CHAPTER 2. ANALYTICAL FRAMEWORK

TABLE OF CONTENTS

2.1 INTRODUCTION ........................................................................................................... 2-1 2.2 BACKGROUND ............................................................................................................. 2-4 2.3 MARKET AND TECHNOLOGY ASSESSMENT ........................................................ 2-4 2.3.1 Market Assessment .............................................................................................. 2-4 2.3.2 Technology Assessment....................................................................................... 2-5 2.4 SCREENING ANALYSIS .............................................................................................. 2-5 2.4.1 Technology Screening ......................................................................................... 2-5 2.5 ENGINEERING ANALYSIS.......................................................................................... 2-6 2.5.1 Manufacturing Cost Model.................................................................................. 2-6 2.5.2 Energy Consumption Model................................................................................ 2-6 2.6 ENERGY USE CHARACTERIZATION ....................................................................... 2-6 2.7 MARKUPS TO DETERMINE EQUIPMENT PRICE ................................................... 2-7 2.8 LIFE-CYCLE COST AND PA YBACK PERIOD ANALYSES .................................... 2-8 2.9 SHIPMENTS ANALYSIS............................................................................................... 2-9 2.10 NATIONAL IMPACT ANALYSIS.............................................................................. 2-10 2.10.1 National Energy Savings Analysis.....................................................................2-10 2.10.2 Net Present Value Analysis ...............................................................................2-10 2.10.3 Efficiency Scenarios and Trends ....................................................................... 2-11 2.11 LIFE-CYCLE COST SUB-GROUP ANALYSIS......................................................... 2-11 2.12 MANUFACTURER IMPACT ANALYSIS.................................................................. 2-12 2.13 UTILITY IMPACT ANALYSIS................................................................................... 2-13 2.14 EMPLOYMENT IMPACT ANALYSIS....................................................................... 2-13 2.15 ENVIRONMENTAL ASSESSMENT .......................................................................... 2-14 2.16 REGULATORY IMPACT ANALYSIS........................................................................ 2-14 2.17 DEPARTMENT OF JUSTICE REVIEW ..................................................................... 2-15

LIST OF FIGURES
Figure 2.1.1 Flow Diagram of Analyses for the Be verage Vending Machine Rulemaking Process

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2-i2-iiCHAPTER 2. ANALYTICAL FRAMEWORK

2.1 INTRODUCTION
Section 6295(o)(3 )(B) of Title 42, United Stat es Code (42 U.S.C.), as directed by 42 U.S.C. 6316(a)(1)

─ (3), requires the U.S. Department of Energy (DOE) to set forth energy conservation standards that are technologically feasible and ec onomically justified, and would achieve the maximum improvement in energy effi ciency. This chapter describes the general analytical framework that DOE uses in developi ng such standards and, in particular, standards for beverage vending machines (BVMs). The analytical framework is a description of the methodology, analytical tools, and re lationships among the various anal yses that are part of this rulemaking. For example, the methodology that addresses the statut ory requirement for economic justification include s analyses of life-cycle cost (LCC); economic impact on manufacturers and users; national benefits; impacts, if any, on u tility companies; and impacts, if any, from lessening competition among manufacturer s. DOE will also solicit the views of the Department of Justice (DOJ) on any lessening of competition likely to result from the imposition of a proposed standard.
Figure 2.1.1 summarizes the analytical components of the standards-setting process. The colum ns labeled “Key Inputs” and “Key Outputs” show how the analyses fit into the rulemaking process, and how they relate to each other. Key inputs are the types of da ta and information that the analyses require. Some key inputs exist in public databases; DOE al so collects other inputs from interested parties and pe rsons with special knowledge. Ke y outputs are analytical results that feed directly into the standards-setting proc ess. Arrows connecting analyses show types of information that feed from one analysis to another.

2-1Utility Impact Analysis

Notice of Proposed Rulemaking (NOPR)

Final Rule Approaches Key Inputs Analyses Key Outputs

Market and Technology Assessment

Screening Analysis

Engineering Analysis

Markups for Equipment Price

Determination Life-Cycle Cost and Payback Period Analyses

National Impact Analysis Energy Use

Revise ANOPR Analyses

Life-Cycle Cost Sub-Group Analysis

Manufacturer Impact Analysis Shipments Analysis

Employment Impact Analysis

Revise Analyses • Product Classes • Technology Options

• Industry Cash Flow • Sub-Group Cash-Flow • Direct Employment Impacts • Competitive Impacts • Cumulative Regulatory Burden • Cost-Efficiency Relationship

