Exhibit 22

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Review of Industrial Organization 23: 121–155, 2003.

© 2003 Kluwer Academic Publishers. Printed in the Netherlands. 121

Economic Analyses of Mergers at the FTC: The

Cruise Ships Mergers Investigation

MARY T. COLEMAN, DAVID W. MEYER and DAVID T. SCHEFFMAN

LECG, LLP, 1725 Eye Street, NW, Suite 800, Washington DC 20006, U.S.A.

Abstract. This paper provides an overview of how economists at the Federal Trade Commission

assess the potential competitive effects of mergers, with a focus on the types of quantitative analyses

frequently employed. The paper first outlines the general approach employed at the Federal Trade

Commission to review mergers. The paper then describes analyses done in the investigation of proposed mergers in the cruise line industry as a specific example. Of particular interest in this example

are the analyses used to assess the potential for coordinated interaction as a result of the merger.

Key words: Antitrust, FTC, mergers, competitive analysis.

I. Introduction

In this paper we provide an overview of how economists at the Federal Trade Commission (FTC) assess the potential competitive effects of mergers and provide, as

a specific example, some of the economic analyses conducted in connection with

the FTC’s cruise ships merger investigation. We believe that industrial organization

economists should find this paper of interest, in part, because it represents a comprehensive discussion of what FTC economists “do” in a merger investigation and

elaborates by discussing a recent example.1 The paper is also of interest because

it demonstrates various empirical analyses relevant to assessing whether a merger

is likely to be anticompetitive due to the creation or enhancement of coordinated

interaction.

 Dr. Coleman is the Deputy Director for Antitrust in the Bureau of Economics at the Federal

Trade Commission. Dr. Meyer is a staff Economist at the Federal Trade Commission. Dr. Scheffman

was the Director of the Bureau of Economics at the Federal Trade Commission during the cruise ships

investigation and when this article was written. He is now adjunct professor of marketing and strategy

at the Owen Graduate School of Management at Vanderbilt University and an economic consultant

with LECG, LLP. The views and opinions expressed in this paper are those of the authors and are

not necessarily those of the Commission or any individual Commissioner. We thank Michelle Kambara, Karl Kindler, and Stephen Tuohy for excellent research assistance, and our colleagues James

Ferguson, Jeffrey Fischer, Elizabeth Schneirov, Charlotte Manning, Elizabeth Callison, Lawrence

White, and James Langenfeld for their assistance and comments.

1 Because of space limitations and confidentiality issues, we can only highlight major issues and

provide some examples of the sorts of analyses that FTC economists conducted in connection with

this investigation.

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122 MARY T. COLEMAN ET AL.

II. Overview of Merger Analysis

In merger investigations, the FTC follows the analysis set forth in the Horizontal

Merger Guidelines.

2 The Guidelines lay out a five step approach to assessing the

competitive implications of a merger: (1) define the market; (2) measure concentration (as a screen for determining whether further investigation is warranted); (3)

identify potentially viable theories of anticompetitive effects; (4) assess whether

the potential for entry (due to the absence of significant barriers-to-entry) would

make anticompetitive effects unlikely; and (5) assess potential efficiencies. It is

important to recognize that each of these steps is essentially a necessary condition

for a viable basis for a merger challenge, and so the decision as to whether or not

a challenge is warranted necessarily involves a compounding of the probabilities

that the conclusions of each of steps 1–5 is correct.

A great deal of information of various kinds is collected and assessed in a

merger investigation. The parties to the proposed merger typically are required to

provide a voluminous amount of their business documents and data.3 Other parties

– e.g., customers and competitors to the merging parties and customers – may

also provide information, documents, and data. Many industry participants (such

as the parties to the merger, competitors, customers, distributors, and third party

“experts”) are interviewed and/or deposed under oath, often extensively. A merger

investigation involves extensive analyses of all this information, generally over a

period of a number of months.

The first step in merger analysis is the delineation of the relevant product market

(“product market definition”). The analysis of market definition outlined in the

Guidelines is to find the smallest set of products, including the products of the

parties to the proposed merger, that a monopolist would need to control to increase

prices profitably by a small but significant amount above competitive levels.4 Of

course concluding that a hypothetical monopolist would find it profitable to raise

prices post-merger does not imply that the merger is anticompetitive.5

Although the Guidelines’ analysis for market definition seemingly poses a

simple question amenable to economic analysis (e.g., estimate demand and costs

facing the hypothetical monopolist and estimate the hypothetical monopoly price),

the evidence available in an investigation, although extensive, generally does not

have data suitable for precise econometric estimation. In many cases, determining

the precise contours of the market is complicated. In such circumstances, conduct2 U.S. Department of Justice and the Federal Trade Commission, “Horizontal

Merger Guidelines”, issued April 2,1992, revised, April 8, 1997. Available at

http://www.fic.gov/bc/docsi/horizmer.htm.

3 Typically, at least dozens, if not hundreds of boxes of documents, the boxes being the size of

the typical copier paper box containing several reams of copier paper. In the cruise ship investigation

dozens of boxes of documents and over 100 gigabytes of data were submitted to the FTC.

4 There is an analogous paradigm for defining geographic markets.

5 Wheat is a presumably a relevant product market, but the merger of two wheat farmers obviously

would not be anticompetitive.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 123

ing “sensitivity tests” by analyzing the competitive effects of the transaction under

alternative plausible market definitions allows us to determine the extent to which

the end result of the analysis is dependent on the exact contours of the market

defined. At a minimum the presence of competitors just “outside” the market must

be accounted for in conducting the analyses of potential competitive effects of a

merger that typically is not a merger to monopoly.

