufacturers' proprietary information, DOE prepared

a cash flow analysis of the potential effects on a "prototypical" smaller manufacturer. The basic

approach to analyzing the economic effects on a smaller manufacturer involved determining the

smaller company's fixed cost structure relative to the industry average and the likely ability of the

smaller company to recover its full costs and investments after implementation of a new standard.

Dryer Analysis. An important consideration regarding new efficiency standards that came

to light during the course of interviews with manufacturers, was the pull-through effect of clothes

washers on the clothes dryer market. The majority of manufacturers indicated that stringent standards

on clothes washers would have an effect on dryers since dryer sales are highly correlated to washer

sales as the two are frequently bought as a set. A separate cash flow analysis was prepared in an

effort to model the financial impact of these considerations on the dryer business. The Dryer GRIM

analysis is incorporated in the GRIM Model.

Impact on Clothes Washer Repair Industry. Should an increase in energy efficiency

standards result in higher prices for new clothes washers, consumers may be influenced to repair old

units rather than purchase new ones at the higher price. Based on the forecast of clothes washer

repairs, the Department estimated the impact of a change in clothes washer repair revenues on the

NPV of the clothes washer manufacturers' repair parts business. Those impacts are calculated and

incorporated in the GRTh4 Model.

11.2 INPUTS TO THE GRIM

11.2.1 Overview of GRIM Spreadsheet

The GRIM was used to evaluate the cash flow impacts of regulations on the clothes washer

industry. The basic structure of the GRIM, illustrated in Figure 11.1, is a standard annual cash flow

analysis that uses manufacturer price, manufacturing costs, shipments, and industry financial

information as an input and accepts a set of regulatory conditions as changes in costs, investments,

and associated margins.

11-4

EE-RM-PET-100 COMMENT 88
Cash

Figure 11.1 Using GRIM to Conduct the Cash Flow Analysis

The GRIM spreadsheet uses a number of factors-annual expected revenues, cost of sales,

selling and administration costs, taxes, changes in working capital, and capital expenditures related

to new standards-to arrive at a series of annual cash flows, beginning from the base year of the

analysis and continuing explicitly for several years after the implementation of the standard. The

measure of industry net present value (NPV) is calculated by discounting the stream of annual cash

flows.

The GRItvI calculates cash flows by year and then determines the present value of those cash

flows, both without regulations (Base Case) and with regulations (Standard Case), using the

appropriate discount rate. For the purpose of this analysis, the Base Case scenario represents the

business scenario in the absence of a standard. If a new clothes washer standard comes into effect,

it will change the product mix of clothes washers being sold in the market and their associated

prices, costs, and shipments. Such a scenario is called the Standard Case scenario. Hence, Base Case

NPV implies the present value of cash flows in the absence of a standard; Standard Case NPV

implies the present value of cash flows in the scenario where a standard comes into effect. To project

future cash flows, the clothes washer GRIM analysis assumes 2001 as the announcement year of the

standard and 2004 as the year when the new standard will come into effect.

The following sections present the inputs used in the industry GRJIIVI. These are:

11.2.2 Financial Inputs

11.2.3 Shipments

11.2.4 Manufacturing Costs

11-5

EE-RM-PET-100 COMMENT 88
11.2.2 Financial Inputs to the GRIM

DOE developed an initial industry characterization using information from relevant industry

and market publications, industry trade organizations, company financial reports, and product

literature. This industry characterization provided the inputs that were used to develop a preliminary

industry cash flow analysis.

The financial reports of the five major U.S. clothes washer manufacturers were studied. The

top three clothes washer manufacturers by market share, namely, Whirlpool, Maytag and General

Electric, together accounted for 88 percent of all clothes washers manufactured in the U.S. in the

year 1996. For Whirlpool and Maytag, home appliance manufacturing represents the major portion

of their business and revenue generation. Hence financial data obtained from a top-down analysis

of their SEC 10-K reports would be representative of the clothes washer industry (assuming that

clothes washers are a microcosm of the total major appliance industry).

GE, however, is highly diversified, and its appliance manufacturing business-GE

Appliance-accounted for only a small percentage (8%) of GE's total revenues in 1996. Similarly

Amana (which was a part of Raytheon until recently when it was sold to Goodman Holdings)

accounted for only about 12 percent of Raytheon's annual sales (and 6 percent of the profits). Hence,

like GE, the information obtained from Raytheon's SEC 10-K reports may not be representative of

its appliance manufacturing business (i.e., of Amana's financial structure).

Frigidaire is a subsidiary company of Electrolux AB, a European company. Electrolux is the

world's largest manufacturer of household appliances, such as white goods, vacuum cleaners and

outdoor products. Most of Electrolux's revenues come from operations outside North America (59%

from Europe, 6% from Asia, and 6.4% from Latin America) and hence financial data from

Electrolux's income statements may not be indicative of the business environment in North America.

Also, differences in accounting principles for financial reporting purposes (between U.S. and other

countries) might lead to a different financial structure.

Value Line and Standard & Poor's (S&P) composite industry statistics for the home appliance

industry were reviewed. Value Line's statistics for the home appliance industry are a composite of

the following companies: Whirlpool, Maytag, Fedders Corp., Black & Decker, Toro, and National

Presto Industries. In S&P reports, appliance manufacturers are included in the "Household

Furnishings and Appliance" industry. The S&P statistics are a composite of the following

companies: Armstrong World, Basset Furniture, Fedders Corp., Maytag, Mohasco, Roper,

Rubbermaid, Whirlpool, White Consolidated Industries, and Zenith Electronics. Given the

composition of the industry-composites, Value Line's industry statistics are possibly more

representative of the clothes washer industry.

The financial inputs to the GRIM are described below. Historical shipments, market share

and market characteristics incorporated in the development of the GRTIvI analysis are presented in

Chapter 3.

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EE-RM-PET-100 COMMENT 88
11.2.2.1 Tax Rate

Firms pay an annual tax, levied by the Federal and state governments, based on income.

Taxable income and the income taxes paid are presented as separate line items in a company's

income statement. Table 11.1 presents the effective income tax rates for two major appliance

manufacturers over the period 1990-96. It also presents the industry average tax rate which is

obtained by weighting effective income tax rates of four clothes washer manufacturers by their

clothes washer shipments. This information was obtained from the manufacturers' income

statements, by dividing the income taxes paid by the taxable income. The tax rate for the industry

composite, as reported by Value Line, is in close agreement with that for the industry average. The

Department proposes using an income tax rate of 42.8% as an input to GRJIIVI. This value is based

on the industry average tax rate.

Table 11.1 Average Income Tax Rates

Manufacturer

________________________

Avg. Tax Rate

(1990-1996)

A 46.5%

B 45.4%

Industry Average 42.8%

Value Line 40.0%

11.2.2.2 Working Capital

Working capital is defined as the difference between a firm's short-term (or current) assets

and short-term (or current) liabilities, where the current assets and liabilities are obtained from the

firm's annual balance sheets. It is the part of a company's capital that must be maintained in order

to undertake day-to-day operations of the company without experiencing liquidity problems.

Table 11.2 presents average working capital maintained by two major appliance

manufacturers as a percentage of their annual revenues. Data has been averaged over the period

1990-96. Working capital data is also presented for the home appliance industry composite as

reported by Value Line.

