The Effectiveness of Collusion 

Under Antitrust Immunity

The Case of Liner Shipping Conferences

Paul S. Clyde

James D. Reitzes

FEDERAL TRADE COMMISSION
2

December 1995
3

 The Effectiveness of Collusion 

Under Antitrust Immunity

The Case of Liner Shipping Conferences

Paul S. Clyde

James D. Reitzes

______________________________

Bureau of Economics Staff Report

Federal Trade Commission

Washington, D.C. 20580
4

December 1995
FEDERAL TRADE COMMISSION

ROBERT PITOFSKY Chairman

MARY L. AZCUENAGA Commissioner

JANET D. STEIGER Commissioner

ROSCOE B. STAREK, III Commissioner

CHRISTINE A. VARNEY Commissioner

BUREAU OF ECONOMICS

JONATHAN B. BAKER Director

RONALD S. BOND Associate Director for Operations and 

Policy

PAUL A. PAUTLER Associate Director for Consumer 

Protection and Research

GARY L. ROBERTS Associate Director for Antitrust

DENIS A. BREEN Assistant Director for Economic Policy

Analysis

ROBERT D. BROGAN Assistant Director for Antitrust

GERARD R. BUTTERS Assistant Director for Consumer

 Protection

TIMOTHY P. DANIEL Assistant Director for Antitrust

TIMOTHY A. DEYAK Assistant Director for Antitrust

The authors are economists with the Antitrust Division,

Department of Justice and Ernst and Young, respectively. This study

expands on work performed while the authors were staff economists

with the Advisory Commission on Conferences in Ocean Shipping

(ACCOS). ACCOS released its report in April 1992. Dr. Reitzes also

was an author of "An Analysis of the Maritime Industry and the

Effects of the 1984 Shipping Act," Report of the Federal Trade

Commission to Congress and ACCOS (November 1989).

The views expressed in this study are those of the authors and

do not necessarily reflect the views of the Department of Justice, the

Federal Trade Commission, or any individual Commissioner.
Acknowledgements

We wish to thank Tim Daniel for his unflagging support of this project

and numerous editorial and conceptual contributions. Also, we thank

Paul Pautler for both support and comments, as well as Ron Bond,

Curt Jernigan, and John Peterman. This study benefitted greatly from

the suggestions of Dave Butz, Mike Metzger, Greg Werden, John

Hilke, Mike Ward, and Bob Rogers. We appreciate the statistical

guidance supplied by Luke Froeb and the useful insights into liner

conferences and maritime regulation provided by Allen Jackson,

Richard Speigel, and Sandy Kusumoto.
 See also Green and Porter (1984), Abreu, Pearce, and Stachetti 1

(1985), Rotemberg and Saloner (1986).

Summary

Collusion, in the form of tacit or explicit price coordination, is

a subject that has fascinated both policymakers and economists for

many years. While collusion can certainly stem from formal pricefixing or market-sharing agreements, economists also have noted that

tacit collusion can be achieved in a noncooperative setting through

repeated contact. Chamberlin (1929), Stigler (1964), Orr and

MacAvoy (1965), and others have identified several factors that

determine whether collusion can be sustained; chief among these

factors are the ability of the cartel to identify and punish defection

from the collusive outcome, and the ability of the cartel to prevent

entry. This study analyzes data from the ocean shipping industry to 1

examine empirically whether the provision of antitrust immunity for

price-fixing agreements and the establishment of a costless mechanism

for policing these agreements are sufficient to foster effective collusion

when there are no regulatory restrictions on entry.

This study analyzes whether liner conferences in ocean

shipping act as effective cartels by testing empirically whether the rate

structure in ocean shipping is consistent with cost-based factors, the

exercise of market power by conferences, or the exercise of market

power by firms in a manner unrelated to the conference system. We

find no statistically significant relationship between freight rates and

the market share of the conference serving the route, which indicates

that conferences do not act as perfect cartels maximizing the joint

profits of their members. Nonetheless, we do find that the level of

freight rates is significantly lower on routes where conference members

are free to negotiate service contracts directly with shippers. In the

routes included in this study, such freedom existed temporarily on two

routes, both of which had conferences with market shares over 80%. 

This latter finding provides some support for the conclusion that some

aspects of the conference system may contribute to higher shipping

rates, particularly when the conference has a sizable market share. 

Finally, we find that increases in market concentration are associated
 Section 2 of the Sherman Antitrust Act (1890). 2

 Ideally, cost and demand data can be used to estimate either firm 3

conjectures or a parameter that measures the collusiveness of industry

conduct. For a detailed discussion, see Bresnahan's (1989) chapter in

The Handbook of Industrial Organization.

3

with statistically significant, but economically small, increases in

freight rates.

I. Introduction

Policy concerns regarding possible collusion have been

reflected in several legislative and administrative actions, beginning

with the Sherman Antitrust Act's prohibition of any attempt to

"combine or conspire ... to monopolize any part of the trade or

commerce among the several States ...." These concerns are still 2

evident today, as a glance at the recent Department of Justice and

Federal Trade Commission Horizontal Merger Guidelines (1992) will

confirm. Economists, however, have provided relatively little

empirical support for the existence of anticompetitive collusive

behavior in particular industries. The development of such support has

been stymied by the paucity of detailed firm and industry cost and

demand data needed to assess empirically firm-specific or industryspecific conduct.3

Determining the effects of collusion would be greatly

simplified if firms merely announced to the general public when they

were colluding. This does not happen in most markets because

collusive pricing behavior typically violates the antitrust laws. There

are exceptions, though. The prime example is in certain transportation

industries where firms are expressly exempt from the antitrust laws. 

These industries provide an excellent opportunity for studying the

effectiveness of collusion in an environment where it is considered

legal.
 In international shipping lanes, these agreements have existed 4

since the 1870's (see Herman, 1983).

 In the period from 1985 through the middle of 1989, the FMC 5

assessed over $12 million in penalties for rebating and other violations

of tariff-filing provisions.

4

One industry in particular, the international ocean shipping

industry, provides a fertile area for research into the effectiveness of

collusive behavior. In most of the world, ocean carriers can enter into

price-fixing agreements that are exempt from antitrust scrutiny and

litigation. This exemption lowers the potential costs of entering into

collusive arrangements. Hence, price-fixing agreements among ocean

carriers, known as conference agreements, are widespread.4

On international routes involving the United States,

conferences enjoy another significant advantage. An agency of the

U.S. government, the Federal Maritime Commission (hereafter,

FMC), polices conference pricing agreements at no cost to the cartel. 

The participants in a conference agreement must collectively file their

freight rates with the FMC, and those rates are open to public

inspection. Any secretive discounting on those rates is considered

"rebating," and a carrier involved in rebating is subject to a stiff fine

by the FMC. The FMC devotes a significant portion of its resources

to investigating alleged rebating activity, and fining any guilty parties.5

Members of conferences serving U.S. trade routes are,

however, allowed to deviate publicly from the conference rate by

taking "independent action" (hereafter, IA) and offering a freight rate

that differs from the conference rate. Conference members must

provide notification to the conference, however, of their intent to offer

an IA rate. Moreover, since an IA rate is publicly available, it must be

offered to all qualified shippers (although the "qualified" group may,

in fact, be quite small). Given that secret rate discounting is illegal

and inhibited by the actions of an outside agency, and that public rate

deviations are immediately recognizable, one might suspect that it
 The existing regulatory system for ocean shipping, unlike those 6

of domestic aviation and trucking prior to their deregulation, allows

any carrier to enter the market.

 When cartel members vary widely in their efficiency, a cartel 7

may encounter difficulty in maintaining a collusive price. The moreefficient members receive relatively larger gains from cheating on a

given cartel price, since their lower cost structure allows them to

profitably expand output by a larger amount. This incentive may

constrain the sustainable price level for the cartel, i.e., the maximum

price level where firms no longer have an incentive to deviate from the

cartel agreement. For further discussion, see Radner (1977), Osborne

and Pitchik (1983), Choi, Menezes, and Tressler (1985), Schmalensee

(1987), and Harrington (1991).

 When customers are heterogenous, cartel members may be 8

tempted to discount selectively to those customers making relatively

large purchases. This type of cheating may be more difficult to detect

and punish than a situation where firms can significantly expand sales

only by offering widespread discounts. Thus, the presence of big

buyers may hold down the cartel's price.

5

would be difficult to cheat profitably on a conference pricing

agreement under the current regulatory structure.

Nevertheless, effective collusion in U.S. international ocean

shipping may still be hindered by the ability of other carriers to enter

the market, the heterogeneity of carriers in the market, and the 6 7

presence of large customers. Ocean carriers tend to be heterogeneous 8

for a variety of reasons. In many trades, the major carriers have

registered their vessels under different national flags. This, by itself,

may lead to a divergence in cost conditions since the treatment of

ocean carriers differs widely across nations with regard to subsidization

and tax policy, crewing requirements, and other factors. These

differences may supplement competitive differences stemming from

variations across firms in technology and entrepreneurial ability. 
 Empirical research on the structure of freight rates includes 9

Heaver (1973), Bryan (1974), Jansson (1974), Devanney, Livanos, and

Stewart (1975), Zerby and Conlon (1983), and Jansson and Shneerson

(1986).

