OMB Review Draft December 17, 2003 4 1 SECTION 4 ECONOMIC IMPACT ANALYSIS Congress and the Executive Office have imposed statutory and administrative requirements for conducting economic analyses to accompany regulatory actions. Section 317 of the CAA specifically requires estimation of the cost and economic impacts for specific regulations and standards promulgated under the authority of the Act. In addition, Executive Order ( EO) 12866 requires a more comprehensive analysis of benefits and costs for significant regulatory actions. Office of Management and Budget ( OMB) guidance under EO 12866 stipulates that a full benefit cost analysis is only required when a regulatory action has an annual effect on the economy of $ 100 million or more. Other statutory and administrative requirements include examination of the composition and distribution of benefits and costs. For example, the Regulatory Flexibility Act ( RFA), as amended by the Small Business Regulatory Enforcement and Fairness Act of 1996 ( SBREFA), requires EPA to consider the economic impacts of regulatory actions on small entities. The OAQPS Economic Analysis Resource Document, which can be found at http:// www. epa. gov/ ttn/ ecas/ econdata/ Rmanual2/ index. html , provides detailed instructions and expectations for economic analyses that support rulemaking ( EPA, 1999).

The engineering analysis described in Section 3 provides estimates of the total annual costs associated with the abatement strategies that bring each facility into compliance with the final standards. Note, however, that these engineering cost estimates do not account for behavioral responses by facilities, such as changes in output quantities and prices. In this section, engineering cost estimates are used as inputs to an economic model of the automobile and LDT assembly industry to predict market, industry and social welfare impacts of the final regulation. Small business impacts are addressed in Section 5 and a benefits analysis is presented in Section 6 of this report.

4.1 Methodology This analysis will address several special characteristics of the automobile industry. First, the industry's products are highly differentiated with vehicles varying along dimensions such as their functions, carrying capacity, fuel efficiency, and comfort features. OMB Review Draft December 17, 2003 1Exclusive dealership arrangements are also found in the sewing machine, agricultural machinery and gasoline markets.

2EPA's 1999 Fuel Economy Guide Data ( EPA, 2000), car buyers guides such as Edmunds. com ( Edmunds, 2001), and the Automotive News Market Databook ( Crain Automotive Group, 2000) were used to assign vehicle models to the appropriate market segments.

3Recall that a semi elasticity refers to the percentage change in quantity demanded of model j when price of model i changes by $ 1 but all other model prices remain unchanged.

4 2 Second, the market for automobiles within the United States may be characterized as imperfectly competitive. Only 14 companies operate in this market. In 1998 1999, the Herfindahl Hirschmann Index for the industry was 1,471, and the four firm concentration ratio ( CR4) was 72 percent. Third, exclusive dealerships play an intermediary role between manufacturers and final consumers. 1 Finally, international trade is a major component of the U. S. market for automobiles. In 1999, imports accounted for approximately 20 percent of car sales in the United States ( Crain Automotive Group, 2000). Given the data available, we will evaluate the economic effects of the final regulation at the facility level within the context of the overall industry conditions. This approach is consistent with accepted economic logic and provides consistent estimates for the impacts on all the required variables.

4.1.1 Product Differentiation To address the high degree of product differentiation in this industry, the Agency has segmented the market into eight vehicle classes: subcompacts, compacts, intermediate/ standard, luxury, sports, pickups, vans, and other. 2 Separate demand and cost curves are developed for each of these market segments.

Since all domestic vehicle categories are subject to price changes due to the final regulation, we will estimate the consumer response to these price changes within each vehicle class. However, we will not estimate spillover impacts between domestic vehicle classes because available estimates of the cross price elasticities of demand suggest that consumers rarely substitute between vehicle classes in response to relatively small price changes. In particular, Goldberg ( 1995) estimates cross price semi elasticities of demand for some specific vehicle models and finds that these semi elasticities are low if the models belong to different classes. 3 For example, the cross price semi elasticity between a Honda Civic and a Honda Accord is only 14.9 × 10 7. Furthermore, our priors suggest that the tendency to switch between vehicle categories will be low given the relatively small OMB Review Draft December 17, 2003 4 3 magnitude of price changes expected for this NESHAP. Therefore, our basic market segmented model is designed to capture the within segment, first order impacts of the regulation.

4.1.2 Imperfect Competition Although the U. S. automobile industry comprises 14 firms, a smaller subset of these firms operates within each vehicle category segment. Given our assumption of imperfect competition in the industry as a whole and within each segment in particular, we will use a Cournot model to characterize the market for each vehicle category. The implicit assumption is that vehicles within a given category are close substitutes. In the Cournot model, one of several models of oligopoly, firms are modeled as choosing production quantities. Unlike a competitive market, in which the price equals the marginal cost of production and firms take the price as given, the Cournot model reflects the fact that automobile manufacturers may have market power and thus charge a price in excess of marginal cost by producing a quantity that is less than in a competitive equilibrium.

4.1.3 Role of Dealerships Manufacturers in the U. S. automobile industry do not actually set final consumer prices. Instead, they set wholesale prices for dealers which are then marked up to form retail or list prices. The final transaction price paid by the consumer can also differ from these retail prices because of dealer specific rebates, local and state taxes, and individual bargaining power. This pricing scheme is summarized in Figure 4 1. Note that manufacturer decisions are based on wholesale prices, while consumer decisions are based on transaction prices.

This relationship can be viewed as a successive oligopoly game, with the manufacturer adding a markup over the marginal cost of production, and the dealer adding Wholesale Price List Price Transaction Price Manufacturer Dealer Consumer Figure 4 1. Pricing in Automobile Markets OMB Review Draft December 17, 2003 4All production facilities located within the United States are subject to the final NESHAP regardless of whether they are owned by domestic or foreign companies. For the purposes of this analysis, imports refers to vehicles produced outside of the United States.

4 4 his own markup. In stage 1, the manufacturer maximizes his profits by comparing his marginal costs to his marginal revenues. His marginal revenue depends on the wholesale price and the wholesale price elasticity of demand. In the second stage, the dealer maximizes her profits by comparing her own marginal costs to her marginal revenue, which depends on the transaction price and the transaction price elasticity of demand.

If the marginal cost of production increases, the impacts can be borne by the manufacturer who changes input output quantities, the dealer who earns a reduced markup, or the consumer who faces a higher list price. Gron and Swenson ( 2000) examine the degree of cost pass through to final consumers in the U. S. automobile market. They find that cost shocks common to all manufacturers have a greater effect on list price than do modelspecific cost shocks. This is consistent with the theoretical predictions of Dornbusch ( 1987) who showed in the context of exchange rate shocks that firms competing in a Cournot game will increase the level of cost pass through as the proportion of the market that is exposed to the cost increase grows.

Because the final regulation covers all facilities assembling vehicles in the United States, we have made the simplifying assumption that the dealer can charge the same percentage markup as before the regulation. Assuming that the percentage markup ( including discounts, taxes, etc.) between the wholesale price ( PW) and the transaction price ( PT) is constant, i. e. PW = 8PT, the demand elasticity with respect to wholesale prices coincides with the transaction price elasticity. Thus we can collapse the two stage game between the manufacturer, dealer, and consumer to a one stage game between the manufacturer and a " composite customer" ( dealer/ consumer).

4.1.4 Foreign Trade While the final NESHAP will directly affect domestic facilities that use coatings in automobile and LDT assembly operations, the rule can also have indirect foreign trade implications. 4 On the import side, the demand for imported cars could increase if they become inexpensive relative to domestic cars that are affected by the coating process standard. We will assume that foreign firms can meet this spillover demand by using excess capacity in their existing plants. On the export side, foreign demand for vehicles produced in the United States can decrease if they become relatively more expensive because of the OMB Review Draft December 17, 2003 4 5 regulation. Finally, domestic facilities could relocate to foreign countries with laxer environmental regulations if domestic production costs increase. However, given the small size of the compliance costs relative to company sale it is unlikely that the final regulations will trigger industrial flight at least in the short run. This assumption is consistent with empirical studies in the literature that have found little evidence of environmental regulations affecting industry location decisions ( Levinson, 1996). This discussion illustrates the theory underlying estimation of the economic impacts of the final MACT standard. The next task is to operationalize this model to calculate the impacts.

4.2 Operational Model The final regulation will increase the cost of production for existing vehicle assembly plants. The regulated facilities may alter their current levels of production or even close a plant in response to the increased costs. These responses will in turn determine the impact of the regulation on total market supply and ultimately on the equilibrium price and quantity. To determine the impact on equilibrium price and quantity, we will C characterize the demand for each domestic vehicle type;

C characterize the costs of production for classes of domestic vehicles at the individual facility and at the market level;

C develop the solution algorithm to determine the new with regulation equilibrium;

C characterize spillover impacts on the demand for imported and exported cars and LDTs; and C compute the values for all the impact variables.

An intuitive overview of our economic model is presented below. Details of the modeling exercise and its implementation are relegated to Appendix A.

The Agency has modeled separate markets for each of the eight vehicle categories: subcompacts, compacts, intermediate/ standard, luxury, sports, pickups, vans, and other. Given the imperfect competition observed within each market segment, Cournot models are used to reflect the fact that oligopolistic manufacturers can charge a price in excess of marginal cost by producing a quantity that is less than the competitive optimum.

U. S. demand for domestic vehicles in each category is characterized by a downwardsloping demand curve, which implies that the quantity demanded is low when prices are high and quantity demanded is high when prices are low due to the usual income and substitution OMB Review Draft December 17, 2003 4 6 P0 P Q0 Q D MR MC0 Figure 4 2. Baseline Equilibrium effects. The demand curve for each vehicle category is constructed using baseline quantity and retail price data and available estimates of own price elasticities of demand.

Given the capital in place, each automobile and LDT assembly facility will be assumed to face an upward sloping marginal cost function. In addition, it is assumed that if revenue falls below its minimum average variable costs, then the firm's best response is to cease production because total revenue does not cover total variable costs of production. In this scenario, producers lose money on operations as well as capital. By shutting down, the firm avoids additional losses from operations.

Figure 4 2 shows how the market prices and quantities are determined by the intersection of the marginal revenue and marginal cost curves in a concentrated market model. The baseline consists of a market price and quantity ( P0, Q0) that is determined by the downward sloping market demand curve ( D) and the upward sloping marginal cost curve ( MC0) that reflects the sum of the individual marginal cost curves of the assembly facilities. Any individual supplier would produce amount Q0 ( at price P0) and the facilities would collectively produce amount Q0. OMB Review Draft December 17, 2003 4 7 P0 P Q0 Q D MR Q1 P1 MC1 MC0 Figure 4 3. With Regulation Equilibrium Now consider the effect of the regulatory control costs ( see Figure 4 3). Incorporating the regulatory control costs will involve shifting the marginal cost curve upward for each regulated facility by the per unit variable compliance cost. As a result, the market output declines from Q0 to Q1 and the market price ( as determined from the market demand curve, DM) increases from P0 to P1.