• Life-Cycle Costs • Payback Periods

• National Energy Savings • Net Present Values

• National Employment Impacts

• Revised Results • Characterize Industry • Market Segmentation • Non-Regulatory Programs Framework Document

• Efficiency-Level Approach • Design Option Approach

• Energy Prices • Installation Costs • Maintenance & Repair Costs

• Accounting Approach

• Backcast and Forecast • Market Saturation

• Stakeholder Comments

• Demographics

• Manufacturer Interviews

• GRIM Analysis

• Emission Rates • National Energy Savings

• Stakeholder Comments • Identify Firms/Products • Historical Shipments

• Define Distribution Channels • Economic Census Data Analysis • Retail Price Collection and Analysis

• Manufacturer Prices • Average Costs

• Manufacturer Financial Data Design Options Product Classes

Retail Prices Design Energy/Use

Advance Notice of Proposed Rulemaking (ANOPR) • Efficiency/Performance • Manufacturing Cost

Candidate Standard

Levels • Analysis of Energy Use Data

Environmental Assessment

Regulatory Impact Analysis Technology Options

• Emission Estimates • Utility Load Factors • National Energy Savings

• Non-Regulatory Alternatives • NEMS-BT

• ImSET

• NEMS-BT • Design Options

• Energy Price Forecasts • Site-to-Source Factors • Energy-Efficiency Levels

Direct Employment Impacts

• National Energy Savings • National Product Costs • National Operating Costs • Utility Impacts • Analysis of Market Data

• Analysis of Product Data

• Life-Cycle Costs • Payback Periods • Installation Costs • Maint Costs • Repair Costs • UEC • Energy Prices Annual Energy Use (UEC)

Preliminary Manufacturer Impact Analysis • Manufacturer Prices • Average Costs • Conversion Capital Expenditures • Direct Employment Impacts

• National Energy Savings • Net Present Values • Trial Standard Levels (TSLs)
TSLs • Product Prototypes

Energy-Efficiency Levels

• Department of Justice Review Cost-Efficiency Relationship

2-2Figure 2.1.1 Flow Diagram of Analyses for the Beverage Vending Machine Rulemaking Process
The analyses performed in the advance not ice of proposed rulemaking (ANOPR) stage and reported in this technical suppor t document (TSD) are listed below.

 A market and technology assessm ent is conducted to character ize the relevant equipment markets and existing technology optio ns, including prototype designs.

 A screening analysis is conducte d to review each technology op tion and determine if it is technologically feasible ; is practical to manufacture, inst all, and service; would adversely affect equipment utility or equipment availa bility; or would have adverse impacts on health and safety.

 An engineering analysis is conducted to deve lop the cost-efficiency relationship, which is the increased manufacturer sell ing prices (material, labo r, factory overhead, selling, general and administrative expenses, research and development costs, and profit) of more efficient equipment.

 An equipment price markup analysis is conduc ted to convert the ma nufacturer’s sellingprice estimates from the engine ering analysis to customer pr ices, which are then used in the LCC and payback period (PBP) analyses and the manufacturer impact analysis (MIA).

 An energy use analysis is conducted to determ ine the annual energy us e characteristics of beverage vending machines located inside and outside of manufacturing facilities and other commercial buildings.

 LCC and PBP analyses are conducted to calcula te, at the customer level, the discounted savings in operating costs (less maintenan ce and repair costs) throughout the estimated average life of the covered equipment compared to any increase in the installed cost for the equipment likely to result directly from the imposition of the standard.

 A shipments analysis is conducted which forecasts equipment shipments. This analysis is then used to calculate the national impacts of standards on energy consumption and costs, net present value (NPV), and fu ture manufacturer cash flows.

 A national impact analysis is conducted to a ssess the aggregate impacts at the national level of NPV of total consumer LC C and national energy savings (NES).

 A preliminary MIA is conducted to assess the potential impacts of energy conservation standards on manufacturers such as capital conversion expenditures, marketing costs, shipments, and research and development costs.
The analyses performed in this notice of proposed rulemaking (NOPR) stage include those listed below. In addition, DOE re-ana lyzes the work done in the ANOPR stage.

2-3 A life-cycle cost sub-group analysis is conduc ted to evaluate variations in commercial business type characteristics (e.g., energy prices, equipment us e patterns, and installation and maintenance costs) that might cause a st andard to affect particular customer subpopulations, such as specific building owners or other customers that purchase and use beverage vending machines differently than the overall population.

 A manufacturer impact analysis is conducted to estimate the fi nancial impact of standards on manufacturers and to calculate im pacts on competition, employment, and manufacturing capacity.