 This claim is based on a Hicksian derived-demand argument, 10

(continued...)

6

Customers differ based on the size of their shipments and the quality of

service desired. Purchasers of ocean transportation services (i.e.,

shippers) range from small manufacturers and importers to Fortune

500 corporations.

This study investigates whether the granting of antitrust

immunity and the use of the FMC to enforce pricing agreements are

sufficient for liner conferences to exercise market power in the U.S.

international ocean shipping market. Alternatively, this analysis could

be considered a case study of whether the possibility of entry and the

existence of heterogeneity across firms and customers is sufficient to

thwart effective collusion. If firms are not able to form an effective

cartel under the relatively favorable conditions described above, one

might expect that it would be difficult to form an effective cartel in

many markets.

Controlling for other factors, we test whether an increase in the

market share of a liner conference, which presumably occurs when

additional firms join that conference, is associated with a change in the

structure of freight rates. To our knowledge, previous empirical

studies of liner shipping have not attempted this type of test. Many of 9

these studies argue that cartel market power exists based on their

finding that freight rates increase as the value of the cargo increases. 

Given that ocean shipping is now widely containerized, so that diverse

commodities are typically shipped in uniform boxes that are handled in

a uniform manner, these "value-based" rate differences are considered

evidence of price discrimination (i.e., "value of service" pricing)

resulting from conference market power.10
 (...continued) 10

where transportation services represent an input in the production of a

"delivered" product. When passed through to consumers in entirety,

a given increase in the freight rate will lead to a progressively smaller

percentage increase in delivered price as the value of the transported

product increases. Thus, if the market elasticity of demand is similar

for a group of products, one would expect that the derived elasticity of

demand for transportation services would be lower for relatively highvalued products. Recognizing this relationship, a conference with

market power would generally charge higher freight rates for highervalued commodities (unless, contrary to most empirical evidence,

higher-valued commodities typically face a more elastic market demand

than lower-valued commodities).

 See Sjostrom (1992) and Butz (1993). 11

 The exercise of firm-based market power, however, does not 12

imply that firms necessarily earn supranormal profits. The presence

of sunk costs could limit the number of firms in equilibrium, with each

of these firms sufficiently large to realize some degree of market power

under certain types of strategic behavior. Price discrimination may

(continued...)

7

Others note that value-based rate differences may still reflect

cost differences related to the value of the commodity, such as

differences in damage liability and service quality. Thus, rates that 11

are positively correlated with the value of the commodity do not

necessarily indicate that conferences have market power. Instead, this

type of rate structure may represent an efficient outcome generated by

a competitive market.

Another explanation is also possible. Value-based rate

differences may result from market power that arises independently of

the conference system. In particular, these rate differences may stem

from the type of pricing behavior that emerges from firm interaction in

a concentrated market. The presence of scale and network economies 12
 (...continued) 12

arise consequently, but the ability of firms to enter the market drives

profits to a normal level. In this case, the equilibrium configuration

would represent a "quasi" Ramsey-pricing outcome. For discussion of

price discrimination under imperfect competition, see Katz (1984),

Borenstein (1985), and Holmes (1989).

 Butz (1993) makes a similar point. 13

 An exception might occur if the conferences, themselves, 14

offered transportation services to the customer. An increase in

conference market share might then be associated with higher quality,

and possibly more costly, transportation services. This might occur,

for example, if conferences with higher market shares offered more

(continued...)

8

may limit the number of sustainable firms on any route, thus allowing

individual firms to exercise some power over price. It is also possible

that the regulatory structure in ocean shipping, particularly mandatory

tariff filing and enforcement for all carriers, facilitates anticompetitive

interaction between carriers inside and outside of liner conferences. In

fact, the distinction between conference members and "outside"

carriers may be limited, since all carriers must make their freight rates

publicly available and conference carriers either can set their own

freight rates (through the "independent action" provision) or exit the

conference with little advanced notice. Freight rates may thus depend 13

more on overall market concentration than on conference market share.

We try to contribute to the debate surrounding market power in

liner shipping. If, ceteris paribus, a conference's freight rates on a

given route generally increase as the conference covering that route

increases its market share, then this outcome is consistent with the

notion that liner conferences exercise market power by themselves.

This result could be explained on an efficiency basis only if some cost

variable can be identified that is positively correlated with conference

market share. At best, this is an unlikely proposition. In addition, if 14
 (...continued) 14

frequent sailings. Due to the higher-quality service, consumers would

be charged higher freight rates as conference size increased. 

Nonetheless, consumers might still benefit on balance if there were

substantial improvement in service quality.

However, with the exception of contract services, no shipping

services are offered by the conference. Instead, individual members

sell their own shipping services to customers. Customers would

generally be expected to judge quality on the basis of the service

offered by the carrier instead of the conference. Because our sample

specifically excludes freight rates for contract services, we believe that

data are free of any methodological problems that would have resulted

from the inclusion of conference-based shipping services.

 Finally, we should mention that one strand of the economic 15

literature on ocean shipping contends that cooperation among ocean

carriers may be necessary to alleviate the problems associated with an

"empty core" (see Sjostrom, 1989, and Pirrong, 1992). Under the

empty-core hypothesis (see Telser, 1978), the presence of "avoidable"

(continued...)

9

an increase in a conference's market share is associated with an

increase in the dispersion of the conference's freight rates based on

commodity values, then this result is consistent with the hypothesis that

larger liner conferences can better discriminate in their pricing on the

basis of commodity value.

Our statistical specification measures the effect of a change in a

given conference's market share on the level of freight rates and the

dispersion of those rates on the route covered by the conference. In

this fashion, we estimate the degree of market power possessed by

liner conferences. Additionally, we explore the relationship between

the freight rates on a given route and an index of market concentration

for that route. This analysis sheds light on the importance of firm size,

as opposed to conference size, in explaining the rate structure in ocean

shipping.15
 (...continued) 15

costs and lumpy production preclude the existence of a noncooperative

equilibrium. As applied to ocean shipping, this theory would

potentially justify the formation of liner conferences as a means of

imposing stability in the market. Our analysis does not explicitly test

the "empty core" hypothesis; instead, we focus on the rate-setting

behavior of liner conferences. Since core theory does not predict

which industry structure is likely to emerge, and offers little insight

concerning the rate behavior under that structure, our results cannot be

used to either affirm or refute the empty-core hypothesis.

Core theory does predict that unless a coalition of firms (or

firms and customers) forms to impose a sustainable outcome,

"destructive competition" will emerge with large swings in rates. 

Thus, if conferences form to alleviate an empty-core problem, one

might observe more stable rate behavior than in the absence of

conferences. However, it may also hold that in the face of demand

uncertainty, a cartel acting solely for anticompetitive gain will exhibit

more stable rate behavior than a competitive market. Notwithstanding

this problem of interpretation, conferences are a longstanding

institution, which prevents the assembling of a data set that contains

periods where conferences are absent. Such data would be potentially

useful in assessing the relationship between conferences and the

stability of freight rates.

10

This study is organized as follows. Section II describes the

history and current status of U.S. regulation of international liner

shipping. Section III provides a brief description of our theoretical

model, and how we implement it empirically. Section IV contains the

theoretical model that underlies our statistical specification, which is

described in Section V. Section VI describes the data used in this

study. Section VII examines the statistical results, and Section VIII

offers concluding remarks.
 This description of the regulatory structure and market 16

characteristics of U.S. international liner shipping is derived from the

Report of the Advisory Commission on Conferences in Ocean Shipping

(April 1992), Chapters 2 and 3.

 See Federal Maritime Commission v. Aktiebolaget Svenska 17

Amerika Linien, 390 U.S. 238 (1968).

 An exception occurred if the conference could establish a prima 18

facie case that the restraint was required by "a serious transportation

(continued...)

11

II. History and Current Status of U.S. Regulation of

International Liner Shipping

Conferences in ocean shipping have existed since the late

1800's on U.S. international routes. Since then, they have been

granted varying degrees of antitrust immunity under the auspices of the

Shipping Act of 1916, the 1961 Amendments, and the Shipping Act of

1984.16

The 1916 Shipping Act allowed ocean carriers to enter into

price-setting agreements that were immune from antitrust action, but

those agreements had to be filed and approved by the U.S. Shipping

Board. The 1961 Amendments weakened this antitrust immunity by

including a "public interest" standard in the approval process for

conference agreements conducted by the U.S. Shipping Board's

successor, the Federal Maritime Commission. The FMC was

authorized to disapprove rates that were so "unreasonably high or low

as to be detrimental to the commerce of the United States."