Because the final coating standard will only be binding on automobile and LDT assembly facilities operating within the U. S., the Agency has also modeled the impact of the predicted domestic price increase on foreign trade. Imports of foreign vehicles into the U. S. could increase because they become cheap relative to domestic vehicles. The ratio between quantities of imported versus domestic vehicles purchased by U. S. consumers is modeled as a function of their relative prices and the ease of substitution between these vehicles. Exports of U. S. made vehicles can also decline if their price increases while other exogenous determinants of foreign demand are held constant. Foreign demand is modeled as a downward sloping function that depends on average price of exported U. S. vehicles and the export elasticity of demand. OMB Review Draft December 17, 2003 4 8 4.3 Economic Impact Results Based on the simple analytics presented above, automobile/ LDT manufacturers will attempt to mitigate the impacts of higher production costs by shifting as much of the burden on other economic agents as market conditions allow. Potential responses include changes in production processes and inputs, changes in output rates, or closure of the plant. This analysis focuses on the last two options because they appear to be the most viable for auto assembly plants, at least in the short term. We expect upward pressure on prices as producers reduce output rates. Higher prices reduce quantity demanded and output for each vehicle class, leading to changes in profitability of facilities and their parent companies. These market and industry adjustments determine the social costs of the regulation and its distribution across stakeholders ( producers and consumers).

4.3.1 Market Level Impacts The increased costs of production due to the regulation are expected to slightly increase the price of automobiles/ LDT and reduce their production and consumption from 1999 baseline levels. As shown in Table 4 1, the regulation is projected to increase the price of all vehicle classes by at most 0.01 percent ( or at most $ 3.08 per vehicle). Similarly, the model projects small declines in domestic production across all vehicle classes ( ranging from 17 to 384 vehicles).

4.3.2 Industry Level Impacts Industry revenue, costs, and profitability change as prices and production levels adjust in response to the increased compliance costs. These impacts are described in detail below.

<IP_ADDRESS> Changes in Profitability As shown in Table 4 2, the economic model projects that pre tax earnings for assembly plants will decrease by $ 152 million, or 1.1 percent. This is the net result of three effects, the first two of which partially offset each other:

C Decrease in revenue ($ 21 million): Revenue decreases as a result of reductions in output. However, these losses were mitigated by increased revenues as a result of small increases in vehicle prices.

C Decrease in production costs ($ 22.5 million): Production costs decline as output declines. OMB Review Draft December 17, 2003 4 9 Table 4 1. Market Level Impacts by Vehicle Class: 1999 Vehicle Class Baseline Absolute Change Relative Change Subcompacts Wholesale Price ($/ unit) $ 15,522 $ 0.40 0.00%

Domestic Production ( 103/ yr) 586,257   50   0.01%

Compacts Wholesale Price ($/ unit) $ 16,487 $ 1.05 0.01%

Domestic Production ( 103/ yr) 1,766,657   384   0.02%

Intermediate/ Standard Wholesale Price ($/ unit) $ 21,155 $ 0.61 0.00%

Domestic Production ( 103/ yr) 2,187,415   280   0.01%

Luxury Wholesale Price ($/ unit) $ 33,587 $ 3.08 0.01%

Domestic Production ( 103/ yr) 749,746   131   0.02%

Sports Wholesale Price ($/ unit) $ 25,797 $ 1.21 0.00%

Domestic Production ( 103/ yr) 349,955   17 0.00%

Pickups Wholesale Price ($/ unit) $ 22,126 $ 0.23 0.00%

Domestic Production ( 103/ yr) 2,908,018   106 0.00%

Vans Wholesale Price ($/ unit) $ 22,910 $ 0.80 0.00%

Domestic Production ( 103/ yr) 1,447,482   220   0.02%

SUV Wholesale Price ($/ unit) $ 27,694 $ 0.41 0.00%

Domestic Production ( 103/ yr) 2,692,763   163   0.01% OMB Review Draft December 17, 2003 4 10 C Increase in control costs ($ 154 million): Costs associated with coating operation HAP controls increase.

Although aggregate industry pre tax earnings decline, the regulation creates both winners and losers based on the distribution of compliance costs across facilities. As shown in Table 4 3, 18 of the 65 plants ( 28 percent) are projected to become more profitable with the regulation with a total gain of $ 2 million. These plants are either not subject to additional controls or have lower per unit control costs ( less than $ 1 per vehicle) relative to other assembly plants. The remaining 47 plants are projected to experience a total loss of $ 154 million. These plants have higher per unit costs ($ 16 per vehicle on average). This results in an average loss of $ 3.3 million and represents a 1.5 percent decline in the average pre tax profit of these plants.

<IP_ADDRESS> Facility Closures and Changes in Employment Economic theory suggests that a facility will cease production if market prices fall below the minimum average variable cost. EPA estimates that no automobile or LDT assembly plant is likely to prematurely close as a result of the regulation. However, employment in the automobile and LDT assembly industry is projected to decrease by 37 full time equivalents ( FTEs) as a result of decreased output levels. This represents a 0.02 percent decline in manufacturing employment at these assembly plants. Table 4 2. National Level Industry Impacts: 1999 Baseline Absolute Change Relative Change Revenues ($ 106/ yr) $ 290,789   $ 20.7   0.01%

Costs ($ 106/ yr) $ 276,746 $ 131.1 0.05%

Compliance $ 0 $ 153.6 NA Production $ 276,746   $ 22.5   0.01%

Pre Tax Earnings ($ 106/ yr) $ 14,043   $ 151.8   1.08%

Plants (#) 65 0 0.00%

Employment (#) 219,817   37   0.02% OMB Review Draft December 17, 2003 4 11 4.3.3 Foreign Trade Given the small changes in domestic vehicle prices projected by the economic model, EPA estimates foreign trade impacts associated with the rule are negligible. The price of domestic vehicles, averaged across all eight vehicle categories, is expected to rise by 0.003 percent as a result of the final regulation, while the price of imported cars will remain unchanged. The Agency computed two quantitative measures of foreign trade impacts based on this predicted price impact. As shown in Table 4 4, the ratio of imports to domestic sales is expected to rise by approximately 0.01 percent. Furthermore, export sales are predicted to decline by approximately 0.01 percent.

4.3.4 Social Costs The social impact of a regulatory action is traditionally measured by the change in economic welfare that it generates. The social costs of the final rule will be distributed across consumers and producers alike. Consumers experience welfare impacts due to changes in market prices and consumption levels associated with the rule. Producers experience welfare impacts resulting from changes in profits corresponding with the changes Table 4 3. Distributional Impacts Across Facilities: 1999 Pre Tax Earnings Total Loss Gain Assembly Plants (#) 47 18 65 Baseline Production Total ( units/ yr) 9,642,611 3,045,681 12,688,292 Average ( units/ facility) 205,162 169,205 195,204 Baseline Compliance Costs Total ($ 106/ yr) $ 153.2 $ 0.5 $ 153.66 Average ($/ unit) $ 15.89 $ 0.16 $ 12.11 Change in Pre Tax Earnings ($ 106/ yr)   $ 153.6 $ 1.7   $ 151.8 Change in Employment (#)   37 1   37 OMB Review Draft December 17, 2003 5Those impacts are the focus of the benefits analysis presented in Section 6 of this report.

4 12 in production levels and market prices. 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 due to the regulation. 5 The national baseline compliance cost estimates are often used as an approximation of the social cost of the rule. The engineering analysis estimated annual costs of $ 154 million ( 1999$). In this case, the burden of the regulation falls solely on the affected facilities that 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. This is typically referred to as a " full cost absorption" scenario in which 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 ( i. e., shifting costs to other economic agents). This approach results in a social cost estimate that may differ from the engineering estimate and also provides insights on how the regulatory burden is distributed across stakeholders.

Higher market prices lead to consumer losses of $ 9.1 million, or 6 percent of the total social cost of the rule. Although automobile or LDT producers are able to pass on a limited amount of cost increases to final consumers, the increased costs result in a net decline in profits at assembly plants of $ 152 million. As shown in Table 4 5, EPA estimates the total social cost of the rule to be $ 161 million. Note that social cost estimates exceeds baseline engineering cost estimates by $ 7 million. The projected change in welfare is higher because the regulation exacerbates a social inefficiency ( see Appendix B). In an imperfectly competitive equilibrium, the marginal benefit consumers place on the vehicles, the market price, exceeds the marginal cost to producers of manufacturing the product. Thus, social Table 4 4. Foreign Trade Impacts: 1999 % change Ratio of imports to domestic vehicles 0.01%

Exports   0.01% OMB Review Draft December 17, 2003 4 13 welfare would be improved by increasing the quantity of the vehicles provided. However, producers have no incentive to do this because the marginal revenue effects of lowering the price and increasing output is lower than the marginal cost of these extra units.

4.4 Energy Impacts Executive Order 13211 " Actions Concerning Regulations that Significantly Affect Energy Supply, Distribution, or Use" ( 66 Fed. Reg. 28355, May 22, 2001) requires federal agencies to estimate the energy impact of significant regulatory actions. The final NESHAP will trigger both an increase in energy use due to the operation of new abatement equipment as well as a decrease in energy use due to a small decline in automobile production. The net impact will be an overall increase in the automobile industry's energy costs by about $ 26.41 million per year. These impacts are discussed below in greater detail.

4.4.1 Increase in Energy Consumption As described earlier in Section 3 of this report, automobile and LDT coating facilities can adopt multiple strategies to reduce their HAP emissions in compliance with the final regulation. Input substitution strategies 2 and 3 will not require significant amounts of extra energy because they only involve the application of modified coating materials. However, adoption of strategy 1 and/ or strategy 4 will necessitate extra fan horsepower to convey Table 4 5. Distribution of Social Costs: 1999$ Value ($ 106/ yr)

Change in Consumer Surplus   $ 9.1 Subcompacts   $ 0.2 Compacts   $ 1.9 Intermediate/ Standard   $ 1.3 Luxury   $ 2.3 Sports   $ 0.4 Pickups   $ 0.7 Vans   $ 1.2 SUV   $ 1.1 Change in Producer Surplus   $ 151.8 Total Social Cost   $ 160.9 OMB Review Draft December 17, 2003 4 14 additional air streams to add on control devices, as well as additional natural gas and electricity for operating these devices ( which are assumed to be regenerative thermal oxidizers). The operation of such abatement equipment is estimated to require an additional 4.9x109 standard cubic feet per year of natural gas and 1.8x108 kilowatt hours per year of electricity nationwide at a cost of $ 3.20 per thousand cubic feet of natural gas and $ 0.06 per kilowatt hour of electricity ( Green, 2002). Therefore, the nationwide cost of the energy needed to operate the control equipment required by strategies 1 and 4 is estimated at $ 26.48 million per year. This incremental energy cost was included in the operation and maintenance component of the engineering cost estimates presented in Section 3.

4.4.2 Reduction in Energy Consumption The economic model described in Section 4.2 predicts that increased compliance costs will result in an annual production decline of approximately 1,300 vehicles valued at $ 21 million collectively. This production decline will lead to a corresponding decline in energy usage by automobile manufacturers. EPA has computed an average " energy per unit output ratio" and multiplied it by the decline in production to quantify this impact.

Census data presented in Table 4 6 indicates that the U. S. automobile and LDT industry incurred energy costs of $ 669 million to produce $ 205.8 billion worth of vehicles in 1997. This translates into an energy consumption per unit of output ratio of about 0.3 percent for the automobile and LDT industry. Therefore, energy costs are estimated to decline by approximately $ 0.07 million per year if the industry's production declines by 1,300 vehicles valued at $ 21 million per year.

4.4.3 Net Impact on Energy Consumption The operation of additional abatement capital is estimated to result in an increase in energy use worth $ 26.48 million per year, while the decline in automobile production will result in a decrease in energy use worth $ 0.07 million per year. These competing factors will result in a net increase in annual energy consumption by the automobile industry of approximately $ 26.41 million, on balance.