 A utility impact analysis is conducted to estimate the effects of proposed standards on electric utilities.

 An employment impact analysis is conducted to assess the aggregat e impacts on national employment.

 An environmental assessment is conducted to provide estimates of changes in emissions of pollutants from electricity ge neration (i.e., carbon dioxide (CO 2 ), oxides of nitrogen (NO x ), mercury (Hg), and sulfur dioxide (SO 2 ).

 A regulatory impact analysis is conducted to present major alternatives to proposed standards that could achieve substantially the same regulatory goal at a lower cost.

2.2 BACKGROUND
DOE developed and documented the analytic al framework for the BVM rulemaking in the Rulemaking Framework for Refrigerated Bottled or Canned Beverage Vending Machines
, and presented the analytical approach to inte rested parties during a public meeting on July 11, 2006. This document is available at http://www.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/ vending_machines_framework.pdf. The following sect ions describe the di fferent analytical components of the rulemaking framework.

2.3 MARKET AND TECHNOLOGY ASSESSMENT

The ma rket and technology assessment charact erizes the relevant product markets and existing technology options, in cluding prototype designs.

2.3.1 Market Assessment
When initiating a standards rulema king, DOE develops information on the present and past industry structure and mark et characteristics for the equi pment concerned. This activity assesses the industry and equipment both quantit atively and qualitative ly, based on publicly available information. DOE addresses the fo llowing: (1) manufacturer market share and characteristics, (2) existing regulatory and non -regulatory equipment efficiency improvement

2-4initiatives, and (3) trends in pr oduct characteristics and retail mark ets. This information serves as resource material throughout the rulemaking.
For this rulemaking, DOE reviewed existing l iterature and interviewed manufacturers to get an overall picture of the BV M market in the United States. Industry publications and trade journals, government agencies, and trade organi zations provided the bulk of the information. The appropriate sections of the NOPR describe the analysis and re sulting information as reported in the TSD.

DOE uses the most reliable and accurate data available at the time of each analysis in its rulemakings. All data is available for public review.

2.3.2 Technology Assessment
DOE typically uses information about existi ng and past technology options and prototype designs to help determ ine which technologies manufacturers use to attain higher energy performance levels. In consultation with interest ed parties, DOE develops a list of technologies for consideration. Initially, these technologies encompass all those it believes are technologically feasible.
For this rulemaking, DOE developed a list of technologically feasible design options after consultation with manufacturers of components a nd systems, and from trade publications and technical papers. Since many options for impr oving equipment efficiency are available in existing equipment, product literature and dire ct examination of the BVM equipment provided additional information, as descri bed in chapter 3 of the TSD.

2.4 SCREENING ANALYSIS
In the screening analysis, DOE screens out technologies that are not technologically feasible; not practicable to m anufacture, install, or service; have an adverse impact on equipment utility or availability; or have adverse impacts on health and safety. In the engineering analysis, DOE further considers design options that remain after the screening process.

2.4.1 Technology Screening
As described in chapter 4 of the TSD, DOE grouped technologies into the fo llowing categories: (1) technologies th at do not affect daily energy consumption, (2) screened-out technologies, and (3) remaining technologies that reduce BVM en ergy consumption under DOE’s test procedure.
Because the energy descriptor for beverage vending machines is daily energy consumption and the test procedure uses a steady state approach, DOE did not include technologies or designs that improve energy consumption under varying ambient conditions (e.g., expansion valves, variable-speed compresso rs). Therefore, only those technology and design options that improve the daily energy consumption rating were considered viable for review and applicati on in the rulemaking.

2-52.5 ENGINEERING ANALYSIS
As presented in chapter 5, the engineering an aly sis establishes the relationship between the price and efficiency of beverage vending machines. This rela tionship serves as the basis for cost/benefit calculations for i ndividual customers, manufact urers, and the Nation. The engineering analysis discusses co st-efficiency curves, equipment cl asses analyzed, representative baseline units, the methodology used to devel op manufacturing selli ng prices, the methodology used to develop the energy consumption model, and the use of alternative refrigerants.

2.5.1 Manufacturing Cost Model

DOE used a cost model to estim ate the core cost of refrigerated beverage vending machines. This cost model is based on work DOE conducted in support of the rulemaking on commercial refrigeration equipment (see http://www.eere.energy.gov/buildings/ appliance_standards/commercial_products.html for further details on and validation of the cost model). The approach for commercial refrige ration equipment involved the disassembly of a piece of commercial refrigeration equipment, an analysis of the materials and manufacturing processes, and the development of a parametric spreadsheet model. DOE then modified the commercial refrigeration equipment model to anal yze the core costs of refrigerated beverage vending machines. DOE obtained input from inte rested parties on the refrigerated beverage vending machine manufacturer selling prices es timates and assumptions to confirm their
accuracy.