This stricter approval criteria for conference agreements was

given practical meaning by the U.S. Supreme Court's Svenska decision

in 1968, which upheld the FMC's ruling that the "public interest" 17

standard created the presumption that any conference restraint was

invalid if it interfered with the policies of U.S. antitrust laws.18
 (...continued) 18

need, necessary to secure important public benefits, or in furtherance

of a valid regulatory purpose of the Shipping Act." 

 See Section 6(g) of the Shipping Act of 1984. 19

 Section 2 of the Shipping Act of 1984. 20

12

Carriers claimed that this standard impeded the formation of

ratemaking, joint venture, service rationalization, and other types of

agreements.

By eliminating the "public interest" standard, the Shipping Act

of 1984 reversed the trend toward greater antitrust scrutiny. The 1984

Act shifted the burden of proof so that conference agreements were no

longer subject to an approval process, but instead could be contested

by the FMC. Agreements automatically became effective after 45 days

unless the FMC sought an injunction on the basis that the agreement

was "likely, by a reduction in competition, to produce an unreasonable

reduction in transportation service or an unreasonable increase in

transportation cost." To date, the FMC has never attempted to enjoin 19

a conference agreement, although it occasionally has "recommended"

changes in the language of an agreement.

The 1984 Shipping Act continued the tariff filing and

enforcement provisions established by the 1961 Amendments. These

provisions require all ocean carriers and conferences to file their rates

with the FMC and publish their rate and schedule information. The

FMC was authorized to enforce that the filed rates were actually

charged; any secretive discounting on a published rate was considered

illegal and subject to punitive action (i.e., fines) by the FMC. The

tariff filing and enforcement provisions were intended to maintain

"a nondiscriminatory regulatory process for the common carriage of

goods by water...." Apparently, Congress was concerned that large 20

shippers may be successful in obtaining lower rates than small shippers

due to a superior bargaining position with carriers.
 Before 1984, a conference member could take independent 21

action only if the conference agreement permitted it.

 For instance, in the 1985-88 period, members of the 22

Transpacific Westbound Rate Agreement (outbound from the U.S.

Pacific Coast to Japan) used independent action to initiate 69,775 rate

filings. During the same period, there were 45,401 additional filings

where conference members matched independent-action rates initiated

by other members. By contrast, members of the Japan, Atlantic, and

Gulf conference (inbound from Japan to the U.S. Atlantic and Gulf

(continued...)

13

Given that the tariff structure in liner shipping permits

differences in rates based on the type of cargo and the volume of

shipment, the tariff filing requirement does not prevent effective price

discrimination. However, the FMC's role in enforcing filed rates

implies that conference agreements are policed by an outside agency at

no cost to the conference. Thus, the tariff filing and enforcement

requirements potentially facilitate the exercise of conference market

power.

The Shipping Act of 1984 required that conferences be open;

any carrier can join or exit a conference agreement with limited

advance notice and without penalty. There were also no statutory

restrictions on the ability of carriers to enter any given route (either as

an independent carrier or as a member of a conference). Moreover,

the 1984 Act mandated that any conference pricing agreement must

allow members the right of "independent action." This right allows

any conference member to offer a rate that differs from the conference

rate, but it must notify the conference in advance (usually ten days

prior) of its intention to do so.21

In the post-1984 period, independent action has been used

frequently in specific trade lanes. Data compiled by the FMC also

indicate that the filed independent-action rates are frequently matched

by other conference members. While the use of independent action 22
 (...continued) 22

Coasts) initiated only 266 independent-action rate filings, and there

were 167 additional filings of matching rates.

 This description of a service contract is based on that provided 23

in Section 3(21) of the Shipping Act of 1984.

14

may imply that there have been "defections" from conference rate

agreements, the evidence of matching behavior may indicate that some

of these defections have been "punished."

The 1984 Shipping Act also specifically authorized the use of

"service contracts," i.e., contractual arrangements whereby a shipper

commits to providing a minimum quantity of cargo or freight revenue

over a fixed time period, and the ocean common carrier or conference

commits to a certain rate or rate schedule as well as a defined service

level (such as assured space, transit time, or port rotation). Prior to 23

1984, the issuance of a service contract could be challenged as

"unjustly discriminatory." Although the 1984 Act liberalized the

contracting environment in ocean shipping, certain constraints remain. 

Service contracts must be filed with the FMC, and their "essential

terms" are publicly available. Moreover, other shippers that can

adhere to the terms of the contract (known as "similarly situated"

shippers) are entitled to the identical arrangement from the carrier or

conference issuing the contract.

Between late 1984 and early 1986, some conferences in the

Asian trades allowed their members to enter autonomously into service

contracts. All other conferences prohibited their members from doing

so, and would only issue a conference-wide service contract. In 1986,

those Asian conferences allowing their members to enter independently

into service contracts revoked that privilege. Casual empiricism

reveals that this change in the contracting environment had a significant

effect on market behavior; consequently, the entire structure of freight
 For instance, when members of the Transpacific Westbound 24

Rate Agreement were allowed to independently enter into service

contracts in 1985 and 1986, 40% of their cargo was carried under

contract. In 1988, after independent contracting was revoked in favor

of a conference-wide service contract, only 1% of the cargo was

carried under contract.

15

rates may have been affected. Our empirical analysis below examines 24

this question in detail.

III. A Brief Description of the Theoretical and Empirical

Models

Our objective is to determine whether liner conferences can

effectively collude, that is, set shipping rates as if the conference

members were a unified, profit-maximizing firm. Before presenting

rigorously the theoretical model and how we implement it empirically,

we briefly describe our conceptual approach, focusing on the

assumptions underlying it.

As mentioned above, we wish to test the hypothesis that

members of a conference perfectly collude. Our theoretical model,

therefore, assumes that conference members can do so; this permits

our empirical work to test directly this hypothesis. We also assume,

consistent with observed practice, that conferences transport a variety

of commodities of varying values, and that they can set different

freight rates for different commodities. Based on this paradigm of

perfect collusion, our model predicts that as a conference on a given

route becomes larger (due to outside firms joining the conference), the

conference will be better able to exercise market power. This

increased market power will result in an increased ability by

conferences to discriminate in their pricing on the basis of commodity

value. Consequently, as conferences increase in size relative to the

share of their nonconference rivals, freight rates are expected to

increase in general and the differential between the freight rates of two

commodities of different value is expected to increase (i.e., the
 While invoking these assumptions simplifies significantly the 25

derivation of the theoretical model, they actually are stronger than

necessary to support our ultimate empirical specification. For

example, the same empirical specification emerges if the degree of

pass-through is independent of commodity value and/or if the supply

elasticity of the nonconference "fringe" firms is similar across the

various transported commodities.

 This is equation (3) in Section IV below. 26

16

dispersion of freight rates across commodity values is expected to

become greater.)

In setting freight rates across the various commodities, a profitmaximizing conference will attempt to equate the marginal profitability

from shipping the last container of each commodity. Basic economic

principles establish that there is an inverse relationship between the

profit-maximizing price for a particular service (in this case,

transporting a particular commodity on a particular route) and the

elasticity of demand for the service. Our theoretical model combines

this relationship with three additional assumptions: (1) that increases

in shipping rates are entirely passed through to final consumers; (2)

that the market demand elasticity for any final good is constant with

respect to price and invariant over time; and (3) that "fringe" firms do

not alter their outputs in response to changes in the conference's

output. The result is an equation that relates the conference's profit- 25 26

maximizing price for shipping a particular commodity on a particular

route to five factors: (1) the value of the commodity, (2) the

conference's market share with respect to transporting the commodity

on that route, (3) the elasticity of demand for the commodity, (4) the

marginal costs incurred in shipping the commodity on that route, and

(5) the "shadow value" of conference capacity on that route. The

"shadow value" of capacity is a measure of the value to the conference

of adding more capacity; this value is positive when the conference is

capacity-constrained, and it equals zero when the conference has excess

capacity.
 The market concentration index treats each firm individually, 27

whether the firm is a member of the conference or not.

17

Two testable hypotheses emerge from this analysis. First, the

theory predicts that, holding all other factors constant, freight rates on

a given route are, in general, positively related to the conference's

market share on that route. Second, the theory predicts that, holding

all other factors constant, the dispersion of rates across commodity

values becomes greater as the conference's market share on that route

increases.

This theoretical construct need only be modified slightly to test

the additional hypothesis that increases in overall market concentration

(as opposed to increases in the conference's market share) contribute to

increased freight rates. The only difference is that an index of market

concentration would replace the conference's market share as an

independent variable explaining the level of freight rates. As before, 27

the two testable implications that emerge are as follows: (1) freight

rates generally increase with overall market concentration on a given

route, and (2) freight rates will become more dispersed across

commodity values as market concentration increases.

Transforming the theoretical model described above into a

specification that can be estimated empirically requires some final

modification. First, we assume that the conference's market share of

total capacity on a particular route is a very good proxy for its market

share in transporting any given commodity on the route. Second, we

assume that the elasticity of demand for any particular commodity is

independent of the commodity's value (or, that there is not a strong

positive relationship between a commodity's value and its elasticity of

demand.) Third, we need to estimate the "shadow" value of capacity. 