The total electricity generation capacity in the U. S. was 785,990 Megawatts in 1999 ( DOE, 1999a). Thus, the electricity requirements associated with the additional abatement capital represent a small fraction of domestic generation capacity. Similarly, the natural gas requirements associated with the final NESHAP are insignificant given the 23,755 billion OMB Review Draft December 17, 2003 4 15 cubic feet of natural gas produced domestically in the U. S. in 1999 ( DOE, 1999b). Hence, the final NESHAP is not likely to have any significant adverse impact on energy prices, distribution, availability, or use. Table 4 6. Energy Usage in Automobile and LDT Production ( 1997)

Industrial Sector NAICS Value of Shipments ($ 106) Fuel & Electricity Costs ($ 106)

Automobile Mfg. 336111 $ 95,385 $ 339 Light Truck and Utility Vehicle Mfg. 336112 $ 110,400 $ 330 Total $ 205,785 $ 669 Source: U. S. Department of Commerce, Census Bureau. October 1999a. " Automobile Manufacturing." 1997 Economic Census Manufacturing Industry Series. EC97M0 3361A. Washington, DC: Government Printing Office.

U. S. Department of Commerce, Census Bureau. October 1999b. " Light Truck and Utility Vehicle Manufacturing." 1997 Economic Census Manufacturing Industry Series. EC97M 3361B. Washington, DC: Government Printing Office. OMB Review Draft December 17, 2003 5 1 SECTION 5 OTHER IMPACT ANALYSES The economic and energy impacts associated with the final NESHAP were described in the previous section. Statements discussing additional impacts on small businesses, unfunded mandates, and new sources are presented below.

5.1 Small Business Impacts The Regulatory Flexibility Act ( RFA) of 1980 as amended in 1996 by the Small Business Regulatory Enforcement Fairness Act ( SBREFA) generally requires an agency to prepare a regulatory flexibility analysis of a rule 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.

For purposes of assessing the impacts of the final rule on small entities, a small entity is defined as: ( 1) a small business that is a parent company according to Small Business Administration ( SBA) size standards for NAICS codes 336111 ( automobile manufacturing) and 336112 ( light truck and utility vehicle manufacturing) with 1,000 or fewer employees; ( 2) a small governmental jurisdiction that is a government of a city, county, town, school district or special district with a population of less than 50,000; and ( 3) a small organization that is any not for profit enterprise which is independently owned and operated and is not dominant in its field.

Based on the above definition of small entities and data reported in Section 2 of this report, the Agency has determined that there are no small businesses within this source category that would be subject to this final rule. Therefore, because this final rule will not impose any requirements on small entities, EPA certifies that this action will not have a significant economic impact on a substantial number of small entities.

5.2 Unfunded Mandates Title II of the Unfunded Mandates Reform Act of 1995 ( UMRA), Public Law 104 4, establishes requirements for federal agencies to assess the effects of their regulatory actions on state, local, and tribal governments and on the private sector. Under Section 202 of the OMB Review Draft December 17, 2003 5 2 UMRA, EPA generally must prepare a written statement, including a cost benefit analysis, for proposed and final rules that includes any federal mandate that may result in expenditures to state, local, and tribal governments, in the aggregate, or to the private sector, of $ 100 million or more in any one year. As indicated below, EPA is responsive to all required provisions of UMRA.

Section 202( a)( 1) requires EPA to identify the relevant statutory authority. The final standard to limit emissions of HAPs associated with the automobile and LTD coating process is being developed under Section 112 of the CAA of 1990.

Section 202( a)( 2) requires a quantitative and qualitative assessment of the anticipated costs and benefits of the regulation. Section 3 of this report provides detailed estimates of the costs incurred by the private sector to comply with the final NESHAP. The estimated effects of the regulation on the national economy are described in Section 4. Section 6 of this report provides a qualitative assessment of the benefits of reducing HAP emissions, as well as the additional benefits of reducing VOC emissions due to HAP controls.

Before EPA establishes any regulatory requirement that significantly or uniquely affects small governments, including tribal governments, it must develop a small government agency plan under Section 203 of UMRA. The final automobile and LDT coating NESHAP does not impose an unfunded mandate on state, local, and tribal governments; the cost of the regulation is borne by industry. Thus, Section 203 of UMRA does not apply to the current rule.

Section 205 of UMRA generally requires EPA to identify and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost effective, or least burdensome alternative that achieves the objectives of the rule. For reasons discussed in the preamble of the rule, EPA has determined that the current rule constitutes the least burdensome alternative consistent with the CAA.

5.3 Impact on New Sources There is a potential that new sources such as new paint shops at existing plants or new plants will operate in the automobile industry in the future. The final rule imposes more stringent limits on emissions from these new sources. If control costs for new sources and facilities are sufficiently higher than that for current producers, new source performance standards can raise the cost of entry in the automobile market. Thus, EPA has analyzed the OMB Review Draft December 17, 2003 5 3 relative effect of new source controls to determine whether they are likely to impose significant entry barriers.

It is difficult to predict which of the 65 facilities that currently operate in the U. S. automobile and LDT assembly industry will replace their existing paint shops in the future. The engineering cost analysis presented in Section 3 of this report assumes that all existing plants will keep their current paint shops and make the necessary material changes and control equipment additions to meet the final Maximum Achievable Control Technology ( MACT) rule. This is a conservative ( higher MACT specific compliance cost) assumption compared to assuming that only some of these paint shops will be replaced.

The construction of greenfield facilities is also difficult to predict. EPA examined the list of current facilities and determined that over the past 23 years there has been about one new greenfield plant per year, on average. These were more frontloaded in the earlier years for many reasons including the industry wide change to basecoat/ clearcoat from single coating topcoats, " retooling" to take advantage of new production strategies and technologies, and the arrival of non U. S. manufacturers such as Honda, Nissan, and Toyota. Thus, the assumption of one new greenfield plant per year in the future would be an overly generous one. The engineering analysis does not explicitly include greenfield facilities because they are difficult to predict, the number is both absolutely and relatively small compared to the existing facility population, and the cost and economic impacts are likely to be very small.

Even though the number of affected entities cannot be predicted, the impact of new source controls can be estimated qualitatively. The additional MACT specific compliance costs for a new source ( greenfield plant or new paint shop at an existing plant) would be very low because these new sources will comply with existing VOC regulations and already have all of the control equipment needed to meet the final MACT rule. The only incremental costs for new sources would be the small cost of lower HAP coating materials and some MACT specific monitoring, reporting, and record keeping costs that they would not have incurred in the absence of the final rule. However, these costs are in line with the costs incurred by existing facilities and thus do not impose any barriers to entry into the industry. Overall, given the minimal impacts on price and production described in Section 4 of this report, it is very unlikely that a substantial number of firms who may consider entering the industry will be significantly affected. OMB Review Draft December 17, 2003 6 1 SECTION 6 BENEFITS ANALYSIS The emission reductions achieved by this environmental regulation will provide benefits to society by improving environmental quality. This section provides information on the types and levels of social benefits anticipated from the automobile and LDT NESHAP. This section discusses the health and welfare effects associated with the HAPs and other pollutants emitted by automobile and LDT coating operations.

In general, the reduction of HAP emissions resulting from the regulation will reduce human and environmental exposure to these pollutants and thereby reduce the likelihood of potential adverse health and welfare effects. This section provides a general discussion of the various components of total benefits that may be gained from reducing HAPs through this NESHAP. The rule will also achieve reductions of VOCs and hence may reduce ground level ozone and particulate matter ( PM), the benefits of which are presented separately from the benefits associated with reductions in HAPs. We do not present a monetized benefits estimate for the HAP and other emission reductions associated with this final rule for reasons discussed later in the chapter. We do provide a qualitative treatment of the benefits of this final rule in this chapter.

6.1 Identification of Potential Benefit Categories The benefit categories associated with the emission reductions predicted for this regulation can be broadly categorized as those benefits that are attributable to reduced exposure to HAPs and those attributable to reduced exposure to other pollutants. Benefit categories include reduced incidence of neurological effects, respiratory irritation, and eye, nose, and throat irritation associated with exposure to noncarcinogenic HAPs and VOCs. In addition to health impacts occurring as a result of reductions in HAP and VOC emissions, welfare impacts can also be identified. Each category is discussed separately below. OMB Review Draft December 17, 2003 1In general, the RfC is an estimate ( with uncertainty spanning perhaps an order of magnitude) of a daily inhalation exposure of the human population ( including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime.

6 2 6.1.1 Benefits of Reducing HAP Emissions The HAP emissions reductions achieved by this rule are expected to reduce exposure to ambient concentrations of ethylbenzene, EGBE, methanol, methyl ethyl ketone ( MEK), methyl isobutyl ketone ( MIBK), toluene, and xylenes. According to baseline emission estimates, this source category will emit approximately 10,000 tons per year of HAPs at affected sources in the fifth year following promulgation. The regulation will reduce approximately 6,000 tons of emissions per year of the HAPs listed above. Human exposure to these HAPs is likely to occur primarily through inhalation, but people may also be exposed indirectly through ingesting contaminated food or water or through dermal contact. These substances may also enter terrestrial and aquatic ecosystems through atmospheric deposition or may be deposited on vegetation and soil. These HAPs may also enter the aquatic environment from the atmosphere via gas exchange between surface water and the ambient air or by wet or dry deposition of particles to which they adsorb. This analysis is focused only on the air quality benefits of HAP reduction. A summary of the range of potential physical health and welfare effects categories that may be associated with HAP emissions is provided in Table 6 1. As noted in the table, exposure to HAPs can lead to a variety of acute and chronic health impacts as well as welfare impacts.

<IP_ADDRESS> Health Benefits of Reduction in HAP Emissions The HAP emissions resulting from automobile and LDT coating operations are associated with a variety of adverse health effects. Acute ( short term) exposure to ethylbenzene in humans results in respiratory effects such as throat irritation and chest constriction, irritation of the eyes, and neurological effects such as dizziness. Chronic ( long term) exposure of humans to ethylbenzene may cause eye and lung irritation, with possible adverse effects on the blood. Animal studies have reported effects on the blood, liver, and kidneys from chronic inhalation exposure to ethylbenzene. No information is available on the developmental or reproductive effects of ethylbenzene in humans, but animal studies have reported developmental effects, including birth defects in animals exposed via inhalation. EPA has established a reference concentration ( RfC) 1 of 1 mg/ m3 to protect against adverse health effects other than cancer. The RfC is based on the critical OMB Review Draft December 17, 2003 2The critical effect is the first adverse effect, or its known precursor, that occurs to the most sensitive species as the dose rate of an agent increases.