Clearly there exists considerable variability in the working capital requirements of various

firms based on information obtained from SEC 1 0-K reports. In general, companies will strive to

lower their working capital needs to the lowest amount possible so as to free up as much cash flow

as possible for revenue-generating investing activities. Discussions with appliance industry analysts

indicate that working capital requirements are in the 7-16% range. Based on this information, the

Department assumed working capital to be 10.50% of revenues for input into GRIIvI.

11-7

EE-RM-PET-100 COMMENT 88
Table 11.2 Average Working Capital as a Percentage of Revenues

Manufacturer Working Capital as % of

Revenues (1990-96)

A (0.70)

B 16.09

ValueLine 6.76

11.2.2.3 Selling, General and Administration (SG&A)

Table 11.3 presents average SG&A expenses for two major appliance manufacturers as a

percentage of their annual revenues. The data has been averaged over seven years, 1990 through

1996. SG&A information is presented as a line item in individual manufacturers' income statements,

presented in separate SEC 10-K reports.

Selling costs include any expense or class of expense incurred in selling or marketing. In a

manufacturing firm, selling costs include both marketing costs and logistics (order-filling) costs.

Marketing costs include market research, advertising, point-of-sale promotions, and salespersons'

compensation and travel costs. Logistics costs include warehousing and delivery costs as well as

record-keeping costs associated with processing an order. General and Administrative (G&A) costs

are expenses incurred for the general direction of the enterprise. G&A costs include the cost of

service and staff units (such as the personnel office) and general corporate costs, including

compensation of top management and donations to charitable organizations. The Department used

a value of 18.0% (revenue weighted average of the two manufacturers in Table 11.3) of revenues for

SG&A expense as an input to GRIM.

Table 11.3 Average SG&A Expense as a Percentage of Revenues

Manufacturer

_______________________________

SG&A as % of Revenues

(1990-96)

A 18.43

B 17.01

11.2.2.4 Research and Development (R&D)

Research and development (R&D) costs are costs incurred for the purpose of developing new

or improved goods, processes or services. The results of R&D efforts are increased revenues or lower

costs. Table 11.4 presents the R&D costs incurred by two major appliance manufacturers as a

percentage of their annual revenues. The R&D cost data has been averaged over the past four years,

11-8

EE-RM-PET-100 COMMENT 88
1993 through 1996. Data for the period 1990-1992 is not available as the separate disclosure of

research and development expense is a relatively recent requirement. Formerly, most companies

included this expense as a part of general and administrative expenses. Because the amount spent

on research and development can provide an important clue as to how energetic the company is in

keeping its products and processes up to date, FASB requires that this amount be reported separately

if it is material.

Based on the information in Table 11.4, the Department used a value for R&D expense of

1.80% (revenue weighted average of the two manufacturers in Table 11.4) of revenues for input into

GRIM.

Table 11.4 Average R&D Costs as a Percentage of Revenues

Manufacturer

____________________________

Avg. R&D Cost as % of Revenues

(1993-96)

A 2.01

B 1.50

11.2.2.5 Depreciation

Plant and manufacturing equipment assets have limited useful lives; that is, they will provide

service to the firm over a limited number of future accounting periods. A fraction of the cost of these

assets is therefore properly chargeable as expense in each of the accounting periods in which the

assets provide service to the firm. The accounting process for this gradual conversion of plant and

equipment capitalized cost into expense is called depreciation. Table 11.5 presents average

depreciation expense for two major appliance manufacturers as a percentage of their annual

revenues. The data has been averaged over seven years, 1990 through 1996. Depreciation is

presented as a separate line item in the manufacturers' income sta tements as presented in SEC 10-K

reports.

Based on information in Table 11.5, the Department proposes using depreciation expense as

3.5 1% (revenue weighted average of the two manufacturers) of revenues for input into GRIM.

Table 11.5 Average Denreciation Exuense as a Percentage of Revenue

Manufacturer Depreciation as % of

Revenues (1990-96)

A 3.54

B 3.43

ValueLine 3.66

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EE-RM-PET-100 COMMENT 88
11.2.2.6 Capital Expenditures

These are the expenditures made for additions to fixed assets, like plant, equipment,

etc.,intended to benefit future accounting periods (in contrast with other expenditures that benefit

the current period). These expenditures are aimed at increasing the capacity, efficiency, life span, or

economy of the operation of an existing fixed asset, or, in some cases, to build entirely new assets.

Table 11.6 presents average capital expenditures for two major appliance manufacturers as

a percentage of their annual revenues. The data has been averaged over seven years, 1990 through

1996. The Department used a value of capital expenditures of -3.90 % as an input into GRIM.

Although initially DOE proposed to use -4.43% (revenue weighted average of the two manufacturers

in Table 11.6 ) as an input into GRD%4, this figure was lowered to -3.90% to reflect the lower

shipment growth forecast compared to the earlier GRIM and to calibrate return on invested capital

for the base case.

Table 11.6 Average Capital Exuenditures as a Percentage of Revenues

Manufacturer Capital Expenditures as

% of Revenues (1990-96)

A 4.47

B 4.33

11.2.2.7 Cost of Capital/Discount Rate

Cost of capital is a measure of a company's cost of using capital that it raises either through

loans (i.e., debt) or by issuing equity. It is the minimum rate of return that must be earned on new

investments that will not dilute the equity of the shareholders. This rate of return is often referred

to as the discount rate, hurdle rate, or the opportunity cost of capital. The company cost of capital

is a weighted average of the returns that investors expect from various debt and equity securities

issued by the firm. It is calculated as the cost of debt capital (which is then adjusted for the income

tax effect of debt financing) plus the cost of equity capital, weighted by the relative amount of each

in a company's capital structure. For the purpose of characterizing financial impacts of regulations

on manufacturers using GRIM, the Department used the company cost of capital to discount future

cash flows for arriving at the clothes washer industry

In order to calculate the company cost of capital, it is essential to identify a company's cost

of raising debt, cost of raising capital through issuing equity, and the capital structure of the

company. The capital structure of a company gives information about the amount of debt versus the

amount of equity in the company.

Cost of debt. Cost of debt is a weighted average cost of debt based on all forms of debt

financing outstanding. Information on the amount of debt outstanding and the interest rate at which

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EE-RM-PET-100 COMMENT 88
it was issued was obtained from SEC 10-K financial statements and Moody's reports for two publicly

traded appliance manufacturers.

Table 11.7 presents the nominal cost of debt and debt ratios for two appliance manufacturers.

The cost of debt is calculated in two ways:

(A) As the weighted average cost of all debt based on the coupon yield, which is the yield that

a company promises to pay on a bond's face value at the time of issuance of the debt. This

weighted average represents a company's nominal cost of debt capital from the time it issued

the debt to the present time.

(B) As the weighted average cost of all debt based on yield to maturity. Yield to

maturitydetermines the rate of return an investor will receive today if a long-term bond is

held to its maturity date. This yield represents the nominal cost of debt to a company if it

needs to raise debt capital at the present time.

Table 11.7 presents cost of debt estimates using both approaches (a) and (b). While regulators

often use an average stated actual cost of debt (as calculated in approach (a)) to determine cost of

debt, it is preferable to use the current replacement cost of debt (market value of debt as calculated

by approach (b)) for calculating the cost of capital for the purpose of assessing the present value of

the future cash flows or for evaluating alternative investment proposals of financial policies if the

policies or proposals involve debt financing. Cash flows associated with new investments should be

matched with the current or prospective cost of all capital associated with such investments. Debt

ratio is defined as the ratio of long-term debt to total long-term capital (i.e., long-term debt plus

equity), and illustrates a company's capital structure.

