Self—Regulation of Pollution: The Role ofMarket Structure and Consumer Information

Devon A. Garviefrom Organized Interests and Self-Regulation: An Economic Approach,

edited by B. Bortolotti and G. Fiorentini, 1999, 206-235, Oxford University Press.

1. Introduction

The purpose of this paper is to provide an analytical framework to assess theefficiency, distributional, and environmental consequences of voluntary codes inpollution—generating industries. In particular, we identify the conditions un-der which voluntary regimes are likely to be a viable alternative to mandatoryregimes. Attention focusses upon the complex interaction among market struc-ture, demand, and environmental factors including imperfect competition amongpollution—generating firms and imperfect consumer knowledge of environmentalconsequences of production.Voluntary codes are a form of self—regulation. Any regulatory regime –

whether it be voluntary or mandatory – consists of a target and institutionalarrangements which provide incentives to attain the target. Institutional arrange-ments include a rule (for example, a voluntary or mandatory code for emissions)and an ex—post governance structure (monitoring and sanctioning activities) whichensure compliance with the rule. A key difference between voluntary and manda-tory regimes is that the choices of target and institutional arrangements are privaterather than public decisions. In particular, since the choice of rule is a privatedecision, the rule is not backed up by the force of law and hence compliance withthe rule is voluntary rather than mandatory. Voluntary codes can be chosen ateither the firm or industry level.1

Four potential sources of market failure are present in our analysis of voluntarycompliance regimes: (i) imperfect competition, (ii) pollution byproducts, (iii) im-perfect consumer information regarding the environmental impact of production,

and (iv) pollution abatement is a public good. These sources of market failureinteract and determine firm and industry incentives to adopt voluntary codes.In an oligopolistic market structure with pollution—generating firms, the first

two sources of market failure work in conflicting directions. The oligopoly itselftends to restrict output relative to the socially efficient (and perfectly competi-tive) level. In contrast, the presence of an unpriced pollution externality leadsto overproduction and hence excessive environmental damage relative to the so-cial optimum. Whether the imperfect competition effect or the externality effectdominates will depend upon the degree of concentration in the industry, technol-ogy and demand conditions, the type of pollutant being emitted and the currentassimilative capacity of the environment (the degree of environmental damage).For instance, the imperfect competition effect will tend to dominate the exter-nality effect in a highly concentrated industry which emits pollutants which tendto break down fairly quickly while the opposite will hold in a less concentratedindustry which emits persistent pollutants.In the absence of legal sanctions, the primary source of compliance incen-

tives in voluntary regimes is consumers. Consumers can effectively sanction firmsby reducing demand for pollution—generating products. Clearly, the ability ofconsumers to sanction firms depends critically on the quality of the informa-tion they possess regarding (or attitudes toward) industrial environmental perfor-mance. Poorly informed consumers possess weak sanctioning power and, hence,compliance incentives are diminished.Finally, the public good nature of pollution abatement efforts leads to an un-

derprovision of abatement technology; firms cannot be excluded from benefittingfrom competitors’ abatement efforts since consumer demand depends upon indus-try environmental performance. Consequently, a free—rider problem in abatementeffort emerges. The free—rider problem is particularly pronounced when consumersare well—informed and can lead to a significant gap in the performance of firm ver-sus industry codes; an industry association is better placed to resolve free—riderproblems since it makes decisions in the industry interest.Simulation results are presented for two broad categories of pollutants – cu-

mulative and noncumulative pollutants.2 The identity of winners and losers involuntary compliance regimes is highly dependent upon the respective levels ofconsumer sanctioning power and market power: for instance, in the case of cu-mulative pollutants, we find that voluntary regimes perform best when consumersanctioning power and market power are strong.The paper is organized as follows. An overview of alternative solutions to the

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externality problem is presented in Section 2. In Section 3, a graphical analysisof voluntary compliance is presented. An algebraic example is derived in Section4. A simulation welfare analysis is presented in Section 5. Concluding remarksare presented in Section 6.

2. Alternative Solutions to the Externality Problem

The idea of fully privatizing or delegating traditional regulatory tasks to a pol-luting industry may initially seem to be a perversion of economic logic. It iscertainly a radical departure from conventional economic thought on solutions tothe externality problem. During the last 75 years, two broad schools of thought– Pigovian and Coasian – have dominated the economic analysis of externalitiesand hence policy—making.3 While Pigovians and Coasians agree that externalitiesare caused by market failure and that correction requires government intervention,they disagree on the scope and degree of public intervention which is required.Neither school of thought suggests full delegation or decentralization as a viablesolution.Pigovians believe that the source of market failure is the missing market for

pollution, that is, environmental assets are not priced. A Pigovian prescriptionfor government intervention entails centralized choice of targets and institutionalarrangements; for example, command—and—control regimes based on performanceor design standards and incentive—based regimes based on taxes or marketablepermits are both centralized solutions to the externality problem – they arecentralized solutions because targets, rules, and ex—post governance structuresare chosen by central authorities even though individual emission decisions maybe decentralized under incentive—based regimes. The regulatory agency, actingin the public interest, acquires and processes information about the costs andbenefits of pollution control and chooses a set of institutional arrangements whichmaximizes social welfare. Pigovian solutions implicitly define a set of propertyrights for polluters.4 Incentive—based rules are based on a polluter pays principle,forcing polluters to internalize external costs imposed on others as a result of theirpolluting activities.In contrast, Coasians maintain that the source of market failure is ill—defined

property rights. They argue that if property—rights are well—defined over environ-mental assets, then decentralized bargaining between polluters and victims willlead to a Pareto—improving and self—enforcing agreement consisting of a mutuallyacceptable level of pollution and compensatory payment. Moreover, if transaction

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costs are zero, then the self—enforcing agreement will attain the social optimum.A Coasian prescription for government intervention is restricted to the definitionof property rights. While the initial assignment of property rights does not haveallocative consequences – even if property rights are not assigned efficiently, de-centralized bargaining will lead to an efficient allocation of property rights – itdoes have distributional consequences. For instance, if a polluter has the right topollute, then correction of the externality requires that the victim pays the polluterto restrict emissions; in contrast, if the victim has the right to a pollution—freeenvironment, then the polluter must compensate victims for any pollution gener-ated. Thus, unlike incentive—based Pigovian rules which require that a polluteralways pays for the right to pollute, the identity of who pays under decentralizedbargaining is determined by the initial assignment of property rights.5