6 3 effect2 of developmental toxicity observed in studies with rats and rabbits. EPA has classified ethylbenzene in Group D, not classifiable as to human carcinogenicity. OMB Review Draft December 17, 2003 6 4 Table 6 1. Potential Health and Welfare Effects Associated with Exposure to Hazardous Air Pollutants Effect Type Effect Category Effect End Point Citation Health Mortality Carcinogenicity EPA ( 1990), Graham, Holtgrave, and Sawery ( 1989) Genotoxicity Graham, Holtgrave, and Sawery ( 1989) Non Cancer lethality Voorhees, Hassett, and Cote ( 1989)

Chronic Morbidity Neurotoxicity Immunotoxicity Pulmonary function decrement Liver damage Gastrointestinal toxicity Kidney damage Cardiovascular impairment Hematopoietic ( Blood disorders) Reproductive/ Developmental toxicity All morbidity end points obtained from Graham, Holtgrave, and Sawery ( 1989), Voorhees, Hassett, and Cote. ( 1989), Cote, Culpit, and Hassett ( 1988)

Acute Morbidity Pulmonary function decrement Dermal irritation Eye irritation Welfare Materials Damage Corrosion/ deterioration NAS ( 1975)

Aesthetic Unpleasant odors Transportation safety concerns Agriculture Yield reductions/ foliar injury Stern et al. ( 1973)

Ecosystem Structure Biomass decrease Species richness decline Species diversity decline Community size decrease Organism lifespan decrease Trophic web shortening Weinstein and Birk ( 1989)

Source: Mathtech, Inc. May 1992. Benefit Analysis Issues for Section 112 Regulations. Final report prepared for U. S. Environmental Protection Agency. Office of Air Quality Planning and Standards. Contract No. 68 D8 0094. Research Triangle Park, NC. OMB Review Draft December 17, 2003 6 5 EGBE is a member of the glycol ethers HAP category, a large group of related compounds. Acute exposure in humans to high levels of glycol ethers results in narcosis, pulmonary edema, and liver and kidney damage. Chronic exposure to glycol ethers may result in neurological and blood effects, including fatigue, nausea, tremor, and anemia. No information is available on the reproductive or developmental effects of glycol ethers in humans, but animal studies have reported such effects, including testicular damage, reduced fertility, maternal toxicity, early embryonic death, birth defects, and delayed development. EPA has established an RfC of 13 mg/ m3 to protect against adverse health effects other than cancer based on the critical effect of decreases in red blood cell count observed in studies with rats.

No reliable human epidemiological studies are available that address the potential carcinogenicity of EGBE, but a draft report of a 2 year rodent inhalation study reported equivocal evidence of carcinogenic activity in female rats and male mice. Because of the uncertain relevance of these tumor increases to humans, the fact that EGBE is generally negative in genotoxic tests, and the lack of human data to support the findings in rodents, the human carcinogenic potential of EGBE cannot be determined at this time. EPA has classified EGBE as a Group C, possible human carcinogen.

Acute inhalation exposure to MEK in humans results in irritation to the eyes, nose, and throat. Little information is available on the chronic effects of MEK in humans, but inhalation studies in animals have reported slight neurological, liver, kidney, and respiratory effects. No information is available on the developmental, reproductive, or carcinogenic effects of MEK in humans. Developmental effects, including decreased fetal weight and fetal malformations, have been reported in mice and rats exposed to MEK via inhalation and ingestion. EPA has established an RfC of 1 mg/ m3 to protect against adverse health effects other than cancer based on the critical effect of decreased birth weight observed in studies with mice. EPA has classified MEK in Group D, not classifiable as to human carcinogenicity.

Acute or chronic exposure of humans to methanol by inhalation or ingestion may result in blurred vision, headache, dizziness, and nausea. No information is available on the reproductive, developmental, or carcinogenic effects of methanol in humans. Birth defects have been observed in the offspring of rats and mice exposed to methanol by inhalation. A methanol inhalation study using rhesus monkeys reported a decrease in the length of pregnancy and limited evidence of impaired learning ability in offspring. EPA has not established an RfC for methanol or classified methanol with respect to carcinogenicity. The OMB Review Draft December 17, 2003 6 6 California Environmental Protection Agency has developed a reference exposure level ( similar in concept to an RfC) of 4 mg/ m3 based on the critical effect of birth defects observed in studies with mice.

Acute exposure to MIBK may irritate the eyes and mucous membranes and cause weakness, headache, and nausea. Chronic exposure to workers has been observed to cause nausea, headache, burning eyes, insomnia, intestinal pain, and slight enlargement of the liver. No information is available on reproductive or developmental effects of MIBK in humans, but studies with rats and mice have reported neurological effects and increased liver and kidney weights. EPA has not established an RfC for MIBK or classified it with respect to carcinogenicity. Animal studies are currently underway that are expected to provide the foundation for an EPA assessment.

Acute inhalation of toluene by humans may cause effects to the central nervous system ( CNS), such as fatigue, sleepiness, headache, and nausea, as well as irregular heartbeat. Adverse CNS effects reported in chronic abusers exposed to high levels of toluene include tremors; decreased brain size; involuntary eye movements; and impaired speech, hearing, and vision. Chronic inhalation exposure of humans to lower levels of toluene also causes irritation of the upper respiratory tract, eye irritation, sore throat, nausea, dizziness, headaches, and difficulty with sleep. Studies of children whose mothers were exposed to toluene by inhalation or mixed solvents during pregnancy have reported CNS problems, facial and limb abnormalities, and delayed development. However, these effects may not be attributable to toluene alone. EPA has established an RfC of 0.4 mg/ m3 to protect against adverse health effects other than cancer. The RfC is based on the critical effect of decreased neurological performance in workers exposed to toluene emitted from glue. EPA has classified toluene in Group D, not classifiable as to human carcinogenicity.

Acute inhalation of mixed xylenes ( a mixture of three closely related compounds) in humans may cause irritation of the nose and throat, nausea, vomiting, gastric irritation, mild transient eye irritation, and neurological effects. Chronic inhalation of xylenes in humans may result in nervous system effects such as headache, dizziness, fatigue, tremors, and incoordination. Other reported effects include labored breathing, heart palpitation, severe chest pain, abnormal electrocardiograms, and possible effects on the blood and kidneys. EPA has not developed an RfC for xylenes. The Agency for Toxic Substances and Disease Registry has published a minimum risk level ( similar to an RfC) for xylenes of 0.43 mg/ m3 based on CNS effects in rodents. EPA has classified xylenes in Category D, not classifiable with respect to human carcinogenicity. OMB Review Draft December 17, 2003 6 7 For the HAPs covered by the automobile and LDT NESHAP, evidence on the potential toxicity of the pollutants varies. However, given sufficient exposure conditions, each of these HAPs has the potential to elicit adverse health or environmental effects in the exposed populations.

EPA recently prepared a relative ranking evaluation for all HAPs for the purpose of selecting 30 HAPs posing the greatest health risk in urban areas ( Smith et al., 1999). This evaluation combined all available data on toxic potential with nationwide emission and ambient concentration information ( i. e., not just urban) for all 188 HAPs, considering both cancer and noncancer end points and both inhalation and ingestion exposures. The available database supported quantitative ranks for more than 150 HAPs, including the seven HAPs most commonly used in ( or emitted by) this source category. None of these seven HAPs were found to present a hazard sufficient to justify including them on the list of urban air toxics.

EPA recently prepared a draft national scale assessment as part of its National Air Toxics Assessment activities ( EPA, 2001). This draft assessment estimates human inhalation exposures to the urban HAPs selected based on the ranking study described above. To the extent that EPA's ranking analysis was effective, HAPs included in the urban list were likely to present greater health risks than those that did not. Less than one third of the noncarcinogens evaluated by the national scale assessment were judged likely to have human exposure exceeding the RfC anywhere in the U. S.

It is important to note that the national scale assessment did not include ingestion exposures or acute time scales and used simplified models that were not efficient at estimating hot spots or maximum individual exposures. However, the results suggest that most of the noncarcinogens included in the assessment do not present national concerns. Because the HAPs in the national scale assessment arguably present greater potential hazards than the seven HAPs most commonly used in ( or emitted by) this source category, EPA has no information that suggests there is presently any widespread overexposure to these six HAPs. Nevertheless, given the limitations of the national scale assessment, this may not be true in all areas or for all receptors.

<IP_ADDRESS> Welfare Benefits of Reducing HAP Emissions The welfare effects of exposure to HAPs have received less attention from analysts than the health effects. However, this situation is gradually changing, as over the past 10 years, ecotoxicologists have started to build models of ecological systems that focus on OMB Review Draft December 17, 2003 6 8 interrelationships in function, the dynamics of stress, and the adaptive potential for recovery. This perspective is reflected in Table 6 1 where the end points associated with ecosystem functions describe structural attributes rather than species specific responses to HAP exposure. This development is consistent with the observation that chronic sublethal exposures may affect the normal functioning of individual species in ways that make them less than competitive and therefore more susceptible to a variety of factors including disease, insect attack, and decreases in habitat quality ( EPA, 1991). All of these factors may contribute to an overall change in the structure ( i. e., composition) and function of the ecosystem.

The overall environmental behavior of these HAPs can be evaluated using fugacity models. Fugacity is a thermodynamic property and is equal to the partial pressure of a substance in compartment. Thus the fugacity of a substance in an environmental medium ( e. g., air, water, soil, or sediment) is a measure of the substance's tendency to escape that medium and enter another medium. The Mackay Level III model is a relatively rigorous representation of multiple environmental compartments and the fate and transport process through which chemicals are moved through them ( Mackay, 1991).

The Level III model indicates that the HAPs released from automobile and LDT coating operations once emitted to the ambient air as vapors are likely to remain in the vapor phase as VOCs. Model estimates of HAPs remaining in the air compartment range from greater than 99 percent of the ethyl benzene, xylenes, and toluene to approximately 85 percent of methanol emissions.

The median half lives for these HAPs in the vapor phase range from 23 hours for xylenes to 57 hours for toluene. As VOCs, they under go various chemical reactions that contribute to the formation of other atmospheric pollutants that can affect welfare. For example, these VOCs can contribute to ozone in the environment. EPA has previously stated ( 59 FR 1788, January 12, 1994) that ozone's effects on green plants include injury to foliage, reductions in growth, losses in yield, alterations in reproductive capacity, and alterations in susceptibility to pests and pathogens. Based on known interrelationships of different components of ecosystems, such effects, if of sufficient magnitude, may potentially lead to irreversible changes of a sweeping nature to ecosystems.

In addition to directly contributing to ozone formation, the reaction of methanol with nitrogen dioxide in a smog chamber has been shown to yield methyl nitrite and nitric acid. The reaction of methanol with nitrogen dioxide may be the major source of methyl nitrite OMB Review Draft December 17, 2003 6 9 that has the potential to cause allergic responses in polluted atmospheres. However, methyl that is short lived in the atmosphere. It is rapidly photolyzed by sunlight, with a mean lifetime of about 10 to 15 minutes. The result is the production of NOx, which contributes to an increase in ozone.

Beyond photochemical removal processes, a relatively small portion of these vaporphase HAPs, as well as some of the particulates, leave the ambient air via removal processes such as wet or dry deposition. Compounds such as methanol, EGBE, and MIBK are slightly miscible in water and can therefore be physically removed from the air by rain. The other HAPs ( i. e, toluene, xylenes, ethyl benzene) are less soluble but can be deposited on surfaces via processes such as dry deposition or impaction.

In water, the HAPs released from automobile and LDT coating operations exhibit low to moderate acute aquatic toxicity. Methanol, EGBE, and MIBK represent the low side and MEK, xylenes, toluene, and ethyl benzene are considered to present moderate acute toxicity. All of these HAPs exhibit low persistence and low bio accumulation potential. The persistence, as indicated by median half lives in water, range from a low of 96 hours for methanol to a maximum of 312 hours for toluene. The bio accumulation factor ( BAF) is defined as the concentration of a substance in an organism divided by the concentration of the chemical in the surrounding medium measured in an intact ecosystem. As such, the BAF takes into account accumulation through ingested food, as well as the concentration from the surrounding medium.

A low bio accumulation potential indicates that they are not likely to bio concentrate through the food chain. However, substances that do not tend to readily bio accumulate or bio concentrate may be taken up by biota and still exert a deleterious effect. These effects could potentially include such impacts as lethality or reproductive impairment to vulnerable species resulting in impacts to recreational or commercial fishers, as well as the ecosystems supporting these fisheries. This not only has potential adverse implications for individual wildlife species, ( including threatened or endanger species) and ecosystems as a whole, but also to humans who may depend on contaminated fish and waterfowl.

