9B -i APPENDIX 9B. ESTIMATION OF POTENTIAL EQUIPMENT PRICE TRENDS FOR

HIGH

- INTENSITY DISCHARGE LAMPS

TABLE OF CONTENTS

9B.1 INTRODUCTION .........................................................................................................9B-1

9B.2 EXPERIENCE CURVE APPROACH ..........................................................................9B-1

9B.3 AEO PRICE TREND APPROACH ...............................................................................9B-3

LIST OF TABLES

Table 9B.3.1 Price Fac tors for HID Lamps ...............................................................................9B-3

LIST OF FIGURES

Figure 9B.2.1 PPI Data for HID Lamps ....................................................................................9B-29B -1 APPENDIX 9 B. ESTIMATION OF POTENTIAL EQUIPMENT PRICE TRENDS FOR

HIGH

- INTENSITY DISCHARGE LAMP S

9B.1 INTRODUCTION

In developing the proposed standards, the U.S. Department of Energy ( DOE ) assumed that the manufacturer costs and retail prices of products meeting various efficiency levels

remained fixed, in real terms, after 2011 (the year for which the engineering analysis estimated costs) and throughout the period of the analys is. In its n otice of d ata a vailability (NODA) , 76 FR 9696 (Feb. 22, 2011), DOE stated that it may consider improving regulatory analysis by addressing equipment price trends. Consistent with the NODA, DOE examined historical producer price indices (PPI) for high

- intensity discharge (HID) lamps and found both positive

and negative real price trends depending on the time period examined. Therefore, in the absence of a definitive trend, DOE decided to use price deflators from the U.S. Energy Information

Administration’s (EIA ’s ) Annual Energy Outlook 2011 ( AEO2011 ) to adjust HID lamp prices over the analysis period.

The following paragraphs briefly describe the experience curve approach and deflator approach and the reasons why the latter was adopted.

9B.2 EXPERIENCE CURVE APPROACH

DOE state d in the NODA that e xamination of historical price data for certain appliances and equipment that have been subject to energy conservation standards indicates that the assumption of constant real prices and costs may, in many cases, overestimate long- term appliance and equipment price trends. Economic literature and historical data suggest that the

real costs of these products may in fact trend downward over time according to “learning” or “experience” curves , or alternatively that the price trends for certain sectors of the U.S. economy may be different than the price trends for the economy as a whole. A draft paper

, “Using the Exp erience Curve Approach for Appliance Price Forecasting ,” posted on the DOE website at www1.eere.energy.gov/buildings/appliance_standards/product.aspx/produc tid/60 , provides a summary of the data and literature currently available to DOE that is relevant to price forecasts for selected appliances and equipment.

The extensive literature on the “learning” or “experience” curve phenomenon is typically based on observations in the manufacturing sector. a In the experience curve method, the real cost of production is related to the cumulative production or “experience” with a manufactured product. A common functional relationship used to model the evolution of production costs in

this case is :

Y = aX - b

a In addition to the draft paper mentioned above, see Weiss, M., H.M. Junginger, M.K. Pat el, and K. Blok. A Review of Experience C urve Analyses for Energy Demand T echnologies. Technological Forecasting & Social Change

. 2010. 77:411

- 428

.9B -2 where a is an initial price (or cost), b is a positive constant known as the learning rate parameter,

X

is cumulative production, and Y is the price as a function of cumulative production. Thus, as 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 (LR), given by:

LR = 1 – 2 - b

In typical learning curve formulations, the learning rate parameter is derived using two historical data series: cumulative production and price (or cost).

DOE examined h istorical price s using the Bureau of Labor St atistics’ (BLS) PPI and gross domestic product ( GDP ) deflator, available from the Bureau of Economic Analysis (BEA).

The PPI data for industrial- type electric lighting fixtures, including parts and accessories

, is

available for 19 87–2010 and is us ed to rep resent aggregate industrial lighting system prices. Figure 9B.2 .1 shows this PPI data series.

Inflation -adjusted price indices were calculated by dividing the PPI series by the GDP

deflator for the same years . The GDP deflator was used as opposed to the Consumer P rice I ndex

because most HID lamps are shipped to commercial and industrial customers.

Figure 9B.2.1 PPI D ata for HID Lamps

Figure 9B.2 .1 shows an apparent price trend in lighting equipment that is trending downward from 1987 to 2005, but shows an increase in the real PPI from 2005 to 2010. Given the presence of both positive and negative real price trends, DOE elected to not use the experience curve approach to adjust HID lamp prices.

0.5 0.6 0.7 0.8 0.9

1 1.1 1.2 1.3

1985 1990 1995 2000 2005 2010

PPI for industrial

- type electric lighting fixtures, including parts and

accessories9B -3 9B.3 AEO PRICE TREND APPROACH

For this interim analysis , DOE instead used the AEO price trend approach. DOE has access to the forecasted price indexes used by EIA to develop AEO2011 . The price index projections used in the EIA model are called deflators. The narrowest index that includes high

intensity discharge lamp s— the series “Non -r esidential investment – Other equipment”— was used. Th is index was inflation -adjusted by dividing by the “GDP Deflator” index, also available

from AEO2011

. The resulti ng factor was reset to 1 in 2011— the year for which the prices were developed.

The AEO pri ce indexes begin in 1990 and extend to 2035. Because the AEO time series does not extend to the end of the analysis period, the forecasted trend was extrapolated for years beyond 2035. Table 9B.3 .1 presents the resulting pr ice factors used in the national impact analysis and all downstream analyses for this proposed rule.

Table 9B.3.1 Pric e Factors for HID Lamps

Year Price Factor

2011 1.000

2012 1.001

2013 1.005

2014 1.005

2015 1.000

2016 0.997

2017 0.990

2018 0.983

2019 0.976

2020 0.967

2021 0.957

2022 0.948

2023 0.938

2024 0.929

2025 0.919

2026 0.909

2027 0.898

2028 0.886

2029 0.875

2030 0.864

2031 0.852

2032 0.841

2033 0.829

2034 0.817

2035 0.804

2036 0.799

2037 0.795

2038 0.790

2039 0.785

2040 0.780

2041 0.776

2042 0.771

2043 0.766

2044 0.762

2045 0.7579B -4 Table 9.B.3.1 (cont)

Year Price Factor

2046 0.753

2047 0.748

2048 0.744

2049 0.739

2050 0.735

2051 0.730

2052 0.726

2053 0.722

2054 0.717

2055 0.713