rent-seeking and the behavior of regulators: an empirical analysis

Rent-Seeking and the Behavior of Regulators: An Empirical AnalysisAuthor(s): Michel BoucherSource: Public Choice, Vol. 69, No. 1 (1991), pp. 51-67Published by: SpringerStable URL: http://www.jstor.org/stable/30025397 .

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Public Choice 69: 51-67, 1991. © 1991 Kluwer Academic Publishers. Printed in the Netherlands.

Rent-seeking and the behavior of regulators: An empirical analysis*

MICHEL BOUCHER Ecole nationale d'administration publique, Universit' du Quebec, 945 avenue Wolfe, Sainte-Foy, Quebec, Canada G1V 3J9

Submitted 14 December 1987; accepted 13 October 1989

1. Introduction

The theory of rent-seeking introduced by Tullock (1967) is typically linked to government action and is now part of the conventional wisdom when analyzing the political behavior of self-interested agents. Forced wealth transfers are unlikely without the exercise of government powerl in that rent-seeker is characteristically trying to get something which will ultimately reduce the net wealth of other people. This specific action may only take place in a non- proprietary setting or in a situation where property rights are attenuated which is generally the domain of the public activities.

The purpose of this article is to throw some light on how economic agents in a regulated industry compete for artificially contrived transfers. The rent- seeking process takes place in the for-hire trucking industry of a Canadian province, Quebec. The empirical analysis is realized by presenting a linear conditional logit analysis of the decision-making behavior of this Canadian provincial regulatory agency, the Quebec Transport Commission. This approach, which focuses on the main barriers to entry set by regulators, turns out to reflect directly how and when producers, consumers, and regulators will allo- cate resources to rent-seeking. In other words, the behavior of regulators gives rents their shadow price and economic agents react accordingly. Section 2 contains the main implications for the theory of economic regulation and also a model of the behavior of regulators when granting a permit authority. Vari- ables and empirical resuls are presented in Section 3; also included are implications for the rent-seeking process that may be drawn from them. Finally, Section 4 offers some concluding remarks.

* I am indebted to the Social Sciences and Humanities Research Council of Canada for its financial support, to Gerard BMlanger, Jean-Luc Migu6 for helpful comments and to Sylvain Veillette, Pascal Migu6, Marc Leduc for valuable research assistance. I benefitted from useful comments by the editor of this journal. All the remaining errors are mine.



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2. The theory of economic regulation

The interest-group theory of regulation has a long history in political science (Posner, 1974). A simple and analytical version of the theory is the so-called "capture theory" of regulation the essence of which is expressed by Stigler (1971: 3) when he argues that "regulation is acquired by the industry and is designed and operated primarily for its benefits." This was later generalized by Peltzman (1976) who notes that the economic approach to political behavior implies a maximization process by the regulators-politicians where the votes gained by a given action are marginally balanced by those lost by the same action. This particular condition is the partial equilibrium result. In a general equilibrium model of the political process, a stable equilibrium implies equal- izing the usual marginal conditions for the utility-maximizing politician, expressed in terms of votes, to the marginal conditions for optimizing opposing groups investing in rent-seeking activities. Votes have a price.

As the political process is not as efficient as an organized private cartel would be for a single interest group, rent-seeking expenditures are generally spent by some factor owners and also outsiders or related groups such as certain consumer groups. Moreover, Peltzman mentions that cross-subsidization and discrimination between interest groups are integral to the regulatory process in that rents need not be spread across consumer and producer groups but only on organized and effective groups or subgroups who can reciprocate a regulatory benefit. A third contribution which is worth nothing is an extension to this wealth-maximizing model by Crain and McCormick (1984). These two authors emphasize the point that regulators, selected by the legislature rather than elected, may constitute an important third party that must be reckoned with. As opacity increases between chosen regulators and voters, the higher is the probability that the former seek to capture wealth transfers. In other words, regulators are perceived as unconstrained by legislatures and thus can pursue their own policy agenda.