Once deposited on soil or sediments these HAPs are subject to a variety of competing removal mechanisms including evaporation, mobility, bio transformation, and chemical reactions. Xylenes deposited on soil can vaporize or, if contained on sediment, be buried. Methanol and ethyl benzene demonstrate high mobility in soil and can end up in ground water, and EGBE and MIBK are readily subject to aerobic and anaerobic bio transformation. OMB Review Draft December 17, 2003 6 10 The estimated median half lives for these HAPs in soil ranges from 96 hours for MIBK and methanol to 420 hours for xylenes. In sediment, the estimated median half lives are 384 hours for MIBK and methanol to 1,248 hours for toluene. Once deposited on soil or in sediments, these HAPs can enter into terrestrial biota through diet or directly from the surrounding media. The potential for this uptake of HAPs to adversely affect individual wildlife species ( including threatened or endanger species) as well as ecosystems as a whole is not understood.

In summary, the potential adverse effects of these HAPs on individual wildlife species or aquatic terrestrial ecosystems have not been characterized. However, HAP emission reductions achieved through the automobile and LDT NESHAP should reduce the associated adverse environmental impacts.

6.1.2 Benefits of Reducing VOC Emissions due to HAP Controls VOCs are a precursor to tropospheric ( ground level) ozone, and exposure to groundlevel ozone has been linked to acute and chronic effects on human health and welfare. This section addresses these effects.

Human exposure to elevated concentrations of ozone primarily results in respiratoryrelated impacts such as coughing and difficulty in breathing. Eye irritation is another frequently observed effect. These acute effects are generally short term and reversible. Nevertheless, a reduction in the severity or scope of such impacts may have significant economic value.

Recent studies have found that repeated exposure to elevated concentrations of ozone over long periods of time may also lead to chronic, structural damage to the lungs ( EPA, 1995b). To the extent that these findings are verified, the potential scope of benefits related to reductions in ozone concentrations could be expanded significantly.

Major ozone adverse health effects are alterations in lung capacity and breathing frequency; eye, nose and throat irritation; reduced exercise performance; malaise and nausea; increased sensitivity of airways; aggravation of existing respiratory disease; decreased sensitivity to respiratory infection; and extra pulmonary effects ( CNS, liver, cardiovascular, and reproductive effects). It is expected that VOC reductions through the automobile and LDT coatings rule will lead to a reduction in ambient ozone concentrations and, in turn, reduce the incidence of the adverse health effects of ozone exposure. OMB Review Draft December 17, 2003 6 11 Major ozone adverse welfare effects are reduction in the economic value of certain agricultural crops and ornamental plants and materials damage. Over the last decade, a series of field experiments has demonstrated a positive statistical association between ozone exposure and yield reductions as well as visible injury to several economically valuable cash crops, including soybeans and cotton. Damage to selected timber species has also been associated with exposure to ozone. The observed impacts range from foliar injury to reduced growth rates and premature death. Benefits of reduced ozone concentrations include the value of avoided losses in commercially valuable timber and aesthetic losses suffered by nonconsumptive users ( EPA, 1995b).

There are some benefits from reduced VOC emissions beyond merely a reduction in ozone concentration. Approximately 1 to 2 percent of VOCs precipitate in the atmosphere to form particulate matter ( PM) with an aerodynamic diameter at or below 10 micrometers ( called PM 10). There are a number of benefits from reduced PM concentration, including reduced soiling and materials damage, increased visibility, and reductions in excess deaths and morbidity. However, the focus of this part of the benefits section is on the benefits from reduced ozone concentrations because they are greater than those from reduced PM 10 concentrations. PM 10 control is already prescribed by primary and secondary National Ambient Air Quality Standards ( NAAQS) promulgated by EPA, which are now under review. For more information on ozone health and welfare effects, refer to the 1996 Ozone NAAQS Staff Paper developed by the Agency.

Sizable uncertainties exist in any risk estimates, including these. Emissions estimates can be off by a factor of two or more one time out of three, and air dispersion models can have a similar uncertainty. Consideration of actual exposures also adds uncertainty. Estimates of the total burden of disease associated with air pollution and air toxics are rough. Cancer potency factors contribute additional uncertainty of often greater magnitude. Although we did not formally estimate the combined uncertainties for these risk estimates, it is very likely that the uncertainty around these estimates is at least a factor of 10 above or below the stated values.

We did not quantify the benefits from VOC reductions for this rule because of a lack of Science Advisory Board ( SAB) approved methods for doing so. EPA is working with the SAB to develop better methods for analyzing the benefits of reductions in VOCs.

6.2 Lack Of Approved Methods To Quantify HAP Benefits OMB Review Draft December 17, 2003 6 12 There are both cancer and non cancer health effects associated with the HAPs that are controlled under this rule. In previous analyses of the benefits of reductions in HAPs, EPA has quantified and monetized the benefits of reduced incidences of cancer. 23, 24 In some cases, EPA has also quantified ( but not monetized) reductions in the number of people exposed to non cancer HAP risks above no effect levels. 25 Monetization of the benefits of reductions in cancer incidences requires several important inputs, including central estimates of cancer risks, estimates of exposure to carcinogenic HAPs, and estimates of the value of an avoided case of cancer ( fatal and nonfatal In the above referenced analyses, EPA relied on unit risk factors ( URF) developed through risk assessment procedures. The unit risk factor is a quantitative estimate of the carcinogenic potency of a pollutant, often expressed as the probability of contracting cancer from a 70 year lifetime continuous exposure to a concentration of one : g/ m3 of a pollutant. These URFs are designed to be conservative, and as such, are more likely to represent the high end of the distribution of risk rather than a best or most likely estimate of risk.

In a typical analysis of the expected health benefits of a regulation ( see for example, " Regulatory Impact Analysis: Heavy Duty Engine and Highway Diesel Fuel Sulfur Control Requirements", December 2000, EPA420 R 00 026), health effects are estimated by applying changes in pollutant concentrations to best estimates of risk obtained from epidemiological studies. As the purpose of a benefit analysis is to describe the benefits most likely to occur from a reduction in pollution, use of high end, conservative risk estimates will lead to a biased estimate of the expected benefits of the regulation.

However the methods to conduct a risk analysis of HAP reductions produces highend estimates of benefits due to assumptions required in such analyses. While we used highend risk estimates in past analyses, recent advice from the EPA Science Advisory Board ( SAB) and internal methods reviews have suggested that we avoid using high end estimates in current analyses. Also, limited input data on non cancer effects associated with exposure to these HAPs does not allow us to quantify the benefits from risk reductions of these effecs. For these reasons, we will not attempt to quantify the health benefits of reductions in HAPs unless best estimates of risks are available. EPA is working with the SAB to develop better methods for analyzing the benefits of reductions in HAPs. While not appropriate as part of a primary estimate of benefits, to estimate the potential baseline risks posed by the Auto and Light Duty Truck source category , EPA performed a " rough" risk assessment, described below. There are large uncertainties regarding all components of the risk quantification step, including location of emission reductions, emission estimates, air concentrations, exposure OMB Review Draft December 17, 2003 6 13 levels and dose response relationships. However, if these uncertainties are properly identified and characterized, it is possible to provide estimates of the reduction in inhalation cancer incidence associated with this rule. It is important to keep in mind that these estimates will only cover a very limited portion of the potential HAP effects of the rule, as they exclude non inhalation based cancer risks and non cancer health effects.

6.2.1 Characterization of Industry Emissions and Potential Baseline Health Effects For the automobile and light duty truck surface coating source category, seven HAP account for over 95 percent of the total HAP emitted. Those seven HAP are toluene, xylene, glycol ethers ( including ethylene glycol monobutyl ether ( EGBE)), MEK, MIBK, ethylbenzene, and methanol. Additional HAP which may be emitted by some automobile and light duty truck surface coating operations are: ethylene glycol, hexane, formaldehyde, chromium compounds, diisocyanates, manganese compounds, methyl methacrylate, methylene chloride, and nickel compounds.

Of the seven HAP emitted in the largest quantities by this source category, all can cause toxic effects following sufficient exposure. The potential toxic effects of these seven HAP include effects to the central nervous system, such as fatigue, nausea, tremors, and loss of motor coordination; adverse effects on the liver, kidneys, and blood; respiratory effects; and, developmental effects. In addition, one of the seven predominant HAP, EGBE, is a possible carcinogen, although information on this compound is not currently sufficient to allow us to quantify its potency.

In accordance with section 112( k), EPA developed a list of 33 HAP which present the greatest threat to public health in the largest number of urban areas. None of the predominant seven HAP is included on this list for the EPA's Urban Air Toxics Program, although three of the other emitted HAP ( formaldehyde, manganese compounds, and nickel compounds) appear on the list. In November 1998, EPA published " A Multimedia Strategy for Priority Persistent, Bioaccumulative, and Toxic ( PBT) Pollutants." None of the predominant seven HAP emitted by automobile and light duty truck surface coating operations appears on the published list of compounds referred to in the EPA's PBT strategy.

To estimate the potential baseline risks posed by the source category , EPA performed a " rough" risk assessment for 56 of the approximately 60 facilities in the source category by using a model plant placed at the actual location of each plant and simulating OMB Review Draft December 17, 2003 6 14 impacts using air emissions data from the 1999 EPA Toxics Release Inventory ( TRI). In addition to the seven predominant HAP, the following additional HAP were included in this rough risk assessment because they were reported in TRI as being emitted by facilities in the source category: ethylene glycol, hexane, formaldehyde, diisocyanates, manganese compounds, nickel compounds and benzene. The benzene emissions and some of the nickel emissions are from non surface coating activities which are not part of the source category. Of the HAP reported in TRI which are emitted from automobile and light duty truck surface coating operations, three ( formaldehyde, nickel compounds, and EGBE) are carcinogens that, at present, are not considered to have thresholds for cancer effects. Most facilities in this source category emit some small quantity of formaldehyde. In the 1999 TRI, however, only two facilities in this source category reported formaldehyde emissions. No other facilities exceeded the TRI reporting threshold for formaldehyde in 1999.

6.2.2 Results of Rough Risk Assessments of Alternative Control Options Under CAA Sections 112 ( d) 4 and 112( c)( 9)

The results of the human health risk assessments described below are based on approaches for quantifying exposure, risk, and cancer incidence that carry significant assumptions, uncertainties, and limitations. For example, in conducting these types of analyses, there are typically many uncertainties regarding dose response functions, levels of exposure, exposed populations, air quality modeling applications, emission levels, and control effectiveness. The risk estimates from this rough assessment are also based on typical facility configurations ( i. e., model plants). As such, they are subject to significant uncertainties. The actual risks at any one facility could be significantly higher or lower. Because the estimates derived from the various scoping approaches are necessarily rough, we are concerned that they not convey a false sense of precision. Any point estimates of risk reduction or benefits generated by these approaches should be considered as part of a range of potential estimates.

If this final rule is implemented at all automobile and light duty truck surface coating facilities, the number of people exposed to hazard index ( HI) values equal to, or greater than, 1 was estimated to be reduced from about 100 to about 10. The number of people exposed to HI values of 0.2 or greater was predicted to decrease from about 3500 to about 1200. ( Details of these analyses are available in the docket.) OMB Review Draft December 17, 2003 6 15 The baseline cancer risk and subsequent cancer risk reductions were estimated to be minimal for this source category. The rough risk assessment indicated that currently no one would be exposed to a lifetime cancer risk above 10 in a million and perhaps 6,000 people would be exposed to a lifetime cancer risk above 1 in a million as a result of emissions from these facilities. The final rule is not expected to have any significant effect on cancer risk. Of the three carcinogens included in the assessment, emission reductions attributable to the final rule could be estimated for only EGBE. The cancer risk for EGBE, however, cannot currently be quantified. OMB Review Draft December 17, 2003 R 1 REFERENCES AAMA/ AIAM/ NPCA. January 7, 2000. " Glossary of Terms: Automobile and Light Duty Truck NESHAPs."