2.5.2 Energy Consumption Model
The energy consumption m odel estimates the daily energy consumption of refrigerated beverage vending machines in kilowatt hours atvarious performance levels using a designoptions approach. DOE developed the ener gy consumption model as a Microsoft Excel spreadsheet. Appendix A provides inst ructions for using the spreadsheet.
For a given equipment class, the model estim ates the daily energy consumption for the baseline and several levels of performance a bove the baseline. The model calculates each performance level separately. For the baseline level, the cost mode l calculates a corresponding cost; for each level above the baseline, the cost increases of the various design options are used to recalculate the final cost.

2.6 ENERGY USE CHARACTERIZATION
The energy use characterizati on analysis assessed the annua l energy consumption of the refrigerated beverage vending m achines that woul d be located inside a nd outside industrial and commercial buildings. DOE modified the ener gy consumption model developed during the engineering analysis to re flect the equipment’s thermal and compressor performance characteristics in order to simulate a realisti c performance of the machine exposed to varying temperature and relative humidity conditions. DOE developed another spreadsheet-based model (described in chapter 7 of th e TSD) to determine the beverage vending machine’s hourly, and hence annual, energy consumption under varying climate conditions around the country. DOE

2-6developed a State-by-Stat e distribution of beverage vending machines using population weights to determine annual energy consumption of machin es located outdoors. The machines that are typically located inside industrial and commercia l buildings were assumed to be in conditioned spaces, and hence are exposed to the same te mperature and relative humidity conditions (75 degrees Fahrenheit (°F) and 45 percent relative humidity) throughout the year.
Most beverage vending machines are locate d inside conditioned spaces and will add to the cooling load in the summer and reduce the h eating load in the winter. DOE believes these impacts are fairly modest in most cases. DOE also believes that the added complexity of determining the overall impact on building space-c onditioning loads is not worth the effort involved in accurately quantifying th is effect, particularly given the variety of building types and vending machine locations (e.g., outside, inside, or in vestibules) that w ould need to be taken into account.

2.7 MARKUPS TO DETERMINE EQUIPMENT PRICE

DOE used ma nufacturer-to-consumer markups to convert the manufa cturer selling-price estimates from the engineering analysis to custom er prices, which were then used in the LCC, PBP, and manufacturer impact analyses. Because retail prices are required for the baseline performance level and all othe r performance levels under consideration, DOE obtained these retail prices by applying manufacturer-to-custom er markups to the manufacturer selling-price estimates.
Before it can develop markups, DOE must iden tify distribution channels (i.e., how the equipment is distributed from the manufacturer to the custome r). Once it established proper distribution channels for each of the equipment classes, DOE relied on economic data from the U.S. Census Bureau and input from the indus try to determine how much product prices are increased as they pass from the manufacturer to the customer (see chapter 6 of the TSD).

DOE’s review of the information revealed that a set of three distri bution channels would be appropriate, as described below:

1. Equipment Manufacturer  Vending Machine Operator (e.g., bottler, beverage distributor)

2. Equipment Manufacturer  Distributor  Vending Machine Operator

3. Equipment Manufacturer  Distributor  Site Owner
In the first distribution channel, the equi pment manufacturer makes the equipment to meet machine performance spec ifications provided by the beve rage company (i.e., the vending machine operator) and sells it di rectly to a bottler or beverage distributor. The vending machine operator owns the machine, places it on site through a “location contract,” maintains the machine and stocks it, and receives a certa in percentage of coin-box revenue. The site owner, in this case, allows the machine to be placed on site, receives a percentage of coin-box revenue and/or other remuneration, and most importantly, pays the electric bill.

2-7In the second channel, the vending machin e operator purchases th e equipment from a distributor instead of directly fr om the equipment manufacturer.

In the third channel, a site owner (e.g., large retail store ch ain) may purchase the vending machines from the distributor and in stall them inside or outside a re tail store location. Other site owners (e.g., gas stations) may purchase vending machines from a distributor and stock the machines for the entire coin-box revenue.