Empirical studies of the American trucking industry confirm some of these previous theoretical points. So Moore (1978) and Rose (1987) develop evidence that the owners of operating rights and unionized workers were among main beneficiaries. Organized labor receives a rent's share because it can extract it from the regulated industry. As a matter of fact, a regulated environment strengthens union power and induces both organized labor and cartelized firms to behave as a bilateral duopoly.2 Kim (1984) shows that energy suppliers to Canadian trucking firms benefit too from regulation because the latter induces suboptimal capacity utilization.3 We want to push a step further the empirical content of the theory of economic regulation, as applied to the trucking industry, by showing how some shipper groups may also achieve benefits or try to mitigate losses, secondly that regulators do not distribute benefits equally



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among trucking firms, and thirdly how regulators may succeed to get a piece of action by playing an intermediary role in rechanneling wealth through the political-regulatory process. As the existence of an agency cost between elected politicians and appointed regulators is assumed, the evidence found will simul- taneously refer to this agency problem and the policy preferences of the regulatory body.

2.1. A model of the behavior of regulators

The raison d'etre of a model explaining the behavior of regulators is based on a remark by Tollison (1982: 584) who writes, "Past behavior of the regulatory agency is important since it influences the formation of expectations by those affected by the regulatory process. These expectations determine the optimal level of resources that the parties will devote to the 'monopolization-demono- polization' process. It stands to reason that attempts to extract rents will be fought by affected parties unless such a contest is deemed futile." As a matter of fact, the regulators' behavior thus gives information to economic agents operating in the industry and reveals the shadow price of a contrived rent incor- porated in each request, inducing economic agents, in turn, to use up resources to obtain it.

The function of a regulatory agency is to act as a mediator between different parties when a permit authority is requested. This intermediary function takes place at a hearing which reproduces some forms of market-like constraint. As a matter of fact, both parties usually present opposite and contradictory views on the economic impact of a new entrant in a given market segment. The applicant provides evidence of additional benefits which he may offer to existing shippers, whereas opposing firms mention (or are concerned by) additional costs to be borne because of this newcomer. The board must derive the opportunity cost of an additional competitor for existing firms and establish the eventual trade-off to make its decision. In other words, it has to assert the immediate negative impact on the market shares of the existing firms in relation to future benefits brought in for shippers.

In public hearings or in chambers, provincial or lower court judges as well as commissioners hear the various motives set by an applicant to demonstrate the validity of his own request and respondents' reactions on the adverse economic impact of this newcomer on their respective market share. They have to assess the pros and cons, then choose one of three possibilities, denial or approval or partial approval.4 This maximizing-utility behavior is captured by a random utility model which is specified by the Commission's evaluations of an application (McFadden, 1976). More specifically, it reads as follows:

Ui = V(X,B,E) i = 1,3



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where Ui denotes the utility corresponding to the i-th decision; its main com- ponents are X, a vector of the relevant elements of a given application as assessed by the board in the written decision, B an unknown parameter vector giving the utility weights or evaluations associated with those various attributes and E the error term. For instance, in a situation where grant i and denial j are the two choices, a permit authority will be granted by the agency if Ui > Uj for all i 0 j. Since the utilities are stochastic across the Board, this decision is a probability which can be noted by Pi = Prob (Ui > Uj) for i 0 j. If the error term is assumed to follow an extreme-value distribution, thus the probability of decision Pi is distributed as a logistic function.

3. Variables and empirical results

A sample of written decisions of the Commission over a five-year period, 1976-1980 is taken because during that particular period of time, very little substantial change occurred. First of all, the 1972 Quebec Transport Act setting up the present regulatory agency was fully implemented by all of the various parties, including applicants as well as respondents. Secondly, few significant and relevant changes in transportation laws and in the internal rules of practice and procedures of the Commission have taken place. In 1982, the Quebec Transport Act was modified and provincial administrative judges were replaced by new commissioners. Thirdly, the external environment was relatively stable in that the American trucking industry was still regulated by the Interstate Commerce Commission. As a matter of fact, the 1980 trucking deregulation must be considered as an American collective good of which production causes externalities to the Canadian trucking industry because of international relations between the two countries (Connolly, 1970). In other words, Canadian provincial governments are also in the process of deregulat- ing their respective for-hire carriage industry because of the spillover effects generated by this American competitive policy. Thus, the 1976-1980 period provides a unique opportunity to study this problem because of a general stable regulatory environment.