One commonly used analysis to implement the Guidelines’ analysis is to conduct a “Critical Loss” analysis.6 Estimates of critical loss are obtained from the

margins contained in the company’s financial data and the size of the price increase

being tested. To estimate actual loss from a price increase, where appropriate, the

Commission begins with qualitative evidence that comes from interviews with

customers. Customers provide information on what alternatives they have to the

products or services sold by the merging parties and the importance of price and

other factors to their decision. Commission staff also examine company documents

for information about what competitors the parties and others focus on, and the

possibilities for substitution.

Where possible, we use historical data to attempt to estimate in various ways

(depending on the limitations of the data) the likely response in sales to a hypothetical post-merger price increase. Sometimes we are able to estimate demand,

and therefore demand elasticity reasonably reliably from historical data. However,

given the type of data typically available (data from the parties to the proposed

merger that are often quite messy and only cover a few years, and fragmentary data

for the rest of the industry), demand estimation frequently is not possible. Thus

the typical quantitative analyses employed include a wide range of methodologies,

from cross-tabs to simple regressions that provide us with information about the

likely magnitude of own- and cross-price elasticities and various financial analyses

bearing on the assessment of costs.

A particularly useful type of analysis for both market definition and competitive effects, is the examination of “natural experiments”, when they exist. Natural

experiments are events that provide relatively stark shifts in “supply”, changes in

6 For further discussion of critical loss, see Harris and Simons (1989). Briefly, this is a three-step

analysis. First, we assess likely customer reactions to a hypothetical price increase (in the “Merger

Guidelines” termed a “SSNIP”) and in particular, to obtain an estimate of the likely actual loss from

a SSNIP. Second, we assess the amount of sales that the hypothetical monopolist would have to lose

such that there would be no increased profits from the price increase. This value is often referred

to as the “Critical Loss”. The critical loss value will depend on the variable profit margins of the

hypothetical monopolist. Finally, we compare the estimate of likely actual loss with the critical loss

estimate to determine whether a price increase would be profitable. Because the critical loss and

actual loss generally cannot be estimated with precision, we also conduct sensitivity analyses on the

estimates. If a SSNIP is not likely to be profitable, then the product market is expanded by including

the next closest substitutes, and the analysis is repeated until the smallest group of products such that

a hypothetical monopolist would likely be able to increase prices profitably is identified. For criticism

and further discussion of critical loss analysis (particularly related to inferring small markets from

large margins), see Langenfeld and Li (2001), Katz and Shapiro (2003), Woodbury and Page (2003),

and O’Brien and Wickelgren (forthcoming).

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124 MARY T. COLEMAN ET AL.

relative prices, or changes in the number of competitors over time or over space.

For example, although we might not have data (or time) suitable for estimating

demand, a substantial shift in supply (as occurred in the cruise industry) might

give us information about the price elasticity of demand. Alternatively, we might

obtain useful evidence bearing on whether widgets and gadgets are in the same

market if during the period for which we have data there have been substantial

changes in the relative prices of the two products. Finally, another way to conceptualize the hypothetical monopolist analysis is to determine, if possible, whether

competition between a particular set of products or producers significantly affects

the price of those products. If so, removing that competition via the hypothetical

monopolist would be likely to raise prices. Thus a potential “natural experiment”

to analyze market definition (and sometimes competitive effects) might exist if’

during the time period for which we have data, there is a new supplier of widgets.

If a careful analysis of data and available evidence shows that prices for widgets

fell significantly due to the presence of the new supplier and that this appeared to

be not a transitory phenomenon, such an analysis would indicate that gadgets are

not “the” constraint on widget prices. This result would be consistent with widgets

being a relevant market. Yet another example involves situations where there are a

varying number of competitors over geographic markets or over time for the same

product, and a careful analysis of prices across the markets may be able to show

whether or not the number of competitors has a significant impact on price.

After the market is defined, the next step is to determine if there are likely

to be anticompetitive effects after the merger within the relevant market(s). As a

first step, we measure market shares and concentration in the relevant market. This

provides a screening device to assess whether further analysis is required. It is well

accepted in economics (and antitrust enforcement and in the Merger Guidelines,

specifically) that an increase in concentration in a relatively concentrated market

does not “prove” that a merger would be likely to be anticompetitive. Rather, a

conclusion that a merger is likely to be anticompetitive requires a theory of potential anticompetitive effects and assessment of potential efficiencies arising from the

merger that is soundly based on all the relevant facts and institutions of the industry

setting.

There are two principal types of anticompetitive theories that are considered

in a merger analysis: unilateral effects and coordinated interaction. In unilateral

theories, the merged entity has the unilateral ability profitably to increase its prices,

which requires that it does not lose enough sales to customers and/or to competitors

to make the price increase unprofitable. Among the theories that may be applicable

for assessment of potential unilateral anticompetitive effects arising from a merger are dominant firm, differentiated Bertrand oligopoly, or auction models with a

merger of the two lowest cost bidders.

Coordinated interaction theories require that the merger results in an increased

likelihood that the remaining firms can coordinate their actions with the effect

of significantly increasing prices, or in a decreased likelihood that any existing

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effective coordination would break down (Scheffman and Coleman, 2003). This

reduction in competition may come from the firms now being able to collude explicitly, but more likely would come from the merger changing the incentive and

ability of the competitors to engage in tacit coordination. As part of the competitive

effects analyses, we take into account the potential for efficiencies and their impact

on the likelihood of competitive harm.

Sometimes the evidence developed in a merger investigation is taken by the FTC

as conclusive on the determination of the likely effects of the merger, even when

there may not appear to be an obvious specific unilateral or coordinated effects

theory (Scheffman, 2003). For example, in industrial products mergers with a relatively small number of sophisticated, knowledgeable customers, if representative

customer opinions, derived from extensive interviews, indicate that these customers

believe that the likely effect of the merger will be to raise price, that evidence is

often conclusive for the federal antitrust agencies. Company documents planning

or predicting anticompetitive price increases are also given substantial weight.

