7.3 Social Cost Estimates The social impact of a regulatory action is traditionally measured by the change in economic welfare that it generates. The social costs of the rule will be distributed across producers of energy and their customers. Producers experience welfare impacts resulting from changes in profits corresponding with the changes in production levels and market prices. Consumers experience welfare impacts due to changes in market prices and consumption levels. However, it is important to emphasize that this measure does not include benefits that occur outside the market, that is, the value of reduced levels of air pollution with the regulation.

The national compliance cost estimates are often used to approximate the social cost of the rule. The engineering analysis estimated annual costs of $ 43.4 million. In cases where the engineering costs of compliance are used to estimate social cost, the burden of the regulation is measured as falling solely on the affected producers, who experience a profit loss exactly equal to these cost estimates. Thus, the entire loss is a change in producer surplus with no change ( by assumption) in consumer surplus, because no change in market price is estimated. This is typically referred to as a " full cost absorption" scenario in which all factors of production are assumed to all factors of production are assumed to be fixed and firms are unable to adjust their output levels when faced with additional costs.

In contrast, the economic analysis conducted by the Agency accounts for behavioral responses by producers and consumers to the regulation, as affected producers shift costs to Table 7 4. Changes in Market Shares for Electricity Suppliers Baseline Shares (%) With Regulation Shares (%)

Existing   unaffected 95.42 96.32 New unaffected 1.07 1.07 New affected   testing only 2.59 2.60 New affected   testing and capital 0.92 0.00 7 7 other economic agents. This approach results in a social cost estimate that may differ from the engineering compliance cost estimate and also provides insights on how the regulatory burden is distributed across stakeholders. As shown in Table 7 5, the economic model estimates the total social cost of the rule to be $ 7.8 million. The social cost estimate is 18 percent of the estimated engineering costs as a result of behavioral changes of producers and consumers. The major behavioral change is that units with testing and add on capital controls are crowded out of the new source market; hence these costs are not incurred by society. Therefore the social costs primarily reflect higher costs by existing units to increase supply, and the deadweight loss to consumers as price increases and quantity decreases.

The analysis also shows important distributional impacts across stakeholders. For example, the model projects consumers will bear a burden of $ 860 million, as a result of higher energy prices. In contrast, producer surplus increases by $ 853 million as energy producers, particularly the electricity industry, become more profitable with higher prices.

7.4 Executive Order 13211 ( Energy Effects)

Executive Order 13211, " Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use" ( 66 Fed. Reg. 28355 [ May 22, 2001]), requires EPA to prepare and submit a Statement of Energy Effects to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, for certain actions identified as " significant energy actions." Section 4( b) of Executive Order 13211 defines " significant energy actions" as " any action by an agency ( normally published in the Federal Register) that promulgates or is expected to lead to the promulgation of a final rule or regulation, including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed rulemaking:

° that is a significant regulatory action under Executive Order 12866 or any successor order, and is likely to have a significant adverse effect on the supply, distribution, or use of energy; or ° that is designated by the Administrator of the Office of Information and Regulatory Affairs as a significant energy action." 7 8 Given the magnitude of the annual costs, no Statement of Energy Effects will be completed. However, to provide some information on the impacts of the rule on affected Table 7 5. Distribution of Social Costs of Stationary Combustion Turbines MACT Standard: 2005 ($ 1998 106)

Change in:

Sectors/ Markets Producer Surplus Consumer Surplus Social Welfare Energy Sector Petroleum ( NAICS 32411, 4861) $ 55.56 NA NA Natural Gas ( NAICS 21111, 4862, 2212) $ 45.41 NA NA Electricity ( NAICS 22111, 221122, 221121) $ 1,297.01 NA NA Coal ( NAICS 2121)   $ 76.94 NA NA Subtotal: $ 1,321.05 NA NA Change in: Industrial Sector NAICS Description Producer Surplus Consumer Surplus Social Welfare 311 Food   $ 6.5   $ 4.9   $ 11.4 312 Beverage and Tobacco Products   $ 0.8   $ 0.4   $ 1.2 313 Textiles Mills   $ 3.3   $ 1.7   $ 5.0 314 Textile Product Mills   $ 0.6   $ 0.3   $ 0.9 315 Apparel   $ 0.5   $ 0.4   $ 0.9 316 Leather and Allied Products   $ 0.1   $ 0.1   $ 0.1 321 Wood Products   $ 2.0   $ 1.5   $ 3.5 322 Paper   $ 8.5   $ 4.3   $ 12.8 323 Printing and Related Support   $ 1.7   $ 0.7   $ 2.5 325 Chemicals   $ 22.9   $ 9.5   $ 32.5 326 Plastics and Rubber Products   $ 6.2   $ 2.6   $ 8.7 327 Nonmetallic Mineral Products   $ 4.1   $ 3.1   $ 7.1 331 Primary Metals   $ 15.2   $ 11.4   $ 26.7 332 Fabricated Metal Products   $ 1.9   $ 6.9   $ 8.8 333 Machinery   $ 1.9   $ 2.8   $ 4.7 334 Computer and Electronic Products   $ 1.8   $ 4.6   $ 6.4 335 Electrical Equipment, Appliances, and Components   $ 1.1   $ 1.6   $ 2.7 336 Transportation Equipment   $ 3.8   $ 5.7   $ 9.6 337 Furniture and Related Products   $ 1.0   $ 0.4   $ 1.5 339 Miscellaneous   $ 0.9   $ 1.1   $ 2.0 11 Agricultural Sector   $ 12.7   $ 5.3   $ 18.0 23 Construction Sector   $ 131.7   $ 98.7   $ 230.4 21 Other Mining Sector   $ 0.7   $ 1.6   $ 2.3 Industrial Sector Subtotal:   $ 229.9   $ 169.7   $ 399.6 Commercial Sector   $ 238.7   $ 179.0   $ 417.7 Residential Sector NA   $ 454.9   $ 454.9 Transportation Sector NA   $ 56.7   $ 56.7 Subtotal   $ 468.6   $ 860.3   $ 1,328.9 Grand Total $ 852.5   $ 860.3   7.8 7 9 energy markets, the following estimates have been prepared Energy Price Effects. As described in the market level results section, electricity prices are projected to increase by less than 1 percent. Petroleum and natural gas prices are all projected to increase by less than 0.1 percent. The price of coal is projected to decrease slightly.

Impacts on Electricity Supply, Distribution, and Use. We project the increased compliance costs for the electricity market will result in an annual production decline of approximately 20.4 billion kWh and a delay of new installed capacity of 7,480 MW. Note these effects have been mitigated to some degree in two ways:

° The delay in installed capacity is offset by increased supply from existing unaffected sources, implying that fewer older units may be retired as a result of the regulation.

° Sectors previously using electricity in the baseline will switch to other energy sources ( see below).

Impacts on Petroleum, Natural Gas, and Coal Supply, Distribution, and Use. The rule will lead to higher electricity prices relative to other fuel types, resulting in fuel switching. The model projects increases in petroleum production/ consumption of approximately 2,000 barrels per day. Similarly, natural gas production/ consumption is projected to increase by 11.7 million cubic feet per day. The model also projects decreases in coal production/ consumption of approximately 8,000 short tons per year. 8 1 SECTION 8 SMALL ENTITY IMPACTS The regulatory costs imposed on domestic producers and government entities to reduce air emissions from combustion turbines will have a direct impact on owners of the affected facilities. Firms or individuals that own the facilities with combustion turbines are legal business entities that have the capacity to conduct business transactions and make business decisions that affect the facility. The legal and financial responsibility for compliance with a regulatory action ultimately rests with these owners, who must bear the financial consequences of their decisions. Environmental regulations potentially affect all sizes of businesses, but small businesses may have special problems relative to large businesses in complying with such regulations.

The RFA of 1980 requires that special consideration be given to small entities affected by federal regulations. The RFA was amended in 1996 by SBREFA to strengthen the RFA's analytical and procedural requirements. Prior to enactment of SBREFA, EPA exceeded the requirements of the RFA by requiring the preparation of a regulatory flexibility analysis for every rule that would have any impact, no matter how minor, on any number, no matter how small, of small entities. Under SBREFA, however, the Agency decided to implement the RFA as written and to require a regulatory flexibility analysis only for rules that will have a significant impact on a substantial number of small entities. In practical terms, the amount of analysis of impacts to small entities has not changed, for SBREFA required EPA to increase involvement of small entities in the rulemaking process.

This section investigates characteristics of businesses and government entities that are likely to install new combustion turbines affected by this rule and provides a preliminary screening level analysis to assist in determining whether this rule is likely to impose a significant impact on a substantial number of the small businesses within this industry.