3.1. Variables

In this sample, 776 applications for general and specialty permits are being analyzed5 to model the decision-making behavior of regulators. Their inter- pretation makes it possible to divide the number of independent variables into three different groups even if they are not mutually exclusive: the first one refers to the content of the applicant's request, the second, to the general



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characteristics of the applicant and the third, to the reactions of existing firms which operate on the coveted market segment.

3.1.1. The content of an application The General Order on Trucking, which defines the regulatory rules applying to the Quebec for-hire trucking industry, specifies, among other things, the broad content of an application. Three particular variables are considered: the extent of the requested permit, its class and the kind of rates and tariffs charged.

An applicant may request a new permit authority or an additional right to its actual existing permit or a minor change in its permit, known as a clause. In the last two cases, requests are for extensions of existing authorities and for the relaxation of the Board's imposed restrictions. A request for a new permit authority, which describes the operations of a trucking firm in a given geographic area, is more apt to be opposed by established firms than the other two because this request is threatening their respective market share. On the other hand, a request for an additional right or a new clause constitutes a minor initiative by an existing firm to marginally expand its actual activities in a market segment where it is already operating. In other words, there exists a direct and positive relation between the extent of a request and the number of respondents. These three elements forming one of the basic elements of a request are represented by dummy variables. However, only the variable new permit (PER) should be statistically significant and its expected sign is negative in that it reduces the probability that the Commission approves its request. Moreover, the other dummy variable, clause (CL), should not be different from zero.

A second variable in this group refers to the two classes of requested permit authority. The general trucking permit authorizes carriage of general commodities, excluding explosives and dangerous goods. The second class of permit, the restricted permit, gives authority to carry particular commodities as explosives and dangerous goods or to use special equipment or to haul commodities for the account of one or more particularly designated shippers. The class of permit requested is defined by a dummy variable which equals one if an applicant requests a restricted permit (RP) and zero otherwise. The coefficient is expected to have a positive sign because this request raises less opposition than a general permit authority, being tailored to avoid direct competition with general freight carriers. Moreover, opposition by other restricted permit holders is overcome by additional restrictions on the number of shippers to be served and mainly on the possibilities of backhaul authority.

A third variable is related to the kind of rates and tariffs which apply to the request. This variable (CONT) equals one if the applicant mentions or specifies the existence of a written agreement with a specific shipper and zero if he intends to charge general rates and tariffs set by the Quebec Tariff Bureau Inc.



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The predicted sign of this coefficient is positive in that large and important shippers are behind such a request.

3.1.2. The characteristics of the applicant Two different variables describe the intrinsic characteristics of an applicant, namely his relative importance and the location of his head office. The size of the applicant is a variable which has a direct influence on the probability of success of an application. Two motives justify it; first of all, it is likely that the Board will process applications by established firms searching to expand their activities in a different manner than those of new intrants; secondly, the Board, as the unique resource allocator, will evaluate differently existing firms based on their relative importance.6 This size variable is defined by the number of trucks and tractors owned by a firm, a physical size measure.7 To take into account of this possible discriminatory action by Quebec regulatory board, established firms are divided up in the Statistics Canada classification, namely in three classes. So class I or large carriers (PSI) which earn a gross annual operating revenue in excess of $2 million are expected to have more success in their respective request than other firms of the industry. These few well established firms, having a large aggregate share of the industry's revenues, and generally, operating in main urban areas, view themselves as members of a small number industry (Olson, 1965; and Stigler, 1974). Their revenues have a definite bearing on the assessment of credibility, because the board tends to look for some permanency in the service which it authorizes. Class III or small firms (PSIII) whose earning revenues vary between $0.1 to $0.5 milion are predicted to be less successful than others. As a matter of fact, these small firms are generally new within the industry and they do not represent as efficient a pressure group as the largest firms in that they account for a high percentage of firms in the industry and they are dispersed throughout the Province of Quebec. Concerning class II or medium size carriers (PSII), namely those earning revenues between one-half million to $2 million, their probability of granted requests must be more similar to that of class I firms than the probability of class III firms. They operate in the industry for many years and are considered to be among the most agressive firms of the industry.

To take into account of the barriers to entry, a fourth class of firms (PSO) is introduced, namely those which do no hold trucking permits at the time of the application. A priori, these potential firms will find it more difficult to obtain permit authorities than all categories of established firms.

