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Industry-Specic vs. Antitrust Agencies: a

contribution on the institutional arrangement of

telecommunications policy

Ral Castro ([email protected])Universitat Pompeu Fabra

Version: July 2003

Abstract

In this paper, we focus on the choice from the institutional rangebetween pure Industry-Specic and pure Antitrust regimes in an in-centive framework that highlights exposure to regulatory capture andregulatory competence as the main driving forces. We show that thetrade-o faced by Government and Parliament in designing regulatoryinfrastructure for business such as telecommunications is determinedby how dierent administrative controls of agencies are with respect

to their dierences in building eective regulatory competence. Ac-cordingly, a dominant Industry-Specic Agency is the chosen patternwhen regulatory capabilities are considered the key factor for insti-tutional design and the cost of raising public funds is large. Finally,the choice of Industry-Specic Agencies has less demanding conditionsthan for Antitrust Agencies, when they are compared with a solutionof regulatory separation that drive large eects of cost duplication andintermediate improvement of collusion detection.

1 Introduction

Regulation of industries is generally performed under any of two broad insti-tutional arrangements: generic institutions and legislation that are equallyvalid to all or a wide range of sectors and industry-specic frameworks thathave their scope of action focused on a relatively well-dened group of sec-tors1. Industry-specic regimes imply that either (i) certain issues of someindustries are regulated by a framework that is specic to them, while the

Revised version of a paper presented at the Business Workshop at the UniversitatPompeu Fabra, Barcelona, December 1999. We thank Bruno Cassiman and EduardoRodes for helpful comments. The usual disclaimer applies.

1 Another way to refer to this dilemma is as light-handed vs. heavy-handed regulationrespectively. They indicate the amount of rules and institutions that the industry faces.

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rest of the industries are not regulated on those issues at all or (ii) those

specic frameworks include the same regulatory agenda applied to most ofindustries (by generic agencies), but only they apply to a particular indus-try or (iii) a combination of both. Industry-specic regulation is generallyassociated to utilities and network businesses, which includes telecommuni-cations, electricity, gas, airlines, water, railways.

We nd in the generic eld regulatory frameworks such as Labor,Health, Competition, Fiscal, or Environmental Regulation.

In the specic case of telecommunications regulation, the division linesbetween those institutional alternatives have been traditionally stable. How-ever, since the late 1980s and 1990s, the choice of what institutional arrange-ment should be used in regulating the above industries became a relevant

issue of discussion and analysis. Regulatory institutional arrangements in-volve at least two features: regulatory jurisdiction assignment and communi-cation channels among government bodies of the same or dierent regulatoryhierarchy2. Firstly, the worldwide process of privatization and liberalizationin telecommunications called for a reform of the regulatory framework tosupport the success of both processes. In most of the cases, the preferenceof industry specic regulation was renovated, although with the shift of reg-ulatory responsibilities from central Government oces (Ministry Oces)to, more or less, independent telecommunications-specic agencies. Sec-ondly, in very few cases, the previous choice was reverted; either becauseno industry-specic agency is created with liberalization (New Zealand) or

because years after their creation, the trend is towards a larger involvementof generic regulatory frameworks (Australia and the UK).

In this paper, building on the Laont and Tirole (1993) framework, wedevelop a model to analyze the conditions that promote the choice in thespectrum between a pure Antitrust regulation and a pure Industry-Specicregulation as well as the dierent combined arrangement of shared respon-sibilities. In such framework, conditions of rents derived from asymmetricinformation and non-benevolence of the regulator explain why the problemof institutional design for regulation is relevant. Despite the model is spe-cic to a business in particular, it has very straightforward implications fortelecommunications regulatory framework.

Why the choice between Industry-Specic and Antitrust regulation? Intelecommunications, the most frequent and largest degree of overlapping ofregulatory scope is usually between Industry-Specic Agencies (ISAs) andAntitrust Agencies (AAs) and, consequently, it is one of the most relevantdilemmas for institutional design3. Most of the issues of the regulatory

2 Laont and Martimort (1998)3 In telecommunications, and for our purposes, a generic framework of regulation may

be implemented based on, not only antitrust enforcement, but also on a multisectoralinstitution that acknowledges the convergence process in technologies and markets aroundtelecommunications (broadcasting, internet, content design and other network industries)

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agenda of an Industry-Specic Agency have competition implications and

therefore are potentially subject of review by an Antitrust Agency. Evensome of the most complex issues of technology, network design or stan-dard compatibility that are traditionally regulated by an ISA, also haveimportant implications for competitive dynamics. Scott (1998) argues thatthe choice between both regimes reects a competition between groups oftheorists and practitioners: Regulatory and competition/anti-trust com-munities are to some degree in competition with each other and oeringcompeting paradigms of oversight or construction of markets . The fol-lowing subsections discusses on the case for assigning more jurisdiction toeither the Industry-specic Agency or the Antitrust Agency based on theirdierences in regulatory competence and transparency4

Competence reasons for choosing an industry-specic regime

In general, the choice of industry-specic agencies tend to be based on rea-sons of competence superiority to perform the regulatory job.

In some industries and specially in telecommunications, one of the mainreasons of such superiority is related to the context complexity. Telecommu-nications has been considered a quite complex industry from a technologicalpoint of view. Part of its regulatory agenda include setting technology stan-dards, technology and demand implications of network externalities, costand quality eects of service interdependence, technical and competitive fea-

tures of unbundling network components, setting access conditions to newplayers and spectrum management. These issues have critical implicationsfor the industry performance and require a degree of technical specializa-tion and amount of resources so large, that might generate organizationalunbalances in a generic regulatory agency5.

Both Cave (1997) and Bergman et al (1999) highlight that the transitionperiod from monopoly to competitive market conditions in telecommunica-tions requires prescriptive powers to face signicant regulatory complexity.We interpret that one reason is that there are so many issues aecting thedevelopment of competition, so many dilemmas aecting eciency and ahigh speed of change in the business environment that prescriptive powers

would be preferred to simplify complexity6

.4 Analyzing allocation of regulatory powers among antitrust EC and member state in-

stitutions, Van den Bergh and Camesasca (2002) indicate: ...information asymmetriesbetween competition authorities and rms may argue in favour of descentralised compe-tition policy. These benets in terms of reduction of infromation costs amy, however, beoutweighed by the increased danger of capture

5 OECD (1999) clasies the regulatory taks for network industries with three categories:competition (antitrust), economic (prices and license issuing) and technical regulation.The issues referred above mainly correspond to features of technical regulation.

