APPENDIX 10-D. NATIONAL NET PRESENT VALUE OF CONSUMER 

BENEFITS USING ALTERNATIVE PRODUCT PRICE FORECASTS

TABLE OF CONTENTS

10-D.1 INTRODUCTION .....................................................................................................10-D-1

10-D.2 ALTERNATIVE COMMERCIAL CLOTHES WASHER PRICE TREND 

SCENARIOS .............................................................................................................10-D-1

10-D.2.1 Exponential Fit Approach (Increasing Price Scenario) .................................10-D-2

10-D.2.2 Annual Energy Outlook 2014 Price Forecast ( Decreasing Price Scenario) .10-D-3

10-D.2.3 Summary........................................................................................................10-D-3

10-D.3 NET PRESENT VALUE RESULTS USING ALTERNATIVE PRODUCT 

PRICE TRENDS........................................................................................................10-D-4

LIST OF TABLES

Table 10-D.2.1 Price Trend Sensitivities..........................................................................10-D-3

Table 10-D.3.1 NPV Using Price Trend, Discounted at 3 Percent, for Commercial 

Clothes Washers (billion 2013$) .............................................................10-D-4

Table 10-D.3.2 NPV Using Price Trend, Discounted at 7 Percent, for Commercial 

Clothes Washers (billion 2013$) .............................................................10-D-5

LIST OF FIGURES

Figure 10-D.2.1 Deflated Commercial Laundry and Drycleaning Machinery PPI versus 

Year, with Exponential Fit from 1982 to 2013 .........................................10-D-2

Figure 10-D.2.2 Commercial Clothes Washer Price Forecast Indexes ...............................10-D-4

10-D-1
APPENDIX 10-D. NATIONAL NET PRESENT VALUE OF CONSUMER 

BENEFITS USING ALTERNATIVE PRODUCT PRICE FORECASTS

10-D.1 INTRODUCTION

DOE used a constant price assumption for commercial clothes washers’ default price 

projection in the NIA described in Chapter 10. In order to investigate the impact of different 

product price forecasts on the consumer net present value (NPV) for the considered TSLs for 

commercial clothes washers, DOE also considered two alternative price trends for a sensitivity 

analysis. This appendix describes the alternative price trends and compares NPV results for these 

scenarios with the default price projection. 

In recent rulemakings for several residential products, DOE has used the experience 

curve method to derive learning rates to forecast future prices. In the experience curve method, 

the real cost of production is related to the cumulative production, or experience, with a 

manufactured product. That experience usually is measured in terms of cumulative production. 

As experience (production) accumulates, the cost of producing the next unit decreases. The 

percentage reduction in cost that occurs with each doubling of cumulative production is known 

as the learning rate. A recent report from Lawrence Berkeley National Laboratory by Taylor and 

Fujita provides an overview of some of the major findings of the academic literature on learning 

curves, and describes the application of a component-based learning curve approach (by the 

Environmental Protection Agency and the National Highway Transportation Safety 

Administration) and a price-based learning curve approach (by DOE) in regulatory impact 

assessment. [1]

For some commercial and industrial products, there are insufficient data to apply a pricebased learning curve approach, particularly with respect to cumulative production. In such cases, 

DOE used a constant price assumption for the default price projection in the NIA, but made use 

of price indexes that are relevant for the product in question to derive alternative price trends for 

sensitivity analysis.a

 

10-D.2 ALTERNATIVE COMMERCIAL CLOTHES WASHER PRICE 

TREND SCENARIOS

DOE considered two alternative price trends for a sensitivity analysis. One of these used 

an exponential fit on the deflated Producer Price Index (PPI) for commercial laundry and 

drycleaning machinery, and the other is based on the “deflator— industrial equipment” that was 

forecasted for EIA’s Annual Energy Outlook 2014(AEO2014). 

a See appendix 10C of the final rule TSD for commercial clothes washers. 

10-D-1

 
10-D.2.1 Exponential Fit Approach (Increasing Price Scenario)

For the increasing price scenario, DOE used an inflation-adjusted commercial laundry 

and drycleaning machinery Producer Price Index (PPI) spanning the time period of 1982-2013 

from the Bureau of Labor Statistics’ (BLS) to fit an exponential model with year as the 

explanatory variable.b The PPI data reflect nominal prices, adjusted for product quality changes. 