American Automobile Manufacturers Association ( AAMA). 1998. Motor Vehicle Facts and Figures 1998. Detroit: AAMA.

Ansdell, D. A. 1995. " Surfacers." Automotive Paints and Coatings, G. Fettis, ed. New York: VCH Verlagsgesellschaft mbH.

Baumol, William J., and Wallace E. Oates. 1988. The Theory of Environmental Policy. Second Edition. New York, NY: Cambridge University Press.

Berry, S., J. Levinsohn, and A. Pakes. 1995. " Automobile Prices in Market Equilibrium." Econometrica 63( 4): 841 890.

Brunnermeier, Smita B., and Martin, Sheila A. March 1999. Interoperability Cost Analysis of the U. S. Automotive Supply Chain. Prepared for the National Institute of Standards and Technology. Research Triangle Park: Research Triangle Institute.

Consumer Reports. April 2000a. " Most Hallowed Hues." p. 7.

Consumer Reports. April 2000b. " The New Consumer Reports Wholesale Price." p. 18.

Consumer Reports. April 2000c. " Survey Surprises." p. 12 13.

Cote, I., L. Cupitt, and B. Hassett. 1988. Toxic Air Pollutants and Non Cancer Health Risks. Unpublished paper provided by B. Hassett.

Crain Automotive Group. 2000. Automotive News Market Databook   2000. Detroit, MI: Crain Automotive Group.

Crain Automotive Group. 2001. Automotive News Market Databook   2001. Detroit, MI: Crain Automotive Group. OMB Review Draft December 17, 2003 R 2 Dornbusch, Rudiger. 1987. " Exchange Rates and Prices." American Economic Review 77: 93 106.

Edmunds. com. 2000a. " Current Incentives and Rebates ( 3/ 10/ 00)." < http:// www. edmunds. com/ edweb/ Incentives. html>. As obtained on March 23, 2000.

Edmunds. com. 2000b. " Dealer Holdback." < http:// www. edmunds. com/ edweb/ holdback_ list. html>. As obtained on March 23, 2000.

Edmunds. com. 2001. " New and Used Vehicles." < http:// www. Edmunds. com>. As obtained January 2001.

Federal Register. January 12, 1994. 59 FR 1788.

Freedonia Group. September 1999. Automotive Coatings, Sealants and Adhesives in the United States to 2003   Automotive Adhesives, Market Share and Competitive Strategies. Cleveland, OH: The Freedonia Group, Inc.

Gallaway, Michael P., Christine McDaniel, and Sandra Rivera. September 2000. " Industry Level Estimates of U. S. Armington Elasticities." U. S. International Trade Commission, Office of Economics Working Paper # 2000 09 A.

Galvin, Patrick J. May 1999. " In High Gear." Modern Paint and Coatings 89( 5): 24 28.

Goldberg, Pinelopi K. 1995. " Product Differentiation and Oligopoly in International Markets: The Case of the U. S. Automobile Industry." Econometrica 63( 4): 891 951.

Graham, J. D., D. R. Holtgrave, and M. J. Sawery. February 1989. " The Potential Health Benefits of Controlling Hazardous Air Pollutants." In Health Benefits of Air Pollution Control: A Discussion. J. Blodgett, ( ed). Congressional Research Service report to Congress. CR589 161. Washington, DC.

Graves, B. A. " Building an Integrated Paint Facility." < http:// www. afonline. com/ articles/ 00sp04. html>. As obtained on March 20, 2000.

Green, David, RTI. Email correspondence with Aaiysha Khursheed, EPA, November 8, 2000a.

Green, David, RTI. Personal communication with Mary Muth, RTI. April 6, 2000b.

Green, David, RTI. Email correspondence with Laura Bloch, RTI. February 29, 2000c. OMB Review Draft December 17, 2003 R 3 Green, David. RTI/ CEA/ EEP. March 2002. Economic Inputs: Automobile and Light Truck Surface Coating NESHAP. Memorandum to David Salman, EPA/ OAQPS/ CCPG.

Gron, Anne and Deborah Swenson. 2000. " Cost Pass through in the U. S. Automobile Market." The Review of Economics and Statistics 82( 2): 316 324.

Harris Info Source. Selectory Online Profiles. < http:// www. harrisinfo. com>. As obtained January 12, 2000.

Ho, Mun S., and Dale W. Jorgenson. 1998. " Modeling Trade Policies and U. S. Growth: Some Methodological Issues." Presented at the Conference on Evaluating APEC Trade Liberalization: Tariff and Nontariff Barriers, Washington, DC, September 11   12, 1997.

Honda. 2000. Honda Breaks Ground for New Plant in Alabama. < http:// www. honda2001. com/ news/ press. html? y= 2000& 3r= 342>. As obtained November 16, 2000.

Hoover's Online. Company Capsules. < http:// www. hoovers. com>. As obtained on January 13, 2000.

J. D. Power and Associates. 1998 Vehicle Quality Survey as reported in American Automobile Manufacturers Association ( AAMA). 1998. Motor Vehicle Facts and Figure 1998. Detroit: AAMA.

Levy, Efraim. 2000. " Motor Vehicles." U. S. Industry and Trade Outlook 2000. New York, NY: McGraw Hill Companies.

Levinson, Arik. 1996. " Environmental Regulations and Industry Location: International and Domestic Evidence." In Fair Trade and Harmonization: Prerequisite for Free Trade? Jagdish Bhagwati and Robert Hudec, eds. Washington, DC: MIT Press.

McCarthy, P. S. 1996. " Market Price and Income Elasticities of New Vehicles Demand." Review of Economics and Statistics 78( 3): 543 47.

Mackay, Donald. 1991. Multimedia Environmental Models: The Fugacity Approach. Chelsea, MI: Lewis Publishers, Inc.

Mathtech, Inc. May 1992. Benefit Analysis Issues for Section 112 Regulations. Final report prepared for U. S. Environmental Protection Agency. Office of Air Quality Planning and Standards. Contract No. 68 D8 0094. Research Triangle Park, NC. OMB Review Draft December 17, 2003 R 4 National Academy of Sciences ( NAS). 1975. Chlorine and Hydrogen Chloride. National Academy of Sciences, National Research Council. Chapter 7.

National Paint and Coatings Association. " Economic Value of Paints and Coatings." < http:// www. paint. org>. As obtained on February 24, 2000.

Office of Management and Budget. 1996. Economic Analysis of Federal Regulations Under Executive Order 12866. Washington DC: Executive Office of the President.

Poth, U. 1995. " Topcoats for the Automotive Industry." Automotive Paints and Coatings, G. Fettis, ed. New York: VCH Verlagsgesellschaft mbH.

Praschan, G. January 7, 2000. " Powder Primer Surfacer Facilities." Memorandum to Greg Dana, Alliance of Automobile Manufacturers, and Amy Lilly, AIAM.

Research Triangle Institute ( RTI). Coating Alternatives Guide ( Developed in cooperation with EPA). < http:// www. cage. rti. org>.

Smith, R. L., C. L. French, D. L. Murphy, and R. Thompson. 1999. Ranking and Selection of Hazardous Air Pollutants for Listing Under Section 112( k) of the Clean Air Act Amendments of 1990. Technical Support Document. http:// www. epa. gov/ ttn/ uatw/ urban/ main_ txt. pdf.

Stern, A. et al. 1973. Fundamentals of Air Pollution. Academic Press, New York.

Trandel, G. A. 1991. " The Bias Due to Omitting Quality When Estimating Automobile Demand." Review of Economics and Statistics 73( 3): 522 525.

U. S. Bureau of Labor Statistics ( BLS). Consumer Price Index   All Urban Consumers: CUUR0000SA0, All Items: 1990 1999. < http:// www. bls. gov>. As obtained on September 9, 2000.

U. S. Bureau of Labor Statistics ( BLS). Consumer Price Index   All Urban Consumers: CUUR0000SS45011, New Cars: 1990 1999. < http:// www. bls. gov>. As obtained on January 3, 2001.

U. S. Bureau of Labor Statistics ( BLS). Consumer Price Index   All Urban Consumers: CUUR0000SS45021, New Trucks: 1990 1999. < http:// www. bls. gov>. As obtained on January 3, 2001. OMB Review Draft December 17, 2003 R 5 U. S. Department of Commerce. 1992. Concentration Ratios in Manufacturing. Washington, DC: Government Printing Office.

U. S. Department of Commerce. 1995. 1992 Census of Manufacturers   Industry Series. Motor Vehicles and Equipment. Washington, DC: Government Printing Office.

U. S. Department of Commerce. 1996. 1994 Annual Survey of Manufactures. Washington, DC: Government Printing Office.

U. S. Department of Commerce. 1998. 1996 Annual Survey of Manufactures. Washington, DC: Government Printing Office.

U. S. Department of Commerce, Census Bureau. October 1999a. " Automobile Manufacturing." 1997 Economic Census Manufacturing Industry Series. EC97M0 3361A. Washington, DC: Government Printing Office.

U. S. Department of Commerce, Census Bureau. October 1999b. " Light Truck and Utility Vehicle Manufacturing." 1997 Economic Census Manufacturing Industry Series. EC97M 3361B. Washington, DC: Government Printing Office.

U. S. Department of Commerce ( jointly with The McGraw Hill Companies, Inc.). 1999c. U. S. Industry and Trade Outlook ` 99. New York: The McGraw Hill Companies, Inc.

U. S. Department of Energy. 1999a. Electric Power Annual, Volume I. Table A2: Industry Capability by Fuel Source and Industry Sector, 1999 and 1998 ( Megawatts). < http:// www. eia. doe. gov/ cneaf/ electricity/ epav1/ elecprod. html# gencap>

U. S. Department of Energy. 1999b. Natural Gas Annual. Table 1: Summary Statistics for Natural Gas in the United States, 1995  1999. < http:// www. eia. doe. gov/ oil_ gas/ natural_ gas/ data_ publications/ natural_ gas_ annual/ nga. html>

U. S. Environmental Protection Agency ( EPA). September 1990. Cancer Risk from Outdoor Exposure to Air Toxics. Volume 1. Office of Air Quality Planning and Standards. EPA 450/ 1 90 004a. Washington, DC: Government Printing Office.

U. S. Environmental Protection Agency. 1991. Ecological Exposure and Effects of Airborne Toxic Chemicals: An Overview. EPA/ 6003 91/ 001. Environmental Research Laboratory. Corvallis, OR. OMB Review Draft December 17, 2003 R 6 U. S. Environmental Protection Agency ( EPA). September 1995a. Profile of the Motor Vehicle Assembly Industry. EPA310 R 95 009. Washington, DC: Government Printing Office.

U. S. Environmental Protection Agency ( EPA). August 1995b. Regulatory Impact Analysis for the Petroleum Refinery NESHAP. Final Report. Office of Air Quality Planning and Standards. Research Triangle Park, NC. EPA 452/ R 95 004.

U. S. Environmental Protection Agency ( EPA). 1996. Economic Analysis of Pollution Regulations: Pharmaceutical Industry. Research Triangle Park, NC: U. S. Environmental Protection Agency, Office of Air Quality, Planning, and Standards.

U. S. Environmental Protection Agency ( EPA). 1999. OAQPS Economic Analysis Resource Document. Durham, NC: Innovative Strategies and Economics Group.