The screening level analysis employed here is a " sales test," which computes the annualized compliance costs as a share of sales/ revenue for existing companies/ government entities. Existing companies/ government entities with combustion turbines are used to provide insights into future companies/ government entities that are likely to install new turbines that are affected by the regulation. 1Public and private electric service providers are defined as small if their annual generation is less than 4 million kWh. Local government entities that own combustion turbines are defined as small if the city population is fewer than 50,000. In the manufacturing sector, companies are defined as small if the total employment of the parent company is fewer than 500.

8 2 8.1 Identifying Small Businesses As described in Section 3 of this report, the Agency has projected that approximately 218 new combustion turbines will begin operation during the 5 year period between 2002 and 2007. Of this population approximately 20 percent of the new turbines are projected to be located at major sources. Thus approximately 44 sources would be required to comply with the combustion turbines NESHAP. No existing combustion turbines will be effected by the regulation. However, because it is not possible to project specific companies or government organizations that will purchase combustion turbines in the future, the small business screening analysis for the combustion turbine rule is based on the evaluation of existing owners of combustion turbines. It is assumed that the existing size and ownership distribution of combustion turbines contained in the Inventory Database is representative of the future growth in new combustion turbines. The remainder of this section presents cost and sales information on small companies and government organizations that own existing combustion turbines of 1 MW or greater.

8.2 Screening Level Analysis Based on the Inventory Database and Small Business Administration ( SBA) definitions, 29 small entities own 51 units, which are located at 35 facilities. 1 The 51 units owned by small entities represent approximately 2.5 percent of the 2,072 units in the Inventory Database with valid capacity information. As with the total population, not all units owned by small entities will incur costs as a result of the regulation. However, because we do not have the information to determine which units will be affected, we have included all potentially affected small entities in the screening analysis, recognizing that this yields an overestimate of the impacts on small entities. 2The Inventory Database also contains small turbines that are not included in Table 8 1. These units, frequently referred to as " micro turbines," did not meet the 1 MW size requirements and are excluded from this rule. Six hundred thirty five units at 204 facilities in the Inventory Database had unit capacities under 1 MW. As a result, a large number of small entities potentially purchasing combustion turbines in the future will not be affected by the regulation due to the rule's size cutoff.

8 3 Table 8 1 presents the distribution of small entities by business type. 2 As is the case with the majority of turbine operators, ownership of turbines in the Inventory Database by small companies is concentrated in the electric services industry. In fact, 22 of small entities are municipalities that own and operate local utility systems. The remaining entities are either small energy ( e. g., oil and gas) firms or small manufacturing companies.

To assess the potential impact of this rule on the 29 small companies and government entities that own combustion turbines, the Agency considered the regulatory control costs presented in Section 7. For this screening level analysis, annual compliance costs were defined as the annualized costs of performance tests, monitoring, recordkeeping, and reporting imposed on each company or government entity assuming that it owned or were to install one turbine. The total annualized cost associated with these activities is $ 25,119 ( 1998 dollars). Control costs of oxidation catalysts and CEMs were not included in the screening analysis because the Agency estimates that only a small number units per year will require these add on capital costs. It is highly unlikely that small entities will be installing 170 MW turbines and would be required to install this equipment.

The results of this initial screening analysis are shown in Table 8 2. If each entity owned or were to install one turbine, the annual compliance costs, as a percentage of annual revenues, for small companies and government organizations would range from 0.01 to 0.46 percent. The average ( median) compliance cost to sales ratio ( CSR) is 0.11 percent. As shown, none of the small entities are affected above the 1 percent level.