The first distribution channel creates a “split-incentive syst em” where bottling companies or distributors purchase and inst all a significant portion of the vending machines from equipment manufacturers, but do not pay the utility bills associated with th e machines’ operation. The site owner may be paid a commission as pa rt of the location contract to defray part of the electricity bill. Therefore, the equipment purchaser has no economic incentive to purchase a more efficient machine. Nonetheless, there may be a growi ng market for energy-efficient beverage vending machines because environmentally conscious beverage companies are asking for energy-efficient machines, and certain site owners are demanding th at energy-efficient machines be installed to reduce energy costs.

2.8 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES
New energy conservation standards on equipm ent usually reduce operating expenses and increase cust omer prices. DOE analyzed th e net effect of new standards on customers by evaluating the net LCC using the cost-efficiency re lationship derived in th e engineering analysis, as well as the energy costs derived from the energy use characterization analysis. Inputs to the LCC calculation include the installed cost to the cu stomer (customer price plus installation cost), operating expenses (energy expenses and maintenan ce costs), the lifetime of the appliance, and a discount rate. These inputs are describe d in detail in chapter 8 of the TSD.
The installed cost typically increases and operating cost typically decreases in response to new standards. Thus, there is a specific tim e in the life of higher-than-baseline efficiency equipment when the net operating-cost benefit (i n dollars) from the time of purchase is equal to the incremental first cost of purchasing the more efficient equipment. The length of time required for equipment to reach this cost-equ ivalence point is known as the payback period.

For the NOPR, DOE conducted the LCC and PBP analyses using typical values to reflect the conditions in the field for equipment life, equipment retail price, national or regional energy costs, energy consumption, and discount rates. The life-cycle cost subgr oup analysis includes an assessment of impacts on customer subgroups.
For beverage vending machines, it was necessary to determine several of the input values for the LCC estimation, including retail prices; el ectricity prices; discount rate; maintenance, service, and installation costs; and equipment lifetimes.
DOE reviewed the Energy Information Admi nistration’s (EIA) energy price data for beverage vending machines to establish electricity prices. DOE relied on regional average energy price data for the commercial and industria l sectors (manufacturing facilities). DOE used

2-8projections of these energy prices for commercia l and industrial customers to estimate future energy prices in the LCC and PBP analyses. DOE used EIA’s Annual Energy Outlook (

AEO ) as the default source of projections for future energy prices.
DOE developed discount rates by estimating th e cost of capital to companies that purchase beverage vending machines covered under this rulemaking. DOE commonly uses the cost of capital to estimate the present value of cash flows to be derived from a typical company project or investment. Most co mpanies use both debt and equity capital to fund investments, so the cost of capital is the weighted-average cost to the firm of equity and debt financing. This corporate finance approach is referred to as the weighted-average cost of capital.
DOE considered expected changes to maintena nce, repair, and inst allation costs for the equipment covered in this rulemaking. Typical ly, small incremental changes in equipment efficiency incur no, or only very small, change s in repair and maintenance costs over baseline efficiency products. There is a greater probabili ty that equipment with efficiencies that are significantly greater than the baseline will incur increased repair and maintenance costs since such equipment is more likely to incorporate technologies that are new to the industry and not widely available. DOE relied on input from ma nufacturers and other in terested parties to develop appropriate repair and ma intenance costs. Unless the efficiency increases considered for this rulemaking result in signifi cantly larger or heavier products , DOE determined that more efficient beverage vending machines woul d not incur increased installation costs.

DOE used information from various literat ure sources (e.g., Automatic Merchandising and American Society of Heating, Refrigerati ng, and Air-Conditioning Engineers Refrigeration Handbook) and input from manufacturers and other interested parties to establish average equipment lifetimes for use in the life- cycle cost and subsequent analyses.

2.9 SHIPMENTS ANALYSIS
Shipme nt forecasts are required to calculat e the national impacts of standards on energy, NPV, and future manufacturer cash flows. DOE developed shipment forecasts based on an analysis of key market drivers for beverage vending machines (see ch apter 10 of the TSD).
For each equipment class, DOE developed a se t of shipment forecasts for the beverage vending machines for each set of standards analy zed. These standards case forecasts were used to evaluate the impacts of standards on product shipments. Standards case forecasts were derived using the same data sets as base case fore casts. The data required to develop sensitivities of shipments to customer price and operating cost savings were limited. Therefore, DOE modeled standards case shipment s forecasts with scenarios (i .e., specific impacts on product shipments) rather than developing sensitivities to customer price or operating cost savings. Comments from interested parties on the shipme nts forecasts at the ANOPR stage indicated that future shipments likely will not increase from present levels and will occur for replacement purposes only, with any sales to new locations offset with reductions at existing locations. This flat-sales scenario was adopted by DOE for the shipments forecast.