U. S. Environmental Protection Agency ( EPA). 2000. Fuel Economy Guide Data   1999. [ computer file]. < http:// www. epa. gov/ feddata. htm>. As obtained December 13, 2000.

U. S. Environmental Protection Agency ( EPA). 2001. National Scale Air Toxics Assessment for 1996. Draft for review by the EPA Science Advisory Board. Office of Air Quality Planning and Standards. EPA 453/ R 01 003. < http:// www. epa. gov/ ttn/ uatw/ sab/ sabrev. html>.

U. S. International Trade Commission. 2001. ITC Trade Dataweb. http:// <IP_ADDRESS>/. As obtained May 31, 2001.

Vachlas, Z. 1995. " Primers for the Automotive Industry." Automotive Paints and Coatings, G. Fettis, ed. New York: VCH Verlagsgesellschaft mbH.

Varian, Hal. 1993. Microeconomic Analysis, 3rd Edition. New York: W. W. Norton & Company.

Vatavuk, William M. July 1999. CO$ T AIR Control Cost Spreadsheets. Second Edition. Research Triangle Park: U. S. Environmental Protection Agency, Office of Air Quality Planning and Standards. < http:// www. epa. gov/ ttn/ catc/ products. html# cccinfo>. OMB Review Draft December 17, 2003 R 7 Voorhees, A., B. Hassett, and I. Cote. 1989. Analysis of the Potential for Non Cancer Health Risks Associated with Exposure to Toxic Air Pollutants. Paper presented at the 82nd Annual Meeting of the Air and Waste Management Association.

Weinstein, D., and E. Birk. 1989. " The Effects of Chemicals on the Structural of Terrestrial Ecosystems: Mechanisms and Patterns of Change." In Ecotoxicology: Problems and Approaches, S. Levin et al. ( eds.). Chapter 7, p. 191 209. OMB Review Draft December 17, 2003 Appendix A Economic Model for Automobile and LDT Market Under Imperfect Competition OMB Review Draft December 17, 2003 A 1 The final regulation will increase the cost of production for existing vehicle assembly plants. The regulated facilities may alter their current levels of production or even close the facility in response to the increased costs. These responses will in turn determine the impact of the regulation on total market supply and ultimately on the equilibrium price and quantity. The economic analysis described below employs standard concepts of microeconomics to model these impacts.

A. 1 U. S. Demand for Domestic Vehicles The Agency has modeled separate markets for eight domestic vehicle categories: subcompacts, compacts, intermediate/ standard, luxury, sports, pickups, vans, and other. Domestic demand for each vehicle category i can be expressed by the following constant elasticity demand function:

where pi is the average price of vehicle category i, , i d is the own price demand elasticity for vehicle category i, and Ai is a multiplicative demand parameter that calibrates the demand equation given data on price and the demand elasticity to replicate the observed baseline year ( 1999) level of domestic consumption of vehicles of class i.

Estimates of average retail prices and own price elasticities by vehicle class are presented in Table A 1. The average retail price for each of the eight vehicle classes is derived from the Automotive New Market Data Book, as described previously in Section 2.4.3. The own price elasticity of demand for each vehicle class is taken from Goldberg ( 1995) who estimates them using micro data on transaction prices and make/ models from the Consumer Expenditure Survey and the Automotive News Market Data Book. Note that these demand elasticity estimates are all greater than one in absolute value but vary across vehicle classes in an intuitive manner. For example, the demand for intermediate and standard automobiles is highly elastic, while that for sports and luxury cars is the least price elastic.

A. 2 U. S. Supply of Domestic Vehicles Given the capital in place, each facility is assumed to face an upward sloping curve for a particular vehicle class. The Generalized Leontief profit function is used to OMB Review Draft December 17, 2003 A 2 Table A 1. Retail Prices and Own Price Elasticities of Demand by Vehicle Class Vehicle Class Average Retail Pricea Elasticityb Subcompact $ 15,522   3.286 Compact $ 16,487   3.419 Intermediate $ 21,155   4.179 Standard   4.712 Luxury $ 33,587   1.912 Sports $ 25,797   1.065 Pick up $ 22,126   3.526 SUV $ 27,694 Van $ 22,910   4.363 Other   4.088 a Includes the MSRP and destination price reported by the Automotive News Market Data Book ( Crain, 2000; p: 75). Prices current as of April 2000 and were considered representative of 1999 prices.

b Goldberg, Pinelopi K. 1995. " Product Differentiation and Oligopoly in International Markets: The Case of the U. S. Automobile Industry." Econometrica 63( 4): 891 951, Table II.

( A. 2) characterize the facility supply function under perfect competition. Under this assumption, the supply function for facility j for producing vehicles of class i would take the form:

where pi is the average price for vehicle class i, and ( ij and $ ij are model parameters. The theoretical restrictions on the model parameters that ensure upward sloping supply curves are ( ij $ 0 and $ ij < 0. Figure A 1 illustrates the theoretical supply function represented by Eq. ( A. 2). As shown, the upward sloping supply curve is specified over a productive range with a lower bound of zero that corresponds with a shutdown price equal to and an upper bound given by the production capacity of qj M that is approximated by the supply parameter ( ij. The curvature of the supply function is determined by the $ ij parameter. OMB Review Draft December 17, 2003 A 3 $

p*

q q *

j   j = q Mj 4  j 2   2i Figure A 1. Facility Level Marginal Cost Function ( A. 3)

( A. 4) The $ parameter is related to the facility's supply elasticity which can be expressed as:

Taking the derivative of the facility supply function ( equation A 2) with respect to price and multiplying this expression by pi/ qij results in the following expression for the supply elasticity:

By rearranging terms, $ can be expressed as follows: OMB Review Draft December 17, 2003 3The calibration method is modified for the basic oligopoly model described in Section A. 3 where the marginal revenue term in Eq. A. 8 is substituted for pi.

A 4 ( A. 5)

Under perfect competition, 3 EPA estimated the $ parameter by substituting an assumed supply elasticity for the vehicle class (> ij), the baseline production level by facility j of vehicle class i ( qij), and the average market price for the vehicle class ( pi). EPA assumed that a facility's ability to respond to small price changes depends on its current capacity utilization rate, as outlined in Table A 2. The remaining supply function parameter, ( ij, does not influence the facility's production responsiveness to price changes as does the $

parameter. Thus, the parameter ( j is used to calibrate the model so that each facility's supply equation replicates the baseline production data.

Table A 2. Supply Elasticity Assumptions Capacity Utilization Rate ( R) Supply Elasticity (>)

R > 1 0.10 0.9 < R < 1 0.50 R < 0.9 1.00 A. 3 Baseline Equilibrium The facility's optimization problem with respect to vehicle class i is then given by:

max Ai, j = P( Qi)* qi, j   C( qi, j) ( A. 6)

where Qi is the total number of vehicles of class i available in the market, and P( Qi) is the average price in this vehicle category. In the short run, a facility owner will be willing to supply vehicles at a markup over marginal cost as long as the market price is high enough to cover average variable costs. If revenue falls below average variable costs, then the facility's best response is to shut down production because total revenue does not cover total variable costs of production. In this scenario, producers lose money on operations as well as capital. OMB Review Draft December 17, 2003 A 5 By shutting down, the facility avoids additional losses from operations. The sufficient condition for production at facility j is non negative profits ( Aj):

Aj = TRj   TCj $ 0 ( A. 7)

where TRj is the total revenue earned from the sale of all vehicles assembled at facility j and TCj is the sum of the variable production costs ( production and compliance) and total avoidable fixed costs ( annualized expenditure for compliance capital) incurred by facility j for all vehicles that it produces. The underlying assumption is that if a facility produces multiple models, these models share some fixed costs that cannot be separated. Thus the facility need not shut down if one product line is unprofitable. It will only shut down if the aggregate profits from all models are negative on balance.

To model each vehicle category as a concentrated market, we have used a Cournot model in which facilities exercise some control over the wholesale price of the vehicle. In these noncompetitive models, each supplier recognizes its influence over the market price and chooses a level of output that maximizes its profits, given the output decisions of the others. Employing a Cournot model assumes that suppliers do not cooperate. Instead, each supplier evaluates the effect of its output choice on price and does the best it can given the output decision of its competitors. Thus, given any output level chosen by other suppliers there will be a unique optimal output choice for a particular supplier.

The basic oligopoly model we consider is the " Many Firm Cournot Equilibrium" described in Varian ( 1993, page 290). As is the case in all imperfectly competitive models of profit maximizing behavior, each oligopolist chooses an output level where marginal revenue equals marginal cost. In the Cournot model, marginal revenue is a fraction, Zi, j, of the market price: Zi, j = ( 1 + si, j/, i), where si, j = qi, j/ Qi. If we optimize Eq. ( A. 7) with respect to qi, j we can derive the following first order condition:

P( Qi)°( 1 + sij/, i) = MCij. ( A. 8)

If facility j's market share of vehicle category i ( sij) is 1, the demand curve facing it is the market demand curve. In that case, Eq. ( A. 8) reduces to the profit maximization condition facing a monopolist where marginal revenue equals marginal cost, and the marginal revenue is only a function of the demand elasticity. On the other extreme, if the producer is a very small part of a large market, its market share is near zero, and Eq. ( A. 8) reduces to the profit maximization condition under perfect competition: price equals marginal cost. OMB Review Draft December 17, 2003 A 6 P0 P Q0 Q D MR MC0 Figure A 2. Baseline Equilibrium Using data on the approximated market price of vehicle by type ( P( Qi)), total quantity produced for the domestic market ( Qi), the amount produced by each affected facility ( qij), and the price elasticity of demand (, i,) for vehicle class i, the baseline equilibrium can be established as depicted in Figure A 2. For each of the affected facilities, the baseline automobile production quantities are provided in Tables 2 11 and 2 12 of Section 2. Some facilities produce vehicles in more than one market segment. In these cases, the Agency treated each market segment for a facility as a separate product line thus, a facility may have multiple product lines for the purposes of the economic impacts model. OMB Review Draft December 17, 2003 4The variable compliance costs per vehicle were calculated given the annual production per facility and the variable cost component of the total compliance cost estimate for each facility. These latter cost estimates were provided by the engineering analysis and include annual operating and maintenance costs and monitoring and record keeping costs.

A 7 ( A. 9) A. 4 With Regulation Market Equilibrium The production decision at assembly facility j is affected by the variable compliance costs, ci, j, which are expressed in dollars per vehicle. 4 Each marginal cost equation is directly affected by the regulatory control costs. Dropping subscripts henceforth for convenience, the profit maximizing solution for each existing facility becomes:

Incorporating the regulatory control costs ( c) will involve shifting the marginal cost curve upward for each regulated facility by the per unit variable compliance cost, as shown in Figure A 3. The marginal cost of the affected facilities shifts upward, causing the market cost curve to shift upward to MC1. At the new with regulation equilibrium, the market price increases from P0 to P1 and market output ( as determined from the market demand curve, DM) declines from Q0 to Q1.

Facility responses and market adjustments can be conceptualized as an interactive feedback process. Facilities face increased production costs due to compliance, which causes facility specific production responses ( i. e., output reduction). The cumulative effect of these responses leads to an increase in the market price that all producers and consumers face. This increase leads to further responses by all producers and consumers and, thus, new market prices. The new with regulation equilibrium is the result of a series of these iterations between producer and consumer responses and market adjustments until a stable market price equilibrium is reached where total market supply equals total market demand. A spreadsheet nonlinear solution algorithm was used to compute the with regulation equilibrium price and quantities in each market.