Since the "shadow value" depends on the total capacity level on the

route, the conference's market share on the route, and cost and demand

factors, we include these variables in our empirical specification. 
 This is represented by equation (4) in Section V below. 28

 The existence of fringe carriers competing with the cartel may 29

be attributable to a variety of factors. As more carriers join the cartel,

the benefits increase from remaining outside the cartel and free-riding

(continued...)

18

Lastly, the specification requires an estimate of the marginal

cost of shipping a specific commodity on a specific route. We resolve

this by noting that the cost factors specific to transporting a given

commodity along a given route (such as, shipping audio equipment

from Japan to the United States) are not likely to vary over the time

period covered by this analysis. Thus, we can control for differences

in transportation costs specific to a given commodity on a given route

by including dummy variables for each commodity on each route. 

Incorporating the four modifications above, we obtain the specification

that is empirically estimated.28

In sum, our empirical specification stems from the hypothesis

that liner conferences set prices as if the member carriers colluded

perfectly. We can test statistically whether the rate behavior of liner

conferences is consistent with the behavior predicted by this

hypothesis. As mentioned previously, the results would be consistent

with this hypothesis if we observed the following: (1) freight rates

generally increasing as conferences increase in size relative to their

nonconference rivals, and (2) the dispersion of freight rates across

commodity values increasing as conferences become relatively larger. 

Our empirical approach also can test whether market concentration, as

opposed to conference market share, affects freight rates.

IV. The Theoretical Model

We base our statistical specification on a model where a liner

conference on a given route acts as a residual monopolist, facing

competition from a fringe of carriers that have refrained from joining

the conference. In this section, we derive an expression for freight 29
MPij MRij MCij kj

,

MRij ,MCij) marginal contribution

revenue, marginal cost) from transporting

additional container of good i on

 (...continued) 29

off of the relatively high cartel prices. Among others, Donsimoni

(1985) and Deneckere and Davidson (1985) find that "stable" cartels

are typically incomplete. Firms outside the cartel have no incentive to

enter, and cartel members have no incentive to leave. 

 The subscripts denoting time have been dropped for expositional 30

convenience.

19

(1)

rates that is consistent with joint profit maximization by a cartel

competing with outside (i.e., fringe) firms. As shown in the following

section, we can econometrically estimate this expression to test

whether the rate behavior of liner conferences conforms with that

predicted by our model. Our statistical specification also considers the

possibility that market power stems from market concentration, and not

from the conference system.

A profit-maximizing cartel operating on a given route would

attempt to equate the marginal contribution to its profits that it receives

from transporting an additional container of any given product. 

Hence, for a cartel transporting good i on route j, it holds that:30
MPij rij(1 1/n

C

ij) MCij kj

.

 Hence, our model is sufficiently flexible to allow for either 31

short-run or long-run profit maximization.

20

(2)

In equation (1), MCij refers to short-run marginal cost. It is assumed

that the cartel maximizes profits subject to its capacity limitation;

hence, the term, kj, represents the shadow value of capacity. If the

cartel's capacity equalled that level needed to maximize longrunprofits, then the shadow value of capacity, kj

, would equal the

marginal cost of capacity.31

Note that MR = r (1 - 1/n ), where r is the freight rate for ij ij ij ij

C

commodity i on route j, and nij is the elasticity of demand that the C

cartel perceives it faces in transporting commodity i on route j. 

Substituting into equation (1), we obtain:

Under appropriate assumptions, we can express nij as a C

function of the market's elasticity of demand for good i and the market

share of the cartel on route j. First, it is assumed that any increase in

transportation costs is entirely passed through to consumers. In other

words, dp /dr = 1, which implies that dq /dr = [( q / p )(dp /dr )] ij ij ij ij ij ij ij ij

= ( qij/ pij), where qij is the total quantity of good i (from the origin

country) demanded in the destination country on route j, and pij is the

delivered price of good i in that country. Second, it is assumed that

the market's elasticity of demand for a given good is constant with

respect to price and invariant over time. Hence, q / p = - ij ij

n (q /p ), where n -( q / p )(p /q ) is the market's elasticity of ij ij ij ij ij ij ij ij

M M

demand for good i in the destination country on route j. Together,

these two assumptions imply that dqij/drij = -nij (qij/pij). Under the M

further assumption that there is no supply response by fringe firms, we

then obtain nij -(dqij/drij)(rij/sijqij) = nij (rij/pijsij), where sij is the C M
rij pij sij /n

M

ij MCij kj

or

rij kj

MCij pij sij/n

M

ij

 More generally, freight rates would increase with respect to 32

commodity value whenever p / is positively correlated with p . ij ij ij

M

This behavior necessarily arises unless pij and ij are positively M

correlated (i.e., unless high-valued goods face relatively elastic

demand). There is no empirical support that such correlation exists.

21

(3)

cartel's market share in transporting good i on route j. Incorporating

this last result into equation (2), we obtain:

Consider equation (3). Within a group of commodities facing

a similar market elasticity of demand (i.e., = i), a profit- M M

ij

maximizing cartel would generally set higher freight rates for the

higher-valued commodities (since drij/dpij > 0). This occurs because 32

although the market elasticity of demand is the same for this group of

commodities, the derived elasticity of demand for transportation

services decreases (in absolute terms) as the value of the commodity

increases. When passed through to consumers, a given increase in

freight rates raises product price by a smaller percentage for those

products that are relatively high-valued. This implies that consumers

of high-valued commodities are potentially less sensitive to changes in

freight rates. Recognizing this relationship, a profit-maximizing cartel

sets freight rates that are generally increasing with respect to

commodity value.

Based on equation (3), as the cartel's market share expands due

to "outside" firms joining the cartel, the rate differential should

increase between two commodities of different value (since d r /dp ds 2

ij ij ij

> 0). This behavior would not occur if the rate differentials across

commodities were based purely on cost factors.
 In a static oligopoly setting, Cowling and Waterson (1976) and 33

others have shown that market price is related to the Herfindahl index

of market concentration (H ). In these circumstances, equation (3) j

becomes:

(continued...)

22

The above specification can also be obtained using more

general assumptions. For instance, instead of assuming "full passthrough" of transportation costs to the product's delivered price, we

can merely assume that the degree of pass-through is independent of

commodity value. Also, instead of assuming that fringe firms do not

change their supply of transportation services, we can assume that

these firms respond to changes in the quantity of transportation

services supplied by the cartel, but their response is similar across all

transported commodities.

The above model allows for the possibility that liner

conferences exercise effective market power. However, another

independent source of market power should also be considered. The

presence of scale and network economies may imply that the ocean

shipping industry can sustain a limited number of firms in equilibrium. 

Additionally, there may be sunk costs involved in serving a given route

(i.e., costs of warehouses, cargo-handling equipment, and other

terminal facilities) that may constrain further the number of firms able

to serve that route. Depending on their strategic behavior, the few

firms operating on a given route may exercise market power sufficient

to permit discriminatory pricing, regardless of whether a conference

system exists. If high levels of market concentration allow firms to

exercise this type of market power, the associated first-order condition

is identical to equation (3), except that an index of market

concentration (i.e., the Herfindahl index) replaces the cartel's market

share.33
rij pij Hj

/n

M

ij MCij kj

or

rij kj

MCij pij Hj/n

M

ij

rij kjMCij pij sj/ n

M.

 (...continued) 33

 We could instead assume that p / is positively correlated 34 M

ij ij

with p . See footnote 32. ij

 Note that p represents the import price in the destination 35

ij

country. Since this price is essentially inclusive of transportation

costs, we use the export price in the origin country to avoid spurious

correlation.

23

(4)

V. The Empirical Specification

In equation (3), freight rates are assumed to be a linear

function of the shadow value of capacity (kj), marginal cost (MCij), and

an expression that includes the value of the transported commodity

(pij), conference market share (sij), and the market elasticity of demand

for the commodity ( ). The term, p s / , can be approximated by M M

ij ij ij ij

assuming that the conference's market share is the same for

transporting any commodity on a given route (i.e., s = s ), and that ij j

the market elasticity of demand is similar across commodities (i.e.,

= ). Incorporating these assumptions into equation (3), we M M 34

ij

obtain:35

Under the assumption that market concentration, in addition to

conference market share, might affect freight rates, equation (4) would

be modified slightly to: 
ij kj

MCij pij sj/ n

M pij Hj

/n

24

(5)

where H is the Herfindahl measure of market concentration on route j. j

To transform the above equation into a usable statistical specification,

we must devise a methodology that: (i) estimates k , (ii) circumvents j

the data problems involved in estimating MC , and (iii) considers ij

possible alternative sources of market power other than liner

conferences.