8.3 Assessment The RFA generally requires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the Administrative Procedure Act or any other statute unless the agency certifies that the rule will not have a significant economic impact on a substantial number of small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions. 8 4 Table 8 1. Number of Units Greater than 1 MW at Small Parents by Industry NAICS Description Number of Units Number of Units Greater than 1 MW Owned by Small Parents Number of Small Parents 112 Animal Production 1 211 Oil and Gas Extraction 365 5 2 212 Mining ( Except Oil and Gas) 3 221 Utilities 983 35 22 233 Building, Developing, and General Contracting 1 235 Special Trade Contractors 2 311 Food Manufacturing 18 321 Wood Products Manufacturing 3 2 1 322 Paper Manufacturing 17 324 Petroleum and Coal Products Manufacturing 34 325 Chemical Manufacturing 63 1 1 326 Plastics and Rubber Products Manufacturing 4 327 Nonmetallic Mineral Product Manufacturing 1 331 Primary Metal Manufacturing 13 332 Fabricated metal Product Manufacturing 2 333 Machinery Manufacturing 2 334 Computer and Electronic Product Manufacturing 6 335 Electrical Equipment, Appliance, and Component Manufacturing 1 336 Transportation Equipment Manufacturing 3 1 1 337 Furniture and Related Product Manufacturing 1 339 Miscellaneous Manufacturing 3 422 Wholesale Trade, Nondurable Goods 6 486 Pipeline Transportation 448 7 2 488 Support Activities for Transportation 1 513 Broadcasting and Telecommunications 1 522 Credit Intermediation and Related Activities 3 541 Professional, Scientific, and Technical Services 2 561 Administrative and Support Services 1 611 Educational Services 10 622 Hospitals 23 721 Accommodation 1 923 Administration of Human Resource Programs 1 926 Administration of Economic Programs 1 928 National Security and International Affairs 42 Unknown Industry Classification Unknown 6 TOTAL 2,072 51 29 8 5 Table 8 2. Summary Statistics for SBREFA Screening Analysis: Recommended Alternative Total Number of Small Entities 29 Average Annual Compliance Cost per Small Entitya $ 15,059 Number Share (%)

Entities with Sales/ Revenue Data 29 100 Compliance costs are < 1% of sales 0 0 Compliance costs are $ 1 to 3% of sales 0 0 Compliance costs are $ 3% of sales 0 0 Compliance Cost to Sales/ Revenue Ratios Average 0.07 Median 0.04 Maximum 0.28 Minimum 0.01 aAssumes no market responses ( i. e., price and output adjustments) by regulated entities.

For purposes of assessing the impacts of today's rule on small entities, small entity is defined as:

C a small business whose parent company has fewer than 100 or 1,000 employees, depending on size definition for the affected NAICS code, or fewer than 4 billion kW hr per year of electricity usage;

C a small governmental jurisdiction that is a government of a city, county, town, school district, or special district with a population of fewer than 50,000; and C a small organization that is any not for profit enterprise, which is independently owned and operated and is not dominant in its field.

It should be noted that small entities in six three digit NAICS codes are affected by this rule, and the small business definition applied to each industry by NAICS code is that listed in the SBA size standards ( 13 CFR 121). 3The increasing trend is for local governments to engage in municipal aggregation and purchase long and shortterm power contracts through the emerging wholesale markets ( see Cliburn, 2001).

8 6 After considering the economic impacts of today's rule on small entities, this analysis determines this action will not have a significant economic impact on a substantial number of small entities. This certification is based on two analytical approaches:

C examining the hypothetical impacts on small entities based on the existing combustion turbines inventory, and presuming that the existing mix of combustion turbines among industries is a good approximation of the mix of new turbines that will be installed over the next 5 years, and C considering influences on the decision by small entities to install new turbines.

First, based on the existing combustion turbines inventory, this analysis determines that only 29 small entities out of 300 small entities would have been impacted by this rule if it had affected existing sources. These 29 small entities own 51 affected turbines in the existing combustion turbines inventory, which represents only 2.5 percent of the existing turbines overall. Of these entities, 22 of these entities are small communities and seven are small firms. None of the 29 affected small entities are estimated to have compliance costs that exceed 1 percent of their revenues. Based on industry profit margin ( i. e., profits per sales) data for the electric services industry ( 92 percent of all affected turbines) shown in the industry profile, the average return on sales for the industries is 4.6 percent. It should be noted that a comparison of profits with costs for small communities in this analysis is valid, for the small communities manage the electric services they own in a similar fashion to the small firms affected by this rule. No small entity is estimated to have compliance cost to sales of greater than the average return on sales. In addition, the rule is likely to also increase profits at the many small firms and increase revenues for the many small communities using turbines that are not affected by the rule as a result of the very slight increase in market prices.

Second, another approach to examining small entity impacts is to look at the influences on purchases of new turbines by small entities in the next 5 years. It is very likely that the ongoing deregulation of the electric power industry across the nation will minimize the rule's impacts on small entities. Increased competition in the electric power industry is forecasted to decrease the market price for wholesale electric power. Open access to the grid and lower market prices for electricity will make it less attractive for local communities to purchase and operate new combustion turbines. 3 Regardless of either analytical approach, 8 7 the Agency concludes that this rule will not have a significant impact on a substantial number of small entities.