However, the expected sign of these physical size coefficients raises some difficulties in that they can be positive as well as negative, depending upon the importance that the Commission gives or concedes to individual firms in relation to the market segment coveted by the applicant. If the regulatory agency believes that the size of trucking firms constitutes an important determinant



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factor of a request, coefficients will be positive and there will be a direct relation between the relative size of applicants and the value of their estimated coefficients. On the other hand, if the board thinks that existing firms' reactions on the market segment coveted by the applicant must prevail on this intrinsic characteristic of firms, estimated coefficients will be negative and the relation between the relative size and the value of the coefficient will be inverse. However, whatever the sign of these estimated coefficients, the presence of a discriminatory behavior must be noted by the fact that that the PSIII coefficient is larger, in absolute value, than those of other variables and that the PSII coefficient is also larger, in absolute value, than that of the PSI variable. On the other hand, the coefficient of the PSO variable must be higher, in absolute value, than those obtained by existing firms, whatever their respective class.

The second variable of this group is the location of the applicant's head office.8 The firm with a head office in Quebec (HOQ) stands a better chance than an applicant whose head office is located in a Canadian province or in an American state. The expected sign of this variable will be positive because the firm's trucks, tractors, trailers and terminals and its employees are more visible and more important than those of the firm outside Quebec. Moreover, its various direct and indirect taxes paid to the Quebec's consolidated fund are worth noting, for instance, in a public hearing.

3.1.3. The coveted market segment The third group of variables is directly related to the market segment where the newcomer expects to be in operation. As a matter of fact, the arrival of a new firm will necessary change the existing firms' behavior in that they will be forced, in the short run, to adjust for fear of losing their clients/shippers.

A first important variable is the opposition (OPP) expressed or recorded by established firms. When a carrier requests a permit authority which overlaps one or some basic activities of existing firms, the latter will express their opposition because of the expected losses they could incur. In other words, if property rights created by the Quebec Commission are valuable, existing producers will rationally commit resources to entry restricting activities up to the point where the marginal cost of these activities is equal to the marginal benefit. This variable, which is an implicit measure of the expected loss, is represented by a dummy variable9 which equals one when opposition is recorded and zero otherwise; the expected sign is naturally negative.

A second variable is the amendment (AMEN) that an applicant introduces to reduce the number of opponents. As a matter of fact, there are gains from trade for both parties because they have to spend time, energy and money, whether to protect their operating rights or to have access to a given market share. Some opposing firms will be satisfied by marginal amendments and they will withdraw at the beginning of the public hearing, whereas other infra-



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marginal respondents will challenge the application through the public hearing because of the potential heavy losses in their market share. A dummy variable is set equal to unity if the application is amended and set equal to zero otherwise.10 The expected sign is positive because it measures the cooperation or the willingness to cooperate between the applicant and opponents. The Commis- sion is more inclined to accept an amended application in that it does not threaten or jeopardize the harmonious equilibrium established over the years on this market segment by the Board's decisions.

A third variable is price competition (PCOM) that an applicant may invoke to promote his request. Up to its statutes, the regulatory agency must set rates and tariffs to be "just and reasonable." However, the Commission when considering a request to provide a given service at a rate inferior to that initially set by itself becomes more interested in the financial viability of existing firms than in that of a newcomer. Permit authorities remain a necessary condition to operate in the industry, and they represent an allocative sharing of the existing level of services offered. Therefore, the board must help them to realize a reasonable rate of return by monitoring the level of tariffs. A dummy variable equals one when an applicant mentions it and zero otherwise. Its predicted sign is negative because it represents the Commission's evaluation of price competition as a force undermining the stability in the industry.

A fourth variable is a traffic increase (TRINC) on other modes of transport. As a matter of fact, an applicant may show that his request generates new traffic and consequently increases the public trucking share without affecting an existing carriers' volume in that he diverts existing traffic from rail, private trucking, leasing trucking firms and pseudo-leasing firms. This traffic diver- sion variable is defined by a dummy variable which equals one where invoking this argument and zero otherwise. The expected sign is positive in that it increases the basic activity regulated by the agency and consequently reduces the possible "leakages" of its regulation.