In theory, Pigovian and Coasian solutions can both sustain competitive equi-libria characterized by externalities as Pareto optimum under well—specified con-ditions. Again, although there are no efficiency consequences of choosing onesolution over the other, there will be distributional consequences.In practice, the implementation of Pigovian and Coasian solutions in West-

ern economies has met with limited success. As predicted by innumerable non—Coasians, Coasian solutions are not well—suited to many environmental problems.Many environmental assets are either public goods or common property resourcesfor which property rights cannot be defined. In addition, many environmentalproblems involve large numbers of polluters and victims, leading to substantivecoordination problems, free—riding and high transaction costs. Finally, imper-fect information regarding the opponent’s bargaining curve can result in missedPareto—improving bargains.6 In short, decentralized bargaining cannot resolve theexternality problem because of multiple sources of market failure.Centralized Pigovian solutions have also failed to solve the externality prob-

lem because of multiple sources of regulatory failure. Regulators have imperfectknowledge about the costs and benefits of pollution abatement which result inerrors in the target and rule—setting process and, consequently, welfare losses.Regulatory capture by interest groups such as environmental groups or industryitself also leads to suboptimal outcomes. In addition, limited regulatory resourcesfor monitoring and enforcement leads to underprovision of compliance incentivesand hence incomplete enforcement of environmental laws.Neither decentralized bargaining nor mandatory compliance regimes have been

effective choices for managing the environment. In addition, mandatory com-pliance regimes, particularly the prevalent command—and—control regime, have

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proven to be prohibitively expensive. It is not surprising that debt—ridden govern-ments are searching for more cost—effective solutions to the externality problem.The key question which this paper addresses is whether or not voluntary compli-ance regimes can provide sufficient incentives for the correction of externalities ina cost—effective manner.The success or failure of voluntary and mandatory regimes is, in large part,

determined by the strength of compliance incentives provided by the regime. Intraditional Pigovian analysis, incentives to comply with mandatory codes areprovided in the form of expected financial penalties for noncompliance with thelaw. The source of compliance incentives is the government – the regulatoryagency and statutory law.7 In contrast, incentives to comply with voluntary codesare primarily provided by consumers of the pollution—generating product and, inthe case of industry codes, the industry association.Our analysis departs from traditional Pigovian analysis by explicitly recogniz-

ing the role that consumers play in the environmental protection process. In theabsence of an agency acting in the public interest, consumers can both acquire andprocess information regarding the environmental consequences of industrial activ-ities as well as exercise a powerful sanctioning role in the marketplace throughreduced demand or consumer boycotts. Depending upon preferences, quality ofinformation, and budget constraints, consumers will, to some extent, internalizethe externality in their consumption decisions; in this sense, the role of consumersin a voluntary compliance regime may play a similar role to pollution victims ina Coasian bargaining situation. The key difference between the role of consumersin a voluntary compliance regime and victims in a Coasian bargaining situationis that the behaviour of agents in a voluntary compliance regime is mediated byprices.

3. A Graphical Analysis

3.1. Environmental Preferences and Consumer Demand

Consumers can play a pivotal role in the provision of incentives for firms to volun-tarily reduce emissions in the absence of regulatory directives. A growing empiricalliterature in environmental benefit measurement identifies a positive willingnessto pay on the part of consumers for improvements in environmental quality.8 Apositive willingness to pay for environmental improvements is a monetary indica-tor that consumers hold preferences over different states of the environment. As a

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result, consumer demand depends, in part, on the environmental consequences ofproduction. Let us suppose, for the sake of argument, that consumers’ willingnessto pay for a pollution—generating good, Q, is given by the following relationship:

P (Q,Z) = f(Q)−MD(Z) (3.1)

where Z is the industry level of pollution emitted during the production pro-cess and MD(Z) is the monetized value of the environmental damage caused byan additional unit of pollution – in other words, the marginal damage curve.If consumers do not care about the environmental consequences of production,then willingness to pay for a good depends solely upon the quantity consumed,f(Q); P = f(Q) is a standard inverse demand curve so that willingness to payis decreasing in the level of consumption, Q, due to diminishing marginal ben-efits of consumption. When consumers care about environmental consequencesof production, then their willingness to pay for a product is also decreasing inthe level of pollution which the industry generates. More formally, willingnessto pay is strictly decreasing in industrial pollution levels when the environmen-tal damage function D(Z) is strictly convex in Z – PZ = −DZZ(Z) < 0 sinceDZZ(Z) > 0. Most pollutants are characterized by convex environmental damagefunctions as damages generally increase at an increasing rate as pollution levelsrise. Thus, consumer demand will be dampened in pollution—intensive industriesand enhanced in environmentally friendly industries.

3.2. Impact of Industrial Pollution Abatement on Consumer Demand

Firms can, to some extent, control their pollution emission levels. In particular,several options for reducing pollution may be available to firms; firms’ may beable to reduce pollution emissions by reducing output, shifting their product mixtoward low pollution—intensive goods, changing their production process or byinstalling pollution abatement equipment which lowers the level of waste residualscreated per unit of output. Let us suppose, for simplicity, that a firm is restrictedto two options for reducing pollution emissions: a firm can reduce output and/orinstall an emission control input. For instance, a public utility could reducesulphur dioxide emissions by reducing electricity generation and/or by installingscrubbers in their tall stacks or switching to low sulphur coal. The total levelof emission control input used by the industry is denoted by E. Pollution isthus generated by a process involving output and emission control inputs – Z =Z(Q,E) – where pollution levels are increasing in the level of industry output

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and declining in the industry’s level of emission control input usage.Firm level choices of output and emission control input usage directly affect

the level of pollution and, hence, consumer demand. To see this, let f(Q) = A−Qand MD(Z) = Z so that consumer demand is given by P (Q,Z) = A − Q − Z,whereA > 0. Suppose further that the pollution production function (and, for thisexample, the marginal damage function) is described by Z = Q−γE, where γ < 1parameterizes the efficiency level of the emission control input. The pollutionproduction function assumes that a unit of production increases pollution by oneunit while installation of a unit of emission control input reduces pollution by lessthan one unit γ. As the abatement technology becomes more efficient, γ increasesand a higher proportion of a unit of pollution can be reduced. Substituting Z =Q−γE into P (Q,Z) yields P (Q,E) = A+γE−2Q. We can now see that consumerdemand or willingness to pay, P (Q,E) is a function of Q and E; willingness topay for a good is decreasing in the level of output and increasing in the industry’susage of abatement technology.– INSERT FIGURE 1 HERE –Figure 1 illustrates consumer demand, P (Q;E = 0), when the industry does

not install any emission control inputs. Note that P (Q;E = 0) is simply thedifference between f(Q) and MD(Q;E = 0) – consumers’ willingness to pay fora pollution—generating good is net of the value of any environmental damage costsgenerated during the production process. In other words, consumers internalizethe value of environmental damage costs in their consumption decisions. Pollutionemissions cause the demand curve to pivot inward towards the origin, resultingin a steeper demand curve, and a lower willingness to pay for any given level ofproduction; the total reduction in consumers’ willingness to pay for Q is given bythe area ABC.– INSERT FIGURE 2 HERE –By installing emission control inputs, the industry can reduce the level of emis-

sions per unit of output, hence the level of environmental damage for any givenlevel of output. The marginal damage curve for a fixed level of industry emis-sion control input usage, E, is labelled MD(Q;E) in Figure 2. The installationof E shifts the marginal damage curve MD(Q;E = 0) down and to the rightto MD(Q;E); the downward shift is equal to γE – the amount of waste resid-uals removed and the environmental damage prevented by the emission controlinputs. Notice that when production is below Q(E), no environmental damageis incurred when E units of emission control inputs are installed. Environmentaldamage is increasing for levels of production in excess of Q(E). As the indus-