6 The view of the British regulator OFTEL in its 1999 Guidelines for Competition Actenforcement in telecommunications illustrates some of the peculiarities of the industry,

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Related to the previous, a specic regulator would build industry-specic

information and professional competences faster than a generic regulator, be-cause it would have a less dispersed policy agenda and face fewer dicultiesto inuence Government resource allocation than being the industry sectionof a broader institution. From this standpoint, the ISA would have betterchances to build eective regulation.

In practice, eectiveness of competition law enforcement might be alsoinsucient. One of the limitations is how lengthy its procedures tend tobe: the procedural framework in Antitrust requires more time for a naldecision at the administrative level than in a specic-heavy-handed agency 7.In particular, comparing the speed of procedures of the Telecommunicationsand the Competition Act in the UK, OFTEL (1999) considers the former a

faster route.The agenda scope of AAs also becomes a competence limitation for

their eectiveness in telecommunications regulation. Antitrust Agencies arethere to build cases against transactions and practices dened as anticom-petitive. Such framework drives two main limitations for managing andenforcing Universal Service Obligations8 (USOs): (i) USOs are usually inconict with competition concerns and (ii) USOs management goes beyondrule denition and involve administrative procedures associated to nancingand allocating responsibilities of the system among rms. Performing suchtasks requires an institutional solution to problems of funding and asymmet-ric regulation (all rms are not equally subject to certain rules9). Based on

that, Green and Teece (1997) consider that Universal Service is a key polit-ical obstacle to complete the shift from regulation to deregulated markets.Scott (1998) and Laont and Tirole (2000) also consider that a signicantrole of the social agenda and redistributive functions in telecommunicationsregulation is an obstacle for moving its regime towards the antitrust frame-work. As well as USO enforcement, Knieps (1997) and Shelanski (2002)state that the enforcement of interconnection regulation and network com-ponents unbundling as well as more service-based market competition rather

used to justify a special regulatory framework. They include (i) bottlenecks in networkaccess, specially local networks, (ii) very high xed and sunk costs and limited availabilityof radio spectrum as sources of monopoly power, (iii) network economies, interoperability

externalities and call termination externalities gives quite specic peculiarities to telecom-munications wholesale and retail demand and (iv) past features such as public ownershipand statutory monopoly for a long period of time determines that history matters intelecommunications. See OFTEL (1999)

7 If antitrust enforcement is usually based on case-by-case investigations while theindustry-specic regulation uses prescriptive rules (applied to all cases), such dierencebetween ex post and ex ante administrative processes would drive dierent lengths.

8 From Noam (1997): A universal telecommunciations service goal, simply dened, isa public policy to spread telecommunications to most members of society, and to makeavailable, directly or indirectly, the funds necessary

9 Traditionally, universal service and social goals of telecommunications policy havebeen assigned and performed exclusively by the larger operator of xed network.

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than facilities-based competition drive signicant complexity that tend to

be better faced by the ISA.Finally, the lack of proved experience of frameworks of pure generic reg-

ulation reduces its attractiveness to be replicated elsewhere. New Zealandhas been the main reference in the OECD of full replacement of industry-specic regulation. Australia has been the main follower since 1989. Thislimited number of illustrative examples supports the case for an industry-specic framework, as far as the cost of implementation other arrangementsincreases with the lack of international experience. Similarly, the increas-ing importance of international coordination of regulation promotes insti-tutional similarity: for example, regulatory institutions in EU forums orin the International Telecommunications Union are usually industry-specic

agencies. However, we may still say that the reluctance towards such in-stitutional redesign is also because the specic regulator itself usually leadsthis process which may aect negatively its own ocials career.10.

Consequently, reasons associated to organizational matters, the speed tolearn and take decisions and eectiveness in managing USOs explain thecompetence advantages of using an Industry-Specic regulator in a highlycomplex context. However, despite the above reasons the Antitrust Agen-cies may also oer other competence advantages as the ISAs. Assumingantitrust enforcement more based on case-by-case investigations and theindustry-specic regulation more based on prescriptive rules (as we didabove), the former seems more adequate to oer telecoms a exible frame-

work of regulation which is required in context with fast technological andmarket innovations11. Additionally, Dewatripont, Jewitt, and Tirole (1999)show that the smaller and more homogenous set of tasks of the AA withrespect to the ISA drive incentives to perform a larger eort. 12.

Although this arguments in favor of the AA may be incorporated inthe model, we work with the assumption that complexity is a key driver ofinstitutional design, making the Industry-Specic Agency a more eectiveregulator who faces smaller costs to learn the relevant pieces of informationabout the industry.

10 Following the previous point, the transformation in the US since the 1996 Telecom-munications Act, despite the complex web of factors, illustrate an institutional movement

from a high antitrust involvement to a high FCC involvement11 Soon (1997): The higher the degree of prescriptiveness the more allied the regula-

tion becomes to existing conditions and hence the more likely it is to become outdated.Innovation in solving the problem that the prescriptive regulation seeks to address is hin-dered because there is no incentive for the regulated party to do other than comply with theprescription.

12 The paper analyzes how incentives of government agencies ocials are aected whenthey face a multitask agency framework It nds that the larger the number of functions(the more multitask and vague the agency), the lower the total eort performed by theagency. This is a result of the damages that multiple tasks create on the linkage betweenoutside perception of talent and actual performance

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Transparency reasons for choosing a (generic) antitrust regime

In general, several of the reasons that explain the choice of an antitrustagency to regulate an industry are based on the advantages to drive trans-parency in its performance and easier-to-control procedures. It reduces therisk of collusion between the agency and the rm.

The specialization distance of antitrust agencies with respect to theindustry context, controls the risk of regulatory capture. Generic humancapital have more outside employment opportunities, which makes it lessattached to and dependent on one particular business. Consequently, therevolving doors problem would be smaller than for specic human capital.As a result, antitrust ocials would be less willing to participate in collusiveagreements with the industry and such larger bargaining power would drivea smaller number of side-contracts than under the regulation of Industry-Specic ocials. Similarly, antitrust enforcement would give new entrantsand other interested parties better opportunities to reduce their disadvan-tage with respect to incumbents in terms of relationships with the regulator.As the number of agents with expertise already built in antitrust proceduresand jurisprudence (as well as knowledge of agency ocials) would belarger and more dispersed than in an industry-specic regulation13, the in-formational rents of incumbents generated by specic assets in experience,knowledge and relationships would be smaller. Consequently, the possibil-ities of the agency to maintain side-contracts with a particular rm or aportion of the industry are smaller.

