APPENDIX 10

- B. NIA SENSITIVITY ANALYSIS FOR

ALTERNATIVE PRODUCT PRICE TREND SCENARIOS

TABLE OF CO NTENTS

10

- B.1 INTRODUCTION

................................ ................................ ................................ ............... 1

10

- B.2 ALTERNATIVE PTAC PRI CE TREND SCENARIOS

................................ ..................... 1

10

- B.2.1 Exponential Fit Approach (High Price Scenario)

................................ .................... 1

10

- B.2.2 Annual Energy Outlook 2013 Price Forecast (Low Price Scenario)

....................... 3

10

- B.2.3 Summary

................................ ................................ ................................ .................. 3

10

- B.3 NPV R ESULTS BY ALTERNATIV E PRICE TREND SCENAR IO

................................ 4

LIST OF TABLES

Table 10

- B.2.1 Price Trend Sensitivities

................................ ................................ .................... 3

Table 10

- B.3.1 Summary of Cumulative Net Present Value for PTAC and PTHP:
Decreasing Price Scenario (S even Percent Discount Rate)

............................... 4

Table 10

- B.3.2 Summary of Cumulative Net Present Value for PTAC and PTHP:

Decreasing Price Scenario (Three Percent Discount Rate)

................................ 5

Table 10

- B.3.3 Summary of Cumulative Net Present Value for PTACs and PTHPs:

Increasing Price Scena rio (Seven Percent Discount Rate)

................................ 5

Table 10

- B.3.4 Summary of Cumulative Net Present Value for PTACs and PTHPs:

Increasing Price S cenario (Three Percent Discount Rate)

................................ . 5

LIST OF FIGURES

Figure 10

- B.2.1 Relative Price of PTACs versus Year, with Exponential Fit

............................ 2
Figure 10

- B.2.2 PTAC Price Forecast Indexes

................................ ................................ ........... 4

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- iAPPENDIX 10

- B. NIA SENSITIVITY ANALYSIS FOR

ALTERNATIVE PRODUCT PRICE TREND SCENARIOS

10

- B.1 INTRODUCTION

The U.S. Department of Energy ( DOE ) used a constant price assumption for the default

forecast in the national impact analysis ( 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 trial standard levels ( T SLs ) for packaged terminal air conditioners ( PTAC s ) , DOE
also considered two alternative price trends for a sensi tivity analysis. This appendix describes the

alternative price trends and compares NPV results for these scenarios with the default forecast

.

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

curve method to derive lear ning 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.

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 from Lawrence Berkeley National Lab oratory 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 Nation al Highway Transportation Safety

Administration ) and a price

- based learning curve approach (by DOE) i n regulatory impact

assessment. 1

For some commercial and industrial equipment

, 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 forecast in the NIA , but made use of

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

sensitivity analysis. This approach was used for PTAC

.

10

- B.2 ALTERNATIVE PTAC PRICE TREND SCENARIOS

For PTAC

, DOE considered tw o alternative price trends for sensitivity analysis. One of

these used an exponential fit on the deflated Producer P rice I n dex (PPI) for all other

miscellaneous refrigeration and air

- conditioning equipments

, and the other is based on the

“ deflator

— industrial equipment ” that was forecasted for the U.S. Energy Information

Administration’s ( EIA’s ) Annual Energy Outlook 201 3 ( AEO201 3 )

.

10

- B.2.1 Exponential Fit Approach ( High Price Scenario )

For this scenario , DOE used an inflation

- adjusted all other miscellaneous refrigeration

and air

- conditioning equipment PPI from 2001

- 201 3 to fit an exponential model with year as the

explanatory variable. DOE obtained historical PPI data all other miscellaneous refrigeration and

air

- conditioning equipment spanning the time period 2001

- 201 3 from the Bureau of Labor

10

- B

- 1Statistics’ (BLS). a The PPI data reflect nominal prices, adjuste d for product quality changes. An

inflation

- adjusted (deflated) price index for all other miscellaneous refrigeration and air

conditioning equipment was calculated by dividing the PPI series by the Gross Domestic Product

Chained Price Index

. The deflated p rice index is now presented in 201 3 dollar values. In this

case, the exponential function takes the form of:

Y = a ∙ e bX

where Y is the all other miscellaneous refrigeration and air

- conditioning equipment 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 PTAC price index versus year from 2001 to 201 3 . See Figure 10

- B.2. 1

.

Figure 10

- B.2

. 1 Relative Price of PTAC s versus Year, with Exponential Fit

The regression performed as an exponential trend line fit results in an R

- square of 0. 75

, which indicates a mode r ate fit to the data. The final estimated exponential func t ion is:

Y = 8

. 12 × 10 (

− 13 )

∙ e 0

. 0138 X

a Series ID PCU3334153334159 ; http://www.bls.gov/ppi/

10

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- 2DOE then derived a price factor index for this scenari o , 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

- B.2.2 Annual Energy Outlook 201 3 Price Forecast ( Low Price Scenario )

DOE also examined a forecast based on the “chained price index

— industrial equipment”

that was forecasted for AEO 201 3 out to 2040. This index is the most disaggregated category that

includes PTAC s. To develop an inflation

- adjusted index, DOE normalized the above index with

the “chained price index

— gross domestic product” forecasted for AEO 201 3 . To extend the price

index beyond 2040, DOE used the average annual price growth rate in 2031 to 2040.