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try’s level of emission control input usage is increased, Q(E) is increasing and themarginal damage curve shifts to the right. Thus, the industry effectively choosesthe location of the marginal damage curve through its choice of E. Substitutingthe marginal damage curve MD(Q;E) into the inverse demand curve given byequation 3.1 yields the following kinked demand curve:

P (Q;E) =

(A+ γE − 2Q if Q ≥ Q(E)

A−Q otherwise(3.2)

P (Q;E) is illustrated in Figure 2. Note that the γE downward shift in themarginal damage curve leads to an γE upward shift in the demand curve for levelsof production in excess of Q(E). Further, by installing E, the industry can lowerthe reduction in consumers’ willingness to pay by the area ADFC. Thus, industryoutput and emission control input usage affect consumer demand in two ways.First, pollution emissions cause environmental damages which reduce consumers’willingness to pay for a good (inward pivoting of the demand curve). Second, firminvestment in pollution abatement technology can reduce the level of emissions perunit of output and hence environmental damages, thereby offsetting the reductionin consumers’ willingness to pay (outward shift of the demand curve).

3.3. Impact of Pollutant Type and Consumer Knowledge on ConsumerDemand

Two additional factors affect the shape and location of the consumer demandcurve: the type of pollutant emitted as a byproduct of production and the extentof consumer knowledge about the environmental consequences of production.Pollutants can be grouped into two broad categories – cumulative and non-

cumulative pollutants. Cumulative pollutants accumulate in the environment asthe environment has no assimilative capacity to break them down. Examples ofcumulative pollutants include inorganic chemicals, minerals, plastics and radioac-tive waste. In contrast, the environment has some natural assimilative capacityto break down noncumulative pollutants. Provided that the absorptive capacityof the environmental medium is high enough relative to the emission rate, noncu-mulative pollutants may not accumulate in the environment at all. For instance,degradable wastes such as organic residuals are attacked and broken down bybacteria in a body of water while the atmosphere has some capacity to absorbcarbon dioxide emissions. If the assimilative capacity of the environment is ex-ceeded, noncumulative pollutants can become cumulative. In order to distinguish

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between cumulative and noncumulative pollutants, we parameterize the marginaldamage curve as MD(Z) = δZ, where δ > 0. Cumulative pollutants are charac-terized by high values of δ while noncumulative pollutants causing gradual, steadyenvironmental degradation are characterized by low values of δ.Consumer knowledge about the true environmental consequences of production

also plays a major factor in the determination of demand for pollution—generatingproducts. Consumer knowledge about environmental consequences is capturedby the parameter θ ∈ [0, 1] in the inverse demand curve P (Q,Z) = f(Q) −θMD(Z). In words, willingness to pay for a pollution—generating good dependsupon how well—informed consumers are about the true marginal damage curve.9

For instance, consumers of paper products are relatively well—informed (high θ)about clear—cutting practices in the British Columbia lumber industry and theconsequent environmental impacts due largely to the public education efforts ofGreenpeace. In contrast, consumers were relatively poorly—informed (low θ) aboutthe environmental impact of unlined oil sumps used in Alberta during the oil boomin the 1980s.Taking into account the type of pollutant and the extent of consumer knowl-

edge about the environmental consequences of the pollutant, we can rewrite con-sumer demand given by equation 3.2 as follows:

P (Q;E, θ, δ) =

(A+ θδγE − (1 + θδ)Q if Q ≥ Q(E)

A−Q otherwise(3.3)

Referring again to Figure 2, if consumers are well—informed about the envi-ronmental consequences of highly toxic emissions (high θ and δ), then the inwardpivoting (measured by θδ) and the outward shift (measured by θδγE) in thedemand curve will be large. If consumers are poorly—informed about the environ-mental impact of relatively benign emissions (low θ and δ), then the impact ofenvironmental preferences on consumer demand will be small.In the following two subsections, we present a graphical analysis of the social

optimum, monopoly and perfect competition outcome to provide an intuitive feelfor the model of voluntary codes. Algebraic examples of the alternative regimesare presented in the next section, followed by a simulation analysis.

3.4. Socially Optimal Pollution Control

The social optimum is a useful benchmark for evaluating industry choices of out-put and emission control input levels and the resulting level of environmental

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quality in voluntary regimes. A benevolent, perfectly informed social plannerwill choose industry levels of output and emission control inputs to maximize so-cial welfare, where social welfare is the sum of gross surplus less producer andenvironmental damage costs.Social welfare maximization requires choosing an activity level so as to equate

the social marginal benefit of the activity with the social marginal cost. Thesocial marginal benefit of installing emission control inputs, MB∗E = −DZZe,is equal to the reduction in environmental damages which can be obtained byinstalling an additional unit of emission control input. Referring to Figure 3,notice that the social marginal benefit of emission control inputs is downward—sloping, reflecting diminishing marginal returns from the installation of emissioncontrol inputs; diminishing marginal returns arise because the marginal benefitaccruing from emission reductions is falling. The social marginal cost of installingemission control inputs,MCE, is simply the marginal cost of installation;MCE isassumed to be upward—sloping, reflecting increasing marginal costs of abatement.The socially optimal level of emission control input usage, E∗, is found at theintersection point of MB∗E and MCE. Note that E

∗ is independent of θ.– INSERT FIGURE 3 HERE –The socially optimal output choice, given installation of E∗, is illustrated in

Figure 4. As noted earlier, the choice of E determines the location of the marginaldamage curve. Installation of E∗ shifts the marginal damage curve southeast toMD∗. When consumers fully internalize the externality (θ = 1), the demandcurve is given by P (Q,E∗) which is simply the difference between f(Q) andMD∗;P (Q,E∗) measures the net social marginal benefit of output, that is, the marginalbenefit of consumption net of environmental consequences. The socially optimallevel of output, Q∗, is found at the intersection point of P (Q,E∗) andMCQ, whereMCQ measures the marginal cost of producing Q. The socially optimal price ofQ when consumers fully internalize the externality is denoted by P ∗ (θ = 1). Ifconsumers do not internalize the externality (θ = 0), then the demand curveis given by f(Q). The socially optimal level of output is now the intersectionpoint of f(Q) andMC∗, whereMC∗ is the social marginal cost incurred with theproduction of Q; MC∗ is the vertical summation of MD∗ and MCQ.– INSERT FIGURE 4 HERE –Notice that while there are no allocative consequences associated with the

value of θ – Q∗ is independent of θ – the price of Q does vary with θ. Whenconsumers do not internalize the externality in their consumption decisions, thenthe socially optimal price of Q is P ∗ (θ = 0); clearly, P ∗ (θ = 0) > P ∗ (θ = 1). The

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socially optimal price of Q is monotonically decreasing in θ. It can also be seen inFigure 4 that consumer surplus is increasing in θ, that is, consumers are better offthe more informed they are about the environmental consequences of production.