Secondly, competition policy would be enforced by the regulatory bodyspecialized in such task. Priorities of contemporary telecommunications pol-icy have evolved towards competition policy issues: interconnection agree-ments, service resale, entry management, numbering portability, unbundlingof network components, mergers and strategic alliances, among others. Bydenition, antitrust agencies have a larger expertise in competition issuesand policy than any other institutions; that is a source of advantage of thegeneric solution in driving ecient regulation.

As a result of the previous, competition policy in telecommunicationswould be more consistent with the policy applied to other industries; all

industries would face similar principles, methodologies and reasoning. Inparticular, consistency and non-contradiction in competition policy enforce-ment would be important among dierent industries that share conditionsof network externalities, essential facilities and asset specicity. On the con-trary, ISAs are not subject to so strong consistency requirements 14. Suchconsistency of the competition policy with the approach applied in other in-dustries increases the degree of transparency to the extent that it reduces the

13 An indication of this would be the larger number of consultancies and legal advisorsspecialized in antitrust than in telecommunications policy.

14 Laont and Tirole (2000)

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space for discretionary decisions and preferential rents derived from special

cases.This is particularly important in the telecommunications business as the

boundaries of its relevant market are being redrawn permanently. This isexplained by a convergence process among telecommunications, broadcast-ing, and internet from the service standpoint, as well as gas, railroads andelectricity from the infrastructure standpoint. Even if a specic agency ischosen as solution, the business redrawing process generated by the con-vergence process would also require redesigning the institutional scope ofregulation in order to fulll a minimum requirement of consistency amongthe related businesses. Obviously, the result would be more generic andcloser to antitrust enforcement.

Similarly, Tiller (1998) show that agencies increase their policy discretionthrough the strategic choice of instruments according to their diculty to bereviewed. The superior industry knowledge of the ISA would allow it to facethe strategic choice of regulatory instruments (and forms side-contracts) inmore advantageous conditions than the AA.

The advantage attributed to single-task (as the AA) over broad-missionagencies (as the ISA) because of their incentive to perform larger eort (asexplained above) is extended in Laont and Martimort (1998) in terms of itslower "exposure" to capture: side-contracts with interest groups are easierto be identied by outsiders and their generic knowledge is accompanied lessintense relationships and communication15.

In summary, the transparency superiority of the Antitrust Agency, as-sumed bellow in the model, is based on the idea that more safeguards restrictthe space for discretionary changes by the AA than by the ISA. Such safe-guards include a better knowledge of the framework by potential entrantsand outsiders, a larger jurisprudence, the requirement of policy consistencyacross industries, better Checks and Balances framework, less exposure ofthe antitrust ocials to revolving-doors problems16 and its less competentchoice ofhard-to-be caught instruments . This explains the model assump-tion that the costs of administrative control are smaller for the AntitrustAgency than for the Industry-Specic one.

In this paper, the regulatory capture model of Laont and Tirole (1993)is used to build a framework of choice in regulatory design from the spec-trum between a pure industry-specic and a pure antitrust regime. Theseare institutional solutions frequently compared by practitioners17, but lack-ing of a model that formalize the choice. In addition to asymmetric in-

15 Creating an anti-trust agency with a broad mission is bad if the centralized agencykeeps the same technologies for information acquisition as what would have bee availableto industry-specic agencies

16 See Heyes (1999)17 See Bergman et al (1998), OCDE (1999), Scott (1998) and Shelanski (2002)

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formation problems between the rm and regulator and across regulatory

hierarchies (New Regulatory Economics approach), dierences in regulatorytechnologies are also considered. Consequently, both extremes of the insti-tutional spectrum are dierentiated by their exposure to regulatory captureand their eectiveness to build regulatory capabilities. Such dierence al-lows the paper to contribute in the discussion of regulatory design with aconguration that highlights the trade-o between regulatory eectivenessand cost of agency control (transparency) as determinant of the institutionalchoice from the spectrum.

In addition to a corner-solution context in which the AA or the ISAare chosen as fully responsible, this paper also consider the case of joint

jurisdiction of the AA and the ISA. Traditionally this problem has been

mostly considered within the context of regulatory federalism18. However,other literature developed from the Multiprincipal and Common Agencyapproach for several organizational issues may also apply to institutionaldesign for regulation at the same geographical scope19. As Laont and Mar-timort (1999), this paper also considers the Common Agency features ofsplitting the regulatory responsibilities between two institutions; however,they make each institution fully specic to a particular dimension of the in-dustry20 and this paper allows both institutions have overlapping (but notidentical) capabilities to regulate.

Although the structure of the model is not telecommunications-specic,its application is quite straightforward. Firstly, the ISA and the AA char-

acterizations are very related to the telecommunication regulatory context:technology and services are perceived as complex enough to value specializedknowledge from regulators, telecommunications-specic agencies usually in-clude very broad missions, complex rules

The model follows the well known three-layer structure, Principal-Supervisor-Agent, used for regulation. The Principal corresponds with the Government,the Parliament or the representative voter. The Regulatory Agency followsthe role of Supervisor. Finally, the Agent is the rm or the whole industry:Note that this agent assumption simplies the competitive dynamics of theindustry:

18 Viscusi et al. (2000) and Van den Bergh and Camesasca (2002) provide useful discus-sions on the federalism discussion on antitrust and regulatory enforcement in the US andEuropean context respectively.

19 See Gal-Or (1997) survey20 Each institution is capable to learn about and regulate business dimensions of the

industry that the other cannot and viceversa

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2 Model

Consider a Principal (Government) and an Agent (a Firm) contracting onoutput q and transfer t. Both are assumed to be risk-neutral.

The Agent: The objective function of the Agent is U = tq, where isan eciency parameter. For simplicity assume 2 f1; 2g where 1 > 2.The probability distribution is hx; 1xi. Therefore, the parameter x informshow likely it is that the rm is of the inecient type. It can be interpretedas an approximation of the innovation spillover environment of the industry,to the extent that the larger 1 x, the more frequent the ecient rms areand the more spread the innovation is among the industry players.

The Principal: The objective function of the Principal maximizes the

expected social welfare which is given by the sum of consumers utility S(q),where S0 > 0 and S00 < 0 plus the expected payo of the Agent minusexpected cost of public funds used in the contract:

W = S(q) + E[U(q)] (1 + )E[t] = S(q) q t (1)

where is the (strictly positive) opportunity cost of raising public funds, is the expected value of sigma, t the expected value of transfers, and E[:] isthe expected value operator.