Finally, a last variable is introduced to reflect the policy preferences (QTC) of the Quebec board to give, proprio motu, permit authorities when new terri- tories (James Bay) are opened and/or new activities (Mirabel Airport) take place. This particular variable is intended to detect if the Commission grants permit authorities to trucking firms by using criteria other than those related to a general request. This variable really shows the regulator's wealth-maximizing goal in the rent-seeking process occurring in the trucking industry. If regulators as an interest group constitute a potential and valid third party and seek to capture wealth transfers for their own, these particular events therefore give them clear opportunities to achieve them. It is represented by a dummy variable which takes unity if the opportunity occurs and zero otherwise. The existence of a positive coefficient implies that the board really participates in the rent-seeking process and exercises its power in a divergent manner from



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that which comes from its founding act as passed and voted by the legislature. In other words, the regulatory agency is pursuing its own policy agenda which is not related to the policy preferences of the elected politicians.

3.2. Empirical results

The empirical analysis is performed in two steps. In the first, there are only two discrete choices made by the board, approval or denial of a request. These two possibilities correspond to a traditional and straightforward view of how regulators behave. The second step directly incorporates explicit negotiations which take place overtly between respondents and an applicant and also implicitly between the Quebec regulatory agency and an applicant when the former writes its decision. In this case, the Commission can arrive at three possible decisions, namely approval, denial and partial approval. This third possibility includes the grant of a permit authority when amended by the applicant himself and/or when modified by the Board itself. In other words, we have broken down the decisions granted into two different subsets: decisions granted as initially written and decisions which have been modified in the process. This was done in order to see if a more disaggregated decision-making process is more revealing on the regulators' behavior.

3.2.1. Results of the traditional model Table 1 contains linear conditional logit estimates of two Commission decision models giving the most satisfactory results in the case of two possibilities of discrete choice by regulators."1 All coefficients are generally of the expected signs, though some of them are not statistically significant at the five-percent confidence level as indicated by t-statistics in parentheses below the model parameters. Also included are standard measures of goodness of fit as the log likelihood, the likelihood ratio statistic (LRS), the likelihood ratio index (LRI) and the percentage of correct predictions for an applicant. These goodness of fit results indicate that these two estimated decision models do a reasonable job of matching actual Quebec Transport Commission decisions.

A careful reading of decision model 1 reveals that the Board behaves as a discriminating monopoly when deciding a permit request. As a matter of fact, two estimated coefficients of the three firms classes (PS) are statistically significant and they are statistically different from each other. So the larger is a trucking firm, the higher is its probability of success when requesting a permit authority. In other words, rational regulators, as deduced by Peltzman, do not equally distribute benefits among trucking firms, but are sensible to their respective political influences. The second hypothesis which refers to the presence of shipper groups in the rent-seeking process cannot be corroborated,



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Table 1. Linear conditional logit models of the Quebec Transport Commission.

Independent Model 1 Model 2 variables

Constant 3.292* 4.112*

(5.125) (6.805) RP (Restricted permit) 1.043* 1.069*

(2.814) (2.911) CONT (Contract) 0.387 0.390

(1.517) (1.556) PER (New permit) -0.493* -0.660*

(1.708) (2.332) PSI (Class I) -0.004* -0.004*

(2.814) (2.779) PSII (Class II) -0.019 -0.018

(1.199) (1.118) PSIII (Class III) -0.100* -0.102*

(2.491) (2.543) HOQ (Head office) 1.100*

(3.432) OPP (Opposition) -4.062* -3.837*

(7.538) (7.297) PCOM (Price competition) -2.695* -3.276*

(2.973) (3.503) AMEN (Amendment) 1.098* 1.029*

(4.208) (4.023) TRINC (Traffic increase) 1.975* 1.752*

(1.997) (1.805) QTC (Discretion) - 1.709

(1.072)

Log likelihooda -223.94 -229.01 LRS 230.62 220.48 LRI 0.3399 0.3250 Percent correctly predicted 89.1 88.8

Note. Two alternatives, approval and denial. a At zero parameter vector, log likelihood is -339.254. t-statistics are in parentheses. * Indicates significance at .05 level.

the relevant variable (CONT) being not statistically significant at the five- percent confidence level. However, this result tentatively indicates that they are present in the rent-seeking process taking place in the regulated industry.