FTC economists are involved in the assessment of all the relevant information,

but of course their comparative advantage is in developing useful, reliable empirical analyses. For example, there may be “natural experiments”, from which

empirical analyses demonstrate that the number of competitors significantly affects transactions prices (controlling for potentially confounding factors), or that

when the parties to the merger compete head-to-head, prices are significantly lower

(controlling for potentially confounding factors).

Both market definition and competitive effects analysis require careful, insightful economic theory applied to data and a great deal of qualitative evidence. In so

doing, we are looking at what the qualitative evidence (e.g., company documents

and customer opinions) and data indicate about the current nature and state of

competition in the industry.

When the competitive effects theory is coordinated interaction, we examine

whether market conditions are conducive to coordination. Dynamic oligopoly

theory has established the conditions necessary for effective coordination of competitors: “consensus, detection, and punishment”.7 Consensus requires sufficient

commonality in the incentives and abilities of the coordination group (important

factors include the costs and perceived benefits of price increases across members

of the coordination group) to reach consensus to coordinate, what to coordinate

“about” and by “how much” (e.g., to raise prices to what level). Coordination

also requires sufficient transparency and simplicity in the market, in the nature of

7 See, for example, Church and Ware (2000, Ch. 10). For an interesting example of the consensus,

detection, punishment paradigm being applied in litigating a merger challenge, see the European

Union’s Competition Commission’s challenge of the AirTours/First Choice merger (see the Commission decision http://europa.eu.int/comm/competition/mergers/cases/decisions/m1524en.pdf, and

the court’s decision that overturned the Commission decision http://europa.eu.int/smartapi/cgi/sga

doc?smartapi!celexplus!prod!CELEXnumdoc&lg=en&numdoc=61999A0342).

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126 MARY T. COLEMAN ET AL.

transactions, and in relevant market outcomes, that reaching a consensus, detecting

cheating, and effectively deterring cheating by credible punishment are feasible.

To begin, we caution that for a coordination theory to be valid, it is necessary that the particular proposed merger leads to a significant change in market

competition. That is, while it is true as a general matter that fewer competitors

potentially make coordination easier, it is necessary to show in any particular case

how the merger in question increases the likelihood of coordination. Careful quantitative analyses of various kinds, using data on prices, outputs, other competitively

important instruments (e.g., sometimes new product introduction or advertising

and promotion) can provide important evidence bearing on the likelihood that the

merger will result in the stimulation or strengthening of coordinated behavior. We

provide a number of examples below in our discussion of our analyses in the cruise

mergers. Here, we briefly summarize some of the types of empirical analyses relevant to an assessment of the potential for coordinated interaction effects arising

from a merger.8

As discussed further below in our discussion of the cruise line merger analyses,

we examine the complexity of pricing by looking at the number of different prices

as well as the distribution of prices across firms, time, and other categories of

interest. We look for systematic relationships in pricing (or capacity) that would

aid in reaching and monitoring coordination. For example, are the data consistent

with some level of coordination? One indication may be systematic patterns in

prices or changes in capacity over time.9 We look to see whether one of the parties

to the proposed merger firm has behaved particularly aggressively in a manner

that has had a significant affect on the state of competition in the market, and

whether the merger would be likely to remove this “maverick” competitor. We look

at factors that could upset any agreement that was reached – for example variability

in demand may make monitoring an agreement and punishing deviation difficult.

We look at the financial incentives of the firms in the industry and their different

positions. We look for any “natural experiments” – for example new product introductions or entry – that may provide evidence of past reactions to events. There are

many quantitative analyses, of which the ones described above are but a few, that

can shed light on the likelihood that the merger will enhance coordination of the

remaining firms.

If the analysis determines that unilateral or coordinated anticompetitive effects are likely, the next step is to consider whether an increase in prices would

encourage other firms to enter into the market. If entry is likely to occur, we

8 For a more detailed discussion, see Scheffman and Coleman (2003). For a summary of recent

thinking on the analysis of potential coordinated interaction effects of a merger by Department of

Justice, Antitrust Division economists, see Dick (2002).

9 This sort of analysis must be used with care, because very competitive markets often have

systematic patterns of prices or changes in capacity across competitors and time. Below, our analyses

of cruise transactions data will further clarify how analysis of the presence or absence of systematic

patterns in data can shed light on the viability of a coordinated interaction theory.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 127

need to determine whether it would it be sufficient to counteract the potential

anticompetitive effects of the merger.

Finally, if the parties to the proposed transaction claim that they will achieve

significant efficiencies through the transaction, we thoroughly investigate those

claims and assess how the efficiencies, if achieved may affect the assessment of the

potential competitive effects of the transaction. For example, a merger that achieves

substantial efficiencies may reduce the likelihood that there will be coordinated

interaction effects of the merger, since such efficiencies may destabilize the ability

to coordinate in the industry.

III. Overview of the Cruise Ships Investigation

On November 20, 2001, Royal Caribbean Cruises and P&O Princess Cruises announced a “friendly” merger. Less than a month later, on December 16, 2001,

Carnival Cruises made a “hostile” bid for P&O Princess Cruises. At the time that

the proposed mergers were announced, Carnival (which sailed under the Carnival,

Holland America, Cunard, Seaborn and Windstar brands) was the largest cruise

ship company in the world. Royal Caribbean, which sailed under the Royal Caribbean and the Celebrity brands, was the second largest cruise ship company in

the world. P&O Princess (which sailed under the Princess, P&O Cruises, AIDA,

A’ROSA, and Swan Hellenic brands) was the third largest cruise ship company in

the world. The other major cruise ship company was Star Cruises, which sailed

under the Norwegian, Star, and Orient brands. The Federal Trade Commission

investigated both proposed mergers to determine whether either deal would likely

be anticompetitive, through higher prices, decreased capacity, or other potential

anticompetitive effects.