The Supervisor: The contract can be dened such that the Principalcontracts a Supervisor (Regulator) with capabilities to uncover the relevantpieces of information about the Agent for the contract enforcement. Dene w

as the transfer of the Principal to the Regulator when unknown informationis reported and normalize to zero her opportunity cost.

2.1 Model with Symmetric Information

At the moment of signing the contract, both Principal and Agent do notknow the value of . When the transfer is paid both know that value.

The Principal maximizes social welfare in q, t(1) and t(2) subject toU(1) 0 and U(2) 0 (individual rationality constraint).

Proposition 1: The rst-best solution is described by q

FB

suchthat S0(q) = (1 + ) and t(i) = iqFB for both j 2 f1; 2g :21

From Laont and Tirole literature on regulation, we know that the in-dividual rational constraint binds because public funds have an opportunitycost, dened by . Under a full information context, such opportunity costmakes that the optimal result is obtained driving no rents to the agent.

The rst-best solution qFB is found within a context of symmetric infor-mation, which implies that the Principal has full access to such informationwith no cost. Therefore, there is no real role for a Regulator. Alternatively,

21 The proofs of all propositions are in the appendix

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the same result is obtained with an institutional setting in which the Reg-

ulator actually works when he is assumed to be benevolent. However, asa building block for the case with asymmetry of information, let us con-sider a Regulator in this model. Since there is symmetry of information,the problem posed by a Regulator is trivial. The Principal maximizes socialwelfare:

W = S(q) + E[U(q)] + w (1 + )(E[t] + w) = S(q) q (t + w) (2)

in q, t(1), t(2), and w subject to U(j) 0 for j = 1; 2 (individualrationality constraint) and w 0 (regulator rationality constraint).

Proposition 2: The rst-best solution is described by qFB such

that S0(q) = (1 + ), w = 0; and t(i) = iqFB for both j 2 f1; 2gIn a context such that the Principal contracts with the Regulator and

the Firm and none of them can hide relevant pieces of information from thePrincipal, the result drives no informational rents. Consequently, the utilityobtained by both rm types and the transfer to the Regulator are equal tozero and the obtained welfare does not have any incentive discount orcost.

2.2 Model with Asymmetric Information

We need asymmetric information to get a more interesting result. In other

words, assume that the Principal does not know the true value of whenthe transfer is paid. Possibly the Principal faces a very high cost to learnsuch information. Clearly, a type 1 Firm is not a problem because it isinecient. But a type 2 Agent is a problem because by declaring to beof the other type, she will make a gain (1 2)q

FB. First-best cannot bedelegated! The role of the Regulator is no longer trivial, to the extent he hasan rm auditing technology that the Principal lacks of. Therefore, incentivearrangements are required to make her reveal what she learns (as we willsee later, we will look for collusion-proof arrangements22).

To solve the problem with asymmetric information, we need to (a) ndthe separating equilibrium by backwards induction and (b) show that the

separating is better than the pooling equilibrium.

2.2.1 Separating Equilibrium

As expected from this three-layer structure, there are two sources of informa-tion hiding: the Firm and the Regulator, and they require specic incentivearrangements to prevent it. The incentives against regulatory capture areconsidered in the Collusion section and in this section, we concentrate on theimplications of incorporating a (Firm) revelation constraint to the Principal

22 Laont (1994)

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action. Type 2 Agent is honest if and only if by lying bears an expected

loss L greater than the gain t(1) t(2).This conguration represents a simplication of an implied process of au-

diting that drives hard information about the Agent with a probability, say

, that is in ]0; 1[ ;used by Laont and Martimort (1999), and L representsthe expected value of loss given by such probability. With this, instead ofworking with two scenarios of income of the 2 Agent depending on whetherthe rm is discovered or not (that is, t2 loss with probability and t2 withprobability 1 ), we work with just one scenario: t2 L; where L = loss:

To enhance an expected loss L, the regulator must have a monitoring andauditing mechanism or technology that costs R(L), where R0 > 0, R(0) = 0,R0(0) = 0, and R00 0. The intuition behind this function denition is

that the main cost driver of the monitoring activities is their degree ofcomplexity. The expected loss L is a proxy for it, because a large value iscalculated in function of large potential gains from hiding, which can nancehiding sophisticated eorts of the rm. Additionally, ne setting could havea clause of automatic accounting of the monitoring costs.

Expected social welfare (the objective function of the Principal) is givenby

W = S(q) + E[U(q)] + w R(L) (1 + )(E[t] + w)

= S(q) q (t + w) R(L) (3)

When comparing (2) and (3), the dierence is given by R(L): Such reg-ulatory costs are the resources invested to uncover the unobserved aspectsof the industry and become the welfare cost of an asymmetric informationcontext.

In this decision context, the Principal maximizes social welfare in q,

t(1), t(2), w, and L subject to U(1) 0 and U(2) 0 (individualrationality constraints), w R(L) (regulator rationality constraint), andL t(1) t(2) (revelation or incentive compatibility constraint).

Proposition 3: Dene r =(1x)1+ . If the marginal cost of audit-

ing R0 is greater than r,t2 = 1q; otherwise, t2 = 2q.The reference value r = (1x)1+ represents the fraction of one unit of

the total cost of public resources that corresponds to the shadow cost ofresources transferred to an ecient rm, which might be considered as areference of the gains obtained from auditing the industry. Consequently,the income transferred to the rm depends on whether the auditing cost ofthe regulator are suciently nanced by such auditing gain.

Proposition 4: If R0 < r, the second-best solution (when thereis asymmetry of information) is described by qAI:1 such that S0(q) =(1 + )[ + R0(1 2)], w = 0, t(1) = 1q

AI:1, and t(2) = 2qAI:1.

Proposition 5: If R0 > r, the second-best solution (when thereis asymmetry of information) is described by qAI:2 such that S0(q) =

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(1 + ) + (1 ), w = R(L), t(1) = 1qAI:2, and t(2) = 1q

AI:2

The positive utility of the type 2 Agent given by U(2) = t(1) 2q >0, includes the informational rent of such type of rm (given by (1 2)q).When R0 > r, the regulator owns an regulatory technology (or regulatoryassets) such that its auditing costs are too high to uncover false informationdeclared by the rm, no regulatory auditing is performed and the maximuminformational rent is allowed.

Proposition 6:The second-best solutions (with asymmetry ofinformation) qAI:1 and qAI:2 are always less than the rst-best so-lution qFB.