2-92.10 NATIONAL IMPACT ANALYSIS
The national impact analysis ass esses the NP V of total customer LCC and NES. DOE determined both the NPV and NES for the performance levels considered for the equipment classes analyzed. To make the analysis more acce ssible and transparent to all interested parties, DOE prepared an NES spreadsheet model in Micr osoft Excel to forecast energy savings and the national economic costs and savings resulting from new standards. The NES spreadsheet model does not use probability distributi ons for inputs or outputs. To assess the impact of input uncertainty on the NES and NPV results, DOE can conduct sensitivity analyses for future analyses by running scenarios on input variables of concern for interested parties. DOE conducted an assessment of the aggregate economic impacts at the national level for this NOPR as described in chapter 11 of the TSD.

2.10.1 National Energy Savings Analysis
The inputs fo r determining NES are (1) annual energy consumption per unit, (2) shipments, (3) equipment stock, (4) national en ergy consumption (calculated from consumption per unit and equipment stock), and (5) site-to- source conversion factors. DOE calculated the national energy consumption by multiplying the numb er of units, or stock, of beverage vending machines (by vintage) by the unit energy consumption (also by vintage). a Then, DOE calculated national annual energy savings from the differe nce between national energy consumption in the base case (without new efficiency standards) and in each higher efficiency standard case. DOE estimated energy consumption and savings based on site energy, and converted the electricity consumption and savings to source energy. Cumu lative energy savings are the sum of the annual NES, which DOE determined over specific time periods.
The stock of beverage vending machines depends on annual shipments and equipment lifetimes. DOE conducted shipments projections under the base efficiency case and higher efficiency standards cases for a variety of possi ble equipment efficiency scenarios and trends. DOE used the flat replacement-sales-only total shipments forecast from the shipments analysis for all efficiency scenarios.

2.10.2 Net Present Value Analysis
The inputs fo r determining NPV are (1) tota l annual installed co st, (2) total annual operating cost savings, (3) discoun t factor, (4) present value of costs (values calculated in the analysis), and (5) present value of savings (also calculated values). DOE calculated net savings each year as the difference between total operating-c ost savings (including electricity, repair, and maintenance cost savings) and increases in tota l installed costs (incl uding equipment price and installation cost). DOE calcu lated savings over the life of the equipment, accounting for differences in yearly energy rates. DOE calcu lated NPV as the difference between the present value of operating cost savings a nd the present value of increased total installed costs. DOE discounted future costs and savings to the present with a discount factor.

a Vintage represents the age of the equipment.

2-10DOE calculated increases in total installed co sts as the product of the difference in the total installed cost between th e base case and standards case and the annual shipments in the standards case. Because costs of more effi cient equipment bought in the standards case are higher than the costs of equipment bought in the base case, price increases appear as negative values in the NPV.
DOE expressed operating cost savings as decrea ses in operating costs associated with the lower energy consumption of equipment bought in the standards case compared to the base efficiency case. Total operati ng-cost savings are the product of savings per unit and the number of units of each vintage surv iving in a particular year.

2.10.3 Efficiency Scenarios and Trends
Several of the inputs for determining NES (e.g., the annual energy consumption per unit) and NPV (e.g., the total annual installed cost and the total annual operating-cost savings) depend on the efficiency of the equipm ent. Thus, DOE developed base case and standards case efficiency trends. The efficiency trends speci fy the annual historical and forecasted shipmentweighted average equipment efficiencies.
At the ANOPR stage stakeholder comments i ndicated that the efficiency of purchased equipment is strongly dependent on the corporat e purchasing policies of a handful of buyers. Chapter 11 of the TSD describes the baseline scen arios developed by DOE to describe the effects of these polices on historical and future baseline efficiency trends.
DOE based its standards case forecasts (i.e., fore casts of efficiency trends after standards take effect) on the use of a roll-up efficiency scenario and parallel growth trend. Under a roll-up scenario, all equipment at perfor mance levels below a prospective standard are moved or rolled up to the minimum performance level allowed u nder the new standard. The distribution of equipment at higher efficiency standard levels is unaffected (i.e., this equipment remains at its pre-standard performance levels). The roll-up ef ficiency scenario dictates how DOE determined efficiency distributions in the first year a ne w standard takes effect, but does not define how equipment efficiency will be distributed in the future. DOE assumes that the initial jump in shipment-weighted efficiency that occurs wh en the standard first becomes effective is maintained throughout the forecast.