The shadow value of capacity on a given route (i.e., k )j

depends on the demand for ocean shipping services on that route, the

amount of capacity on that route, the conference's market share on that

route, and (possibly) the degree of overall market concentration on that

route. More specifically, with respect to equation (5), we assume that

k = f(CAP , Y , P , P , s , H ) where f is a linear function, CAP is j j j j j j j j

d d o

total capacity on the route, Y and P are (respectively) the destination d d

j j

country's income and price level, P is the origin country's price level, o

j

s is the conference's share of total route capacity on route j, and H is j j

the Herfindahl measure of market concentration on route j. As

capacity increases on the route, the shadow value of capacity is

expected to decrease until it finally reaches zero (where capacity is no

longer binding). An increase in the destination country's income or its

domestic price level (relative to the foreign price level) is expected to

raise import demand, and consequently, the demand for shipping

services on the route. Thus, when capacity is a binding constraint, we

expect kj to be positively related to Y j and P j, and negatively related d d

to P . Finally, as the conference's market share (or the index of o

j

market concentration) increases on the route, the benefit to conference

carriers (or carriers in the market generally) of increased output

becomes progressively smaller, for the same reason that the marginal

revenue is lower for a monopolist than for a perfect competitor. The

shadow value of capacity is therefore expected to decrease as

conference market share and overall market concentration increases.
 From year to year, cargo values may change moderately for a 36

given commodity on a given route. Since annual data for cargo value

were not available for this study, we assume that relative cargo values

across commodities and routes are constant over time.

 For a discussion of such "fixed-effects" models, see Judge, et al. 37

(1982), pp. 477-502.

25

The effect of these variables on freight rates is identical to that

described above, since freight rates are positively related to the shadow

value of capacity (see equation (5)). Of course, if the capacity

constraint is not binding (i.e., k = 0), these variables would not affect j

freight rates.

The short-run marginal cost of transporting commodity i on

route j (i.e., MCij) depends on such factors as the distance traveled, the

value and weight of the cargo, and the need for special handling (e.g.,

refrigeration). Note that these variables are practically invariant over

time for a given commodity on a given route, implying that 36

differences in marginal cost arise across commodities and routes. 

Thus, we can account for the impact of these variables by using a

model which includes dummy variables for each commodity on each

route. This approach not only circumvents the data problems 37

involved in accurately estimating marginal costs, but as we discuss

later, it also eliminates potential biases involved in examining the

relationship between freight rates and conference market share (or

market concentration) from data covering multiple commodities and

multiple routes.

Dummy variables for each year (1985,...,1988) are also

included in the specification, and an additional dummy variable (IA )j

denotes those routes for which conference members were allowed to

enter independently into service contracts in that specific year. While

our data excludes rates on service contracts, we hypothesize that
 Table 1 defines each of variables used in the analysis. 38

26

allowing conference members to autonomously enter into service

contracts could have altered the entire rate structure.

In addition to considering the possibility of joint profitmaximizing cartel behavior, our specification allows that,

independently of the conference system, market concentration may lead

to market power. Since this hypothesis implies that a relationship

exists between freight rates and market concentration, we have

included a Herfindahl index of market concentration (hereafter, Hj) in

our specification. This variable is included by itself and interacted

with cargo value.

The complete specification is described as follows:38

r = s + s p + H + H p + CAP + Y (6) ij 1 j 2 j ij 3 j 4 j ij 5 j 6 j

d

+ P + P + IA + 1985 + 1986 7 j 8 j 9 j 10 11

d o

+ 1987 + 1988. 12 13

In the above specification, we avoid using dummy variables for

each commodity on each route by instead expressing each observation

on a given variable in terms of its deviation from the variable's

respective mean for that commodity on that route. This approach is

statistically equivalent, and can be interpreted analogously, to the

regression where all variables are expressed in terms of their levels and

dummy variables are included for each commodity on each route (see

Judge, et al., 1982, pp. 478-481).

The above specification is capable of estimating the

relationship between conference market share and freight rates. It can

also determine whether the relationship between conference market

share and freight rates is different for high-valued commodities and

low-valued commodities. From the above specification, the change in

freight rates associated with an increase in conference market share
 Algebraically, the change in freight rates associated with an 39

increase in conference market share is: dr /ds = + p . ij j 1 2 ij

 As explained above, the coefficient measures the effect of an 40

1

increase in conference market share on the shadow value of capacity. 

When capacity is not a binding constraint, this effect necessarily equals

zero.

27

depends on the estimated coefficients from two variables: conference

market share (s ) and conference market share multiplied by commodity j

value (sjpij). The first of these estimated coefficients is 1

; the second

is 2. Note that the sign of this effect may depend on commodity 39

value, p . If conference pricing is consistent with the joint profit- ij

maximizing behavior in our model, then the degree of price

discrimination should increase with conference market share (implying

that > 0). In addition, when capacity is not a binding constraint, 2

an increase in conference market share should raise freight rates for all

commodity values. In that case, we would expect that 1 = 0 and

2 > 0. However, when capacity is a binding constraint, an 40

increase in conference market share should raise rates only for highervalued commodities. This occurs because, ceteris paribus, an increase

in the cartel's market share (due to an outside firm joining the cartel)

lowers its perceived marginal revenue. This drop in marginal revenue

is relatively larger for those commodities where the derived demand

for transportation services is relatively inelastic. To put its price

structure back in equilibrium, a capacity-constrained cartel would raise

rates for those commodities with a relatively inelastic derived demand

for transportation services (i.e., higher-valued commodities), and lower

rates for those commodities with a relatively elastic derived demand

(i.e., lower-valued commodities). Thus, we would expect that 1 < 0

and > 0. Note that this discussion presupposes that conferences act 2

as profit-maximizing cartels and are able to price discriminate, which

may not hold in reality.
 That is, the derivative of freight rates with respect to market 41

concentration (drij/dHj = 3 + 4pij) should assume a positive value

for all commodity values.

 The reported results also treat total route capacity as exogenous. 42

Industry participants indicated that ocean shipping and shipbuilding are

highly subsidized industries, and that capacity decisions may be heavily

influenced by government policies. To see whether capacity was more

heavily influenced by traditional market forces or national policies, we

(continued...)

28

In fact, conferences may not be able to price discriminate if

nonconference carriers act as "cream skimmers." In this case, if a

conference attempts to set different freight rates for commodities that

bear the same transportation cost, nonconference carriers would choose

to transport only those commodities with relatively high freight rates. 

This "arbitrage" activity prevents conferences from discriminating

across commodities in setting freight rates. When conferences act as

profit-maximizing cartels under these conditions (and capacity is not a

binding constraint), we would expect that an increase in conference

market share would lead to a uniform rate increase across all

commodities (i.e., > 0 and = 0). 1 2

 Now, consider the possibility that market power stems instead

from market concentration. According to our model, the degree of

price discrimination should increase as the market becomes more

concentrated (i.e., 4 > 0 in equation (6)). When capacity is not a

binding constraint, freight rates should generally increase as market

concentration increases. We would thus expect = 0 and > 0. 

41

3 4

When capacity is a binding constraint, an increase in price

discrimination should lead to higher freight rates for higher-valued

commodities and lower freight rates for lower-valued ones. This

implies that < 0 and > 0 if capacity is binding. 3 4

Due to limited data, no attempt was made to formulate an

instrument for conference market share or market concentration.42
 (...continued) 42

regressed capacity on a variety of cost and demand factors (relative

prices, gross domestic product, etc.) as well as route-specific dummy

variables. Consistent with information gathered in interviews, all of

the route dummies were statistically

significant, but few cost and demand factors were statistically

significant. It might be possible to construct an appropriate instrument

for route capacity from the subsidy levels for ocean shipping (and

shipbuilding) in various countries. Unfortunately, such data were

unavailable.

 For discussion, see Bresnahan's and Schmalensee's (1989) 43

chapters in the Handbook of Industrial Organization. See also Froeb

and Werden (1991).

29

This econometric approach is therefore subject to some of the same

criticisms that have been aimed at prior empirical research treating

market structure as exogenously determined. However, our fixed- 43

effects model does avoid potential sources of bias that would arise if

our analysis compared rate behavior across routes instead of within

routes. Our specification examines the relationship between deviations

over time in the freight rate for a given commodity on a given route

and deviations in other variables pertaining to that route, such as

conference market share and market concentration on the route. 

Accordingly, we avoid any examination of the relationship across

routes between the level of freight rates and the level of conference

market share (or market concentration). Much of the past criticism of

the exogenous treatment of market shares and market concentration

relates to its use in the cross-sectional analysis of behavior across

markets, which is avoided in our treatment of the data.

As a final point, we note that changes in conference market

share on a given route are measured holding market concentration

constant on the route. Our analysis is therefore designed to capture the

movement of "outside" firms into a given liner conference. Our

examination of the sample data confirmed that most of the variation in
 Appendix A lists the routes and the commodities used in our 44

sample.

30

a given conference's market share over time was attributable to carriers

entering or leaving the conference.

VI. Data

The sample consists of port-to-port freight rates charged by

liner conferences serving the United States between 1985 and 1988. 

Pursuant to Section 18 of the Shipping Act of 1984, the FMC collected

conference freight rates for the most popular commodities on a given

route, accounting for at least 50 percent of the volume on that route. 