On the other hand, these results give additional evidence why already established firms dominate the Board. Coefficients of the coveted market segment are all statistically significant, their level of significance not being approached by any of the other groups, and their numerical values are higher than those



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of two other groups. Moreover, among the estimated coefficients of this group, those evaluating the negative impacts of an applicant, namely opposition (OPP) and price competition (PCOM), are higher than those weighting the beneficial consequences of an applicant, amendment (AMEN) and traffic increase (TRINC). We test the hypothesis that the commission weighs benefits and costs in the same manner. Under the null hypothesis that benefits (AMEN + TRINC) and costs (OPP + PCOM) have the same weight, LRS obtained 40.11 is x2 with one degree of freedom. We can reject this hypothesis at the five-percent confidence level.

Two minor considerations have to be made to conclude this first part of the empirical analysis. First of all, the coefficient of the Quebec Board's policy preferences (QTC) as estimated in decision model 2 is not statistically significant. So regulators, as an interest group, do not directly participate to the rent-seeking process in that their proprio motu decisions cannot be interpreted differently from their general behavior when granting a permit authority. This evidence seems to support the view that agencies are constrained by legislators and cannot have a different policy agenda from that of elected politicians. Secondly, as expected, the clause variable (CL) is not statistically different from zero; surprisingly, this is also true for the potential firms' physical size variable (PSO). The fact that outsiders are not handicapped in their first request implies that they must necessarily apply for a very restricted permit authority.

3.2.2. The results of the disaggregated model Table 2 contains the estimates for the same independent variables when the Board has three discrete choices for an application. First of all, an increase in all the standard measures of goodness of fit is observed, showing that the disaggregation of the dependent variables is worthwhile. Secondly, the discriminating monopoly hypothesis is as strong in the three-discrete-choice model as in the previous one. Thirdly, the disaggregated model shows statistical evidence that some shipper groups are really part of the rent-seeking process. Finally, it has to be noted how relatively important the amendment variable is now and how unimportant the traffic increase variable becomes, being not statistically significant. In other words, a three-choice decision model suggests that negative weights are highly valued opponent characteristics among the regulatory agency when making decisions and therefore, an applicant must negotiate to overcome the existing carrier's reactions. The null hypothesis that benefits (AMEN + TRINC) and costs (OPP + PCOM) have the same weight is rejected at the five-percent confidence level, the computed value of LRS obtained 88.32 being X2 with one degree of freedom.



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Table 2. Linear conditional logit models of the Quebec Transport Commission.

Independent Model 1 Model 2 variables

Constant (Approval) 3.171* 3.185*

(12.95) (12.92) Constant (Denial) 1.625* 0.931*

(3.77) (2.58) RP (Restricted permit) 0.819* 0.841*

(2.51) (2.60) CONT (Contract) 0.515* 0.502*

(2.55) (2.49) PER (New permit) 0.586* 0.654*

(2.78) (3.13) PSI (Class I) 0.005* 0.005*

(4.04) (4.10) PSII (Class II) -0.020 -0.019

(1.28) (1.16) PSIII (Class III) 0.090* 0.091*

(2.35) (2.38) HOQ (Head office) 0.850*

(2.98) OPP (Opposition) 2.308* 2.262*

(11.33) (11.19) PCOM (Price competition) 3.378* 3.805*

(3.83) (4.25) AMEN (Amendment) 3.515* 3.486*

(15.15) (15.13) TRINC (Traffic increase) 1.001 0.934

(1.59) (1.48) QTC (Discretion) - -0.254

(0.36)

Log likelihooda -476.327 -480.49 LRS 603.21 594.88 LRI 0.3877 0.3823 Percent correctly predicted Approval 75.2 75.0

Partly granted 65.6 65.4

Note. Three alternatives, approval, partial and denial. a At zero parameter vector, log likelihood is -777.93. t-statistics are in parentheses. * Indicates significance at .05 level.