Information asymmetries, in any of its solutions, drive higher marginalcosts than in a full information context. Both, (1 + )R0(1 2) and

(1 ); are additional marginal costs that reduce output in both scenariosof regulatory auditing costs with respect to the rst-best level.

2.2.2 Pooling Equilibrium

The Government can also decide to avoid any regulatory eort to monitorthe industry performance. In this setting, this would imply the Governmentavoids learning relevant pieces of information for its contract agreementswith the industry. Consequently, the contract is not contingent to anythingto be identied later on. In the model, this pooling solution drives t(2) =t(1) = 1q (and consequently L = 0).

By construction, the Government could have chosen this solution whensolving above. And the Government actually does it when R0 > r, that is,when auditing is too costly. Therefore, the separating must be necessarilybetter than pooling equilibrium. In fact, as (1 + )[ + R0(1 2)] >(1 + ) (1 ); when regulation is performed, the output level underseparating is larger than under a pooling strategy of the Government.

2.3 Collusion

The separating equilibrium we have derived above is not collusion proof.Why? Because, when regulatory auditing is performed, both the Regulatorand the Agent make zero gains whereas if they collude, they could sharet(1) t(2). A collusion proof equilibrium is achievable as long as theexpected loss from collusion osets the gain. Assume the Regulator is alsoaudited and, if colludes, it has an expected loss F (as in the case of L; thisis a simplication of a process of Government auditing with a probabilityof detection dierent than 1). To enhance an expected loss F the Principalmust invest T(F)(1 + ), where T0 > 0, T(0) = 0, T0(0) = 0, and T00 0.

Aiming at deriving a collusion proof equilibrium, we need to (a) nd thecollusion proof separating equilibrium and (b) show that it is better than

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the separating equilibrium with collusion. Expected social welfare is now:

W = S(q) q (t + w) R(L) T(F)(1 + ) (4)

The Principal maximizes social welfare in q, t(1), t(2), w, L, and Fsubject to U(1) 0 and U(2) 0 (individual rationality constraint),

w R(L) (regulator rationality constraint), L t(1) t(2) (revelation orincentive compatibility constraint), and F t(1) t(2) (collusion proofconstraint).

Proposition 7: Dene r = (1x)1+ T0

. If the marginal cost ofauditing R0 is greater than r, t2 = 1q; otherwise, t2 = 2q.

Note that the critical value under collusion-proofness constrains is smallerthan under the second-best result, because the latter is discounted by T

0

(inthe second-best result no Government auditing was performed and T0 = 0).As nancing the Government auditing of the Regulator implies shrinkingthe gains from regulation itself; it makes the whole regulatory mechanismmore expensive and the Government (Principal) becomes more willing togive rents to the ecient type of rm (Agent 2).

Proposition 8: If R0 < r, the collusion-proof equilibrium is de-scribed by qCP such that S0(q) = (1 + )[ + R0(1 2)] + T

0(1 2),w = R(L), t(1) = 1q

CP, and t(2) = 2qCP.

Proposition 9: If R0 > r, the equilibrium is described by qAI:2

such that S0(q) = (1 + ) + (1 )], w = 0, t(1) = 1qAI:2, and

t(2) = 1qAI:2:

As above, when the auditing technology is too expensive to be -nanced by its marginal gain, (1x)1+ T

0, the contractual setting does notinclude a Regulator and the industry (or the ecient type of rms) enjoysinformational rents. In such case, the output contracted by the Govern-ment is equal to the output contracted under Asymmetric Information withno collusion-proof conditions; note that both drive the same regulation-freecontext with a pooling solution.

Proposition 10: If R0 < r, the collusion-proof solution qCP isalways less than the second-best solution qAI:1.

Again, Government monitoring of the Regulator performance adds an-other source of marginal cost. It reduces the output level under a collusion-proof setting with respect to the second-best result, when R0 < r: Otherwise,it is the same, since there is no regulatory enforcement mechanism. Actually,what happens is that, now, the Government adds to the Regulator eortsto overcome information asymmetries its own eort to overcome the non-benevolence of the Regulator, requiring a smaller output to be sustainable.

2.3.1 Pooling Equilibrium

From propositions 5 and 9 we know that when regulatory auditing is toocostly or its gains are too small, the Government decides not to include a

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Regulator in its industry contracts. Given its lack of competence to learn

relevant pieces about the industry, this would imply a pooling strategy ofcontracting. Similarly, the non-regulation setting does not have any riskof regulatory capture and such collusion-proof solution, by construction,determines that no Government activity of auditing is required.

2.4 Types of regulatory regimes: Antitrust and IndustrySpecic Regulation

Now we move to use the previous setting to analyze the dilemma between twodierent types of regulators: an antitrust and an industry-specic one. Therst section considers them as alternatives for a pure regulatory structure:

either the antitrust agency (AA) or the Industry-Specic Agency (ISA) ischosen as the model for regulatory actions. The following section considersthe combined action of both models of regulations and the conditions inwhich a combined regulatory setting is preferred to a pure one.

Both regulators, AA and ISA, are dened as dierent in the two maindimensions of the model and based on the telecommunications characteriza-tion from the above discussion in the Introduction: regulatory technologies(regulatory eectiveness) and willingness to build eective side-contractswith the industry (exposure to regulatory capture). In terms of the rstdimension, the AA is assumed as less eective in auditing the industry thanthe ISA, which means that R0AA(L) > R

0

ISA(L) for all L > 0: The degree

of specialization of the ISA is given by a larger endowment of informationalassets about the industry or more specic expertise in monitoring it thanthe AA. Additionally, the prescriptive approach of the ISA in telecommuni-cations gives it advantages in dealing with the industry complexity and theenforcement of Universal Service Obligations.

On the other hand, the ISA is assumed as more likely and capable tobuild successful collusive agreements with the industry; this is a larger ex-posure to regulatory capture. Above in the introduction, several argumentshave been considered to support such assumption. The revolving-doors phe-nomena is particularly intense for the ISA; the AA is less competent tomake its strategic choice of regulatory instruments protected from admin-

istrative controls; the better knowledge, larger jurisprudence and enforce-ment consistency across businesses of the Antitrust framework reduces theagency discretion. Therefore, the cost of being audited by the Govern-ment and being detected in its side-contracts is larger for the ISA than theAA: T0AA(F) < T

0

ISA(F) for all F > 0. Note that the model assumptionspresented above imply a simplication of the dierences between both in-stitutional solutions discussed in the introduction. In the model, regulationenforcement of the AA is only focused on the telecommunications business,which implied that its regulatory oversight on other sectors is not considered.