10

- B.2.3 Summary

Table 10

- B.2. 1 shows the summary of the average annual rates of changes for the product

price index in each scenario

. Figure 10

- B.2. 2 shows the resulting price trends.

Table 10

- B.2

. 1 Price Trend Sensitivities

Sensitivity Price Trend Average Annual rate of

change %

Medium (Default) Constant Price Projection 0.0 0

Low Price Scenario AEO201 3

-- “ chained price index

— industrial equipment ” - 0.25

High Price Scenario Exponential Fit using data from 2001 to

201 3 1. 39

10

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- 3Figure 10

- B.2

. 2 PTAC Price Forecast Index es

10

- B.3 NPV RESULTS BY ALTERNATIVE PRICE TREND SCENARIO

Table 10

- B.3

. 1 Summary of Cumulative Net Present Value for PTAC and PTHP:

Decreasing Price Scenario (Seven Percent Discount Rate)

Equipment Class Net Present Value (Billion 2012$)

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

PTAC < 7,000 Btu /h 0.0

- 0.4

- 1.3

- 2.2

- 2.4

PTAC 7,000

- 15,000 Btu /h 0.2

- 1.6

- 7.5

- 15.5

- 17.5

PTAC > 15,000 Btu /h

- 0.4

- 2.4

- 5.6

- 8.6

- 9.2

PTHP < 7,000 Btu /h 0.2 0.4 0.4 0.3 0.3

PTHP 7,000

- 15,000 Btu /h 6.7 15.8 25.6 30.4 30.8

PTHP > 15,000 Btu /h 0.3 0.8 0.3

- 0.7

- 1.0

10

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- 4Table 10

- B.3

. 2 Summary of Cumulative Net Present Value for PTAC and PTHP:

Decreasing Price Scenario ( Three Percent Discount Rate)

Equipment Class Net Present Value (Billion 2012$)

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

PTAC < 7,000 Btu /h 0.0 0.0

- 0.3

- 0.9

- 1.0

PTAC 7,000

- 15,000 Btu /h 5.0 16.4 26.3 26.1 25.2

PTAC > 15,000 Btu /h 0.0

- 2.2

- 6.8

- 10.6

- 11.3

PTHP < 7,000 Btu /h 0.7 2.1 3.3 3.8 3.9

PTHP 7,000

- 15,000 Btu /h 19.0 54.1 96.7 119.2 121.9

PTHP > 15,000 Btu /h 1.2 4.0 5.5 5.3 5.1

All Classes 25.9 74.4 124.8 143.0 143.7

Table 10

- B.3

. 3 Summary of Cumulative Net Present Value for PTACs and PTHPs : Increasing Price Scenario (Seven Percent Discount Rate)

Equipment Class Net Present Value (Billion 2012$)

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

PTAC < 7,000 Btu /h 0.0

- 1.0

- 2.9

- 4.4

- 4.7

PTAC 7,000

- 15,000 Btu /h

- 2.6

- 13.1

- 32.2

- 47.8

- 50.7

PTAC > 15,000 Btu /h

- 1.1

- 4.7

- 9.7

- 13.6

- 14.3

PTHP < 7,000 Btu /h 0.0

- 0.3

- 0.9

- 1.4

- 1.5

PTHP 7,000

- 15,000 Btu /h 3.9 5.5 4.8 3.2 3.0

PTHP > 15,000 Btu /h

- 0.1

- 0.8

- 2.8

- 4.6

- 5.0

All Classes 0.1

- 14.4

- 43.7

- 68.6

- 73.2

Table 10

- B.3

. 4 Summary of Cumulative Net Present Value for PTACs and PTHPs:

Increasing Price Scenario ( Three Percent Discount Rate)

Equipment Class Net Present Value (Billion 2012$)

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

PTAC < 7,000 Btu /h 0.0

- 1.3

- 3.8

- 5.4

- 5.7

PTAC 7,000

- 15,000 Btu /h

- 1.0

- 9.0

- 27.6

- 41.3

- 43.3

PTAC > 15,000 Btu /h

- 1.7

- 7.6

- 15.8

- 21.2

- 22.0

PTHP < 7,000 Btu /h 0.2 0.4 0.3 0.1 0.1

PTHP 7,000

- 15,000 Btu /h 12.7 30.6 49.5 60.9 62.6

PTHP > 15,000 Btu /h 0.3 0.4

- 1.5

- 3.2

- 3.5

All Classes 10.5 13.6 1.0

- 10.0

- 11.7

10

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- 5REFERENCES

1. Margaret Taylor and K. Sydny Fujita. Accounting for Technological Change in Regulatory

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

Berkeley, CA. April 2013.

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