When we present below some of the examples of empirical analyses, these

represent just a few of literally hundreds of analyses of various kinds – including

regression analyses, various kinds of cross-tabs, summary statistics, and extensive

financial analyses that were conducted in evaluating these mergers.10 As is always

10 This paper can only briefly summarize some of the economic analyses conducted by FTC

economists in connection with this investigation. Confidentiality limitations prevent disclosure of

any specific information. Further, space limitations preclude doing full justice to FTC economist

analyses; memoranda describing these analyses approached 200 pages. We also cannot do full

justice to the innumerable empirical analyses that were conducted. We had over 100 gigabytes of

transactions price data. We also had data on capacity over time and some public source data. We

also had extensive financial data from the parties to the merger. As part of the investigation, the

parties submitted hundreds of gigabytes of data on passengers that took a cruise between January

1, 1999, and December 31, 2001. The data included basic information on the cruise (line, ship,

itinerary), the gross price paid by the passengers, the net price received by the cruise line (gross

price less commissions and the cost of non-cruise add-ons such as airfare or land packages), the

date of purchase, the class of cabin booked, and the class of cabin the passenger sailed in (basically

whether the passenger received an upgrade). We did not have data on all bookings (most bookings

are cancelled before sailing). What we had were data on bookings where the passenger actually paid

and sailed.

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the case, besides conducting empirical analyses FTC the economists reviewed and

analyzed all the relevant qualitative evidence developed in the investigation. In this

paper we focus to a significant extent on the analyses relevant to an assessment

of potential anticompetitive coordinated effects arising from the mergers. This

is for reason of space and because the issues here are relatively novel from the

perspective of the published economic literature.

To get the “punch line” up front, the FTC chose not to challenge the proposed

mergers. On October 5, 2002, the Commission voted 3 to 2 to close the investigation, determining that the merger was unlikely to result in competitive harm. In

this matter (as with a number of other matters investigated by the Muris Commission) the FTC has been quite transparent in explaining its decisions. There was an

extensive statement by the majority Commissioners,11 dissenting statements by the

minority Commissioners,12 a speech (Simons, 2002) by the head of the Bureau of

Competition (the legal bureau at the FTC that handles antitrust cases) explaining

his decision to recommend not challenging the mergers, and a presentation (Scheffman, 2002) to the American Bar Association Mergers Acquisition Committee of

the Antitrust Section by the head economist Scheffman explaining some of the

relevant economic analysis.

The decision not to challenge the mergers has been criticized (Grimes and

Kwoka, 2003). We did not write this paper to argue the merits of this FTC decision. Rather, the purpose is to highlight the important role of empirical economic

analyses in antitrust. Empirical economic research could contribute more to developing new analyses and refining existing analysis. This is a very important area for

industrial organization economists to pursue, both as an academic contribution and

as a contribution to improving merger and other antitrust investigations.

In the investigation, there were three key issues. First, what was the relevant

market? In particular, are vacations on cruise ships part of a broader vacation

market? If so, the share of the combined firm would be low, and competitive effects

would be unlikely without further analysis.13 Conversely, if the market were limited

to ocean cruising, the combined firm would have a substantial share of a concentrated market, and thus further analysis of potential competitive effects would

be required. Second, if cruises are a market, what were the relevant theories of

potential anticompetitive effects? As explained below, the evidence did not support

a unilateral effects theory, so the primary focus was whether the merger created

a significantly increased potential for coordinated interaction. Would the merger

create the ability and incentive for the various cruise companies to coordinate

11 See http://www.ftc.gov/os/caselist/0210041.htm. Examples of other notable FTC statements

explaining decisions occurred in Synopsys/Avant! (http://www.ftc.gov/os/caselist/0210049.htm),

in Cytec/Digene (http://www.ftc.gov/opa/2002/06/cytycdigene.htm), Phillips/Tosco (http://www.ftc.gov/opa/2001/09/phillipstosco.htm), And Kroger/Raleys

(http://www.ftc.gov/opa/2002/11/krogerraley.htm).

12 See http://www.ftc.gov/os/caselist/0210041.htm.

13 As we will discuss below, there were important “interactions between market definition and the

analysis of potential competitive effects.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 129

and increase prices to (at least some) cruise ship passengers, or to coordinate on

increments in capacity? Finally, we had to assess the potential for and impact of

entry and/or expansion by “fringe” competitors.

The remainder of the paper is organized as follows. The next section provides

some background on the cruise ship industry. Section V discusses market definition

and the analyses we conducted to assess the relevant market in this matter. Sections

VI–VIII discuss the potential theories of competitive harm from the merger and the

analyses we conducted to assess these theories. Our conclusions are presented in

Section IX.

IV. The Cruise Ship Industry

The modern cruise industry is a relatively new vacation option. Today there are

over 200 ships with over 225,000 lower berths.14 The industry continues to grow

rapidly, with twenty-five new ships with more than 50,000 lower berths scheduled

to be constructed in 2003 and 2004. As the cruise industry has grown, the ships

have grown larger and more amenities have been added.15 The industry has also

seen entry, exit and consolidation over the years.16 At the time of the proposed

mergers (late 2002), world shares of cruise ship capacity (measured by lower berth

capacity) were Carnival 28%, Royal Caribbean 23%, Princess 13%, Star (which

owns the Norwegian line, among others) 11%, with the remaining 25% spread

among various other firms such as Disney, Crystal, and Radisson Seven Seas and

several smaller firms in Europe, including Louis Cruise Lines, Royal Olympic

Cruises (partially owned by Louis Cruise Lines), Festival, and MSC. As mentioned

above, 25 ships entered service in 2003 and 2004, with about 83% going to the four

largest companies. If these companies do not sell or scrap older ships, their combined shares will increase. If all current ships continue to sail, the shares at the end

of 2004 would have been Carnival 31%, Royal Caribbean 21%, Princess 15%, Star

10%, and the other cruise lines a combined 23%. Since the merger investigation

14 There are typically two lower berths per cabin. Some cabins will also have upper berths that

were not included in the capacity of the ships for these market share calculations. Capacities are

based on various public sources such as company websites and travel guides.