3.5. Industrial Incentives to Adopt Voluntary Codes

What incentive do firms have to voluntarily install emission control inputs? Sup-pose that there is a single producer of the product who has the power to setprices. A profit—maximizing monopolist will choose a level of emission controlinput usage by equating the private marginal benefit of an additional unit of in-put to the marginal cost of installation. The marginal benefit to the monopolistof installing the input, MBME , is the incremental revenue earned; MB

ME = PEQ,

where PE = θδγ is the value of the reduction in the marginal damage when anadditional unit of the emission control input is installed. Alternatively, PE is theincrement which consumers are willing to pay for a unit of a more environmen-tally friendly good. Referring to Figure 2, each additional unit of emission controlinput installed results in an outward shift in the demand curve of θδγ. Thus, theincentive for a monopolist to install abatement technology is a pecuniary one –the monopolist can increase profits by exploiting consumers’ environmental pref-erences to raise consumers’ willingness to pay. It is important to emphasize thatthe monopolist’s decision to install abatement technology is a purely voluntarydecision. The decision is motivated by self—interest and does not require govern-ment intervention in any form, including mandated technology—based standardswherein regulations require the installation of a particular kind or level of emissioncontrol input.The monopolist’s privately optimal choice of emission control input is illus-

trated in Figure 3. Note that, in contrast to MB∗E, MBME is upward—sloping.

The monopolist’s profit—maximizing choice of E is found at the intersection pointof MBME and MCE and is denoted by EM . It can be shown that MBME willalways cut MCE below MB∗E, hence a monopolist will install too low a level ofemission control inputs relative to the social optimum – EM < E∗.– INSERT FIGURE 5 HERE –Underprovision of abatement technology results in a higher level of environ-

mental damages for any given level of output. The marginal damage curve asso-ciated with EM is labelled MDM in Figure 5. Note that MDM lies everywhereabove and to the left of MD∗.When θ = 1, market demand for the monopolist’s output Q is given by

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P (Q,EM). The monopoly output level is the level of output which equates theprivate marginal benefit of output, MR(Q,EM), with the marginal productioncost, MCQ. It is easy to see in Figure 5 that the monopolist restricts outputbelow the socially optimal level – QM(θ = 1) < Q∗. In addition, the monopolyprice, PM(θ = 1), is higher than the socially optimal price, P ∗.The divergence between Q∗ and QM is decreasing in θ. In words, as consumers

become better informed about the environmental consequences of production, amonopolist will adopt more environmentally friendly production processes, raisingconsumers willingness to pay for its product and hence enhancing the monopolist’sincentive to produce output. As θ decreases, consumers willingness to pay for theproduct is less responsive to the monopolist’s choice of abatement technology,reducing both the incentive to adopt more environmentally friendly productionprocesses and to expand output. For instance, when θ = 0, any pecuniary ad-vantage of installing emission control inputs is removed as demand is no longerresponsive to environmental performance. Consequently, MBME = 0 and henceEM = 0. Referring to Figure 5, demand is now given by P (Q,EM = 0). Themonopolist’s optimal output choice is restricted further to QM(θ = 0). Notice,however, that the monopoly price which emerges when θ = 0, labelled PM(θ = 0),is lower than PM(θ = 1). When 0 < θ < 1, QM and PM will lie in the respectiveintervals

hQM(θ = 0), QM(θ = 1)

iand

hPM(θ = 0), PM(θ = 1)

i.

The monopolist’s ability to mark—up prices derives directly from its marketpower. Figure 5 illustrates a paradox – a monopolist’s market power is increasingin consumer knowledge about the environmental consequences of production. Tosee this, observe that the monopolist’s market power or ability to mark—up pricesis directly related to the price elasticity of the demand curve, ²:

P −MCQP

=1

|²| (3.4)

where 0 < |²| ≤ 1. As the price elasticity of demand declines, demand becomesless responsive to price changes and the monopolist’s ability to mark—up pricesincreases. The price elasticity of demand is strictly decreasing in θ, hence, marketpower is strictly increasing in θ. Intuitively, as consumers become better informedabout environmental consequences, the demand curve becomes steeper and hencedemand is less responsive to price changes.The price elasticity of demand (market power) is also decreasing (increasing)

in δ, the slope parameter of the marginal damage curve. Hence, the monopolist’smarket power will be increasing as the hazardousness of the pollution emissions

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is increasing; for instance, market power will be stronger when the pollutant is acumulative as opposed to a noncumulative pollutant.An important implication of the positive relationships between market power

and θ and δ is that voluntary codes can potentially have strong anti—competitiveeffects. The anti—competitive effects of voluntary codes will be strongest whenthe industry is concentrated, consumers are well—informed and the pollutant inquestion is particularly damaging to the environment.The extent to which consumers’ environmental preferences affect firm choice

of emission control input usage also depends upon the level of competition inthe industry. As competition in the industry increases, individual firm’s marketpower is declining and, as a result, incentives to install emission control inputs arediminished. In a perfectly competitive industry, for instance, firms are sufficientlysmall that individual decisions will not affect market prices. When firms areprice—takers, there is no incentive to voluntarily install emission control inputssince firms cannot capture the pecuniary benefit. In other words, the marginalbenefit to a perfectly competitive firm of installing abatement technology is zeroand, given positive costs of installation, profit maximization requires that notechnology be installed. The perfectly competitive output equilibria QC(θ = 0)and QC(θ = 1) are shown in Figure 5. When 0 < θ < 1, the competitive outcomewill lie somewhere between these two solutions.

4. An Algebraic Example

For simplicity, we adopt a linear—quadratic model of homogeneous firms.10 Thenumber of firms, n, is fixed, hence there is no entry or exit into the industry.Each firm produces a pollution—generating good q, where Q = nq is industryoutput. Individual producers may choose to install an emission control input e toreduce emission levels z, where z = q − γe; industrial emission control usage andpollution emissions are given by E = ne and Z = nz, respectively. An individualproducer’s cost of production and abatement is assumed to be C(q, e) = bq+ k

2e2,

where b, k > 0. Pollution generated by the industry causes environmental damageD(Z) = δ

2Z2, where δ > 0. Consumer inverse demand is given by equation 3.3.