Although this rule will not have a significant economic impact on a substantial number of small entities, EPA nonetheless has tried to reduce the impact of this rule on small entities. In this rule, the Agency is applying the minimum level of control and the minimum level of monitoring, recordkeeping, and reporting to affected sources allowed by the CAA. In addition, as mentioned earlier in the preamble, turbines with capacities under 1.0 MW are not covered by this rule. This provision should reduce the level of small entity impacts. EPA continues to be interested in the potential impacts of the rule on small entities and welcomes comments on issues related to such impacts. R 1 REFERENCES 1998 99 GTW Handbook. " Turnkey Combined Cycle Plant Budget Price Levels." Fairfield, CT: Pequot Pub. Pgs 19 26.

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Whelan, Michael. 1998. " Improving Compressor Station Performance: Getting at the Heart of the Matter." < http:// www. gri. org/ pub/ content/ sep/ 19990923/ 145119/ wtcompressor12. html>. A 1 ( A. 1) APPENDIX A OVERVIEW OF THE MARKET MODEL To develop estimates of the economic impacts on society resulting from the regulation, the Agency developed a computational model using a framework that is consistent with economic analyses performed for other rules. This approach employs standard microeconomic concepts to model behavioral responses expected to occur with the regulation. This appendix describes the spreadsheet model in detail and discusses how the Agency  characterized the supply and demand in the energy markets,

 characterized supply and demand responses in industrial and commercial markets,

 introduced a policy " shock" into the electricity market by using control costinduced shifts in the supply functions of affected supply segments ( new and existing sources),

 introduced indirect shifts in market supply functions resulting from changes in energy prices  used a solution algorithm to determine a new with regulation equilibrium in each market.

A. 1 Energy Markets The operational model includes five energy markets: coal, electricity ( base load energy), electricity ( peak power), natural gas, and petroleum. The following sections describe supply and demand equations the Agency developed to characterize these markets. The data source for the price and quantity data used to calibrate the model is the Department of Energy's Supplemental Tables to the Annual Energy Outlook 2000 ( DOE, EIA, 2001).

A. 1.1 Supply Side Modeling The Agency modeled the existing market supply of energy markets ( Q Si) using a single representative supplier with an upward sloping supply curve. The Cobb Douglas ( CD) function specification is A 2 ( A. 2)

( A. 3) where = the supply of energy product i,

A i = a parameter that calibrates the supply equation to replicate the estimated 2005 level of production ( Btu),

p i = the 2005 ($/ Btu) market price for product i, and c i = direct compliance costs ( electricity markets only). Supply shifts were computed and reported in Section 6, Table 6 2.

= indirect effects of changes in input prices, where   is the fuel share, i indexes the energy market. The fuel share is allowed to vary using a fuel switching rule using cross price elasticities of demand between energy sources, as described in Section 5 of the report.

= the domestic supply elasticity for product i.

For the electricity markets, new supply sources are characterized with a constant marginal cost ( supply) curve. In baseline, these units are willing to supply their generation capacity at the baseline market price ( P 0i). With regulation, affected sources are willing to supply their generation capacity if the new price ( P 1i) exceeds costs ( baseline + direct + indirect) :

A. 1.2 Demand Side Modeling Market demand in the energy markets ( Q Di) is expressed as the sum of the energy, residential, transportation, industrial, and commercial sectors: A 3 ( A. 4)

( A. 5)

( A. 6) where i indexes the energy market and j indexes the consuming sector. The Agency modeled the residential, and transportation sectors as single representative demanders using a simple Cobb Douglas specification:

where p is the market price,   is an assumed demand elasticity ( actual values are presented in Section 5, Table 5 2), and A is a demand parameter. In contrast, the energy, industrial and commercial sectors demand is modeled as a derived demand resulting from the production/ consumption choices in agricultural, energy, mining, manufacturing, and service industries. Changes in energy demand for these industries respond to changes in output and fuel switching that occurs in response to changes in relative energy prices projected in the energy markets. For each sector, energy demand is expressed as follows:

where q D is demand for energy, Q D is output in the final product or service market, FSW is a factor generated by the fuel switching algorithm, i indexes the energy market, j indexes the market. The subscripts 0 and 1 represent baseline and with regulation conditions, respectively.