15 Amenities may include such features as skating rinks, climbing walls and personalized dining.

A modern state of the art cruise ship is in many ways analogous to a floating Las Vegas hotel.

16 Norwegian and Holland America began as operators of transatlantic ocean liners, but transformed themselves into cruise lines. Princess entered in 1965, Royal Caribbean in 1969, Carnival in

1972, Celebrity and Renaissance in 1989, Regal in 1993, and Disney in 1998. Regency exited in 1995,

Premier in 2000, Renaissance in 2001, and Regal in 2003. (With the exception of Renaissance, which

shutdown on September 11, 2001, most cruise lines that exited were continuing to operate converted

ocean liners as opposed to ships designed for destination cruise vacations.) Previous mergers include

P&O buying Princess (1974), Carnival buying Holland America (1989), Costa (1997), and Cunard

(1998); Royal Caribbean buying Celebrity (1997); and Star Cruises buying Norwegian Cruise Lines

(2000), which had just purchased Orient Lines (1998).

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ended, Star has announced the purchase of two former mothballed ocean liners,

which it plans to refurbish for its Norwegian Cruise Lines subsidiary.17

Different cruise lines focus on passengers from different geographic areas, and

we will refer to cruise lines based on the where the majority of passengers live

as opposed to where the ships sail.18 The market shares for North American firms

(based only on the lower berth capacity of their North American lines), are Carnival

(Carnival and Holland America lines) 35%, Royal Caribbean (Royal Caribbean

and Celebrity lines) 34%, P&O Princess (Princess line) 12%, Star (Norwegian and

Orient lines) 12%, and other lines including Disney, NYK’s Crystal line, Radisson,

and Silversea, 7%. These cruise lines made up two thirds of worldwide capacity.

The types of cruises offered vary in many ways. Key distinguishing factors

include: destination (often referred to as a “trade”), length, and departure date.

Cruises also vary based on the characteristics of the ship and the cruise line.19

Different cruise brands also vary to some extent as to the types of consumers that

they cater to, which influences the types of amenities that the cruise lines offer.

For example, Carnival and Royal Caribbean to some extent focus their marketing to younger active passengers, while Holland America and Silversea to some

extent market themselves to more mature passengers looking for more luxurious

accommodations.

Roughly 40% of passengers on a particular cruise are taking their first cruise.20

The fact that so many passengers are first time “cruisers”, who are likely to have

considered other vacation options, is relevant to product market analysis. Also

important was the fact that many passengers who take a cruise never cruise again

or, if they do, do so infrequently. Thus cruise lines are constantly seeking to attract

passengers who have never cruised or only cruise infrequently.

17 Norwegian Cruise Line press release, April 14, 2003. Available at

http://www.ncl.com/news/pr041403.htm

18 However, North Americans often sail on European lines, and Europeans often sail on North

American lines. In addition, ships from North American lines will sail in Europe during part of the

year, and ships from European lines will sail in North America for part of the year.

19 The largest ships have over 1500 cabins, with smaller ships having as few as 100 cabins. Ships

also vary in their mix of different cabin types. Cabins fall into four basic categories: inside, ocean

view, balcony, and suites. Many older ships have no cabins with balconies, while some of the new

ships have over 70% balcony cabins. Each type of cabin is classified further based on which deck it

is on, or whether it is fore or aft. For example, similar cabins on higher decks are considered better.

20 Cruise Lines International Association website. Available at

http://www.cruising.org/press/press-kits/kits/pko-57.cfm

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Buying a cruise can be a complicated purchase.21 Unlike many other travel

options, most cruises (over 90%) are still sold through travel agents.22 That travel

agents overwhelmingly account for sales is important to the competitive analysis,

limiting the scope of potential theories of anticompetitive price discrimination,

since the cruise lines have very limited information about the characteristics of

specific customers when they book.

A given ship/itinerary starts booking eighteen months or more before departure.

Until late in the booking cycle, there usually are no penalties for cancelling a

booking. The majority of bookings are cancelled. Like most other participants in

the hospitality industry, cruise lines use some type of “yield” or “revenue” management system, which was a major focus of the analyses bearing on market definition

and the competitive effects analysis.23

V. Market Definition

Any market broader than cruise ships would mean that the mergers were not problematic because the merging parties would have very low market shares. Thus, as

is often the case, market definition is a critical first step in the merger analysis.

Cruises are one form of vacation. Because vacations on cruise ships have differences as compared to land-based vacations, a cruise ship market was possible.24

As is frequently the case, the qualitative evidence was not conclusive on whether

the hypothetical monopolist test would pass or fail.25 Thus quantitative analyses,

particularly “critical loss” analysis, were important to resolve market definition.

21 Cruise lines often bundle related products with the cruise, allowing them to offer package

discounts. For example, the passenger can choose to add airfare to and from the cruise, add land

packages before or after the cruise, and add shore packages during the cruise. The prices for the cruise

and some of the add-ons will change regularly during the months leading up to sailing depending on

how well the cruise is selling. The complexity of purchase also affects the competitive analysis, in

that such complexity – along with the complexity of the many itineraries, types of ships, and berths

on ships – is likely (other things equal) to make some types of coordination difficult.

22 One explanation for the reliance on travel agents is the heterogeneous product mix of different

cruises. Travel agents help ensure that cruise passengers are matched with the cruise that best fits the

passengers’ preferences. Another explanation is the complex nature of the purchase.