Finally, in order to satisfy the Second Law of Thermodynamics, we make thefollowing parameter assumption:11

γ <

sk

θδ(4.1)

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4.1. Social Optimum

We assume that the social planner has full information about the environmentalconsequences of production. The social planner will choose levels of q and e tomaximize social welfare SW (Q,E;n), where social welfare is the sum of grosssurplus, U (Q,E) =

RQ0 f(t)dt − θD(Z(Q,E)), less environmental damage costs

not internalized by consumers, (1− θ)D (Z (Q,E))), and industry production andabatement costs, C(Q,E):

maxq,e

SW (Q,E;n) =Z Q

0f(t)dt−D (Z (Q,E)))− C(Q,E)

Note that social welfare is independent of θ since the social planner takes intoaccount the full environmental consequences of production. The social planner’sdecision rules for output and emission control input are characterized by thefollowing pair of equations:

q∗ : f(Q)−DZZq − Cq = 0 (4.2)

e∗ : −DZZe − Ce = 0 (4.3)

Substituting the assumed functional forms and after some algebraic manipu-lation, we can derive the Pareto optimal decision rules as:

q∗ =³k + nδγ2

´F (4.4)

e∗ = nδγF (4.5)

z∗ = kF (4.6)

where

F =A− b

n [k(1 + δ) + nδγ2](4.7)

Again, note that the Pareto optimal decision rules do not depend upon θ. Fur-ther, the environmental damage parameter δ is negatively correlated with outputand pollution and positively correlated with the level of emission control input.Firm (industry) level quantities are strictly decreasing (increasing) in n.

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4.2. Uncoordinated Industry Equilibrium: Company Codes

Following convention, we adopt the standard assumption that firms behave asCournot—Nash competitors, that is, each producer chooses output and emissioncontrol input levels to maximize own profits, πi, taking as given that the otherproducers are also choosing their best actions:

maxqi,ei

πi(q1, ..., qn, e1, ..., en;n) = P (nXi=1

qi,nXi=1

ei)qi − C(qi, ei)

An individual firm’s decision rules are characterized by the following equations:

qci : P + Pqqi − Cq = 0 (4.8)

eci : Peqi − Ce = 0 (4.9)

An individual firm’s private incentive to undertake abatement, Pe = θδγ, isstrictly increasing in the level of consumer information, θ. If consumers are un-informed about the industry’s environmental performance, then θ = 0 and themarginal benefit to a firm from abating pollution vanishes since price no longervaries with e. As a result, firms do not have any incentive to adopt pollutioncontrol methods and ec = 0. If consumers have knowledge about industrial envi-ronmental performance, then 0 < θ ≤ 1 and consumers can exercise their powerto discipline an industry, providing firms with a positive price incentive to vol-untarily undertake abatement efforts to reduce emission levels. Note that theincentive to voluntarily comply is also related to a firm’s market power: if firmsare price—takers, then the positive price effect and, hence, the incentive to volun-tarily comply are absent.Equation 4.9 also illustrates that a free—rider problem exists in the choice of

abatement effort. Abatement effort or emission control input usage is a publicgood. No firm can be excluded from the positive benefits (outward shift in thedemand curve) of an individual firm’s installation decision – nonexclusivity leadsto a free—rider problem. Since firms cannot be excluded from the benefits of com-petitors abatement efforts, their own incentive to invest in abatement technologyis diminished when investment choices are uncoordinated. Individual producersdo not internalize the benefits to others of their adoption level. An individualproducer only takes into account the private marginal benefit of adoption, Peqi,when choosing a level of abatement rather than the social marginal benefit, PeQ,which is the increase in industry marginal revenue.

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Turning to equation 4.8, we can observe that an individual producer’s outputlevel also depends upon consumer knowledge about the industry’s environmentalperformance as well as own and competitors abatement efforts and competitorsoutput levels. The direction of the distortion in output levels will largely dependupon the relative magnitudes of the imperfect competition effect and the exter-nality effect. Output levels will be too low if the imperfect competition effectdominates and too high if the externality effect dominates.To determine which output effect dominates – the imperfect competition

effect or the externality effect – we evaluate equation 4.2 at Qc and E∗. LetP = P (Qc, E∗). The imperfect competition effect dominates if and only if thefollowing inequality holds:

P − (1− θ)DZZq − Cq > 0 (4.10)

Define the Cournot equilibrium price as P c = P (Qc, Ec). Equation 4.10 canbe rewritten as:

P c − CqP c

>P c − P − (1− θ)DZZq

P c

or, alternatively, as:

s

|ε| >P c − P (θ = 1)

P c(4.11)

where s measures the market share and ε measures the price elasticity of thedemand curve at the Cournot—Nash equilibrium. The left—hand side of equation4.11 measures the degree of market power at the Cournot—Nash equilibrium whilethe right—hand side measures the proportion of uninternalized damage in themarket price. Equation 4.11 is more likely to hold when θ is large and n or δ issmall.In equilibrium, since firms are symmetric, qci = q

cj = q

c and eci = ecj = e

c. Sub-stituting the symmetry conditions and the assumed functional forms into equa-tions 4.8 and 4.9 and after some algebraic manipulation we can derive the followingsolutions:

qc = kG (4.12)

ec = θδγG (4.13)

16

zc =³k − θδγ2

´G (4.14)

where

G =(A− b)

k(1 + n)(1 + θδ)− n(θδγ)2 (4.15)

Output and pollution levels are strictly decreasing and emission control in-puts are strictly increasing in θ and δ. Firm (industrial) quantities are strictlydecreasing (increasing) in n.Comparing equations 4.5 and 4.13, it is easy to show that ec < e∗, that is,

abatement effort will always be underprovided relative to the social optimum.Comparing equations 4.4 and 4.12, we can show that qc < q∗ whenever equation4.11 holds.

4.3. Coordinated Industry Equilibrium: Industry Code

Industries have the legal option of coordinating on pollution control efforts. Al-though firms cannot explicitly collude on output levels without violating anti—trustlaws, they can coordinate on pollution levels by cooperatively choosing abatementtechnologies. The irony is clear – choice of an industry code results in pricecollusion since the industry association effectively holds price—setting power. Ac-cordingly, we model a coordinated industry equilibrium as a two—stage game. Inthe first stage of the game, an industry association chooses a level of emissioncontrol input, e, to maximize joint or industry profits, given individual firm out-put levels. In the second stage of the game, firms noncooperatively choose outputlevels, qi, taking the emission control input level as fixed at e. The nature of thegame captures two features of the competitive environment. First, as mentionedabove, while firms can legally collude on an industry voluntary code, they cannotcollude on output levels, hence output levels must be chosen at the individualfirm level. Second, the sequential moves of the industry association and firmsintroduces the ability of the industry association to commit to a voluntary code.We adopt the equilibrium concept of subgame perfection and, accordingly, solvethe game backwards.In the second stage of the game, an individual producer chooses an output

level to maximize own profits, taking the voluntary code as fixed:

maxqi

πi(q1, ..., qn; e, n) = P (nXi=1

qi; e, n)qi − C(qi; e)