3.3. Implications for the underlying rent-seeking process

This empirical research strongly suggests that regulators implicitly behave as if the coveted market segment is in a short-run tight equilibrium and conse-



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quently that it is impossible to increase the market share of a new trucking firm without harming that of existing firms. This situation will generally be more beneficial to established firms than to a new entrant because regulators weigh more intensively the losses of the former than the gains of the latter. It implies that the regulatory body operates in a partial equilibrium situation where the substitution is (perceived as) expensive for existing firms. That basic signal information is continuously sent to the trucking industry by regulators through the flow of their decisions taken all year long. This institutional environment in which rent-seeking takes place is well known and assimilated by economic agents. So regulators like elected politicians value stability in its own right.

Let us consider, first of all, the behavior of trucking firms. As an interest group, trucking firms will spend money and exert effort, not only to acquire rents, artificially created by the regulation, but also to maintain those acquired rents from intrusion by already established firms in the coveted market or new- comers in the industry; competition is ever present. So in this context, a general trucking permit for a given coveted market will not be requested because of the expected behavior of the regulatory agency. All applicants perfectly know that strong opposition from firms within this coveted segment will induce surely and systematically the Board to deny the request.12 On the other hand, a restricted permit will be more easily granted than in the previous case because of its inherent restrictions; opposition will be less intense in that stakes are generally perceived, in some circumstances, as modest by established firms. These particular circumstances, favorable to such a request, are generally when a shipper develops a need that existing carriers are not able to satisfy, when the new authorized service does not divert customers away from established carriers and when the new restricted permit increases the share of the for-hire trucking industry in the overall transportation of goods. Consequently, new restricted permits or permit clauses requested (and eventually granted) will con- tain many restrictions on the commodities carried, the route to be used and the shippers to be served, since this is the only means for any carrier to overcome the full range of obstacles.13 So, the general prevailing rule in the Quebec trucking industry is to seek a general trucking permit when a firm wants to expand its activities in a new market and to request a restricted permit to the regulatory agency when a marginal incursion in a new market is only considered. In brief, incumbents will generally have the opportunity some day to cash in the market value of their general permits because past behavior of regulators is a reliable predictor.

On the other hand, the trucking industry does not constitute an homogeneous interest group, especially when considering their political effectiveness. A cartel of large trucking firms is easier to organize and more efficient because their group size is very limited in numbers and that per capita prospective gains are large, whereas a numerically large interest group of small trucking firms is



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placed at a disadvantage and is unlikely to be as politically effective promoting their economic interests. The members of the first group will be more effective bidders, at the margin, when securing or protecting regulatory benefits than the other members of the industry.14 This distribution of rents among the members of the trucking industry up to their political effectiveness to the regulators' cause, their policy or their political party is made possible because regulators behave as a discriminating monopoly in that they grant permit authorities, whatever they may be, on a piecemeal basis, although they are always constrained by the due process.

Some powerful shippers represent the second interest group which invests time and money in rent-seeking activities. Their high demand for trucking services, the presence of modal substitutes as well as their direct political support to regulators constitute very strong arguments when supporting a particular request. Their eventual escape reduces the transfer of wealth sought by regulators for their constituency and undermines regulators' probability to be again appointed. They are in position to capture rents because regulators can tailor them a particular structure of benefits or to reduce them the deadweight loss of their general policies, without having to extend them to all the shippers.

Finally, this empirical research shows that trucking interest groups and some shipper groups do not seem to share rents with regulators. Therefore, the Crain and McCormick's hypothesis that regulators appointed by the legislature will be a third interested party seeking to capture wealth transfers is not statistically shown. So far, the Stigler's perspective (1975: 162) always holds, that "our theory of industry-acquired regulation predicts that the regulatory body will have the character of trustworthy bureaucracy rather than the dangerous potentialities of competitive politics."

The explanation of this regulators' behavior is to be found in what Adam Smith called "the discipline of continuous dealings." The general cooperative behavior of a commissioner is induced by his investment in reputation, considered to be a highly valuable asset for an ex post opportunity, whatever it may be. His selection as a regulator is not a random event, but a deliberate and voluntary choice made by politicians who also want to be seen as trustworthy by their peers and by their constituents. On the other hand, this trucking regulatory agency has a well-defined area of responsibility; moreover, because the legislature has not provided detailed regulatory standards and judicial over- sight is strictly limited to matters of due process, rather than to matters of fact and substance, there exist gains from trade between the regulator and those primarily subject to the regulations. His repeated and consistent decisions help to maintain his reputation with his associates, his peers, with the regulated trucking firms as a group and also with some particular groups of shippers. In the language of agency theory, the regulator is directly monitored by politicians who select him and also by producer and consumer groups who audit him on



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a regular basis. Moreover, both interest groups as a constituency monitor politicians so that their regulators' choice allow them to have access to the rent created by the legislature.