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2.4.1 Anti-trust Regulation versus Industry-Specic Regulation

Propositions 8 and 9 provide a rule for including a Regulator or not in thecontract, which allows to analyze the suitability of each of the institutionalsolutions considered, the AA and the ISA. If for both agencies R0 + T0 >(1x)1+ , auditing is too costly, none of them is chosen, the pooling solution

is optimal and hence there is no regulatory problem. Regulation does nothave any justication because every type of rm is considered behaving thesame way. If for only one of the agencies R0 + T0 < (1x)1+ , that should bethe chosen as Regulator. So the interesting case is when both have R0 and

T0 so that we have a separating equilibrium for both types of regulatoryarrangement.

Dening the above notation of costs so that they are specic to eachagency, consider T0AA and R

0

AA as the AA0s marginal costs of administrative

control and regulation respectively: Similarly, dene T0ISA and R0

ISA as theISA0s marginal costs of administrative control and regulation respectively:Assuming that for both agencies such costs drive separating equilibrium,their rule of choice comes from identifying the one with the lowest marginalcost: R0AA + T

0

AA 7 R0

ISA + T0

ISA:

Proposition 11:If R0AA+T0

AA < R0

ISA+T0

ISA, the Regulator shouldbe AA; otherwise, it should be ISA.

This expression is an straightforward approximation of the relative de-gree of cost advantage of an Antitrust regulator over an Industry-Specicone. The smaller R0ISA + T

0

ISA (the larger the ISAs advantage); the morelikely that the ISA is preferred. Consequently, when R0AA + T

0

AA > R0

ISA +

T0ISA, the output level under the supervision of an ISA is larger than un-der an AA (because Industry-Specic operation is marginally less costly);otherwise, qAA < qISA (because the Antitrust framework is marginally lesscostly).

Rewriting this rule, grouping the administrative costs and the regulatoryones, R0AA R

0

ISA < +T0

ISA T0

AA, makes the choice of the AA directly de-termined by its lower relative cost of being audited and inversely determinedby the ISA smaller relative cost of monitoring the industry.

Let us consider the case in which = 0. This would imply that theactivity of raising public funds itself does not drive any ineciency andGovernment transfers to the Firm and the Regulator (t and w) do not haveany cost premium. This would drive a net loss from regulating such thatR0 + T0 > 0, which, as was stated above, would make pooling an optimalsolution. Regulation is not an issue because the cost of a regulatory set-ting based on the chain of supervision of a regulator and the Government(expressed by R0 + T0) becomes innitely expensive with respect to no gainobtained from such activities. Similarly, as is an approximation of theweight that the Government gives to collusive agreements as a problem of

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welfare distribution, = 0 corresponds to a neutral attitude of the Govern-

ment to the problem that eliminates the motivation to regulate 23.What about the relevance of x? The lower x; the larger the gains from

establishing a regulatory setting for the industry, because a larger frequencyof rms of the most ecient type makes lying more likely and the transfercost of their eventual lying (and the savings from their supervision) largeras well. Note that the intuition of this eect is related to the advantages ofbuilding regulatory assets (knowledge investment) when a large technologyspillover reduces the obsolescence of such investment.

2.4.2 A solution with both Regulators

Let us now consider the possibility of having both regulators with concurrentpowers and call such institutional arrangement as regulatory separation24.Consider R0B and T

0

B as the consolidated marginal costs of auditing whenboth Regulators coexist. Eventually both marginal cost function can bewritten as weighted averages of the two corner solutions:

Marginal cost of auditing the rm: R0B(L) = 0R0

AA(L) + 1R0

ISA(L)for all L > 0

Marginal cost of the Government auditing of the Regulator: T0B(F) =

0T0

AA(F) + 1T0

ISA(F) for all F > 0In a context in which both regulatory agencies do not have overlapping

competencies, Laont and Martimort (1999 and 1998) show that there exists

eects of improved administrative control25

but also duplication of regula-tory eorts. Consequently, we assume that the weights s and s do notnecessarily add to one, because cost ineciencies would imply 0 + 1 > 1and the higher likelihood of collusion detection would imply 0 + 1 < 1:

Following the analysis in Proposition 11, we can compare the combinedregulatory setting with each of the unique regulator settings. As in suchanalysis, marginal cost comparisons would determine which alternative ispreferred in each pair.

Comparing combined regulation and a pure Antitrust regulation, we ndthat if T0B T

0

AA > R0

AA R0

B the pure Antitrust setting is less expensivesolution than any combined action of both agencies; otherwise some degree

of shared responsibility is recommended. Similarly, comparing regulatory

separation and a pure Industry-Specic regulation, we nd that if T0ISA

T0B < R0

B R0

ISA the pure Industry-Specic setting of regulation would bepreferred to any combined setting with an Antitrust regulator; otherwisethe shared responsibility solution is preferred.

23 See Jellal and Garoupa (2002)24 See Laont and Martimort (1999)25 Administrative control is improved with regulatory separation because of discretion

reduction and increase of transaction costs of regulatory capture

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There are some issues to consider about:

In essence, the key decision driver on the institutional arrangements notonly comes from comparing the cost dierences of the Government auditingwith the cost dierences of the agencies regulatory technologies, but alsoindicates which of both pairs of eectiveness tend to be more dierent amongthe institutions: internal administrative controls vs. regulatory controls ofthe industry. This interpretation might provide an explanation why the ISAhas been the dominant pattern of regulation. The involvement of the ISAwould be larger when the cost dierences of the Government auditing tend tobe smaller than the cost dierences of the agencies regulatory technologies.This would be the case if, for example, the industry knowledge is whatmainly dierentiate a telecommunications agency from a competition agency

rather than their diculty to be controlled. Empirically, the latter makessense because agencies generally face the same mechanisms of administrativecontrol (enforced by the Government and/or the Congress) which determinesthat the eectiveness of such administrative controls tends not to be asdierent as their eectiveness of regulatory controls.

Secondly, the values of the parameters j and j directly aect the rangefrom which each institution is chosen over any combined action of bothagencies. Each of them corresponds to only one of the marginal cost com-ponents or institutional dimensions and one of the institutions might haveover-weighted its advantage or disadvantage factor or both, aecting sig-nicantly its preference and leaving little space for any other solution. As

such weights reect the importance that society assigns to the institutionaldimensions of each agency, the strong preferences for a given institutionalsolution might be also due to strong perceptions about the agencies, despitetheir actual dierences in competence and transparency are relatively small.