Table 11.7 Cost of Debt and Debt Ratio

Manufacturer

__________________

Cost of debt

(Coupon Yield)

Cost of debt

(Yield to Maturity)

Debt Ratio

(1990-96)

A 8.27 6.92 0.38

B 9.01 7.07 0.49

The real cost of debt is obtained by adjusting the nominal value for inflation. Average annual

inflation in the U.S. over the period 1990-96 was 3.42%, and more recently, it was 2.2% in the year

1

997a For Manufacturer A, 8.27% represents the average nominal cost of debt that it raised through

corporate bond offerings at different points in time over the past 10 years, a time frame during which

the interest rates and inflation rates have been varying; whereas, 6.92% represents the nominal cost

aNona1 cost implies that the cost has not been adjusted to take account of inflation.

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EE-RM-PET-100 COMMENT 88
of debt if Manufacturer A raised its debt in 1997 when both interest rates and inflation were low. In

the long run, for raising debt required to meet regulations, it could be assumed that Manufacturer A's

nominal cost of debt would fall between 7% and 9% provided there are no sharp changes in interest

rates. The same argument holds for Manufacturer B, which would also be able to raise debt at the

7-9% nominal rate. According to Statements of Management Accounting, cost of debt based on yield

to maturity would provide a better estimate. However, it is difficult to estimate the exact costs at

which these companies could raise debt at some point of time in the future.

Another way of looking at corporate debt rates is by treating them as spreads (basis points)

over the Treasury bill rates. Both manufacturers have similar bond ratings (Baal as provided by

Moody's). Looking at historical annualized return spreads for corporate bonds, both manufacturers,

with their Baal ratings, would be able to raise 30-year debt instruments at approximately 120 basis

points above U.S. Treasuries.a Looking at current interest rates, this would mean a nominal cost of

debt in the range of 7.3% for 30-year debt instruments. Adjusting for an inflation rate of 2.2% in

1997, the real cost of debt would be around 5%.

Ibbotson Associates, a company that publishes industry specific financial information on a

quarterly basis, reports a nominal cost of debt of 7.14% for the home appliance industry for the year

1997. The July 1991 AHAM report, entitled "Financial Impact of DOE Top Loading Horizontal Axis

Standards on Washing Machine Manufacturers," used a nominal cost of debt of 9.2%. Adjusting for

inflation (2.2% in 1997 and 4.2% in 1991), the real costs of debt as reported by Ibbotson Associates

and the AHAM report would be 4.94% and 5.0%, respectively.

Based on arguments above, the Department used 5% as the real cost of debt.

Cost of equity. Cost of equity is the rate of return that equity investors expect to earn on their

investments in a company's stock. These expectations are reflected in the market price of the

company's stock. One way of estimating the cost of equity is by using the capital asset pricing model

(CAPM). The CAPM is based on the premise that the expected or the required rate of return on any

firm's common stock equals the riskless rate of interest plus a premium for risk. The CAPM is

widely used by large corporations to estimate their costs of equity.b

According to the CAPM, the cost of equity, or, the expected return for equity, is determined as:

cost of equity = riskiess rate + beta * [risk premium]

where:

aUsed with permission. © 1998 Ibbotson Associates, Inc. All rights reserved. [Certain portions of this work

were derived from copyrighted works of Roger G. Ibbotson and Rex Sinquefield.]

bFor more information on CAPM the readers are referred to Chapters 7,8 and 9 of Corporate Finance by

Brealy, R.A., and Myers, S.C.; and to article entitled Does capital asset pricing model work by Mullins, D.W.,

published in the Harvard Business Review.

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EE-RM-PET-100 COMMENT 88
riskless rate is usually the short-term Treasury bill rate, or the long-term government bond

rate adjusted for the risk premium over Treasury bills,

risk premium is the difference between the expected return on the market portfolio and the

riskiess rate, and

beta is a measure of the sensitivity of a company's stock to market movements.

Table 11.8 presents yields on Treasury bills and government bonds, and the average risk

premium associated with these securities. Each portfolio offers different degrees of risk. Treasury

bills are about as safe an investment as one can make. There is little risk of default, and their short

maturity means that the prices of Treasury bills are relatively stable. However, investors cannot lock

in a real rate of return; there is still some uncertainty about inflation. By switching to long-term

government bonds, investors acquire an asset whose prices fluctuate as interest rates vary. (Bond

prices fall when interest rates rise and rise when interest rates fall.) An investor who switches from

government bonds to common stocks has a direct share in the risks of the enterprise, and hence

accepts the additional default risk. Investors who accepted the extra risk of common stocks received,

on average, a premium of 8.5% a year over the return on Treasury bills.

Table 11.8 Average Rates of Return (1990-96) and Risk Premiums (1926-94) on Some

Securities (figures in percent per year)

Portfolio Average Annual Rate of Average Risk Premium

Return (Nominal) (Extra return vs. Treasury

(199096)a bills) (1926_94)b

________________________

Treasury bills 5.00 0

Government bonds(l0 yr.) 7.06 1.5

Common stocks 8.5

(S&P_500_index)

____________________________ _________________________

Table 11.9 presents average values of beta for two appliance manufacturers. The data has

been averaged over the period 1991-96. The values of beta are obtained from financial services

provided by the Dow Jones Company. They measure the sensitivity of a stock's price to overall

fluctuations in the S&P 500 stock index. Beta measures the sensitivity of the return on an individual

stock to the return on the market portfolio. A stock with a beta of 1 tends to move up and down in

the same percentage as the market. Stocks with a beta coefficient less than 1 tend to move in

percentage terms less than the market. Similarly, a stock with a beta that is higher than 1 will tend

to move up and down more than the market.

aBd on data from the Federal Reserve Statistical Release.

'Used with permission. ©1 998 Ibbotson Associates, Inc. All rights reserved. [Certain portions of this work

were derived from copyrighted works of Roger G. Ibbotson and Rex Sinquefield.]

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EE-RM-PET-100 COMMENT 88
Table 11.9 Average Beta Values for Two Appliance Manufacturers

Manufacturer

___________________________

Beta

(1991-96)

A 0.94

B 0.90

Using CAPM to calculate the cost of equity, the following results are obtained for two

appliance manufacturers:

Manufacturer A: Cost of equity = (7.06-1.5) + 0.94 *

(8.5) = 13.55 %

[riskiess rate] beta *

[risk premium]

ManufacturerB: Costofequity=(7.06-1.5)+0.90 *(8.5)= 13.21%

[riskless rate] beta * [risk premium]

Adjusting for inflation (averaging 3.42% per year over the period 1990-96), the real cost of equity

for Manufacturer A is 10.13% and for Manufacturer B is 9.79%.

Weighted Average Cost of Capital (WACC) is defined as:

WACC = (1-tax rate) * cost of debt * [debt/(debt+equity)] +cost of equity * [equity/(debt+equity)]

Manufacturer A: WACC = [(1-0.465) * 5.00 * 0.38] + [10.13 *

(1-0.38)] = 7.30%

Manufacturer B: WACC = [(1-0.454) * 500 * 0.49] + [9.79 *

(1-0.49)] = 6.33%

The weighted average cost of capital calculated accounts for inflation, as real values of cost

of equity and debt are used in the calculation. In calculating WACC it is assumed that the two

manufacturers maintain the same capital structure in the future, i.e. future debt ratios are the same

as those in the past (see Table 11.7).