The data covered fourteen conferences carrying outbound and inbound

freight between the U.S. Atlantic and Pacific coasts and Japan,

Germany, Italy, and Australia. Freight rates (r ) were expressed as 44

ij

total charges per twenty-foot-equivalent (i.e., TEU - the standard

measure of container volume), including all relevant surcharges, such

as bunker-adjustment, currency-adjustment, terminal-handling, and

container-yard fees. Due to the use of "independent action",

conference carriers occasionally offered more than one rate for the

transportation of a given commodity. In that situation, we used the

rate under which the majority of the cargo was transported.

Commodity value (p ) was derived from export and import ij

data collected by the Bureau of the Census and compiled by the

Maritime Administration of the U.S. Department of Transportation. 

From these data, we used standard conversion factors to translate from

commodity value per long ton to commodity value per TEU.

Capacity (CAP ), conference market share (s ), and market j j

concentration (H ) were compiled from data furnished by Lloyd's j

Maritime Information Services. Lloyd's collects capacity data (in

TEUs) for each carrier on a given route, and identifies whether the
 To determine carrier capacity on a given route, each vessel's 45

capacity is multiplied by the number of voyages it made on that route

during that year. These "adjusted" vessel capacities are then summed

over all vessels used by a given carrier on that specific route.

31

carrier belongs to the conference covering that route. Conference 45

market share is the proportion of total capacity operated by conference

carriers. Market concentration is measured by the Herfindahl index,

that is, each carrier's share of total capacity is squared and then these

figures are summed for all carriers serving the route.

The destination country's gross domestic product and price

deflator (Y and P , respectively) and the origin country's price d d

j j

deflator (P ) were obtained from International Financial Statistics,

o

j

published by the International Monetary Fund. The price indices were

adjusted for exchange rate movements.

The final data set, containing 620 observations, is one of the

largest ever used to analyze rate behavior in international ocean

shipping. Since there are four annual observations (from 1985 to

1988) for each commodity on each route, our sample contains 155

commodity-route combinations. Table 1 contains a description of each

variable and its data source, while Table 2 contains summary statistics

for key variables.
 Note that the R statistic in Table 3 is based on the regression 46 2

where each observation on a given variable is expressed in terms of its

deviation from that variable's respective mean for that commodity on

that route. In other words, R omits the explanatory power provided 2

by the dummy variables for each commodity on each route. However,

the calculation of the degrees of freedom must recognize that these 155

dummy variables are implicitly included (see Judge, et al., 1982). 

Hence, the degrees of freedom equal 620 - 13 - 155 = 452.

 Since the coefficient on market concentration alone is not 47

statistically significant, and the coefficient on market concentration

interacted with commodity value is statistically significant, our results

are consistent with profit-maximizing behavior in a concentrated

market when capacity is not a binding constraint. Additional statistical

tests further support that capacity is not binding; in particular, an F-test

does not reject the null hypothesis that the coefficients equal zero on all

variables (i.e., CAPj, Y j, P j, P j) relevant to determining the shadow d d o

value of capacity.

It should be noted that, contrary to the predictions of our

(continued...)

32

VII. Results

Table 3 presents regression results for the entire sample of 620

observations. The results offer some support for the hypothesis that 46

increased market concentration leads to higher freight rates. The total

effect of market concentration on freight rates (i.e., drij/dHj =

-.026 + .0000018pij) is positive and statistically significant at the

10%(5%) level for commodity values exceeding $77,268($103,172),

representing 24%(19%) of the total sample. Since the coefficient on

the variable that interacts market concentration with commodity value

is positive and statistically significant (at the 10% level), our results

are also consistent with the hypothesis that increased market

concentration leads to greater price discrimination on the basis of

commodity value.47
 (...continued) 47

model, the coefficient on the origin country's price level is positive and

statistically significant at the 5% level. Our model posits that this

variable affects the destination country's demand for the products of

the origin country. It is quite possible that this variable instead

captures movements in wages and input prices in the origin country

that are relevant to the cost of transportation services on that particular

route.

 Two outbound routes fit this categorization. In 1985, the 48

conferences on the U.S. East Coast - Japan and the U.S. West Coast -

Japan routes permitted their members to enter independently into

service contracts with shippers. The conferences on these routes had

market shares of 82% and 85% in 1985.

33

The results in Table 3 do not support the hypothesis that an

increase in conference market share leads to higher rates or greater

price discrimination. Neither of the variables that include conference

market share are statistically significant; moreover, an F-test does not

reject the null hypothesis that the coefficients equal zero on both of

these variables.

Despite the apparent lack of a statistical relationship between

conference market share and freight rates, our results indicate that

changes in conference rules, such as those pertaining to service

contracts, are associated with changes in freight rates. Specifically, the

coefficient is negative and statistically significant for the IA variable, j

which identifies those routes where conference members could enter

independently into service contracts within a given year. Ceteris 48

paribus, freight rates were approximately $590 lower (on average) on

those routes allowing "independent action" on service contracts during

that particular year. This reduction represents about 19% of the mean

freight rate in our sample.

"Independent action" on service contracts allowed an

individual conference carrier to enter into an agreement with an
 Our fixed-effects model essentially measures the relationship 49

(continued...)

34

individual shipper without any conference restriction on the terms or

services provided under the agreement. These contracts were then

filed with the FMC, but certain elements of the contract were not

publicly available (i.e., the name of the shipper and the carrier, and

certain information relating to service provisions). Consequently, the

advent of independent action on service contracts could have increased

the cost to the conference of monitoring the rate and service offerings

of its members. Further, unlike independent action on regular tariff

rates where the "discount" must be offered to all shippers of that

commodity on that route, contracts could be written in a manner which

effectively allowed the conference carrier to offer a "selective" discount

to that particular shipper (or a small group of "similarly-situated"

shippers). Due to these circumstances, permitting independent action

on service contracts could have increased the attractiveness of cheating

and inhibited the ability of the conference to detect and punish

cheating. The associated reduction in conference market power might

have resulted in lower freight rates for all types of transactions,

including the "spot" (i.e., noncontract) transactions that comprise our

sample.

The above findings are consistent with three primary

conclusions: 1) conference rate behavior is not consistent with the joint

profit-maximizing behavior predicted by our model; (2) conference

rules nonetheless may affect the exercise of market power, given that

rates were lower when conference members were allowed to enter

independently into service contracts with shippers; and, 3) an increase

in market concentration is associated with increased freight rates,

particularly for high-valued commodities. With respect to the third

conclusion, it is important to consider whether the positive relationship

between market concentration and freight rates is economically

significant, as well as statistically significant. Table 4 shows the effect

on freight rates of a one-standard-deviation (hereafter 1-s.d.) increase

in market concentration, evaluated at various commodity values. At 49
 (...continued) 49

over time between the freight rate for a given commodity on a given

route and the variables relevant in determining that rate. Since freight

rates for a given route are influenced only by changes in market

concentration on that route, we derived the standard deviation of

market concentration used in Tables 4 and 7 from an average of the

individual standard deviations of market concentration calculated for

each route (based on changes in the route's concentration over time). 

In Table 4, which includes all routes, this average value is 384; in

Table 7, which includes outbound routes only, it is 407.

 As shown in Table 6, we omitted from these regressions certain 50

variables that were invariant across outbound routes (i.e., origincountry price index) or inbound routes (i.e., destination-country price

index and GDP). Since these variables only changed from year-toyear, they were perfectly collinear with the yearly dummy variables.

35

the median commodity value (of $31,912), a 1-s.d. increase in market

concentration is associated with a rate increase of $12, which

represents only 0.4% of the average freight rate. Calculated at the

highest commodity value (of $415,493), a 1-s.d. increase in market

concentration is associated with a $277 increase in freight rates, or

about 8.9% of the average freight rate.

Because the substantial U.S. trade deficit between 1985 and

1988 led to considerably heavier ocean traffic on inbound routes, we

decided to examine whether the results change qualitatively when

inbound and outbound routes were analyzed separately. Table 5

presents summary statistics, and Table 6 presents the regression

results.50

According to Table 6, the results from the pooled data stem

largely from behavior observed on inbound routes. For those routes,

market concentration is a statistically significant determinant of freight

rates, while conference market share is not. On outbound routes,

neither market concentration nor conference market share is a
 An F-test does not reject the hypothesis that the coefficients on 51

the inbound and outbound regressions are the same; however the

results on the outbound routes are qualitatively different from those

previously mentioned.

 Another effect may work in the opposite direction of that 52

suggested by Stigler. Firms with relatively large market shares may

face lower costs (or flatter marginal cost curves). This result suggests

(continued...)

36

significant determinant of freight rates. During the period covered by 51

this analysis, significant excess capacity existed on outbound, but not

inbound, routes. It seems likely that the presence of this excess

capacity prevented the exercise of market power on outbound routes.