17

An individual firm’s output decision rule is characterized by the followingequation:

∂πi∂qi

= P + Pqqi − Cq = 0 (4.16)

Equation 4.16 implicitly defines an individual producer’s output level as a func-tion of competitors output levels, qJj , where j 6= i, and the industry voluntarycode, e. Given firm symmetry, qJi = q

Jj = q

J , and substituting the assumed func-tional forms, we can write an individual producer’s output rule or voluntary coderesponse function as

qJ (e) =A− b+ nθδγe(n− 1) (1 + θδ)

(4.17)

Equation 4.17 reveals that firm level output is strictly increasing in the in-dustry voluntary code, e. Once again, the positive relationship between q ande derives from the demand externality – installation of abatement technologyshifts the demand curve outward, enhancing the incentive to produce.In the first stage of the game, the industry association chooses an emission

control input level, e, to maximize industry profits subject to firms’ voluntarycode response function qJ (e). Clearly, the ability to choose and commit to avoluntary code effectively gives an industry association price—setting power. Theindustry association’s decision problem can be written as:

maxe

Π = nπ = nhP (nqJ (e) , ne)qJ (e)− C(qJ (e) , e)

iThe industry association’s decision rule is characterized by the following equa-

tion:

∂Π

∂e=

∂π

∂qJdqJ

de+

∂π

∂e= 0 (4.18)

Note that ∂π∂qJ

= ∂πi∂qi+ Pqq

J(n − 1), where ∂πi∂qi

is defined by equation 4.16.Applying the Envelope Theorem, equation 4.18 reduces to:

∂Π

∂e= Pqq

J(n− 1)dqJ

de+

∂π

∂e= 0 (4.19)

Substituting for ∂π∂eyields:

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eJ :

"Pq(n− 1)n

dqJ

de+ Pe

#QJ − Ce = 0 (4.20)

Two key results emerge from equation 4.20. First, an industry association canresolve the free—rider problem which characterizes uncoordinated firm choice ofabatement technology. When an industry code is adopted, the industry associa-tion chooses a level of installation which maximizes the benefits to all membersof the industry, that is, the increase in industry marginal revenue due to higherdemand for environmentally friendly products, PeQJ . In other words, the indus-try association fully internalizes the benefits accruing to all members from anygiven level of installation. In contrast, when firms choose voluntary codes nonco-operatively, they only consider the private benefits of installation. Since industrybenefits of emission control input installation always exceed individual benefits,underprovision of abatement technology will be less pronounced in the case ofcompany codes.Second, the industry association takes into account the strategic costs asso-

ciated with the indirect effect on industry output. Comparing 4.20 and 4.9, weobserve that an industry association takes into account the indirect output effecton industry marginal revenue, Pq

(n−1)n

dqJ

deQJ ; the indirect output effect is a cost

associated with increasing the level of a voluntary code – an additional cost ofincreasing e is the loss in marginal revenue due to movement down the demandcurve.Substituting the assumed functional forms into equation 4.20 and after some

algebraic manipulation, we can derive the following solutions:

qJ = k(1 + n)H (4.21)

eJ = 2nθδγH (4.22)

zJ =³k(1 + n)− 2nθδγ2

´H (4.23)

where

H =(A− b)

k(1 + n)2(α+ θδ)− 2(nθδγ)2 (4.24)

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Comparing equations 4.13 and 4.22, it can be shown that an industry asso-ciation will choose a higher level of emission control input usage than an unco-ordinated industry, that is, eJ > ec. The gap between levels of company andindustry codes is increasing in θ and δ, that is, when consumers are well—informedand pollution emissions are cumulative; incentives to adopt voluntary codes arestrongest under these conditions and hence the free—rider problem will be mostpronounced. In addition, since dq

de> 0, it follows that qJ > qc. Further, it can be

shown that pollution levels are lower and market prices are higher when industrycodes are implemented, that is, zJ < zc and P J > P c.Summarizing, a stable and credible industry association can resolve the free—

rider problem, resulting in higher overall levels of abatement efforts which enablefirms to produce higher levels of output and emit lower levels of pollution.1 How-ever, although firms do not explicitly collude on output choice when industrycodes are adopted, output and emission control input decisions are interdepen-dent. As a result, market power is enhanced when industry codes are adopted,resulting in higher market prices.

5. Simulation Analysis

Simulation of the oligopoly models of company and industry voluntary codesprovide important insights into the conditions under which a voluntary complianceregime is likely to be a viable alternative to a mandatory regulatory regime forprotecting the environment. The simulations focus on the roles of three criticalparameters in the model: θ (consumer knowledge), n (market structure), and δ(environmental damage). Numerical simulation results on quantities and welfaremeasures are presented in Tables A1-A3 in the Appendix. Discussion of thesimulation results are presented below.We first discuss the role of consumer information, parameterized by θ. As

consumers become better informed about the environmental consequences of pro-duction, firm incentives to reduce pollution levels are enhanced; as θ increases,pollution abatement is achieved by installing increasingly higher levels of emissioncontrol inputs and reducing production levels. Although emission control inputsare underprovided in both industry and company code regimes, higher levels areinstalled when firms coordinate; the gap between installation levels in industryand company code regimes is increasing in θ and is particularly large when the

1We note that an assurance problem may exist, leading to cartel stability and commitmentissues. However, analysis of such issues is beyond the scope of this paper.

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free—rider problem is significant (high θ, δ and n). Output levels are also higherwhen firms coordinate on abatement technology choices. When consumers arepoorly—informed, pollution levels will be excessive, particulary in competitive in-dustries, leading to market prices which do not reflect the full social costs ofproduction. However, as θ increases, higher levels of emission control input usageand output levels in highly concentrated industries can lead to a reduction in pol-lution below the socially optimal level. This strategic manipulation of pollutionlevels enhances market power, leading to high mark—up pricing. Referring backto Figure 4, recall that the socially efficient price is declining in θ. When θ = 0,the socially efficient price equals the full social marginal cost of production. Asθ increases, consumers internalize an increasingly higher level of the externalityin their consumption decisions and hence, the socially efficient price is falling.When θ = 1, the socially efficient price reflects only the marginal production cost.In contrast, in a market economy, price is an increasing function of θ. Thus, theproportionate change in price between a voluntary regime and the social optimumis increasing in θ.Given that the adoption of pollution reduction practices is voluntary and that

firms are profit—maximizers, firms will always gain as a result of the introduc-tion of voluntary regimes. Producer surplus will also be higher when firms cancoordinate and resolve the free—rider problem. We find that producer gains arehighest when consumers are well—informed (as market power is increasing in θ)and are particularly high in concentrated industries. Consumer surplus, on theother hand, is strictly decreasing in θ in a voluntary regime – knowledge makesconsumers worse off; in contrast, consumer surplus evaluated at the socially effi-cient levels of output and emission control inputs in strictly increasing in θ, thatis, knowledge does make consumers better off in a first—best world. Declining con-sumer surplus is due to the strategic manipulation of prices in voluntary regimes.Consumer losses are particularly high when industry is concentrated and lowestwhen industry codes are implemented in competitive markets. In general, thereis a transfer of surplus from consumers to producers in voluntary regimes.The environmental consequences of voluntary regimes is also highly depen-

dent on the level of consumer information. In general, environmental damagesare declining as θ increases. However, damages will be excessive (and perhapscatastrophic) in competitive industries. Environmental damages will also be ex-cessive in concentrated industries when consumers are poorly—informed. However,as consumer knowledge increases, strategic behaviour will result in substantiallyreduced emission levels and damage levels below the socially optimal level.