23 The industry frequently uses the term “revenue management” to describe their version of yield

management. We will use the more common “yield management” term.

24 In many ways, however, vacations on cruise ships are analogous to 6ther vacations and thus a

broader market is also plausible. For example, for some customers, a week at an all-inclusive resort

in the Caribbean may be similar to a week on a cruise ship in the Caribbean, since for both vacations

most of the customers’ expenses are covered by the weekly rate, and there are similar activities such

as eating, swimming, sunning, and night life. For other customers, a long weekend in Las Vegas

would be similar to a three- or four-day cruise to the Bahamas since most cruise ships have Vegasstyle shows and casinos. The investigation uncovered some evidence that cruise competitors focused

primarily on each other, but there was also evidence that the cruise lines worried about selling in a

broader vacation market and capturing a larger share of that market by offering a competitive product.

25 That cruise vacations differ in various respects from other vacations and that cruise lines view

each other as important competitors do not, themselves, resolve the hypothetical monopolist test.

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132 MARY T. COLEMAN ET AL.

As discussed above, the critical loss value is determined by the variable margins

in the industry. Once the decision has been made for a cruise ship to sail, the

margins in the cruise ship industry are very high since most of the costs at that

point are fixed and the cruise ship makes money on complementary goods and

services once the person is on board.26 Therefore, only a relatively small number

of consumers would need to be lost for a price increase to be unprofitable. This

does not mean by itself that the market is broader than cruise ships – rather one

still must analyze what the actual loss is likely to be.

This is a very complex industry with many prices. Prices vary across types of

accommodations, itinerary, type of ship, and other factors. In addition prices for

any particular type of cabin on any specific cruise vary significantly over the booking cycle, which is about 18 months. Quantities are also complex in that there are

different types of berths, ships and itineraries. Thus, estimating demand elasticities

would, at best, be highly problematic. We also had only a few years of data.

However, we had the advantage that during the period of the data there was

a very large increase of capacity in a short time during 2000 and 2001. We used

this natural experiment to develop some crude estimates of demand elasticity. This

natural experiment provided striking evidence – the industry “absorbed” this large

short run increase in capacity with very little impact on capacity utilization and a

very modest effect on the level of prices. This outcome was accomplished, in part,

through use of yield management. But the result was still striking. That the cruise

industry could absorb this capacity so readily with only a modest reduction in price

levels is consistent with cruise vacations being in a broader vacation market.

Because of the confidentiality issues, we cannot report specific results. We estimated arc elasticities of demand (response of average revenue to the large short

run change in quantity) in several different ways. Our first approach was to estimate an arc elasticity using the percentage change in the average price per day

in each year of the natural experiment.27 We also ran regressions to control for

various factors.28 The estimates of arc elasticity of demand based on this natural

26 Our data on margins was based on accounting data, which have their own imperfections. One

might question whether or not the cruise lines could reduce the number of sailings. Ships generally

sail every week during the year other than for maintenance. Maintaining a ship in port without sailing

it is very costly and thus unlikely to occur. Thus reducing the number of sailings requires reducing

the number of ships. We discuss this further below in the competitive effects sections.

27 This simple calculation, however, has several potential issues as it does not control for several

factors that might affect pricing. As a first step, to control for the impact of millennium cruises and

post-September 11 cruises, we simply excluded these time periods from the analysis in each of the

comparison years, so as to maintain an “apples-to-apples” comparison.

28 The dependent variable was the average price on a ship in a month (overall and by berth

category). Independent variables include controls for annual effects, month effects, ship effects,

types of berth (where appropriate), millennium cruises, and post-September II cruises. The estimated

coefficient on the annual effects was then used to calculate a percentage change in price, which was

then compared to the percentage change in capacity.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 133

experiment were about −2 or greater (in absolute value) for various measures of

price and for various specifications.29

Employing critical loss analysis, with this level of elasticity of demand, in order for a hypothetical monopolist to increase prices profitably, its margins would

have to be below 50% much lower than short-run cruise ship margins.30 Thus, our

analyses showed that an across-the-board price increase would not be profitable.31

This means that cruise vacations would not be a market for what is the typical

Guidelines market definition test; i.e., an examination of an across-the-board price

increase.32

Although an across-the-board price increase would not support a cruise market,

product market analysis also considers whether a hypothetical monopolist could

identify less price-sensitive customers and use price discrimination to increase

prices to a subset of consumers in the market.33 The cruise lines use yield management, and the data showed that different cruise ship passengers in similar cabins

often pay very different prices. Of course, the fact that different consumers pay

different prices does not in itself indicate that there is a “competitive problem” that

is exacerbated by a merger. For example, most hotels currently use some form of

yield management, but that, in itself’ does not mean that there are competitive prob29 Note that these should probably be interpreted as short run elasticities, since it is plausible that

the industry could accommodate a large increase in capacity with less downward pressure on price

over a longer period of time (even with the level of demand constant). Thus the longer-run elasticity

of demand might be considerably greater (in absolute value) than −2.0.

30 Critics of the critical loss analysis in this merger have questioned how high margins and relatively high market elasticity of demand could exist at the same time, since the Lerner Index should link

high margins with relatively low firm elasticity of demand, and the market elasticity of demand would

need to have an even lower elasticity of demand. First, there are many highly competitive industries

with high fixed costs and implausible unilateral market power. In addition, this relationship need

not hold if there are capacity constraints, which is the case in the cruise industry. When making the

decision on whether to build new ships or not, firms will consider the impact that adding an additional

ship will have on the profitability of its fleet. It is likely that the outcome of these decisions will lead

to binding capacity constraints in the short run. This type of behavior would be similar to the model

in Kreps and Scheinkman (1983). See Grimes and Kwoka (2003) for criticism of critical loss as

applied to the cruise ship investigation. Grimes and Kwoka did not have available the details of the

analysis supplied in this paper (or various confidential facts that cannot be disclosed).