The results on the inbound routes are qualitatively similar to

those obtained from the pooled data. One difference is that an increase

in market concentration is associated with a statistically significant

increase in freight rates for a larger portion of commodities in the

inbound sample than in the pooled sample (e.g., at the 10%(5%) level

of significance, 45%(40%) of the sample as compared to 24%(19%)). 

A comparison of Tables 4 and 7 also shows that this increase in freight

rates is relatively larger in magnitude in the inbound sample. For

instance, a 1-s.d. increase in market concentration on inbound routes is

associated with an $50 increase in the freight rate at the median

commodity value, representing about 1.4% of the average inbound

freight rate (see Table 7). At the highest commodity value, this

increase in market concentration is associated with a rate increase of

$439, or about 12.6% of the average inbound freight rate.

In closing this section, we acknowledge Stigler's (1964)

hypothesis that a cartel's ability to reach a joint profit-maximizing

pricing agreement may be facilitated as the number of colluding firms

declines. In other words, his model predicts that prices may be higher

when the cartel contains firms with large market shares instead of

small ones. To test this hypothesis, we constructed a "conference" 52
 (...continued) 52

that relatively large firms may gain more from cheating on a given

cartel price. Consequently, as firms become larger, the sustainable

cartel price may decline.

37

Herfindahl index, which represented the sum of the squared values of

each conference member's share of conference capacity. We added

this variable, by itself and multiplied by cargo value, to the

specification in equation (6). This variable was found not to be

statistically significant in either the full sample or the samples of

inbound and outbound routes only. Thus, we found no apparent

relationship between the concentration of the conference and the

behavior of freight rates.

VIII. Concluding Remarks

The U.S. international ocean shipping industry enjoys antitrust

immunity and a conference system that allows carriers to enter into

pricing agreements which are then monitored and enforced by a

government agency. Previous empirical analysis has concluded that

this system allows the exercise of cartel-based market power, based on

evidence that freight rates are increasing with respect to cargo value. 

This finding has been interpreted as consistent with discriminatory

pricing by an effective cartel, but the literature has ignored the

possibility that these rate differences stem from cost differences or

other sources of market power. In this study, we attempt to address

these shortcomings by directly examining the relationship between

freight rates and both conference market share and market

concentration. Our statistical approach controls for cost differences

across commodities and routes.

Although we find no significant relationship between

conference market share and freight rates, our evidence indicates that

freight rates were significantly lower on those routes where individual

conference carriers were allowed to enter into service contracts with

individual shippers. These results suggest that some conference rules,
 Even when firms apparently wield market power (i.e., set price 53

above marginal cost), there may still be a cost-based explanation for

the positive relationship between market concentration and price. As

applied to ocean shipping, it is likely that there are some fixed (but,

not sunk) costs involved in serving a given route. If those costs were

to rise, some carriers would exit the route. Consequently, both market

concentration and freight rates would increase, but the rate increase

might only be sufficient to allow firms to again cover their fixed costs. 

Thus, the exercise of market power by individual firms does not

necessarily imply that those firms earn supranormal profits.

38

perhaps when combined with relatively high conference market share,

may allow carriers to maintain rates at levels higher than they would

otherwise. Market power is undermined when carriers within a

conference are allowed to independently contract with shippers.

Our results show that an increase in market concentration is

associated with increased rate levels and increased rate dispersion on

the basis of commodity value; this is consistent with the hypothesis that

greater market concentration leads to greater market power. 

Nonetheless, a one standard deviation increase in concentration

increases rates only 0.4% of the median freight rate for the entire

sample.53

When we divided the sample between inbound and outbound

routes, the above results continued to hold for the inbound routes only. 

Relative to the entire sample, the increase in freight rates associated

with increased market concentration was larger in magnitude and

statistically significant for a wider range of commodities in the inbound

sample. At the median freight rate for outbound routes, a one standard

deviation increase in market concentration increases freight rates

approximately 1.4%. On outbound routes, where there may have been

considerable excess capacity, the analysis could not identify a

significant statistical relationship between freight rates and either

market concentration or conference market share. Perhaps the
 Ocean carriers have been particularly concerned with excess 54

capacity in recent years, spawning both formal and informal

agreements to reduce capacity. These agreements include the

Transpacific Stabilization Agreement, a so-called "discussion

agreement" between conference carriers and nonconference carriers to

voluntarily limit capacity on U.S.-Far East routes. The Trans-Atlantic

Agreement, a ratemaking agreement involving liner transportation

between the United States and Northern Europe, also contains

provisions to reduce capacity. It is quite possible that these agreements

are intended to inhibit any procompetitive pricing behavior that stems

from the existence of excess capacity. 

39

presence of substantial excess capacity eliminated any sources of

market power.54

In general, our results show that a perfectly-collusive outcome

is unlikely even under the favorable conditions that exist in ocean

shipping. Liner conferences do not, or cannot, maximize joint profits,

even when rate information is publicly available and a government

agency attempts to prevent cheating on collusive pricing agreements. 

The "sustainable" cartel pricing structure apparently diverges

considerably from that which maximizes the joint profits of its

members. A cartel's market power may erode in the presence of

excess capacity, firm heterogeneity, and multidimensional competition,

which all arise in liner shipping. In particular, this study shows that

collusive prices may be adversely affected by increased contracting,

which allows firms to expand service offerings and engage in selective

discounting.

In light of the liner shipping industry's unique regulatory

structure, there may be another explanation for the above results. The

required public filing of freight rates and the associated enforcement of

those rates, which applies to all carriers and conferences, may facilitate

anticompetitive interaction between firms inside and outside of liner

conferences. At the same time, conferences may be inhibited in

maintaining internal pricing discipline by their members' ability to
 For further discussion of this point, see Butz (1993). 55

40

autonomously set rates (through the "independent action" provision)

and exit the conference at any time with limited notice. This reasoning

suggests that the importance of conference market share as an indicator

of market power in ocean shipping may be less important than market

concentration.55

What does our analysis imply about the costs and benefits from

the regulation of liner shipping? Our finding that freight rates were

significantly lower when conference carriers were free to negotiate

directly with shippers provides some support for the proposition that

the conference system imposes costs on consumers through higher

freight rates. At the same time, however, it is important to point out

that this finding is based on routes where the conference's market share

is relatively high (over 80%), and that freight rates are not directly

related to the market share of the conference serving the route. 

Further, it is also possible that conferences provide some offsetting

benefits, such as increased efficiency in providing a network of ocean

transportation services.

Coordinated activities among ocean carriers may be beneficial

when those activities lead to improved rationalization of resources

(e.g., through vessel-sharing and space-chartering arrangements) or

induce efficiency-enhancing investments (e.g., through consortia that

offer additional transportation services). It is unclear, however, that

collective pricing behavior actually facilitates those coordinated

activities which improve efficiency. Moreover, even if collective

pricing is required to encourage efficiency-enhancing investment, the

associated anticompetitive harm may still outweigh the efficiency

benefits. Certain regulatory aspects of the open conference system,

particularly the ability of carriers to enter or leave the conference with

limited notice, would presumably discourage carriers from using
 Butz (1993) and Reitzes (1993) consider these issues in detail. 56