4. Summary and conclusions

The main contribution of this paper is to describe empirically how the rent- seeking process takes place in a regulated industry through the consistency in Board decisions. Evidence provided by discrete-choice decision models of regulators confirms that the conventional rent-seeking view of regulation is correct, namely to distribute wealth between various groups differently from what market forces would do. First of all, the structure of the rent-seeking activities in the Quebec regulated trucking industry is well explained. There exist behav- ioral uniformities (Russell and Shelton, 1974) in decisions taken by the Quebec Transport Commission, given its wide range of choice provided by the absence of detailed regulatory standards by the Quebec legislature. Secondly, trucking firms and large shippers are the interest groups seeking to extract artificially contrived rents. The capture theory of regulation is not a dominant political strategy and therefore does not analytically explain various trades taking place among interest groups when a permit authority is requested. So logrolling by regulators is clearly essential to maintain their non-transferable investment of time and talent and protect their political afterlife. Thirdly, large firms are more successful, at the margin, than small firms in their expansion because of their political effectiveness. The regulatory agency gives more rents to those who offer relatively strong electoral support to its party. Finally, appointed regulators do not achieve other positive payoffs from the regulatory process than those which may result from the agency problem. So the regulatory agency does not promote its own policy agenda, but rather that of the elected politicians, given the organizational and control problem between these two.

Notes

1. Even monopolies are dependent on governments for sustained durability. 2. More exactly, trucking firms have to share the regulation rent because regulation reinforces

organized labor in that it reduces the competition of nonunion firms and also bases its rate regulation on operating ratio, making easier to the cartel of agreeing to a non-efficient wage increase proposed by an union.

3. The truck and trailer manufacturing industry could also be included because it benefits as well as other suppliers of inputs from severe restrictions imposed on the operation of carriers.

4. In Canada, quasi-judicial boards have a certain degree of latitude and flexibility in their



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decision. That is not to say that the regulatory agency operates in a purely arbitrary fashion, but rather that the basis for interpreting it is subjective and depends on the particular circumstances of each situation. The validity of this philosophy is confirmed by Mr. Justice Rand in Union Gas v. Synderham (1957, S.C.C.: 185) in the following terms: "It is not an objective existence to be ascertained; the determination is the formulation of an opinion in this case, the opinion of the Board and of the Board only."

5. The sample procedure, based on the information contained in the Quebec Official Gazette, is available upon requests.

6. This variable may also be an indicator of the resources that a firm is ready to invest to obtain a permit authority and consequently the benefits which the firm expects to derive from this investment.

7. This physical size measure (PS) is preferred to the gross annual operating revenue because the former gives better statistical results.

8. The choice of the head office variable as representing the industry criterion is an empirical one. Many other criteria have been tried, but without success.

9. The number of oppositions expressed is rejected in that it is statistically inferior to the dummy variable.

10. The dummy variable provides a better fit than the exact number of amendments consented by the applicant.

11. A likelihood ratio variant of Chow's test is performed here and we do not reject the null hypothesis that the coefficients of the initial year and subsequent years are equal. The four computed values are systematically inferior to 23.34 which is X2 with 12 degrees of freedom, at the five-percent confidence level.

12. No general trucking permit in a narrow geographic region was granted by the Quebec Trans- port Commission for 15 years, namely from 1972 to 1987. In 1988, the Province of Quebec started to deregulate its trucking industry.

13. Moore (1978: 330) concludes that it was also the case of the ICC's applications. 14. The brief American experience with the deregulation of trucking suggests that many smaller

firms have entered the industry and that the expansion of large firms was more induced by the regulation per se than by economies of scale.

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Kim, M. (1984). The beneficiaries of trucking regulation revisited. Journal of Law and Economics 27 (April): 227-241.

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Rose, N.L. (1987). Labor rent sharing and regulation: Evidence from the trucking industry. Jour- nal of Political Economy 95 (December): 1146-1178.

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rent-seeking and the behavior of regulators: an empirical analysis

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