31 This is consistent with the cruise lines’ behavior – i.e., they do their best to fill up, and generally,

on average, fill up to practicable capacity. For example, the large short-term increase in capacity had

very little short-run effect on capacity utilization and no effect after the first season.

32 This result should not be surprising. It is quite plausible that there is some non-trivial proportion

of consumers who purchase cruises and seriously consider other vacation options. The critical loss

analysis shows that proportion does not have to be very large for an across-the-board price increase

to be unprofitable. In addition, a high proportion of people who purchase cruises are first-time “cruisers”, and repurchase frequencies by repeat cruisers are low, suggesting that many cruisers are likely

to consider other vacations as alternatives.

33 Such “price discrimination” markets are also discussed in the Guidelines at §1.12.

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134 MARY T. COLEMAN ET AL.

lems in the hotel industry. Rather, yield management is one way that competitive

markets price perishable goods and services.34

Thus the typical approach to market definition was modified to have a hypothetical monopolist using yield management. A monopolist using yield management

would likely generate higher total revenue than would be generated by all competitors in a market with more than one firm, but this does not “prove” that a

cruise merger would be anticompetitive. Cruise lines within practical limits approximately sell out. They have strong incentives to do so, because of the very

high variable margins. A monopolist has similar incentives. In fact, it is likely that

the hypothetical monopolist would practicably sell out also. Thus the effects of the

hypothetical monopolist would not likely be on “output” (for fixed capacity), but

rather for the pricing of fixed capacity.35

Our analysis of market definition focused on determining whether we could

identify a segment of customers and/or transactions that could be a viable price

discrimination market.36 To begin, since cruises are overwhelmingly sold by travel

agents, a theory involving the characteristics of the customers was not viable. Instead, we focused on the characteristics of the transactions – such as type of cruise,

type of berth, or time of booking. We were looking for something analogous to

“business travelers” in the airline industry.37 (Again, cruise lines are unlike airlines

in that they generally run at practical capacity, so in this critical dimension, and

some others, cruise lines differ from airlines). There were several different categories of transactions that were considered as potential target segments for a price

increase by a hypothetical cruise ships monopolist. Candidates for potentially less

price elastic transactions included: customers that booked their cruise early,38 consumers that purchased a particular type of cabin (such as the higher-priced balcony

34 For examples, participants in “farmers markets” generally use pricing strategies and tactics

analogous to yield management.

35 This last outcome produces somewhat complex (for antitrust analysis) issues as to what outcomes would be anticompetitive. For example, a plausible result would be that the hypothetical

monopolist charges higher prices to some consumers and lower prices to other consumers. Is this

anticompetitive? Under a total welfare standard, there would be no effect because there would be

no deadweight loss. For a consumer welfare standard, which is generally the standard employed in

antitrust analysis, on average consumer welfare would decline since average prices would increase.

However, even here the effects are complex since some consumers would have a welfare increase

while others would have a welfare decrease. Finally, there is an issue, of course, whether competition

would lead to more capacity. We discuss these issues in more detail in Section VIII below.

36 Of course a price discrimination market, itself, raises issues about the viability of a competitive

effects theory (e.g., arbitrage by suppliers and/or customers) that would have to be addressed.

37 It is of interest to note that the Department of Justice airline merger cases have generally focused

on business, rather than leisure travelers, in part for reasons analogous to those that arise in the

antitrust analysis of the cruise line industry.

38 A difficulty for this theory is that most early bookings are cancelled, and there is generally not

a penalty for cancellation until close to sailing.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 135

cabins),39 or a particular kind of cruise (“trade”) (e.g., Alaska). Such candidates are

discussed in the context of our empirical analyses in Section VII.C. Our analyses

were not able to identify a viable price discrimination segment. Briefly, this is

because there is substantial variation in prices that cannot be explained by any

characteristics of customers, transactions, ships, or trade.40

VI. Analyses of Potential Competitive Effects of the Proposed Mergers

1. EMPIRICAL ANALYSES OF “NATURAL EXPERIMENTS”

To begin, as part of our empirical analyses we used various “natural experiments”

to assess whether there appeared to be any significant relationship between the

number of competitors or concentration and the level or distribution of prices,

or between the presence of particular competitors and the level and distribution

of prices. First, industry concentration had increased over time (due to unequal

capacity increases across cruise lines and to some past mergers). The available

data indicated that average prices had fallen during this period so there was not

a positive historical relationship between concentration and price levels. Furthermore, increased concentration appeared to have no effect on incentives and actions

to increase capacity.

Regression analyses were also used to test the relationship between concentration and price. Different trades offered different vacation experiences for

consumers and thus arguably could be considered relevant markets from the demand side. Although, ease of supply side substitution (shifting ships from one trade

to another) might indicate that a broader market is appropriate, because ships are

committed to itineraries well in advance of sailing, supply side substitution might

not arbitrage price differences in the short run. Regressions were run estimating the

relationship between pricing and concentration using annual observations by trade

and controlling for other factors such as trade-specific dummy variables and variables to control for changes in demand. We also considered whether ships in certain

trades with higher seller concentration were more “profitable” than ships in other

39 Of course, it is not obvious, a priori, whether we should expect that the proportion of consumers who would shift to other types of vacations would differ by price, income class, or other

demographics factors.

40 As we will explain below, identifying a viable price discrimination segment would not, itself,

provide a viable theory of anticompetitive effects of either proposed merger, since we did not have a

merger to monopoly, and the facts rejected a dominant firm theory. Nonetheless, because a hypothetical monopolist using yield management could increase its profits over competition, we concluded,

following a modification of the Guidelines’ market definition analysis, that cruise lines were a relevant product market. Put differently for those not conversant with the Guidelines analysis, our analyses

indicated that a merger to monopoly would be problematic, but neither proposed merger would be

likely to alter pricing (or capacity) anticompetitively. That said, our empirical analyses demonstrated

that how pricing under the hypothetical monopolist would differ from the status quo was unclear.