Independent estimates of the WACC were obtained from Ibbotson Associates, a company

that tracks the industry cost of capital for over 300 industries. Their analysis reports a WACC of

11.6% for the household appliance industry (represented by the SIC code 363) in the year 1997.

Adjusting for inflation (2.2% in 1997), the WACC net of inflation would be 9.4%. This analysis is

a compositeof eight companies: Whirlpool Corporation, Maytag Corporation, Royal Appliance

Manufacturing Company, National Presto Industries Inc., Rival Company, Health 0 Meter Products

Inc., Salton/Maxim Housewares Inc., and Windmere-Durable Holdings.

The July 1991 AHAM report used a cost of debt of 9.2% (bond rate) and a cost of equity of

13% based on average return on equity earned by the Standard and Poor's 500 Industrial Average in

11-14

EE-RM-PET-100 COMMENT 88
1990. Adjusting for tax effects and using a typical capital structure, the AHAM report calculated a

total cost of capital of 10% before inflation. Adjusting for inflation (which was 4.2% in 1991) the

AHAM report used 6% as the discount rate for conducting industry cash flow analysis. Table 9.10

compares the cost of debt, cost of equity, and WACC calculated for manufacturers A and B to the

household appliance industry composite values obtained from Ibbotson Associates and to the values

used in the AHAM 1991 report.

Table 11.10 Comparison of Financial Data

Item Manufacturer Manufacturer Thbotson Associates AHAM

A B Industry composite 1991 Report

_________________ _____________ _________________

(1997)

Cost of debt* 5.00 5.00 4.94

________________

5.20

Cost of equity 13.55 13.21 15.87 13.00

Capital structure 0.38 0.49 0.38 -

(Debt/Total

value)

WACC* 7.30 6.33 9.40 6.00

Beta 0.94 0.90 0.85 6

*Values have been adjusted for inflation.

11.2.3 GRIM Shipments

The Department chose three shipment scenarios for the final cash flow analysis. Stakeholders

consider these shipment scenarios to represent the full range of possible outcomes following a

clothes washer standard. The three shipment scenarios are described below:

High Price Elasticity - Assumes consumers will react negatively to higher prices on clothes

washers. This shipment scenario corresponds to the largest decrease in shipments because

of standards. This scenario is very close to the shipment scenario used in the earlier version

of the GRIM, which was reviewed by manufacturers.

2. Medium Price Elasticity - Assumes consumers will have a reaction to the higher prices of

less magnitude than the high price elasticity scenario.

3. Medium Price/Income Elasticity - Assumes the price a consumer will pay is inversely related

to their annual income. This scenario has the least impact on clothes washer shipments.

The following series of tables present the Base Case and Standard Case shipment forecasts

for the years 1999 through 2020 for the three shipment scenarios. Shipments are given for trial

standard levels presented in the NOPR.

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EE-RM-PET-100 COMMENT 88
Table 11.11 Clothes Washer Shipment Forecasts for the Base Case and Standard Case (High

Price Elasticity Shipment Scenario)

IClothes Washer Shipments (High Price Elas*icity Shipment Scenario) I

lase/ine Tria' Stc,ndrd Level I Trial Siendard Lewl 2 Trial Standard Level 4

ff ___________________

lmproi'e;nent 20% Eff Improvement = 25% Eff Improvement = 35%

-

Base Ca. iI4EF.iI7 MEFL02! MEFJ.089 ( MEFJ.257

Year V-Als H-Axi. V-4x1c H-Axis V-.ttvis H-Axis V-.4.th H-Axis

Shipment jthn,tent Shipment Shipment Shipment ShipiiienI Shipmenr Shipment

million u/lion in i//ice million million million million million

1999 6.28 0.45 6.28 1•1.45 6.28 0.45 6.28 0.45

6.32 0.49 6.32 0.49 6.32 0.49 6.32 0.49

6.34 0.53 6.34 0.53 6.34 0.53 6.34 0.53

2002 6.34 0.56 6.34 0.56 6.34 0.56 6.34 0.56

2003 6.32 0.59 6.32 0.59 6.32 0.59 6.32 0.59

2004 6.34 (1.63 6.21 0.62 5.83 0.58 0.00 5.62

2005 6.40 11.67 6.28 0.66 5.92 0.62 0.00 5.76

2006 6,49 0.72 6.38 (L7{) 6.03 0.67 0.00 5.94

2007 6.60 u.76 6.49 0.75 6.16 0.71 0.00 6.13

2008 6.70 0.81 6.59 11.80 6.28 0.76 0.00 6.33

2009 6.75 0.86 6.66 (L85 6.37 0.81 0.00 6.50

2010 6.82 0.91 6.73 0.89 6.47 0.86 0.00 6.71

2011 6,)0 0,96 6.82 0.94 0.59 0.91 0(10 6.93

2012 6.97 1.00 6.90 0.99 6.69 0.96 0.00 7.14

2013 7.02 1.05 6.95 .04 6.77 .02 0.00 7.31

2014 7.05 1.10 6.99 L0) 0.83 1.06 0.00 7.46 1

2015 7.08 1.14 7.02 [.13 6.87 1.11 0.00 7.57

2016 7.08 1.19 7.02 .17 6.85 [5 0.00 7.56

7.08 1.23 7.01 [.21 6.80 1.18 0.00 7.47

2018 7. 10 1,27 7.00 [.25 6.75 I .2 0.00 7.36

2019 7.13 1.32 7.03 .30 6.73 [.25 0.00 7.28

2020 7.18 --1.37 7.06 [.35 6.75 1.29 0.00 7.28

11-16

EE-RM-PET-100 COMMENT 88
Table 11.11 Clothes Washer Shipment Forecasts for the Base Case and Standard Case

(High Price Elasticity Shipment Scenario) (Continued)

IClothes Washer Shipments (High Price Elasticity Shipment Scenario)I

__________ Trial Standard Level 5 Trial Siwidaid i.evel Trial Standard Level 3

_________

Eff !mproltnwnt = 40% Eff Improvement 50% ElI Improvement = 21.4%/35.2%

________ MEF=I.362 MEFL 634 MEF=1.04/1.26

Year V-Axis H-Axis V-Axis Fl-iLis V-Axis H-Axis

_________ Shipment Shipment Shipment Shipmenm Shipment Shipment

million mi/lftiii nnlliun million ,l/lvi million

1999 6.28 0.45 6.28 0.45 6.28 0.45

2000 6.32 0.49 6.32 0.49 6.32 O.491

2001 6.34 0.53 6.34 0.53 6.34 0.53

2002 6.34 0.56 6.34 0.56 6.34 0.56

2003 6.32 0.59 6.32 0.59 6.32 0.59

2004 1)00 5,60 0.00 4.99 5.97 0.59

2005 0.00 5.74 0.00 5.13 6.04 0.63 J

2006 0.0(1 5.92 0.00 5.30 6.15 0.68

2007 (1.00 6.11 0,011 5.49 0.00 6.02

2008 0.00 6.31 0,01J 5,70 0.00 6.21

2009 0,00 6.49 0.00 5.90 0.01) 6.36

2010 (1.00 6.69 0.(1C) 6.14 0.00 6.53

2011 0.00 6.91 0.00 6.39 0.00 6.73

2012 0,00 7.12 0.00 6.64 0.00 6.92

2013 0.00 7.30 0.00 6.84 0.00 7.12

2014 0.00 7.44 0.00 7.02 0.00 7.29

2015 0.00 7.56 0.00 7.16 0.00 7.45

2016 0.00 7.55 0.00 7.15 0.00 7.54

2017 0.00 7.46 0.00 7.03 0.00 7.58

2018 0.01) 7.34 0.00 6.84 0.00 7.62

2019 0.00 7.26 0.00 6.69 0.00 - 7.61

2020 0.00 7.26 0.011 6.63 0.00 7.58

In the revised NES and shipments analysis, operating costs along with the different model

parameters and assumptions affect the base case shipments projection. The baseline shipments differ

because of the shipment scenario elasticities.