2.11 LIFE-CYCLE COST SUB-GROUP ANALYSIS
The LCC sub-group analysis evaluates ec onomic im pacts on virtually any group of customers, for example, customers of different business types that might be adversely affected by a change in the national energy efficiency st andard levels for beverage vending machines. During the NOPR stage, DOE evaluates the impacts of particular sub-groups of customers in part by analyzing the LCC and PBP for these customers.
DOE evaluated variations both in regional ener gy prices and use that might affect the NPV of an energy-efficiency standard to custom er sub-groups. To the extent possible, DOE

2-11sought estimates of the variability of each input parameter and considered this variability in calculating customer impacts.
Then, DOE determined the impact on customer sub-groups using the LCC spreadsheet model. The spreadsheet model used for the LCC anal ysis can be used with different data inputs. The standard LCC analysis includes various commercial building types that use beverage vending machines. Moreover, DOE can analyze the LCC for any sub-group by using the LCC spreadsheet model and only sampling that sub-group. Details of this model are explained in the section describing the LCC and PBP analyses.
DOE considered which categories would be likeliest to be adversely affected. Manufacturing facilities th at own their own BVMs were considered to be the likeliest businesses to be adversely affected since they had the hi ghest financing costs fo r new equipment of any group of BVM owners (leading to the highest in itial equipment cost) and faced the lowest electricity prices (thus showing the lowest value of energy savings). As a result, the LCC and payback calculations would be least favorable for this group.
DOE aims to avoid a negative economic imp act on any identified customer sub-group, such as small businesses with low annual revenues that might not be able to afford a significant increase in the price of beverage vending mach ines. The Small Business Administration defines a small business from a customer persp ective by either its annual receipts ( i.e ., revenues) or its number of employees. Manufact uring businesses are generall y defined to be small if employment of the entire business is 500 pe rsons or less. DOE does not have sufficient information to correlate employment with the co sts of more efficient BVMs to identify the subgroup of small businesses in the manufacturing sa mple. However, DOE believes that the results from the LCC sub-group analysis found in chapte r 12 of the TSD provide an adequate indication of whether the small manufacturing businesses might be disproportionately advantaged or disadvantaged by a proposed standard.

2.12 MANUFACTURER IMPACT ANALYSIS
DOE perform ed an MIA to estimate the fina ncial impact of higher energy conservation standards on BVM manuf acturers, and to calculate the imp act of such standards on domestic manufacturing employment and plant capacity. The MIA has both quantitative and qualitative aspects. The quantitative part of the MIA primarily relies on th e Government Regulatory Impact Model (GRIM) - an industry- cash-flow model customized for this rulemaking. The GRIM inputs are data characterizing the industry cost structure, shipments, and revenues. The key output is the industry net presen t value. Different sets of assumptions (scenarios) produce different results. The qualitative part of the MIA addresses factors such as equipment characteristics, characteristics of particular fi rms, and market and equipment trends, and includes an assessment of the impacts of standa rds on subgroups of manufacturers.

DOE conducted the manufacturer impact analysis in three phas es. Phase one consisted of preparing an industry ch aracterization and identifying key issues. Phase two addressed the broader industry where DOE woul d use the Government Regulatory Impact Model to perform an industry cash flow analysis. DOE also deve loped a questionnaire for interviewing BVM

2-12manufacturers about the potenti al impacts of new energy c onservation standards on their business during phase two. Phase three involved interviewing manufactur ers and adjusting the industry cash flow analysis as needed. Phase three also examined any additional impacts on competition, manufacturing capacity, direct employment, and the cumulative burden of other regulations on manufacturers. The complete MIA is outlined in Chapter 13 of the TSD.

2.13 UTILITY IMPACT ANALYSIS
The utility impact analysis includes an anal ysis of the im pact of higher efficiency standards on the electri c utility industry. DOE is consid ering adapting EIA’s National Energy Modeling System (NEMS) for this analysis b . NEMS is a large multi-sectoral partialequilibrium model of the U.S. energy sector th at has been developed over the past decade, primarily for the purpose of preparing DOE’s AEO . In prior rulemakings, a variant of NEMS (currently termed NEMS-BT, BT referring to the DOE’s Building Technologies Program) was developed to better address th e specific impacts of an equipment efficiency standard.
NEMS produces a widely recognized baseline energy forecast for the United States through 2030. The typical NEMS outputs include fo recasts of electricity sales, price, and avoided electric generating capacity. DOE mode led the energy savings impacts from amended energy conservation standards using NEMS-BT to generate forecasts that deviate from the AEO reference case.