41

conferences to engage in efficiency-enhancing joint investment and

rationalization activities.56

It is this tradeoff between the potential for anticompetitive

harm and the potential for increased efficiency that should form the

basis for analyzing coordinated activities in ocean shipping and

assessing whether antitrust immunity should be continued. A similar

cost-benefit test could be usefully applied to other aspects of the

regulatory structure in ocean shipping, such as tariff filing and

enforcement and restrictions on contracting.
42

APPENDIX A

ROUTES AND COMMODITIES CONTAINED IN THE SAMPLE

Australia - U.S. Atlantic Coast U.S. Atlantic Coast - Australia

1. Apples 1. Automobile Parts

2. Beef (frozen) 2. Boxboard

3. Beer 3. Candy

4. Casein 4. Cigarette Tow

5. Cheese 5. Citric Acid

6. Canned Fruit 6. Clay

7. Gluten 7. Glass (flat)

8. Nickel 8. Glassware

9. Pears 9. Magazines

10. Wine 10. Plastic Sheeting

11. Wool 11. Tires

12. Tobacco

13. Whiskey

Australia - U.S. Pacific Coast U.S. Pacific Coast - Australia

1. Automobile Parts 1. Automobile Parts

2. Beef (frozen) 2. Borax

3. Beer 3. Citrus

4. Casein 4. Dried Fruit

5. Glassware 5. Lubricating Oil

6. Gluten 6. Marine Engines

7. Steel Sheets 7. Nuts

8. Steel Tubes 8. Pulses (beans)

9. Tin Plate 9. Roadmaking Equipment

10. Wire Rods 10. Salmon

11. Zinc 11. Vegetables (frozen)
43

Germany - U.S. N. Atlantic Coast U.S. N. Atlantic Coast - Germany

1. Apple Juice 1. Automobile Parts

2. Automobile Parts 2. Corn Seed

3. Beer 3. Electrodes

4. Chemicals 4. Engines

5. Engines 5. Lumber

6. Furniture 6. Medical Supplies

7. Glassware 7. Photographic Equipment

8. Ham (canned) 8. Pork Offals

9. Iron Castings 9. Roadmaking Equipment

10. Metal Working Machinery 10. Rubber (synthetic)

11. Moulding Machines 11. Tobacco

12. Offset Presses 12. Yarn (synthetic)

13. Plastic Foils 13. Veneers

14. Tires

15. Wine

16. Wine Gums

Germany - U.S. S. Atlantic Coast U.S. S. Atlantic Coast - Germany

1. Automobile Parts 1. Automobile Parts

2. Beer 2. Clay

3. Engines 3. Ferns

4. Furniture 4. Grapefruit

5. Ham 5. Lumber

6. Steel Pipes 6. Peanuts

7. Steel Strips 7. Pork Offals

8. Textile Machines 8. Rubber (synthetic)

9. Titanium Dioxide 9. Tobacco

10. Wine 10. Wood Pulp
44

Italy - U.S. Atlantic Coast U.S. Atlantic Coast - Italy

1. Automobile Parts 1. Copper and Brass Scrap

2. Ceramic Tiles 2. Corn Seed

3. Footwear 3. Hides

4. Furniture 4. Lumber

5. Macaroni 5. Peanuts

6. Marble Tiles 6. Rags

7. Paper (for printing) 7. Tobacco

8. Textiles 8. Waste Paper

9. Tomatoes (peeled) 9. Wood Pulp

10. Tractor Parts

11. Tractor Tracks

12. Vermouth

13. Wine

Japan - U.S. Atlantic Coast U.S. Atlantic Coast - Japan

1. Aluminum Sheets 1. Butterfish

2. Audio Equipment 2. Lubricating Oil

3. Auto Parts (of iron and steel) 3. Peanuts

4. Auto Parts (other) 4. Tobacco

5. Auto Parts (panel group) 5. Wood Pulp

6. Bolts, Nuts, and Screws

7. Electrical Goods

8. Machine Tools

9. Motorcycles

10. Porcelain

11. Textiles

12. Tires

13. Tractors

14. Transportation Equipment

15. TV Cameras

16. Video and TV Receiving Sets
45

Japan - U.S. Pacific Coast U.S. Pacific Coast - Japan

1. Auto Parts (other) 1. Beef

2. Auto Parts (panel group) 2. Cotton

3. Audio Equipment 3. French Fries

4. Electrical Appliances 4. Milk Carton Stock

5. Motorcycles 5. Salmon

6. Photocopying Equipment 6. Wood Pulp

7. Porcelain

8. Tires

9. TV Cameras

10. Video and TV Accessories

11. Video and TV Receiving Sets
46

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50

TABLE 1 

Definitions of Variables and Data Sources

VARIABLE

rij = freight rate per container for commodity i on route j (from

conference rate data collected by the Federal Maritime Commission)

sj = conference market share on route j (from Lloyd's Maritime

Information Services)

pij = value per container of commodity i on route j (from export and

import data collected by Bureau of the Census and compiled by the

Maritime Administration of the U.S. Department of Transportation)

H = Herfindahl index of market concentration on route j (from Lloyd's j

Maritime Information Services)

CAP = total capacity on route j (measured in TEU's -- i.e., containers) j

(from Lloyd's Maritime Information Services)

Y = gross domestic product in destination country on route j (in dollars) j

d

(from International Financial Statistics of the International Monetary

Fund)

p = price index for destination country on route j (converted into dollars) j

d

(from International Financial Statistics of the International Monetary

Fund)

p = price index for origin country on route j (converted into dollars) j

o

(from International Financial Statistics of the International Monetary

Fund)

IA = dummy variable denoting whether conference on route j allows its j

members to independently enter into service contracts

1985,1986,1987,1988 = dummy variables for years 1985-88
51

TABLE 2 

Summary Statistics For Entire Sample 

(620 observations)

Variable mean standard minimum maximum

deviation

Freight Rate

(Revenue per

TEU)

3,104 1,598 722 14,239

Commodity

Value

60,814 70,628 568 415,493

Conference

Market Share

63 17 13 92

Market

Concentration

(Herfindahl)

1,906 990 528 4,285

Capacity 580,026 693,365 50,644 3,048,461

Destination

Country GDP

(in billions of

dollars)

2,848 1,836 160 4,435

Destination

Country Price

Index

118 26 100 190

Origin Country

Price Index

124 30 100 190
52

TABLE 3 

Estimation of the Determinants of Ocean Freight Rates

Variable Coefficient

 (t-value)

Conference Market Share (s )j

-3.18

(-1.23)

Conference Market Share x Commodity Value (s p ) j ij 0.000017

(0.70)

Market Concentration (H )j

-0.026

(-0.31)

Market Concentration x Commodity Value (H p ) j ij 0.0000018

(1.80)*

Capacity (CAP )j

-0.000032

(-0.17)

Destination Country GDP (Y )

d

j

0.25

(1.07)

Destination Country Price Index (P )

d

j

3.41

(1.14)

Origin Country Price Index (P )

o

j

8.94

(2.93)**

Independent Action Dummy (IA )j

-590.47

(-2.09)**

1985 243.53

(2.05)**

1986 -43.93

(-0.78)

1987 -70.14

(-1.14)

1988 -129.46

(-1.14)

number of observations

(degrees of freedom)

 620

(452)

R

2 0.18

*(**) indicates significance at the 10%(5%) level in a two-tailed test
53

TABLE 4 

The Effect on Freight Rates of a One-Standard-Deviation

Increase in Market Concentration

(Evaluated at Various Commodity Values)

Commodity Value 

(in dollars) 

 percentile*

568 17,078 31,912 73,345 415,493

0% 25% 50% 75% 100%

Change in

in dollars

freight

rates:

-9 +2 +12 +41 +277

as a %

of the

mean

freight

rate

-0.3% +0.1 +0.4% +1.3% +8.9%

%

* percentage of commodity values in the sample that lie below the

specified dollar level (i.e., $568 ($415,493) is the minimum

(maximum) commodity value)
54

TABLE 5 

Summary Statistics For Samples of Inbound and Outbound Routes

Variable mean standard minimum maximum

deviation

Inbound (352 obs.)

Freight Rate 

(Revenue per TEU)

3,482 1,673 991 14,239

Commodity Value 68,193 80,512 8,178 415,493

Conference Market 

Share

66 14 31 92

Market Concentration

(Herfindahl)

1,956 1,116 528 4,285

Capacity 623,862 725,997 50,644 2,899,698

Origin Country 

Price Index

140 32 100 190

Outbound (268 obs.)

Freight Rate 

(Revenue per TEU)

2,607 1,344 722 7,087

Commodity Value 51,123 53,638 568 276,754

Conference Market 

Share

59 19 13 85

Market Concentration

(Herfindahl)

1,841 792 544 3,127

Capacity 522,450 644,832 72,687 3,048,461

Destination Country 

GDP(in billions 

of dollars)

835 711 160 2,849

Destination Country 

Price Index

136 31 100 190
55

TABLE 6 

Estimation of the Determinants of Ocean Freight Rates on Inbound and Outbound Routes

Variable (t-value) (t-value)

Inbound Outbound

Coeff. Coeff.

Conference Market Share (s )j

-6.75 -1.81

(-1.58) (-0.56)

Conference Market Share x 

 Commodity Value (s p ) j ij

0.000017 0.000047

(0.55) (1.02)

Market Concentration (H )j

0.039 -0.15

(0.35) (-1.09)

Market Concentration x 

 Commodity Value (H p ) j ij

0.0000025 0.00000061

(1.85)* (0.40)

Capacity (CAP )j

-0.00034 0.00035

(-1.29) (1.21)

Destination Country GDP (Y )

d

j

0.38

(1.13)

Destination Country 

 Price Index (P )

d

j

3.35

(0.79)

Origin Country 

 Price Index (P )

o

j

9.51

(2.15)**

Independent Action Dummy (IA )j

-284.19

(-1.06)

1985 149.62 189.63

(0.81) (1.54)

1986 -112.98 -9.66

(-1.52) (-0.15)

1987 -25.44 -70.82

(-0.26) (-1.00)

1988 -11.21 -109.14

(-0.07) (-0.93)

number of observations

(degrees of freedom)

R

2

352 268

(254) (189)

0.21 0.20

*(**) indicates significance at the 10%(5%) level in a two-tailed test
56

TABLE 7 

The Effect on Inbound Freight Rates of a One-Standard-Deviation 

Increase in Market Concentration 

(Evaluated at Various Commodity Values)

Commodity Value 

(in dollars) 

 percentile*

8,178 17,172 33,625 79,765 415,493

0% 25% 50% 75% 100%

Change in

in dollars

freight

rates:

+24 +33 +50 +97 +439

as a %

of the

mean

freight

rate

+0.7% +1.0 +1.4% +2.8% +12.6%

%

* percentage of commodity values in the sample that lie below the

specified dollar level (i.e., $8,178 ($415,493) is the minimum

(maximum) commodity value)