Tables 11.11 through 11.13 illustrate the shipment forecasts. For most efficiency levels there

is a drop in shipments beginning at the standard year (2004), with an increasingly negative impact

on sales at the more-stringent-standard levels. The medium price/income elasticity scenario is

associated with a less negative impact on sales in the year the standard is introduced than the high

price elasticity scenario. Figure 11.2 shows the magnitude of the shipment scenarios for the two-tier

standard. Notice the two dips, one beginning in 2004, and the other 2007, resulting from the two

standard dates. The shipment forecasts of the other standard scenarios behave in the same manner

as Figure 11.2.

11-17

EE-RM-PET-100 COMMENT 88
Table 11.12 Clothes Washer Shipment Forecasts for the Base Case and Standard Case

(Medium Price/Income Elasticity Shipment Scenario)

'Clothes Washer Shipments (Medium Puce/Income Elasticity Scenario) I

_______

Trial Standard Lere/l Trial Slandard l.,eve( 2 Trial Standard Level 4

_______

___________________

__________________

Eff hnjnoiemen 20% Eff Iinproiemenl 25% Eff Improvement =

______

Bnse Case MEF 817 MEF 1.02) ME11. 089 MEFJ.257

Year V-4xis H-Axi. V-Axis il-Axis' V-Axis ti-Axis V-Axis

_______

Shipment Shipment pmeni jpmenr ,,,pment Shipment Shipment

mi//ion ,niI/Thn iI//on milhioi /17/i/ton mU/Tho ii/lccm

____________

1999 6.36 0.4 6.36 0.46 6.36 0.46 6.36 Year

2000 6.39 0.40 6.39 H.49 6.39 0.49 6.39 0.49

2001 6.40 0.53 6.40 0.53 6.40 0.53 6.40 0.53

2002 6.38 0.56 6.38 0.56 6.38 0.56 6.38 0.56

2003 6.34 0.59 6.34 0.59 6.34 0.59 6.34 0.59

2004 6.32 0.63 6.32 0.63 6.29 0.62 0.00 6.63

2005 6.36 0.67 6.35 0.67 6.33 0.66 0.00 6.73

2006 ô.44 0.7l 6.43 0.71 6.4 I 0.71 0.00 6.87

2007 6.53 0.76 6.53 0.76 6.51 0.75 0,00 7.04

2008 6.64 0.81 6.64 0.81 6.62 0.80 0.00 7.21

2009 6.71 0.85 b.71 (1.85 (,.70 0.85 0.00 7.36

2010 6.81 0.90 6.81 0.90 6.80 0.90 0.00 7.54

2011 6.91 0.96 6.91 0.96 6.90 0.96 0.00 7.72

2012 7.01 1.01 7.01 I .01 7.00 I (1 I 0.01) 7.90

2013 7.08 1.06 708 1.06 7.08 1.06 0.01) 8.04

2014 7.12 1.11 7.12 1.11 7J2 1.11 0.00 8.15

2015 7.14 1.15 7.14 1.15 7.14 1.15 0.01) 8.23

2016 7.14 1.20 7.14 1.2.0 7.15 1.20 0.00 8.26

2017 7.14 1.24 7.14 1.24 7.[4 1.24 0.00 8.26

2018 7.14 1.28 7.14 1.2$ 7.14 1.28 0.00 8.27

2019 7.18 1.33 7.18 1.33 7.18 .33 0.00 8.32

2020 7.22 .38 7.22 1.38 7.22 1.38 0.00 8.40

11-18

EE-RM-PET-100 COMMENT 88
Table 11.12 Clothes Washer Shipment Forecasts for the Base Case and Standard Case

(Medium Price/Income Elasticity Shinment Scenario) (Continued)

'Clothes Washer Shipments IMedium Price/Income Elasticity Scenario)

Trial S1zudard Le'1 5 Trial Standard Level6 Trial Standard Level 3 __________

________

EJf Improvement 40% _±/7 bnpravement 50% Eff Improvement 2l.4%/35.2%

i'iEF=1.3i52 131EF-1J34 MEF=1.09/1.26 ________

Year V-'Axis II -.4 xis V-Avis it-Axi V-Axis H-Axis

__________

Shipment Shipweni Sinjrn:ent Shipmezt Shipmenl Shipment

pn//um rflilliQH mI//,orF ,ne//umfl il/fun million

1999 t'.36 0.46 6.36 0.46 6.36 0.46

2000 639 0.49 6.39 0.49 6.39 0.49

2001 6.40 0,53 6,40 0.53 6.40 0.53

2002 6.38 0.56 6.38 0.56 6.38 0.56

2003 6.34 0.59 6.34 0.59 6.34 0.59

2004 0.00 6.62 0.00 6.44 6.19 0.61

2005 0.00 6.72 0.00 6.54 6.23 0.65

2006 0.00 6.86 0.00 6.69 6.32 0.70

2007 p.00 7.03 0.00 6.86 0.00 7.01

2008 0.00 7.21 0.00 7.05 0.00 7.18

2009 11.00 7.35 0.00 7.21 0.{)0 7.33

2010 11.00 7.53 0.00 7.40 0.00 7.51

2011 0.00 7.71 0.00 7.59 0.00 7.68

2012 0.00 7.89 0.00 7.78 0.00 - 7.86

2013 0.00 8.03 0.00 7.94 0.00 8.01

2014 0.00 8.15 0.00 8.06 0.00 8.12

2015 0.00 8.23 0.00 8.14 0.00 8.21

2016 0.00 8.26 0.00 8.16 0.00 8.26

2017 0.00 8.25 0.00 8.14 0.00 8.29

2018 100 8.27 0.00 8.13 0.00 8.33

2019 0.u0 8.32 0.00 8.16 0.00 8.39

2020 0.00 8.40 0.00 8.23 0.00 8.45

11-19

EE-RM-PET-100 COMMENT 88
Table 11.13 Clothes Washer Shipment Forecasts for the Base and Standard Case (Medium

Price Elasticity Shipment Scenario)

Clothes Washer Shipments (Medium Price Elasticity Ship inent Scenario)!