2.14 EMPLOYMENT IMPACT ANALYSIS
The imposition of standards can affect em ployme nt both directly and indirectly. Direct employment impacts are changes in the number of employees at the plants that produce the covered equipment and at affiliated distribution and service companies. DOE evaluates the direct employment impacts in the manufacturer impact analysis. Indirect employment impacts may result from expenditures shifting between goods (the substitution effect) and changes in income and overall expenditure levels (the income effect). The combined direct and indirect employment impacts will be investigated in the employment impact analysis using the Pacific Northwest National Laboratory’s “Impact of Sect or Energy Technologies” (ImSET) model. The ImSET model was developed for DOE’s Office of Planning, Budget, and Analysis to estimate the employment and income effects of energy-sa ving technologies on buildings, industry, and transportation. Compared to simple economic multiplier approaches, ImSET allows for more complete and automated analysis of the economic impacts of energy conservation investments.

b Summary documentation of NEMS can be found in National Energy Modeling Sy stem: An Overview 2003
, DOE/EIA-0581(2003), March 2003. The AEO 2008 versions of the submodels used in the utility and environmental analyses are documented on EIA’s website: http://www.eia.doe.gov /oia f/forecasting.html

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2-132.15 ENVIRONMENTAL ASSESSMENT
The primary environm ental effects of ener gy conservation standards for the beverage vending machines covered under this rulemaking will be decreased emissions resulting from reduced electrical energy consumption. Th e environmental assessment in TSD chapter 16 tracked the impact of possible standards on CO 2 , NO x , Hg, and SO 2 . DOE based these calculations on the NEMS-BT modeling work proposed for the utility impact analysis. This approach has the advantage of examining the marg inal impact of higher efficiency standards for the covered equipment on the utility genera tion mix and the subsequent environmental emissions.

CO 2 emissions are tracked in NEMS-BT by a de tailed module that produces robust results because of its broad coverage of all sectors and inclusion of inte ractive effects. NEMS-BT also includes a module for SO 2 - allowance trading and NO x - allowance trading in the 28 states where NO x -allowance trading occurs, a nd delivers a forecast of SO 2 -allowance and NO x -allowance prices. Simulation of national SO 2 trading and regional NO x trading tends to imply that physical emissions effects will be zero where this trading occurs. However, there is an SO 2 benefit and a NO x benefit from conservation in the form of a lo wer allowance price and, if big enough to be calculable by NEMS, this value can be reported. NEMS-BT also has an algorithm for estimating untraded NO x emissions from power generation. Hg emissions were estimated based on electricity generation by fuel type in NEMS and a range of Hg emission factors.

In addition to the estimation of reductions in physical emissions from an energy conservation standard DOE also considered th e monetary benefits a ssociated with these reductions. The monetary values were based on values found in the environmental economic literature. Details can be found in Chapter 16 of the TSD.

2.16 REGULATORY IMPACT ANALYSIS
In the NOPR stage, DOE prepared a regulat ory impact analysis (RIA) pursuant to Executive Or der 12866, “Regulatory Planning an d Review,” 58 FR 51735 (October 4, 1993), which is subject to review under the Execu tive Order by the Office of Information and Regulatory Affairs at th e Office of Management and Budget. The RIA addressed the potential for non-regulatory approaches to supplant or augment energy conservation standards to improve the energy efficiency or reduce the energy c onsumption of the beverage vending machines covered under this rulemaking.
Voluntary and other non-regul atory efforts by manufacturer s, utilities, and other interested parties can result in substantial impr ovements to energy efficiency or reductions in energy consumption. DOE considered and qualitatively evaluated a number of non-regulatory approaches in chapter 17 of the TSD. Based on the qualitative review, DOE is not confident that any of the alternatives DOE examined would save as much energy as today’s proposed rule, and the financial incentives in partic ular may engender sign ificant free ridership issues. Also, several of the alternatives would require new enabling legislation, since author ity to carry out those alternatives does not exist.

2-142-15 2.17 DEPARTMENT OF JUSTICE REVIEW
Section 325(o)(2)(B)(i)(V) of the Energy Policy and Conserva tion Act states that before the Secretary of Energy ma y prescribe a new or amended energy cons ervation standard, the Secretary shall ask the Attorney General to make a determination of “the impact of any lessening of competition...that is likely to result from the imposition of the standard.” (42 U.S.C. 6295) Pursuant to this requirement, DOE will solicit the views of the DOJ on any lessening of competition that is likely to result from the im position of a proposed standard and will give the views provided full consideration in assessing the economic justific ation of a proposed standard. DOE may consult with DOJ at earlier stages in the standards development process to seek to obtain preliminary views on competitive impacts.