A. 5 Impact on Foreign Trade The final coating regulation will only be binding on facilities that assemble vehicles in the United States. The consequent change in relative prices of domestic versus foreign OMB Review Draft December 17, 2003 5Vehicle classes are aggregated in the foreign trade section because of data limitations.

A 8 P0 P Q0 Q D MR Q1 P1 MC1 MC0 Figure A 3. With Regulation Equilibrium vehicles has two impacts on foreign trade. Foreign imports become more attractive to U. S. consumers and U. S. exports become less attractive to foreign consumers. The Agency has used available data to estimate the magnitude of these impacts as described below.

A. 5.1 U. S. Imports The final regulation may lead to an increase in the price of domestic vehicles, which, in turn, could potentially trigger an increase in demand by U. S. consumers for substitutes such as unregulated, imported vehicles. To estimate this spillover effect, EPA assumed domestic and foreign vehicles are imperfect substitutes that are differentiated by their country of origin ( commonly referred to as the Armington assumption). The conceptual approach for estimating spillover effects using Armington elasticities is described in Gallaway, McDaniel, and Rivera ( 2000). From an economy wide perspective, a representative consumer maximizes his utility for " composite" vehicles ( V) by allocating expenditures between domestic ( D) and imported vehicles ( M), taking relative prices as given. 5 The Armington specification assumes a constant elasticity of substitution ( CES) utility function of the form:

V = " [* M ( F 1)/ F + ( 1*) D ( F 1)/ F] F/( F 1) ( A. 10) OMB Review Draft December 17, 2003 A 9 where F is the Armington elasticity of substitution between domestic and imported vehicles, and " and * are calibrated parameters of the demand function. Utility maximization subject to the budget constraint leads to the following first order condition:

M/ D = [(*/( 1*)) * ( PD/ PM)] F ( A. 11)

Thus, the ratio between imported and domestic vehicles is a function of their relative prices and the elasticity of substitution. Gallaway, McDaniel, and Rivera ( 2000) use monthly data from 1989 through 1997 to estimate Armington elasticities for several manufacturing industries. For SIC 3714, motor vehicle parts and accessories, they estimate a value of 2.07. Additional substitution elasticity estimates for motor vehicles are reported in Ho and Jorgenson ( 1998) and range from 1.52 to 3.59. The Agency has used all three estimates to compute low and high end estimates of the change in import to domestic vehicles ratio for a given change in the price of domestic cars.

A. 5.2 U. S. Exports Exports of U. S. made vehicles can also fall if their own price increases due to the final regulation. While U. S. exports of passenger cars in this industry are only one fourth the level of imports, they still represent about 18 percent of domestic production in 1997 and are growing ( AAMA, 1998). Unfortunately, data were lacking connecting specific facilities to specific markets. Thus, foreign demand for U. S. made vehicles is modeled by one representative foreign consumer using the following constant elasticity demand function:

qx = Bx[ p], x ( A. 12)

where p is the average price of exported U. S. vehicles, , x is the export demand elasticity, and Bx is a multiplicative demand parameter that calibrates the foreign demand equation, given data on price and foreign demand elasticity to replicate the observed baseline year 1999 level of exports. Ho and Jorgenson ( 1998) report export demand elasticities for motor vehicles. These estimates range from   0.9 to   1.55. These export demand elasticity estimates are used along with our estimates of change in the average price of U. S. vehicles to forecast the corresponding change in quantity demanded by foreign consumers. OMB Review Draft December 17, 2003 Appendix B Estimating Social Costs Under Imperfect Competition OMB Review Draft December 17, 2003 6The Agency has developed this conceptual approach in a previous economic analysis of regulations affecting the pharmaceutical industry ( EPA, 1996). For simplicity, this appendix assumes constant marginal costs. The marginal cost curves developed for the economic model are upward sloping curves .

7Fixed control costs are ignored in this example but are included in the analysis.

B 1 B. 1 Social Cost Effects Under Imperfect Competition6 The conceptual framework for evaluating social costs and distributive impacts in an imperfectly competitive market model is illustrated in Figure B 1. The baseline equilibrium is given by the price, P0, and the quantity, Q0. In a pure monopoly situation, the baseline equilibrium is determined by the intersection of the marginal revenue curve ( MR) and the MC curve. In imperfect competition, such as in the Cournot model used in this analysis, the baseline equilibrium is determined by the intersection of MC with some fraction of MR. Without the regulation, the total benefits of consuming automobiles is given by the area under the demand curve up to Q0. This equals the area filled by the letters ABCDEFGHIJ. The total variable cost to society of producing Q0 equals the area under the original MC function, given by IJ. Thus, the total social surplus to society from the production and consumption of output level Q0 equals the total benefits minus the total costs, or the area filled by the letters ABCDEFGH.

The total social surplus value can be divided into producer surplus and consumer surplus. Producer surplus accrues to the suppliers of the product and reflects the value they receive in the market for the Q0 units of output less what it costs to produce this amount. The market value of the product is given by the area DEFGHIJ in Figure B 1. Since production costs IJ, producer surplus is given by area DEFGH. Consumer surplus accrues to the consumers of the product and reflects the value they place on consumption ( the total benefits of consumption) less what they must pay on the market. Consumer surplus is thereby given by the area ABC.

The with regulation equilibrium is P1, Q1. Total benefits of consumption are ABDFI and the total variable costs of production are FI, yielding a with regulation social surplus of ABD. 7 Area BD represents the new producer surplus and A is the new consumer surplus. The social cost of the regulation equals the total change in social surplus caused by the regulation. Thus, the social cost is represented by the area FGHEC in Figure B 1. OMB Review Draft December 17, 2003 B 2 $

P 1 P 0 P 1 C P0 C Q 1 Q 0 Output MC + Control Costs MC D MR A B C D E F G H I J Figure B 1. Economic Welfare Changes with Regulation: Imperfect Competition The distributive effects are estimated by separating the social cost into producer surplus and consumer surplus losses. First, the change in producer surplus is given by ) PS = B   F   ( G+ H+ E) ( B. 1)

Producers gain B from the increase in price, but lose F from the increase in production costs due to regulatory control costs. Furthermore, the contraction of output leads to foregone baseline profits of G+ H+ E.

The change in consumer surplus is ) CS =   ( B + C) ( B. 2)

This reflects the fact that consumer surplus shrinks from the without regulation value of ABC to the with regulation value of A.

The social cost or total change in social surplus shown earlier can then be derived simply by adding the changes in producer and consumer surplus together OMB Review Draft December 17, 2003 B 3 ) SC = ) PS + ) CS =   ( F+ G + H + E + C) ( B. 3)

B. 3 Comparison of Social Cost with Control Cost It is important to compare this estimate of social costs to the initial estimate of baseline control costs and explain the difference between the two numbers. The baseline control cost estimate is given by the area FGH, which is simply the constant cost per unit times the baseline output level. In the case of imperfect competition, the social cost estimate exceeds the baseline control cost estimate by the area EC. In other words, the baseline control cost estimate understates the social costs of the regulation. A comparison with the outcome under perfect competition helps illustrate the relationship between control cost and total social cost.

Suppose that the MR curve in Figure B 1 were the demand function for a competitive market, rather than the marginal revenue function for a monopolistic producer. Similarly, let the MC function be the aggregate supply function for all producers in the market. The market equilibrium is still determined at the intersection of MC and MR, but given our revised interpretation of MR as the competitive demand function, the without regulation ( competitive) market price, P0 C, equals MC and Q0 is now interpreted as the competitive level of product demand. In this type of market structure, all social surplus goes to the consumer. This is because producers receive a price that just covers their costs of production.

In the with regulation perfectly competitive equilibrium, price would rise by the perunit control cost amount to P1 c. Now the social cost of the regulation is given entirely by the loss in consumer surplus, area FG. As this is compared to the initial estimate of regulatory control costs, FGH, the control cost estimate overstates the social cost of the regulation. The overstatement is due to the fact that the baseline control cost estimates are calibrated to baseline output levels. With regulation, output is projected at Q1, so that control costs are given by area F. Area G represents a monetary value from lost consumer utility due to the reduced consumption, also referred to as deadweight loss ( analogous to area C under the monopolistic competition scenario).

Social cost effects are larger with monopolistic market structures because the regulation already exacerbates a social inefficiency ( Baumol and Oates, 1988). The inefficiency relates to the fact that the market produces too little output from a social welfare perspective. In the monopolistic equilibrium, the marginal value society ( consumers) places on the product, the market price, exceeds the marginal cost to society ( producers) of OMB Review Draft December 17, 2003 B 4 producing the product. Thus, social welfare would be improved by increasing the quantity of the good provided. However, the producer has no incentive to do this because the marginal revenue effects of lowering the price and increasing quantity demanded is lower than the marginal cost of the extra units. OMB explicitly mentions the need to consider these market power related welfare costs in evaluating regulations under Executive Order 12866 ( OMB, 1996). OMB Review Draft December 17, 2003 TECHNICAL REPORT DATA ( Please read Instructions on reverse before completing)

1. REPORT NO.

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

4. TITLE AND SUBTITLE Regulatory Impact Analysis for the final Automobile and Light Duty Truck Coating NESHAP 5. REPORT DATE December 2003 6. PERFORMING ORGANIZATION CODE 7. AUTHOR( S) 8. PERFORMING ORGANIZATION REPORT NO.

9. PERFORMING ORGANIZATION NAME AND ADDRESS U. S. Environmental Protection Agency Office of Air Quality Planning and Standards Research Triangle Park, NC 27711 10. PROGRAM ELEMENT NO.

11. CONTRACT/ GRANT NO.

None 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 Final regulation 14. SPONSORING AGENCY CODE EPA/ 200/ 04 15. SUPPLEMENTARY NOTES 16. ABSTRACT Pursuant to Section 112 of the Clean Air Act, the U. S. Environmental Protection Agency ( EPA) has developed National Emissions Standards for Hazardous Air Pollutants ( NESHAP) to control emissions released from the coating of automobiles and light duty trucks ( LDT). The purpose of this rule is to reduce the flow of HAPs from potential emission points within auto and LDT facilities. Eighty percent of the HAPs released are xylene, glycol ethers ( EGBE), MIBK, and toluene. The other HAPs include methanol, glycol ethers, MEK, formaldehyde, and ethyl benzene. The facilities in the auto and LDT source category are controlling HAP emissions from their coatings operations, as required, to meet maximum achievable control technology ( MACT) standards. As of 1999, there were 65 auto and LDT assembly facilities owned by 14 companies. The estimated total annual cost for these facilities to comply with the final MACT standard is approximately $ 154 million. Due to the total annual cost of compliance, an economic impact model estimates that production of autos and LDT declines by 0 to 0.02 percent across various vehicle classes. The estimated price increase due to the regulation is less than 0.01 percent. Pre tax earnings for the companies owning the facilities in this source category decline by about 1.08 percent according to the economic model developed in the regulatory impact analysis. According to the Small Business Administration size standards, none of these businesses are considered small. Based on the economic impact analysis, impacts of the NESHAP on companies owning auto and LDT assembly facilities are anticipated to be negligible.

17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b. IDENTIFIERS/ OPEN ENDED TERMS c. COSATI Field/ Group air pollution control, environmental regulation, economic impact analysis, maximum achievable control technology, automobile and light duty truck 18. DISTRIBUTION STATEMENT Release Unlimited 19. SECURITY CLASS ( Report)

Unclassified 21. NO. OF PAGES 131 20. SECURITY CLASS ( Page)

Unclassified 22. PRICE EPA Form 2220 1 ( Rev. 4 77) PREVIOUS EDITION IS OBSOLETE