______ Bas'eli,ze Triul Slaudi,r1 Let'el I Trial Standard Level 2 Trial Standard Level 4

______ __________________ Eff Improvement 20% / Jmproiement 25% Eff Improvement = 35%

_____ Bute Cu&e ________ MEFL 021 MEF=1.089 MEFJ.257

Year L..Axix H-4xi, H-.4x1,%' V-Axi. H-.4xix

_________

Shi'pueir/ Shi!pnrent SIFiJmL'FlI Sliipme;it JHdn1 S)'upinenI Shi/met,l

iii/l/ieti mi/f/on mi/finn n///ion: mill/un n61/ion mi/lion

____________

1999 6.33 0.46 .33 0.46 6.33 0.46 6.33 Year

2000 6.35 0.49 6.35 0.49 6,35 0.49 6.35 0.49

2001 6.35 0.53 6.35 0.53 6.35 0.53 6.35 0.53

2002 33 0.56 6.33 0.56 6.33 0.56 6.33 - 0.56

2003 6.30 0.59 6.30 0.59 6.30 0.59 6.30 0.59

2004 6.29 0.62 6.25 0.62 6.11 0.61 0.00 6.27

2005 6.33 0.66 6.29 0.66 6.Ib 0.65 0.00 6.38

2006 6.41 0.71 6.38 0.70 6,25 0,69 0.00 6.53 1

2007 6.51 0.75 6.47 0.75 6.36 0,74 0.00 6.69

2008 6.60 0.80 6.57 0.80 6.47 0.79 0.00 6.87

2009 6.67 0.85 6.64 0.84 6.54 0,83 0.00 7.02

2010 6.75 1)90 6.72 (1 89 6.64 0.88 0.00 7.19

2011 o.84 0.95 o.82 0.94 6.74 0.93 0.00 7.38

2012 6,92 1.00 6.90 0.99 6.83 0.99 0,00

-

7.55

2013 6.98 1.05 6.96 I .04 6.90 1.03 0.00 7.69

2014 7.01 1.09 6.99 1.09 6.94 1.08 0.00 7.80

2015 7.02 1.13 7.01) 1.13 6.96 1.12 0.00 7.88

2016 7.02 1.18 7.00 1.17 6.95 1.16 0.00 7.88

2017 7.01 1.21 6.99 1.21 6.92 1.20 0.00 7.84

2018 7.02 1.26 6.99 1.25 6.90 1.24 0.00 7.80

2019 7.04 1.30 701 1.30 692 1.28 0.00 7.81 -

2020 7.08 1.13 705 [.

________

3 ____________

7.86

11-20

EE-RM-PET-100 COMMENT 88
Table 11.13 Clothes Washer Shipment Forecasts for the Base and Standard Case (Medium

Price Elasticity Shipment Scenario) (Continued)

'Clothes Washer Shipments - (Medium Price Elasticity S hipment Scenario)

Trial Standard Level 5 Trial Standard Level 6 Trial Standard Level 3 _____

_____

Eff Improvement = 40% Eff Improvement = 50% Eff Improvement = 21.4%/35.2%

____ MEF=1.257 MEF=i 634 MEF=1.09/1/26

Year V-Axis H-Axis V-Axis H-Axis V-Axis H-Axis

Shipment Shipment Shipment Shipment Shipment Shipment

____

million million million million million million _____

1999 6.33 0.46 6.33 0.46 6.33 0.46

2000 6.35 0.49 6.35 0.49 6.35 0.49

2001 6.35 0.53 6.35 0.53 6.35 0.53

2002 6.33 0.56 6.33 0.56 6.33 0.56

2003 6.30 0.59 6.30 0.59 6.30 0.59

2004 0.00 6.26 0.00 5.93 6.08 0.60

2005 0.00 6.37 0.00 6.05 6.13 0.64

2006 0.00 6.52 0.00 6.20 6.22 0.69

2007 0.00 6.68 0.00 6.38 000 6.63

2008 0.00 6.86 0.00 6.56 0.00 6.81

2009 0.00 7.01 0.00 6.72 0.00 6.95

2010 0.00 7.18 0.00 6.92 000 7.11

2011 0.00 7.37 0.00 7.12 0.00 7.29

2012 0.00 7.55 0.00 7.32 0.00 7.46

2013 0.00 7.69 0.00 7.48 000 7.61

2014 0.00 7.79 0.00 7.60 0.00 7.73

2015 0.00 7.87 u.00 7.69 0.00 7.83

2016 0.00 7.87 0.00 7.68 0.00 7.88

2017 0.00 7.83 0.00 7,60 0.00 7.90

2018 0.00 7.79 0.00 7.52 0,00 7.93

2019 0.00 7 80 0 00 7.48 0 00 7.95

2020 0.00 7.84 0.00 1 7.50_ I 0.00 7.98

11-21

EE-RM-PET-100 COMMENT 88
Clothes Washer Shipments Forecasts

9.00

7.50 _ _

Year

-S---Base: High P Elasticity -s--Base: Med P Elasticity ----Base: Med P/I Elasticity

---2-tier Standard: High P Elasticity -*-2-tier Standard: MedP Elasticity ----2-tier Standard: Med P/I Elasticity

Figure 11.2 Clothes Washer Shipment Forecasts for Base Case and the Negotiated Standard

Level

11-22

EE-RM-PET-100 COMMENT 88
Table 11.14 provides the percent decrease between the base and standard year shipments for

2004, 2009, and 2007 (for the two-tier efficiency standard).

Table 11.14 Percentage Decreases in Shipments

Trial

Standard

Level

High Price Elasticity

Shipment Scenario

Medium Price Elasticity

Shipment Scenario

Medium P/I Elasticity

Shipment Scenario

2004

(% decrease)

2009

(% decrease)

2004

(% decrease)

2009

(% decrease)

2004

(% decrease)

2009

(% decrease)

1 2.0 1.4 0.6 1.4 1.1 0.0

2 8.0 5.7 209 0.9 0.6 0.2

3 5.8/18.3 16.4 3.4/8.6 7.6 2.2/3.9 3.1

4 19.3 14.6 9.3 6.7 4.6 2.7

5 19.6 14.8 9.5 6.8 4.7 2.8

6 28.4 22.5 14.2 10.6 7.4 4.7

Table 11.14 shows the effects of the standards in the standard year and 5 years following the

standard year. Following an initial decline in shipments in the year the standard is introduced

(2004), shipments gradually start recovering to the baseline shipment forecasts. A standard level

1 (MEF= 1.021) using the medium P/I elasticity shipment scenario has the least impact on shipments.

During the interviews, manufacturers were asked for their reactions to the high-price

elasticity shipment forecast and invited to contrast them to their own expected product shipments

with and without new energy-efficiency standards. The vast majority of manufacturers commented

that the shipment forecasts appeared reasonable. They were particularly supportive of the "shape"

of the curves-a sharp drop in the standard year followed by a partial recovery in later years. They

expressed the view that short-term effects were explained by the increased proportion of consumers

electing to repair washers instead of replacing them in the event of a breakdown. Eventually, the

"extended-life" washers would need to be replaced, and the market would equilibrate at a new,

higher, clothes washer average stock age.

The magnitude of the projected drop in shipments was at the higher end of what

manufacturers expected. All believed that drops in shipments of the magnitudes the Department

predicts would have devastating effects on the industry.

Offering a contrary view, one manufacturer believed that over time shipments of H-axis

washers would return to current levels, based on the assumption that the lifetime of H-axis washers

is shorter than for V-axis washers, meaning that over time consumers would have no option but to

replace their washers.

