### 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 decreasing0.5percent 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

### 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

### Table 10.8 NESResults: oronosed rule(MEF =1.04 @ 2004 &MEF=1.26 @2007) Costand 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 

# uuuuIiU LI Ii U -2.0 0 -4.00 Figure 10.1 AnnualCostand Savings for the Proposed Clothes Washer

Rule 10-17

### 10.5 USER INSTRUCTIONS FOR NES/SHIPMENTS SPREADSHEET

Theclothes 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 aReset Base Casebutton 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 theReset 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

10-18

### 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 15-2T.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

### 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

### 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

### 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

RequirementsAre

### 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

.......................... 

### 11-56 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

### 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 forGRIM

### 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 DryerGRIM

............... 

### 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(35percent 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

### 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

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### 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

### 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 December14-15,1998. 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

### 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

### 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

### 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

## Cash

Figure 11.1 Using GRIM to Conduct the Cash Flow Analysis

TheGRIM 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

### 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.

11-6

### 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

### 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

### 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 3.51% (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

11-9

### 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
11-10

### 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 1997aFor 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. 11-11

### 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 around5%. 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% and5.0%,respectively. Based on arguments above, the Department used5%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.
11-12

### 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 of8.5%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.] 11-13

### 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 ofequity

=

### (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

### 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.

11-15

### Table 11.11 Clothes Washer Shipment Forecasts for the Base Case and Standard Case (High Price Elasticity Shipment Scenario) IClothes Washer Shipments (High PriceElas*icity Shipment Scenario) 

# I

lase/ine Tria'Stc,ndrd LevelI TrialSiendardLewl 2 Trial Standard Level 4

fflmproi'e;nent 20% EffImprovement=25% Eff Improvement=35%

___________________ BaseCa. iI4EF.iI7 MEFL02! MEFJ.089 

# ( ME FJ.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 ini//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

### 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 Level5 TrialSiwidaid 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

### 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 ElasticityScenario) 

# I

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

_______ ___________________

__________________ Effhnjnoiemen 20% Eff Iinproiemenl 25%EffImprovement=

______ Bnse Case MEF 817 MEF1.02) ME11. 089 ME FJ.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(1I 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

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### 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'15 TrialStandardLevel6 Trial Standard Level 3

__________ EJfImprovement 40% _±/7bnpravement 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 Sin jrn: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

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### Table 11.13 Clothes Washer Shipment Forecasts for the Base and Standard Case (Medium Price Elasticity Shipment Scenario) Clothes Washer Shipments (Medium PriceElasticityShipinentScenario)!

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

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

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### 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 Shipment 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

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### Clothes Washer Shipments Forecasts 900

.

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: MedP/IElasticity



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

Level

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### 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 MediumP/IElasticity 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 and5years 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.

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### 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

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### 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 a35percent 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 a35percent 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 a35percent efficiency-improvement level.

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### 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 the35percent 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 levelIuseful 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$285.90results in a Base Case H-axis washer price of $478.16. 

### Definition of H-axis price assumption used in GRIM analysis Il-AxisMarinthuii-crPrice 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

### 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 through5,for the medium price
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### 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
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### 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 approximately650-700rpm 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(35percent 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(25percent 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 a35percent 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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