Additionally, whatever the values of jand j; they are a result of thelegal and administrative setting: who is in charge of the largest regulatoryagenda and who is supervised closer. Although they are aected by govern-ment decisions that might change periodically, their substantive dependencyon the legal framework would make them relatively stable. For example, al-though part of the responsibility assignment may change as easy as a cabinetchange or a government reform, basic issues are xed in legal pieces that

establish the regulatory setting. Similarly, most of administrative controlsare not specic to each agency but are enforced through general mechanismsthat oversee almost all government oces; this general scope makes themharder to be changed.

Finally, let us assume harder conditions of cost duplications and in-termediate improvements in Government auditing derived from regulatoryseparation26.

26 This corresponds to the context in which the additional costs due to the jurisdictionoverlapping of agencies and their coordination are not suciently compensated by better

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0R0

AA + 1R0

ISA > R0

AA > R0

ISA

T0AA < 0T0

AA + 1T0

ISA < T0

ISA

This scenario provides an adequate proxy of the decision to move fromone-agency solution towards a combined solution: in real world cases, dupli-cation of regulatory costs begins since the moment that both agency shareresponsibilities whereas the improvement of administrative control may takelonger.

We nd that, under such circumstances, it is always more likely to prefera pure Industry-Specic framework when it is compared with regulatory

separation (a both-agencies-regulate context) than when it is compared witha pure Antitrust framework (corner solution context):

T0ISA T0

AA > T0

ISA T0

B

R0AA R0

ISA < R0

B R0

ISA

On the other hand, it is not clear whether the choice of a pure An-titrust Agency arrangement is more likely when it is vis-a-vis a concurrentarrangement than vis-a-vis a pure Industry-Specic one.

T0ISA T0

AA > T0

B T0

AA

R0AA R0

ISA > R0

AA R0

B

In a concurrence context, the AA choice becomes more attractive whenits advantage with respect to the eect of regulatory cost duplication (R0AAR0B) is larger than the AAs transparency attractiveness in corner solutioncontext due (T0ISA T

0

AA). As a result, Principals seeking to incorporatethe ISA specialized knowledge in AA issues enforcement have to balancethe improved auditing eect of concurrence with its cost duplication eect.Empirically, concurrence of agencies usually do not avoid much of its costduplication as their costs appear since the rst day and few resource ad-

justment that drive its potential synergies are implemented. Therefore, thestrictness of this condition reduces the feasibility of the AA choice.

As it is accounted bellow, some degree of combined action of both insti-tution is present in all country cases. Therefore, in analyzing the empiricalrelevance of these results the comparative analysis with respect to concur-rence arrangements seem more relevant than the decision rule between cornersolutions only.:

The following list presents a synthesis of the results and statements.

1. The closer the conditions to a full information context, the closer theindustry prots and the regulator compensation to zero.

administrative control

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2. The larger the shadow cost of public funds and the cost of administra-

tive controls, the less likely that industry regulation is performed andlarger the industry prots

3. The larger the industry innovation spillover, the more necessary aregulatory setting of the industry.

4. The larger the dierence of the cost of administrative controls withrespect to the dierence in regulatory eectiveness of regulations, themore likely that Antitrust is used as institutional solution.

5. The larger the shadow cost of public funds, the more likely that theIndustry-Specic framework is used as institutional solution.

6. When compared with a concurrence arrangement, the conditions forpreferring a pure Industry-Specic framework are less strict than forpreferring a pure Antitrust framework

The rst two implications are consistent with the results of Laont andTirole (1993). The following implications allows us to build a framework forthe institutional design within the spectrum of generic and industry-specicregimes.

3 Concluding Remarks and Further ResearchThis paper has been focused on one particular feature of institutional de-sign of regulation which is particularly relevant to the telecommunicationsbusiness: the choice of institutional arrangement from the spectrum of al-ternatives between a pure Industry-Specic and a pure (generic) Antitrustregime. The framework on which the discussion is built is the model of regu-latory capture from Laont and Tirole (1993). In doing so, Industry-SpecicAgencies and Antitrust Agencies were dierentiated in terms of their regu-latory competencies and their degree of exposure to capture by the industry.In addition to comparing pure regimes, arrangements with some degree of

responsibility sharing (regulatory separation) were allowed.The paper has shown that the preference of the institutional solution de-

pends on how dierent the advantage of the Antitrust Agency (AA) in costsof administrative controls is with respect to the advantage of the IndustrySpecic Agency (ISA) in costs of regulatory enforcement. In a Governmentcontext that tends to standardize the eectiveness of its agencies control,despite their signicant dierences in driving eective regulation, the pref-erence for an Industry-Specic regime is enlarged. Moreover, if regulatorycompetencies of agencies to face the industry complexity are perceived by

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the Government as more important than their administrative control prob-

lems, the Industry-Specic regime will be always chosen.Finally, it is also shown that, in a context of institutional concurrence

with large eects of cost duplication and intermediate improvement of ad-ministrative controls, the conditions for preferring a pure Antitrust frame-work are harder to fulll than for preferring a pure Industry-Specic frame-work. An interesting implication is that it goes over the context in whichinstitutional reforms on certain regulatory domains leaded by one singleagency (pure arrangement) re-assign responsibilities to another agency withconcurrent involvement (mixed arrangement). For example, merger reviewand competition policy enforcement are domains that the AA has tradi-tionally leaded, as well as the ISA has leaded price regulation. The harder

conditions for AA than ISA for maintaining them in their current conditionof unique enforcer when the alternative is the concurrence both agencies,helps to explain why empirical evidence in industries such as telecommu-nications is signicantly concentrated on concurrent arrangements with aleading part on the ISA27.

We nd that the discussion above drive issues which might become rel-evant for additional research. For example, as in Laont and Martimort(1999), there can be more than one dimension of the industry subject to belearned by regulators. This would allow us to dierentiate the eectivenessof one regulator to learn each of the pieces of information and nally makeit more or less specic to such dimension. In such case, we would maintain

the regulatory overlapping context used above but giving each agency ad-vantages to regulate certain features of the industry with respect to otheragencies. The framework used in the present paper also simplies the compe-tition process, and an approximation to it would probably expand the rangeof determinants of the institutional choice. Similarly, costs of governmentauditing are assumed exogenous and the shift towards making them as partof the Principals optimization process would be relevant. The assumptionof Government benevolence is a limitation to analyze countries with largeimperfections in the political market. More obvious, the empirical review ofthis discussion should be extended with respect to the list of case referencespresented above. More detailed and comprehensive case studies and data

base on regulatory arrangements and institutional frameworks might helpin such task.