A. 2 Industrial and Commercial Markets Given data limitations associated with the scope of potentially affected industrial and commercial markets, EPA used an alternative approach to estimate the relative changes in price and quantities. These measures are used to compute change in economic welfare as described in Section A. 4.

A. 2.1 Compute Percentage Change in Market Price First, we computed the change in production costs resulting from changes in the market price of fuels ( determined in the energy markets): 1The fuel share is allowed to vary using a fuel switching rule using cross price elasticities of demand between energy sources, as described in Section 5.

2The approach is based on a mathematical model of tax incidence analysis decribed in Nicholson ( 1998) pages 444 445.

A 4 ( A. 7) where   is the fuel share1, i indexes the energy market, and j indexes the industrial or commercial market. We use the results from equation A. 6 and the market supply and demand elasticities to compute the change in market price2:

A. 2.2 Compute Percentage Change in Market Quantity Using the percentage change in the price calculated in Equation A. 7 and assumptions regarding the market demand elasticity, the relative change in quantity was computed. For example, in a market where the demand elasticity is assumed to be  1 ( i. e., unitary), a 1 percent increase in price results in a 1 percent decrease in quantity. This change was then input into equation A. 5 to determine energy demand.

A. 3 With Regulation Market Equilibrium Determination Market adjustments can be conceptualized as an interactive feedback process. Supply segments face increased production costs as a result of the rule and are willing to supply smaller quantities at the baseline price. This reduction in market supply leads to an increase in the market price that all producers and consumers face, which leads to further responses by producers and consumers and thus new market prices, and so on. The new with regulation equilibrium is the result of a series of iterations in which price is adjusted and producers and consumers respond, until a set of stable market prices arises where total market supply equals market demand ( i. e., Qs = Q D) in each market. Market price adjustment takes place based on a price revision rule that adjusts price upward ( downward) by a given percentage in response to excess demand ( excess supply).

The algorithm for determining with regulation equilibria can be summarized by seven recursive steps: A 5 1. Impose the control costs on electricity supply segments, thereby affecting their supply decisions.

2. Recalculate the market supply in the energy markets. Excess demand exists.

3. Determine the new energy prices via a price revision rule.

4. Recalculate energy market supply.

5. Account for fuel switching given new energy prices. Solve for new equilibrium in final product and service market.

6. Compute energy demand.

7. Compare supply and demand in energy markets. If equilibrium conditions are not satisfied, go to Step 3, resulting in a new set of energy prices. Repeat until equilibrium conditions are satisfied ( i. e., the ratio of supply to demand is arbitrarily close to one).

A. 4 Computing Social Costs In the energy markets, consumers( residential and transportation) and producer surplus were calculated using standard methods based on the price and quantity before and after regulation. In the industrial and commercial markets, however, there is no easily defined price or quantity due to the wide variety of products that fall under each sector ( i. e. NAICs code). Therefore, methods of calculating consumer and producer surplus are defined based on relative changes in price and quantity and total industry sales rather than on the price and quantity directly. The following sections describe how we derive welfare estimates for these markets.

A. 4.1 Change in Consumer Surplus If price and quantities were available, a linear approximation of the change in consumer surplus can be calculated using the following formula:

 CS =   [ (  P) Q 0   0.5(  Q) (  P)], ( A. 8)

where Q 0 denotes the baseline quantity. Given the model only estimates relative changes in price and quantity for each industrial/ commercial market, changes in consumer surplus were calculated using these data and total revenue by NAICS code as shown below: 3Multiplying price and quantity in an industry yields total industry revenue. The U. S. Census Bureau provides shipment data for the NAICs codes included in the economic model.

A 6   CS =   [ (  P) Q 1   0.5 (  Q) (  P)] ( P 1 Q 1)/( P 1 Q 1)

 CS =   [ %  P   0.5 (%  P) (%  Q)] ( P 1 Q 1). ( A. 9)

A. 4.2 Change in Producer Surplus If price and quantities were available, a linear approximation could also be used to compute the change in producer surplus:

  PS =   [ (( CC/ Q 1)     P)( Q 1     Q)]+ 0.5 [( CC/ Q 1     P) (  Q)], ( A. 10)

where CC/ Q 1 equals the per unit " cost shifter" of the regulation. Again, we transform this equation into one that relies only on percentage changes in price and quantity, total revenue, 3 and compliance costs:

  PS =   [(( CC/ Q 1)     P)( Q 1     Q)]+ 0.5 [(( CC/ Q 1)     P)(  Q)]( P 1 Q 1)/( P 1 Q 1)

  PS =   [(% cost shift   %  P)( 1   %  Q)+ 0.5 (% cost shift   %  P )(%  Q)][ P 1 Q 1]

  PS =   [% cost shift   %  P ][ 1   0.5(%  Q)][ TR], ( A. 11) B 1 APPENDIX B ASSUMPTIONS AND SENSITIVITY ANALYSIS In developing the economic model to estimate the impacts of the stationary combustion turbine NESHAP, several assumptions were necessary to make the model operational. This appendix lists and explains the major model assumptions and describes their potential impact on the analysis results. Sensitivity analyses are presented for numeric assumptions.

Assumption: The domestic markets for energy are perfectly competitive.

Explanation: Assuming that the markets for energy are perfectly competitive implies that individual producers are not capable of unilaterally affecting the prices they receive for their products. Under perfect competition, firms that raise their price above the competitive price are unable to sell at that higher price because they are a small share of the market and consumers can easily buy from one of a multitude of other firms that are selling at the competitive price level. Given the relatively homogeneous nature of individual energy products ( petroleum, coal, natural gas, electricity), the assumption of perfect competition at the national level seems to be appropriate.

Possible Impact: If energy markets were in fact imperfectly competitive, implying that individual producers can exercise market power and thus affect the prices they receive for their products, then the economic model would understate possible increases in the price of energy due to the regulation as well as the social costs of the regulation. Under imperfect competition, energy producers would be able to pass along more of the costs of the regulation to consumers; thus, consumer surplus losses would be greater, and producer surplus losses would be smaller in the energy markets.

Assumption: Base load energy and peak power represent 80 percent and 20 percent, respectively, of the total cost of electricity production.

Explanation: With deregulation, it is increasingly common for base load energy and peak power to be traded as different commodities. This economic model segments the electricity market into these separate markets. However, no production cost or sales data are currently available to partition the electricity market into base load and peak power markets. The 80/ 20 percent was obtained from discussions with industry experts. B 2 Sensitivity Analysis: Table B 1 shows how estimated economic impacts change as the share of base load versus peak power costs varies.

Assumption: The elasticity of supply in the base load and peak power electricity markets for existing sources is approximately 0.75 and 0.38, respectively.

Explanation: The price elasticity of supply in the electricity markets represents the behavioral responses from existing sources to changes in the price of electricity. However, there is no consensus on estimates of the price elasticity of supply for electricity. This is in part because, under traditional regulation, the electric utility industry had a mandate to serve all its customers and utilities were compensated on a rate based rate of return. As a result, the market concept of supply elasticity was not the driving force in utilities' capital investment decisions. This has changed under deregulation. The market price for electricity has become the determining factor in decisions to retire older units or to make higher cost units available to the market.

Sensitivity Analysis: Table B 2 shows how the economic impact estimates vary as the elasticity of supply in the electricity markets varies. Table B 1. Sensitivity Analysis: Base Load and Peak Power Markets' Share of Electricity Production Costs ($ 106)

Base Load = 70% Peak = 30% Base Load = 80% Peak = 20% Base Load = 90% Peak = 10%

Change in producer surplus 870.4 852.5 835.2 Change in consumer surplus   878.6   860.3   842.7 Change in social welfare   8.1   7.8   7.5 Table B 2. Sensitivity Analysis: Elasticity of Supply in the Electricity Markets ES =   25% Base Case ES = + 25%

Change in producer surplus 942.4 852.5 778.8 Change in consumer surplus   951.2   860.3   785.8 Change in social welfare   8.8   7.8   7.0 B 3 Assumption: The domestic markets for final products and services are all perfectly competitive.

Explanation: Assuming that these markets are perfectly competitive implies that the producers of these products are unable to unilaterally affect the prices they receive for their products. Because the industries used in this analysis are aggregated across a large number of individual producers, it is a reasonable assumption that the individual producers have a very small share of industry sales and cannot individually influence the price of output from that industry.

Possible Impact: If these product markets were in fact imperfectly competitive, implying that individual producers can exercise market power and thus affect the prices they receive for their products, then the economic model would understate possible increases in the price of final products due to the regulation as well as the social costs of the regulation. Under imperfect competition, producers would be able to pass along more of the costs of the regulation to consumers; thus, consumer surplus losses would be greater, and producer surplus losses would be smaller in the final product markets.