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Welfare losses will always arise in voluntary regimes but are declining in θ.Welfare losses will be substantively higher in company code regimes whenever thefree—rider problem is significant. In addition, welfare losses will be high when con-sumers are poorly—informed about the environmental consequences of cumulativepollutants and in the case of a competitive industry emitting a noncumulativepollutant. Notably, welfare losses are relatively small when consumers are well—informed and the industry is highly concentrated.We next discuss the role of market structure, parameterized by n. As the

level of competitiveness in a pollution—generating industry increases, the abilityof firms to exploit consumer environmental preferences declines. As a result, thecapacity of a voluntary regime to control emission quantities, a fundamental con-cern of environmental regulators, rapidly deteriorates. Excessive emissions leadto the highest level of damages and the highest welfare losses when pollutants arecumulative and consumers are poorly—informed. Welfare losses are not significantwhen there is a small degree of competition in industries which emit noncumu-lative pollutants and in industries which adopt industry codes to limit emissionsof cumulative pollutants. In general, voluntary regimes will not perform well inhighly competitive industries. However, welfare losses may potentially be smallfor sufficiently high levels of competition.Finally, we discuss the role of pollutant type, parameterized by δ. We find

that voluntary regimes result in relatively small welfare losses when consumershave strong sanctioning power (high θ) and producers have strong market power(low n) for a wide range of pollutants. In contrast, voluntary regimes result inrelatively large welfare losses whenever producers have weak market power; theexception is the case of strong consumer power and an extremely benign pollutant.Voluntary regimes also perform well in the case of noncumulative pollutants, weakconsumer power and strong producer power.The simulation results are conveniently summarized in Tables 1 and 2. Con-

clusions, derived from the simulation tables presented in the Appendix and Tables1 and 2, are summarized in Tables 3 and 4.– INSERT TABLE 1 HERE –– INSERT TABLE 2 HERE –Whether voluntary regimes provide efficient and cost—effective arrangements

for protecting the environment depends upon the relative performances of vol-untary and mandatory regimes. As discussed in Section 2 of the paper, there isconsiderable evidence that current regulatory structures are neither efficient norcost—effective. Measures of welfare losses incurred under current regulatory struc-

22

tures are not available but anecdotal evidence suggests that losses may potentiallybe quite large. We adopt the rather arbitrary rule—of—thumb that if welfare lossesunder a voluntary regime are less than 12-15%, then voluntary regimes are poten-tially a viable alternative to mandatory regulation. Applying this rule—of—thumbto our simulation results we find that there are indeed conditions under which vol-untary regimes should be seriously considered as a viable alternative to mandatoryregulation.– INSERT TABLE 3 HERE –Referring to Table 3, we conclude that voluntarism or self—regulation should

not generally be considered as a viable means of dealing with cumulative pollu-tants except in an environment where consumers are well—informed and an indus-try code can be successfully implemented in a highly concentrated industry. Inthis case only, the imperfect competition effect dominates the externality effect,leading to small welfare losses overall. However, it must be recognized that insuch an environment, self—regulation will result in a large transfer of surplus awayfrom consumers to producers. Consumers will experience large losses in surplusrelative to the social optimum due to the anti—competitive effects of voluntarycodes in this environment.– INSERT TABLE 4 HERE –Referring to Table 4, we conclude that self—regulation should be considered

as a viable alternative to mandatory regulation for noncumulative pollutants ex-cept in an environment where consumers are poorly—informed and the industryis relatively competitive. When both consumers and producers are weak, vol-untarism can potentially have disastrous environmental and welfare implications.Whether voluntarism may potentially dominate mandatory regulation in a com-petitive environment as consumers become better informed depends largely onhow rapidly environmental damages escalate. If consumers are strong and pro-ducers are weak, voluntarism should be considered if and only if damages fromthe pollutant are rising slowly and gradually and competition is not too strong.In contrast, when producers are strong, the models analysed and simulated abovepredict that overall welfare losses are well—contained in voluntary regimes. Again,there are distributional and environmental consequences associated with the adop-tion of voluntarism. Voluntary regimes lead to a transfer of surplus away fromconsumers to producers. In addition, whenever there is an asymmetric distri-bution of power between consumers and producers, the environment loses. Theenvironment wins only in the case of strong producers and strong consumers.

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6. Conclusions

An analytical framework for assessing the efficiency, distributional and environ-mental consequences of voluntary codes is derived and presented in the paper. Theanalysis shows that conditions do exist under which welfare losses incurred undervoluntary regimes can be relatively small. For instance, voluntary regimes mayprovide viable alternatives to mandatory regulation when consumers are well—informed and producers have significant market power. In addition, if pollutantsare of a noncumulative nature, voluntary regimes can be a viable alternative evenwhen there is an asymmetry in producer and consumer power.A number of important issues emerge from the foregoing analysis. When firms

have price—setting power, market incentives do exist for firms to voluntarily re-duce pollution emissions in the absence of regulatory directives. Moreover, marketincentives are enhanced the better informed consumers are regarding the environ-mental consequences of production. We find that firms will strategically exploitconsumers environmental preferences to raise profits and that market power ispositively related to the level of consumer informedness. Ironically, when the anti—competitive effects of voluntary codes are the strongest, overall welfare losses fromvoluntary regimes are the lowest. Anti—competitive effects can, however, have po-tentially strong distributional consequences – namely a large transfer of surplusaway from consumers to producers.A direct implication of the positive relationship between consumer knowledge

and producer power is that government strategies which focus exclusively on pub-lic information provision to enhance the efficiency of voluntary regimes may havethe unexpected and undesired effect of strenthening the anti—competitive effectsof voluntary codes. The analysis strongly suggests that delegation of environmen-tal regulation to the private sector should be subject to some form of governmentoversight. For instance, voluntary codes should be subject to vigorous scrutinyor monitoring by the government agency charged with the task of enforcing anti—trust laws since voluntary codes may have strong anti—trust implications.The analysis also emphasizes the importance of understanding the role of mar-

ket structure when deciding among alternative approaches for protecting the en-vironment. Although the analysis presented above focusses on an oligopolisticmodel of industry structure, preliminary analysis of a dominant firm—competitivefringe market structure shows that voluntary regimes can potentially have lessextreme distributional consequences when a firm with strong market power issubject to the pressure of a competitive fringe.12 The presence of the competitive