11-23

EE-RM-PET-100 COMMENT 88
11.2.3.1 Impact of New Energy-Efficiency Standards for Clothes Washers on Export

Sales

Export sales are not included in the shipment forecasts shown in Tables 11.11 through 11.14

and in Figure 11.2. The shipment forecasts developed for the NES include only clothes washers that

are being used domestically. The NES spreadsheet calculates the national energy savings; hence, the

shipments used in this spreadsheet include clothes washers that are:

manufactured in the United States for the domestic market

imported for use in the domestic market

Export and import statistics for the United States (U.S.) clothes washer industry, obtained

from the AHAM Fact Book, are presented in Table 11.15. The AHAM Fact Book reports shipments

under three categories: (1) industry unit shipments (including shipments for the U.S. market whether

imported or domestically produced, and export shipments); (2) exports; and (3) imports. (Export and

import data in the AHAM Fact Book is obtained from the Department of Commerce's EMS 45 and

IM 145 reports, respectively.)

Table 11.15 Annual Shipments of Clothes Washers from 1990 through 1996 (million)

Shipments 1990 1991 1992 1993 1994 1995 1996

Industry unit

shipments

6.192

_________

6.197

_____

6.515

_______

6.793

________

7.035 6.901 7.129

Export 0.601 0.690 0.756 0.764

_______

0.868

________

0.801

____________

0.884

Import 0.044 0.035 0.077 0.132 0.100 0.105 0.145

Source: AHAM Fact Book

As can be seen in Table 11.15, export sales accounted for approximately 12.5 percent of

industry unit shipments in 1996.

Most manufacturers that were interviewed were adamant that export sales would be

significantly hurt by the introduction of new energy.efficiency standards. They would become less

competitive internationally if the new standards forced them to completely retool, thereby incurring

additional costs which be would be passed on through higher prices.

Manufacturers maintain that, for the purposes of the MIA, retooling costs need to be applied

to export volumes as well as to domestic volumes. Since exports represent only a fraction of total

sales, manufacturers believe it will not be feasible to continue producing small quantities of older

models solely for export as the volumes would not warrant the commitment of dedicated resources.

Furthermore, manufacturers believe it is important that the impact of a decline in the export volume

11-24

EE-RM-PET-100 COMMENT 88
of clothes washers also be factored into the industry shipment calculations, as any decline in

international competitiveness would reduce industry volumes.

To account for the impact on both domestic and export sales, DOE adjusted the shipment

forecasts from the NES spreadsheet for the MIA. The shipment information for 1996 was used for

calibration. The calibration process is summarized in Table 11.16.

Table 11.16 Calculation of Calibration Factor for GRIM Shipment Forecast

Shipments(million) AHAM Fact DOE Calibration

Book Shipment Factor (applied to

Forecast DOE Shipment

Forecast)

Industry unit shipments* 7.129

Export 0.884

Import 0.145

Clothes washers used domestically 6.245 6.120

Clothes washers produced by U.S. 6.984 1.141

manufacturers (domestic + export)

____________ _______________

(=6.984/6.120)

*Jncludes 1996 shipments for the U.S. market whether imported or domestically produced, and export shipments

Source: AHAM Fact Book

11.2.4 Manufacturing Costs

11.2.4.1 Baseline Industry Cost Structure

The GRIM developed for the NOPR MIA analysis considers V-axis and H-axis clothes

washer segments separately. The baseline cost of an H-axis washer was characterized using the

incremental cost data representing a 35 percent efficiency improvement level (standard level 4) as

submitted by AHAM, i.e., the Base Case H-axis washer is assumed to be an H-axis machine

representing a 35 percent efficiency improvement over the baseline V-axis machine (MEF=0. 817).

H-axis costs are equal to the Base Case V-axis costs plus incremental costs for a 35 percent

efficiency-improvement level.

11-25

EE-RM-PET-100 COMMENT 88
Definition of H-axis cost assumpitons used in the GRIM analysis

I I-Ask M eriii (o Baseline V-axis material cost + Incremental material cost for the

35percent efficiency level

_________________________

1.1.-Axis Labor CsL Baseline V-axis labor cost + Incremental labor cost for the 35 percent

efficiency level

11-Axis vcrhead Lo Baseline V-axis overhead cost + Incremental overhead cost for the 35

percent efficiency level

H-Axis De1ii'ciUiui Baseline V-axis depreciation cost + (Incremental capital conversion cost

per unit for the 35 percent efficiency level I useful life of the fixed

investment)

Publicly available information suggests that currently sold H-axis washers are, on average,

more profitable than the baseline V-axis washers characterized in GRIM. To reflect this, the GRIM

assumes a profit of 10 percent before tax for the H-axis segment, compared to 6.2 percent for the

V-axis market. This profit level likely understates the current profitability of H-axis models but

accounts for the expected increased competition in this segment in future years.

The baseline H-axis washer price was estimated using the baseline H-axis washer costs and

applying the markup needed to arrive at a 10 percent profit-before-tax value. This corresponds to a

markup of 1.5 over the incremental full production cost at the 35 percent efficiency level (standard

level 4). Adding this amount to the baseline V-axis price of $285.90 results in a Base Case H-axis

washer price of $478.16.

Definition of H-axis price assumption used in GRIM analysis

Il-Axis Marinthuii-cr Price Baseline V-axis manufacturer price + Mark-up x (Incremental full

production cost per unit)*

: Jne&rncnLI full .ideon Incremental material + incremental labor + incremental overhead +

cus per wilt capital conversion + design conversion

Table 11.17 summarizes the revised cost structures for baseline V-axis and H-axis washers.

11-26

EE-RM-PET-100 COMMENT 88
Table 11.17 Industry Average Baseline Cost Structure

Paiaineters J V-Axis Washers TT-Ais Whrs

As a % of V-axis baseline $ per unit Incr. Cost over

V-axis

$ per unit

Manufacturer price 100% $285.90 $478.16

Manufacturing Cost

Material 52.0% $148.70 $86.73 $235.43

Labor 10.2% $29.30 $10.94 $40.24

Overhead 8.3% $23.45 $7.78 $31.23

Depreciation 3.5% $10.01 $22.72 $27.70

SG&A 18.0% $51.46 $86.07

R&D 1.8% $5.15 $8.61

Profitbeforetax 6.2% $17.73 $48.88

Tax rate 42.8%

Profit after tax 3.6% $10.14 $27.96

11.3 IMPACTS ON CASH FLOW

Manufacturers were invited to discuss their interpretations of the cash flow analysis results

for the various potential standards levels and comment on the implications of the results for the

future of their business.

11.3.1 Base Case NPV

Using the shipment information in Section 11.2.3 and the baseline cost structure described

in Section 11.2.4, Base Case cash flow estimates were constructed for the U.S. clothes washer

industry. The GR1IVI spreadsheet models cash flows for the V-axis and H-axis market segments

separately in the Base Case. The baseline manufacturer price and cost structure summarized in Table

11.17 was used to develop cash flow estimates and hence the value of the V-axis and H-axis washer

segments. The values of these two segments were then summed to arrive at the overall industry

value in the Base Case.

The assumptions used to arrive at the Base Case NPV along with the Base Case cash flow

spreadsheet outputs are presented in Appendix P, Exhibits 1 through 5, for the medium price

11-27

EE-RM-PET-100 COMMENT 88
shipment elasticity scenario. Based on these assumptions, Base Case clothes washer industry values

(NPV) of$ 1,445.8, $1,439.1, $1,452.0 million were calculated for the high price, medium price, and

medium price/income elasticity shipment scenarios respectively.