An inflation-adjusted (deflated) price index for commercial laundry and dry cleaning machinery

was calculated by dividing the PPI series by the Gross Domestic Product Chained Price Index. In 

this case, the exponential function takes the form of:

YY = aa ∙ eebbbb 

where Y is the commercial clothes washer price index, X is the time variable, a is the constant 

and b is the slope parameter of the time variable. 

To estimate these exponential parameters, a least-square fit was performed on the 

inflation-adjusted commercial laundry and dry cleaning machinery price index versus year from 

1982 to 2013. The fitted regresion is shown in Figure 10-D.2.1.

Figure 10-D.2.1 Deflated Commercial Laundry and Drycleaning Machinery 

PPI versus Year, with Exponential Fit from 1982 to 2013

The regression performed as an exponential trend line fit results in an R-square of 0.76, 

which indicates a decent fit to the data. The final estimated exponential function is:

YY = 3.49 × 10−5 ∙ ee0.0051 

b Series ID PCU3333183333182; <http://www.bls.gov/ppi/>

10-D-2

 
DOE then derived a price factor index for this scenario, renormalized with 2013 equal to 

1, to project prices in each future year in the analysis period considered in the NIA. The index 

value in a given year is a function of the exponential parameter and year.

10-D.2.2 Annual Energy Outlook 2014 Price Forecast (Decreasing Price Scenario)

DOE also examined a forecast based on the “deflator— industrial equipment” that was 

forecasted for AEO2014 out to 2040. AEO 2014 is the most current price trend projection that 

DOE acquired. This index is the most disaggregated category that includes commercial laundry 

and drycleaning machinery. To develop an inflation-adjusted index, DOE normalized the above 

index with the “chained price index—gross domestic product” forecasted for AEO2014, with 

2013 equal to 1. To extend the price index beyond 2040, DOE used the average annual price 

growth rate in 2031 to 2040. 

10-D.2.3 Summary

Table 10-D.2.1 shows the summary of the average annual rates of change for the product 

price index in each scenario. Figure 10-D.2.2 shows the resulting price trends under all scenarios.

Table 10-D.2.1 Price Trend Sensitivities

Sensitivity Price Trend Average Annual Rate 

of Change %

Medium (Default) Constant Price Projection 0.0

Decreasing Price 

Scenario

AEO2014-- “deflator— industrial equipment” -0.38

Increasing Price 

Scenario

Exponential Fit using PPI data from 1982 to 

2013 0.51

10-D-3
Figure 10-D.2.2 Commercial Clothes Washer Price Forecast Indexes

10-D.3 NET PRESENT VALUE RESULTS USING ALTERNATIVE 

PRODUCT PRICE TRENDS

This section presents the NPV results using the alternative product price forecast for each 

key product class. The results are only sensitive to the alternative product price forecasts for 

TSL3 and TSL4.

Table 10-D.3.1 NPV Using Price Trend, Discounted at 3 Percent, for Commercial 

Clothes Washers (billion 2013$)

Price Trend Product Class

Trial Standard Levels

TSL1 TSL 2 TSL 3 TSL 4

Default Top-loading 0.435 0.433 2.049 1.874

Front-loading 0.000 0.099 -0.115 -0.298

Decreasing Price Top-loading 0.435 0.433 2.055 1.880

Front-loading 0.000 0.099 -0.115 -0.295

Increasing Price Top-loading 0.435 0.433 2.038 1.862

Front-loading 0.000 0.099 -0.115 -0.303

10-D-4
Table 10-D.3.2 NPV Using Price Trend, Discounted at 7 Percent, for Commercial 

Clothes Washers (billion 2013$)

Price Trend Product Class

Trial Standard Levels

TSL1 TSL 2 TSL 3 TSL 4

Default Top-loading 0.202 0.201 0.919 0.838

Front-loading 0.000 0.042 -0.050 -0.128

Decreasing Price Top-loading 0.202 0.201 0.922 0.841

Front-loading 0.000 0.042 -0.050 -0.127

Increasing Price Top-loading 0.202 0.201 0.913 0.832

Front-loading 0.000 0.042 -0.050 -0.130

10-D-5
REFERENCE

1. Taylor, M. and K.S. Fujita, Accounting for Technological Change in Regulatory Impat 

Analyses: The Learning Curve Technique. 2013, Lawrence Berkeley National Laboratory

LBNL-6195E: Berkeley.

10-D-6