24

fringe restricts the ability of the dominant firm to exploit consumers environmen-tal preferences and hence the exercise of market power. In particular, consumersmay actually gain from a transition to voluntarism. In addition, a model withentry and exit could be examined to determine whether the adoption of voluntarycodes can act as a strategic barrier to entry. Thus, further analyses of alterna-tive market structures should be undertaken to obtain additional insights into theworkings of voluntary regimes.Although the above analysis focusses on the use of voluntary codes for control-

ling pollution, the framework could, with the appropriate modifications, be used toanalyse the use of voluntary codes in other areas. For instance, the analysis couldbe fruitfully applied to the adoption of voluntary codes in the area of industrialhealth and safety practices as well as industrial labour practices. The frameworkpresented above is useful for understanding the efficiency and distributional con-sequences of voluntary codes whenever a demand externality is present, that is,whenever consumer demand is dependent upon industrial practices. In addition,the analysis clearly shows that the success of voluntary regimes is environmentor industry dependent; the outcome of voluntary regimes is highly dependent ontechnological, demand and environmental factors. An important advantage of theabove framework is that it enables policy—makers to identify the key determiningfactors which must be present to ensure that adoption of voluntary codes will bea viable alternative to mandatory regulation.

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7. Endnotes

1. While polluters will always adopt self—enforcing voluntary codes at the firmlevel, a free—rider induced compliance problem may arise in the case of in-dustry voluntary codes; if firms cannot credibly commit to comply with anindustry code, the industry association must provide sufficiently strong com-pliance incentives or an ex—post governance structure to prevent instability.Although enforcement issues are potentially important, we restrict attentionto an analysis of the incentives to adopt voluntary codes at both the firmand industry level.

2. In general, the environment has some assimilative capacity for breakingdown noncumulative pollutants while cumulative pollutants, as the namesuggests, cumulate in the environment. As a result, environmental damagestend to escalate much more rapidly for cumulative as opposed to noncumu-lative pollutants.

3. I broadly classify the Pigovian school of thought to include the literature onmandatory regulatory regimes. See Pigou (1920) and Coase (1960).

4. Under a command—and—control regime, the public holds the right to a so-cially acceptable level of pollution. Polluters may freely pollute up to thesocially acceptable level of pollution but must pay for the right to pollutebeyond that point in the form of penalties for noncompliance. In contrast,the public holds the right to a clean environment under an incentive—basedregime and polluters must pay for the right to pollute any level of pollution.

5. Under Pigovian solutions, the extent to which pollution control costs arepassed on to consumers in the form of higher prices depends upon the elas-ticity of the demand curve.

6. See Farrell (1988) and Maskin (1994).

7. The levying of financial penalties requires that the regulatory agency under-take two costly activities – monitoring and sanctioning activities. Monitor-ing entails site visits to obtain measurements of emission or concentrationlevels and testing to determine whether or not the firm is in compliance withthe law. If a firm is found to be out of compliance, then regulators oftenhave a range of sanctioning options available, ranging from administrative

26

hassling or fines to criminal prosecution. For a detailed analysis of regula-tory choice of monitoring and sanctioning activities see Garvie and Keeler(1994).

8. See generally Braden and Kolstad (1991).

9. An alternative interpretation of θ is that θ represents the weight that a fully—informed consumer places on the environmental consequences of production.

10. See Garvie (1998) for a more general analytical treatment.

11. The Second Law of Thermodynamics states that entropy increases. In otherwords, it is physically impossible to eliminate all waste, hence z > 0 for allq > 0.

12. See Garvie (1998).

8. References

Braden, J. and Kolstad, C. (eds.). (1991). Measuring Demand for EnvironmentalQuality. Amsterdam: North—Holland.

Coase, R. (1960). ‘The Problem of Social Cost’. Journal of Law and Economics,3: 1-44.

Farrell, J. (1988). ‘Information and the Coase Theorem’. Journal of EconomicPerspectives, 1: 113-129.

Garvie, D. (1998). ‘Voluntary Codes: The Role of Market Structure and Con-sumer Information’. Queen’s University Mimeo.

Garvie, D. and A. Keeler. (1994). ‘Incomplete Enforcement and EndogenousRegulatory Choice’. Journal of Public Economics, 55: 141-162.

Maskin, E. (1994). ‘The Inisible Hand and Externalities’. American EconomicReview, 84: 333-337.

Pigou, A. (1920). The Economics of Welfare.

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9. Appendix

Simulation results for different values of θ, δ, and n are presented in the Tablesbelow. Each Table provides data on proportionate changes in market price (P )and industry quantity variables (output, Q, emission control input usage, E, andpollution discharges, Z) which emerge under company codes (labelled c) andindustry codes (labelled J) relative to the socially optimal variables. In addition,proportionate changes in consumer surplus (CS), environmental damages (D)and social welfare (W ) relative to the social optimum are also reported for thetwo regimes to facilitate analysis of the distributional and efficiency consequencesof voluntary codes. We do not report proportionate changes in producer surplussince profit—maximization always results in higher firm profits in voluntary regimesand strictly higher profits in coordinated voluntary regimes.Table A1 reports the simulation results regarding the role of consumer infor-

mation, θ. Results are reported for four different environments: (i) cumulativepollutant emitted by highly concentrated industry (δ = 4, n = 2), (ii) cumulativepollutant emitted by highly competitive industry (δ = 4, n = 250), (iii) non-cumulative pollutant emitted by highly concentrated industry (δ = .5, n = 2),and (iv) noncumulative pollutant emitted by highly competitive industry (δ = .5,n = 250).– INSERT TABLE A1 HERE –Table A2 reports the simulation results regarding the role of market structure,

n. Simulation results are reported for four different environments: (i) consumerspoorly about cumulative pollutant (θ = .2, δ = 4), (ii) consumers well—informedabout cumulative pollutant (θ = .8, δ = 4), (iii) consumers poorly—informed aboutnoncumulative pollutant (θ = .2, δ = .5), and (iv) consumers well—informed aboutnoncumulative pollutant (θ = .8, δ = .5).– INSERT TABLE A2 HERE –Table A3 reports the simulation results regarding the role of pollutant type,

δ. Simulation results are reported for four different environments: (i) poorly—informed consumers, highly concentrated industry (θ = .2, n = 2), (ii) well—informed consumers, highly concentrated industry (θ = .8, n = 2), (iii) poorly—informed consumers, highly competitive industry (θ = .2, n = 250), and (iv)well—informed consumers, highly competitive industry (θ = .8, n = 250).– INSERT TABLE A3 HERE –

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