11.3.2 Standard Case NPV

The Department used the interviews to understand each manufacturers' ability to pass through

its incremental costs at the various standards levels. Some manufacturers provided us with their cash

flow analysis using the GRIM spreadsheet while others provided information on manufacturing

costs, markups, cost pass-through assumptions, prices, and expected shipments, which were then

used to develop their standards-induced changes in NPV. These manufacturer estimates or implied

changes in NPV were aggregated to arrive at the change in industry NPV at each of the potential

standards levels.

The cash flows incorporate each manufacturer's forecasts of the competitive dynamics set in

motion by potential new standards at all possible efficiency levels. A partial list of considerations

includes:

• The technology status of existing product offerings as it relates to the cost-efficiency

relationship

• The status of manufacturing technology, including an assessment of conversion and

restructuring costs

• Likely product offerings at each efficiency level (e.g., V-axis, H-axis)

• Consumer demand for product features and its implications for trade-offs between

manufacturing cost and consumer utility

• Patent restrictions on design options

• Brand equity

• Availability of technical and financial resources

• Manufacturing versus sourcing strategies

• Company cost structure and ability to pass on fixed (and sometimes even variable) costs

11.3.2.1 Impact of Standards on Manufacturer Prices and Profit Margins

During the interviews, manufacturers were asked to explain differences, if any, between their

expected product prices with and without new energy-efficiency standards and those presented in

the sample results for the industry as a whole. Manufacturers discussed their assumptions

concerning gross and net margins (as a percent of revenue) pre- and post-standards, and causes for

any change. Finally, DOE probed as to what mark-ups manufacturers expected to obtain at the

various efficiency levels and what effects these new prices might have on their market share.

At higher standards manufacturers stated that, based partially on the shipment forecasts, there

will definitely be an impact on profit margins, as the clothes washer business is volume-based.

Decreased volumes will erode profit margins for manufacturers due to increased fixed and capital

costs. Moreover, manufacturers felt that because the clothes washer industry is volume-based, any

11-28

EE-RM-PET-100 COMMENT 88
drop in volume is likely to result in price decreases as the larger manufacturers try to regain their

volumes.

An important point raised in the discussions with some manufacturers is that historically the

appliance industry has not been an industry where one can recuperate standard-induced capital costs

in prices. Over time, industry margins have actually decreased as large manufacturers, who need

certain volumes to operate efficiently, are willing to reduce margins to increase volume. This has

considerable significance when evaluating possible scenarios and the impacts on manufacturers,

especially for smaller manufacturers who would be particularly disadvantaged.

The profit margin impact would be minimized if manufacturers could produce

higher-efficiency products at small incremental costs without lowering product utility. However, as

manufacturers believe this is not possible, and they cannot significantly pass on their fixed costs

(prevalently because customers are unwilling to pay higher prices for higher-efficiency products),

profit margins will likely erode or be destroyed. The industry's costs will increase and, while the

price of an average washer will also increase, not all costs will be passed on to consumers.

Manufacturers expect that those among them with market power will continue to set prices and the

remaining members of the industry will adapt and accept any resulting impacts on profitability if they

wish to remain in the market.

11.3.2.2 Impact of New Energy-Efficiency Standards on Manufacturing Costs

The majority of manufacturers maintained that it is not possible to attain a greater than 20

percent improvement (standard level 1) without significantly affecting consumer utility or incurring

large cost increases.

Most manufacturers stated that to achieve standard levels 1 and 2 there is no option but to

retool their existing V-axis washer platforms. Based on the capabilities of their current platforms,

some manufacturers reported their first significant investment thresholds at standard level 1 (20%

improvement) while all others reported it at standard level 2 (25% improvement). For most clothes

washers that are produced, spin speeds are already at approximately 650-700 rpm and to go higher

would require retooling for new platforms as machine stability would be affected. However,

manufacturers indicated that improvements of up to 15 percent above baseline (MEF=0 .961) maybe

achieved by experimenting with design options (e.g., increased spin speeds and cycle time).

The manufacturer responses are consistent with the AHAM cost data, which clearly shows

a step jump in investment levels beyond the 15 percent efficiency level (MEF= 0.961) -at the 15

percent level the total industry conversion costs are $36.08 million, compared to conversion costs

of $221.9 million and $689.2 million at the 20 percent (MEF=1.021) and 25 percent (MEF=1.089)

efficiency levels, respectively. Manufacturers estimate that these retooling costs would be in the

vicinity of $1 00-s 120 per annual unit of production. We in fact found a significant relationship

between capital investment and production volume, which is detailed in Section 11.6 of this report.

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Some manufacturers stated that going above 15 percent (to 20 percent) without retooling

could be achieved through various temperature- and water-control measures (such as rinse cycle, spin

speed, or spin time), although even these would require incurring significant incremental cost and

could affect consumer utility to differing degrees. Adaptive fill or control measures would also not

be viable as they would have too great an impact on consumer prices. As shown by the focus group

results in the consumer studies, some of the top consumer concerns are price, load-size options,

durability, water-temperature options, wash-cycle options, etc., all of which may be affected by

changes in the standards. The only top- 10 rated attributes that will clearly be improved by the new

standards are energy and water costs.

Manufacturers believe the rise in aggregate industry costs is significant and will lead to lower

customer demand for clothes washers. But perhaps even more important to their own bottom line

are the differential costs among manufacturers of achieving high efficiency levels, as well as relative

expertise in the new technology. As such, the cash flows include each manufacturer's understanding

of its own position vis-à-vis other manufacturers on these issues.

Most manufacturers stated that at standard level 4 they would have to build H-axis washers

to comply with the regulations. Thus, the few manufacturers that do have an expertise in H-axis

technology are likely to be competitive at the higher standard levels. At the same time, some

manufacturers felt it was possible that one or more of their competitors could produce a

high-efficiency V-axis washer that met standard level 4 (35 percent improvement). Such a scenario

could significantly alter the industry's competitive dynamics due to the possible price and consumer

utility advantages of a V-axis machine over an H-axis washer.

Some firms were concerned that patent restrictions could prevent them from achieving

standard level 2 (25 percent improvement in efficiency) using V-axis designs. Consequently, they

believe this level of improvement can only be achieved by moving to H-axis technology. For them,

the capital investment required for a 25 percent improvement would thus be no different from that

required for a 35 percent improvement(standard level 4).

Manufacturers were asked if they could provide some insight into the variations of costs at

each efficiency level. Some manufacturers indicated that, for new standards within V-axis

technology, the range in costs observed in the industry submittal may reflect different technology

jump points. For instance, existing suspension systems may allow some manufacturers to increase

spin speed. For others, increases in efficiency may be achieved with adjustments in other

components.

U.S. manufacturers have been producing V-axis washers for almost 40 years and have

reduced their costs and optimized their designs to an extent that there isn't much variation among

different manufacturers. In contrast, H-axis washers are relatively new in the U.S.. Few of the

manufacturers have sufficient manufacturing expertise in that technology; thus the range of costs is

greater for H-axis clothes washers. Even manufacturers that have European divisions that produce

H-axis machines find that these machines have small capacities that do not scale-up easily for the

U.S. market.

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