27 See Tyler and Bednarczyk (1993), Herguera and Stehman (1997) and OECD (1999)

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Appendix

Proof of Proposition 1

Let us write the Lagrangian:

L = W + 1U(1) + 2U(2)

The rst-order derivatives of this Lagrangian are:

Lq = S0(q) 11 22 = 0

Lt1 = x + 1 = 0

Lt2 = (1 x) + 2 = 0

The second-order derivative of the Lagrangian is:

Lqq = S00(q) < 0

This conrms that the derived result correspond to the maximum. Fromthe rst-order derivatives, it is clear that both constraints are biding, as 1and 2 are positive, and S

0(q) = (1 + )



L = W + 1U(1) + 2U(2) + 3w


Lq = S0(q) 11 22 = 0

Lt1 = x + 1 = 0

Lt2 = (1 x) + 2 = 0

Lw = + 3 = 0The second-order derivative of the Lagrangian is:

Lqq = S00(q) < 0

This conrms that the derived result correspond to the maximum. As above,

1 > 0, 2 > 0 and 3 > 0, which implies that their corresponding con-straints are bidding; additionally, S0(q) = + 11 + 22 is obtained

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L = W + 1U(1) + 2U(2) + 3[w R(L)] + 4[L t(1) + t(2)]


Lq = S0(q) 11 22 = 0

Lt1 = x + 1 4 = 0

Lt2 = (1 x) + 2 + 4 = 0

Lw = + 3 = 0LL = R

0 3R0 + 4 = 0

It is clear that 1 > 0, 3 > 0, and 4 > 0, that is, the three constraintsassociated with these Lagrangian multipliers are binding. We can re-writtenthe following two rst-order derivatives:

Lq = Sq [R0(1 + ) + x]1 22 = 0

Lt2 = (1 x) + R0(1 + ) + 2 = 0

The result now depends on R. If R0 < r, we must have 2 > 0 and the

constraint is binding. Conversely, if R0

> r, we must have 2 = 0 and t(2)takes the highest possible value, 1q.


From the previous proposition, we have that 2 > 0 (the constraint is bind-ing) if R0 < r. Consequently,

Lq = S0(q) [R0(1 + ) + x]1 + [R

0(1 + ) (1 x)]2

= S0(q) (1 + )[ + R0(1 2)] = 0

And the result follows.

The second-order derivative of the Lagrangian is Lqq = S00(q) (1 +)R00(1 2)

2 < 0. This conrms that the derived result corresponds tothe maximum.

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From proposition 3, we have that 2 = 0 (the constraint is not binding)if R0 > r. Consequently, t(2) = t(1), L = 0, R = 0, and R

0(0) = 0.Re-arranging terms, we have:

Lq = S0(q) 1

= S0(q) (1 + ) (1 ) = 0

And the result follows.The second-order derivative of the Lagrangian is Lqq = S

00(q) < 0. Thisconrms that the derived result correspond to the maximum.


From Proposition 2, the rst-best solution satises S0(q) = (1+). In bothpropositions 3 and 4, Lq(q

FB) < 0. Therefore, it is necessarily the case thatqFB < qAI.



L = W + 1U(1) + 2U(2) + 3[w R(L)]+

4[L t(1) + t(2)] + 5[F t(1) + t(2)]


Lq = S0(q) 11 22 = 0

Lt1 = x + 1 4 5 = 0

Lt2 = (1 x) + 2 + 4 + 5 = 0

Lw = + 3 = 0

LL = R0 3R

0 + 4 = 0

LF = T0(1 + ) + 5 = 0

As above, 1 > 0, 3 > 0, and 4 > 0, as well as 5 > 0 which meansthat their four corresponding constraints are binding. We can re-writtenthe following two rst-order derivatives:

Lq = S0(q) [R0(1 + ) + x + T0(1 + )]1 22 = 0

Lt2 = (1 x) + R0(1 + ) + T0 + 2 = 0

The result now depends on R. If R0 < r, we must have 2 > 0 and theconstraint is binding. Conversely, if R0 > r, we must have 2 = 0 and t(2)takes the highest possible value, 1q.

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From the previous proposition, we know that 1 > 0, 3 > 0, 4 > 0 and

5 > 0, (which implies that t(1) = 1qCPand w = R(L) ). Similarly, as it

is shown above, we have that 2 > 0 if R0 < r; as the constraint is binding,

t(2) = 2qCP. Consequently,

Lq = S0(q) [R0(1 + ) + x + T0]1 + [R

0(1 + ) (1 x) + T0]2

= S0(q) (1 + )[ + R0(1 2)] T0(1 2) = 0

And the result follows.The second-order derivative of the Lagrangian is:

Lqq = S00

(q) (1 + )R00

(1 2) T

00

(1 2) < 0This conrms that the derived result corresponds to the maximum


From proposition 7, we have that 2 = 0 ifR0 > r. Consequently, U(2) > 0

because t(2) = t(1). Similarly as in Proposition 3, L = 0, R = 0, andR0(0) = 0 as well as T(0) = 0 and T0(0) = 0. Re-arranging terms, we have:

Lq = S0(q) 1 = 0

= S0(q) (1 + ) (1 ) = 0

And the result follows.The second-order derivative of the Lagrangian is:

Lqq = S00(q) < 0

This conrms that the derived result correspond to the maximum


From Proposition 4, the second-best solution satises S0(q) = (1 + )[ +R0(1 2]. In proposition 8, Lq(q

AI:1) < 0 (it satises S0(q) = (1 +)[ + R0(1 2)] + T

0(1 2)). Therefore, it is necessarily the case that

qSB < qCP.


The exercise is solved by comparing marginal costs for a given level of outputq. Solving for the marginal costs, we can identify:

(1 + )R0AA + T0

AA = [(1 + )R0

ISA] + T0

ISA

(1 + )(R0AA R0

ISA) = T0

ISA T0

AA ) C =

T0ISA T0

AA

R0AA R0

ISA

1

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Assuming that =T0ISA

T0AA

R0AA

R0ISA

1 + "

> C; where " > 0

1 +

T0ISA T

0

AA

R0AA R0

ISA

1 + "

(R0AA R

0

ISA) > T0

ISA T0

AA

R0AAT0

ISA R0

ISAT0

AA

R0AA R0

ISA

+ "R0AA >R0AAT

0

ISA R0

ISAT0

AA

R0AA R0

ISA

+ "R0ISA

And the result follows because R0AA > R0

ISA.

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