APPENDIX 10

- D. NATIONAL NET PRESENT VALUE OF CONSUMER BENEFITS USING ALT ERNATIVE PRODUCT PRI CE FORECAST S

TABLE OF CO NTENTS

10

- D.1 INTRODUCTION

................................ ................................ ................................ ..... 10

- D

- 1 10

- D.2 ALTERNATIVE COMMERCI AL CLOTHES WASHER PR ICE TREND SCEN ARIOS

................................ ................................ ................................ ............. 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 RE SULTS USIN G ALTERNATIVE PRODUC T 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-1APPENDIX 10

- D. NATIONAL NET PRESENT VALUE OF CONSUMER BENEFITS USING ALT ERNATIVE PRODUCT PRI CE FORECAST S

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 us ed the exper ience 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 t erms of cumulative production. A s experience (production) accumulates, the cost of prod ucing 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 fr om Lawrence Berkeley National Laboratory by Taylor and Fujita provides an overview of some of the major findings of the academi c 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 price

based 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 tre nds for sensitivity analysis. a

10

- D.2 ALTERNATI V E COMMERCIAL CLOTHES W ASHER 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 201 4 ( AEO201 4 )

.

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

. 10

- D

- 110

- 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 198 2

- 2013 from the Bureau of Labor Statistics’ (BLS) to fit an exponential model with year as the explanatory vari able. 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 ∙ ee bbbb

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 198 2 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 201 3
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

∙ ee 0

. 0051

b Series ID PCU3333183333182 ; < http://www.bls.gov/ppi/ > 10

- D

- 2DOE then derived a price factor index for this scenario, renormalized with 201 3 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 AEO201 4 out to 2040. AEO 201 4 is the most current price trend projection that DOE acquired. This index is the most disaggregat ed 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 AEO201 4 , with 2013 equal to 1

. To ex tend the price index beyond 2040 , DOE used the average annual price growth rate in 20 31 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 scen arios

.
Table 10

- D.2.1 Price Trend Sensitivities

Sensitivity Price Trend Average Annual R ate of C hange % 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

- 3Figure 10

- D.2

. 2 Commercial Clothes Washer Price Forecast Indexes

10

- D.3 NET PRESENT VALUE RE SULTS USING ALTERNAT IVE PRODUCT PRICE TREND S
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 forecast s 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

- 4Table 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

- 5REFERENCE

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