Assumption: The elasticity of supply in final product markets.

Explanation: The final product markets are modeled at the two, and three digit NAICS codes level to operationalize the economic model. Because of the high level of aggregation, elasticities of supply and demand estimates are not often available in the literature. The elasticities of supply and demand in the final product markets primarily determine the distribution of economic impacts between producers and consumers.

Sensitivity Analysis: Table B 3 shows how the economic impact estimates vary as the supply and demand elasticities in the final product markets vary.

Table B 3. Sensitivity Analysis: Supply and Demand Elasticities in the Final Product Markets ES =   25% ED =   25% ES = Base Case ED = Base Case ES = + 25% ED = + 25%

Change in producer surplus 853.0 852.5 851.9 Change in consumer surplus   860.9   860.3   859.8 Change in social welfare   7.8   7.8   7.8 B 4 Assumption: The amount of energy ( in terms of Btus) required to produce a unit of output in the final product markets remains constant as output changes and prices.

Explanation: The importance of this assumption is that when output in the final product markets changes as a result of a change in energy prices, it is assumed that the amount of fuel used changes in the same proportion as output, although the distribution of fuel usage among fuel types may change due to fuel switching. This change in the demand for fuels feeds into the energy markets and affects the equilibrium price and quantity in the energy markets.

Possible Impact: For example, fuel usage per unit output may change if the price of energy increases because of increased energy efficiency. National energy efficiency trends are included in the model through projected Btu consumption ( i. e., Btu consumption is projected to grow more slowly than output). However, if the regulation leads to increased energy efficiency because of higher fuel prices, this will result in a smaller economic impact than the model results presented in Section 6 indicate.

Assumption: Sensitivity to Fuel Switching.

Sensitivity Analysis: Table B 4 shows how the economic impact estimates vary as fuelswitching is turned on or off in the model.

Table B 4. Sensitivity Analysis: Own and Cross Price Elasticities Used to Model Fuel Switching Base Case Without Fuel Switching Change in producer surplus 852.5 194.2 Change in consumer surplus   860.3   208.6 Change in social welfare   7.8   14.3 TECHNICAL REPORT DATA ( Please read Instructions on reverse before completing)

1. REPORT NO.

EPA 452/ R 03 014 2. 3. RECIPIENT'S ACCESSION NO.

4. TITLE AND SUBTITLE Economic Impact Analysis of the Final Stationary Combustion Turbines NESHAP: Final Report 5. REPORT DATE August 2003 6. PERFORMING ORGANIZATION CODE 7. AUTHOR( S) 8. PERFORMING ORGANIZATION REPORT NO.

RTI Project Number 7647 004 385 9. PERFORMING ORGANIZATION NAME AND ADDRESS RTI International Center for Regulatory Economics and Policy Research, Hobbs Bldg. Research Triangle Park, NC 27709 10. PROGRAM ELEMENT NO.

11. CONTRACT/ GRANT NO.

68 D 99 024 12. SPONSORING AGENCY NAME AND ADDRESS Director Office of Air Quality Planning and Standards Office of Air and Radiation U. S. Environmental Protection Agency Research Triangle Park, NC 27711 13. TYPE OF REPORT AND PERIOD COVERED 14. SPONSORING AGENCY CODE EPA/ 200/ 04 15. SUPPLEMENTARY NOTES 16. ABSTRACT This report evaluates the economic impacts of the Final Stationary Combustion Turbines NESHAP. The social costs of the rule are estimated by incorporating the expected costs of compliance in a partial equilibrium model and projecting the market impacts. The report also provides the screening analysis for small business impacts.

17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b. IDENTIFIERS/ OPEN ENDED TERMS c. COSATI Field/ Group economic impacts small business impacts social costs Air Pollution Control Economic Impact Analysis Regulatory Flexibility Analysis 18. DISTRIBUTION STATEMENT Release Unlimited 19. SECURITY CLASS ( Report)

Unclassified 21. NO. OF PAGES 156 20. SECURITY CLASS ( Page)

Unclassified 22. PRICE EPA Form 2220 1 ( Rev. 4 77) PREVIOUS EDITION IS OBSOLETE United States Office of Air Quality Planning and Standards Publication No. EPA 452/ R 03 014 Environmental Protection Air Quality Strategies and Standards Division August 2003 Agency Research Triangle Park, NC