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136 MARY T. COLEMAN ET AL.

trades. These studies showed no systematic relationship between concentration and

price or profitability.41

Finally, we conducted some intensive investigations of particular trades and

found no relationship within or across trades between concentration and price.42 Of

course these analyses did not prove that the proposed mergers were competitively

benign. Rather more analysis is required to assess whether the proposed mergers

are likely to result in higher prices. Because individual trades do not appear to

be a relevant market, the analysis focuses on the impact of the merger on cruises

generally.

2. UNILATERAL EFFECTS

There are three main categories of unilateral effects theories considered in merger

investigations: dominant firm, homogeneous Cournot, or differentiated Bertrand

models.43 We considered all three theories in the investigation. Both proposed

mergers would lead to a firm owning between one-third and one-half of cruise ship

capacity (depending on the geographic market). For a number of reasons (some of

which we cannot disclose because of confidentiality), a dominant firm (or Cournot)

theory was rejected. First, the critical-loss calculus for a dominant firm (or Cournot

competitor) is less hospitable than for the hypothetical monopolist, so a unilateral

restriction in output was not financially viable.44 With respect to a yield management theory, various theories of a firm with a share of 50% or less raising average

rates through unilateral yield management were not viable. For example, “waiting

longer” to fill berths to try to defend higher prices would leave potential customers

to be “picked off” by competitors who are searching for higher willingness-to-pay

customers, with such a strategy again being defeated by the critical-loss calculus.45

We also assessed unilateral capacity reduction theories. This capacity reduction

could come from building fewer ships or, if the focus is on cruises marketed to

North Americans, by transferring ships to lines marketed to Europeans or Asi41 The data that we had to test this hypothesis were limited, and thus the tests used were somewhat

crude. However, we did not find evidence supporting an argument that the number of competitors

mattered. This finding was supported by other qualitative and quantitative evidence.

42 One issue examined extensively was whether cruises to Alaska had significantly different

margins and profitability than Caribbean cruises.

43 See “Merger Guidelines” at § 2.2. See also Canton and Perloff (2000, Ch. 6) and Church and

Ware (2000, Ch. 8.3). The facts developed in the investigation should support that competition is

adequately “explained” by such models.

44 We discuss capacity (rather than output) restriction theories below.

45 Finally, as we will see below when we discuss some of our empirical analyses, head-to-head

competition on price is actually not a very important determinant of prices. (Of course, this is

consistent with a broader vacation market. Recall, again, for example, that about 40% of customers

each year have never taken a cruise vacation before and the repurchase rates are small and relatively

infrequent). This is, in part, because cruises are largely “sold” rather than “purchased”. We conducted

various analyses that showed that the number of competitors on a given itinerary or given trade did

not significantly affect the level or distribution of prices.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 137

ans.46 Consider first the ship-transfer theory. For example, the merged entity could

transfer some of its Princess ships to its A’Rosa line that is marketed to Germans.

We rejected this capacity-shifting theory based on detailed financial analyses of

confidential information that analyzed the financial incentives of both the merged

entity and of the competitors to shift capacity.47 These are discussed in Section

VIII.

For theories involving potential future capacity reduction, a very important fact

was that industry participants already had commitments to future capacity that

would substantially increase industry capacity (a large number of ships are on order

that will be delivered by the end of 2005). There was no viable theory by which the

merged entity had the ability and incentive to affect industry capacity meaningfully

for at least several years. We also conducted financial analyses of the profitability

of adding new ships for the merged entity to assess its incentives to reduce capacity

in the future.48 These are discussed in Section VIII.

Finally, we assessed whether a differentiated Bertrand model was viable – i.e.,

would the merged entity control two products that are sufficiently close competitors

that they have the ability and incentive to raise prices, given Nash behavior by the

competitors.49 We found that such a theory was not viable. To begin, the various empirical analyses showed that head-to-head competition between particular

competitors did not, itself, have a significant sustained impact on prices. In addi46 Another option would be to scrap existing ships. However, most existing ships continue to sail

even when the cruise company goes bankrupt. The main ships that are being scrapped are former

ocean liners that were converted for use as cruise ships. The potential merging parties own very few

of these ships, such as Cunard’s (Carnival’s) Queen Elizabeth II or Norwegian’s (Star’s) Norway, so

the amount of capacity the merged entity would consider scrapping is too small to have a significant

impact on industry capacity.

47 The basic intuition for the results is as follows: First, the North American cruise lines, with two

thirds of the world’s capacity, are much larger than all the foreign cruise lines combined. Therefore,

transferring enough ships out of North American lines to increase prices in the North American

market would have a much larger effect on prices in foreign markets. Moreover, this would affect

a significant fraction of the merged firm’s North American capacity, as well as the merged firm’s

foreign capacity (recall the relatively high price elasticity). Our financial analyses of confidential

data showed that this would not be a profitable strategy. Furthermore, competing firms with ships in

the foreign markets could reposition their ships to the North American market, making the capacity

shift by the merged entity even more unprofitable.

48 These analyses assumed that prices would fall as new ships were built (based on our estimates

of price elasticity) so that one of the costs of building new ships was the lower profits on existing

ships. Even after the current ships on order are delivered, the analyses showed that the merged entity

would find it profitable to keep building new ships. In addition, various industry participants, large

and small, continued to announce commitments to new capacity during and after the investigation.

49 In this case, when the company increases the price of one firm’s product, a significant portion of

the lost sales go to the other firm’s product. Since the merged entity now internalises these lost sales,

it would find it profitable to increase prices on at least one of the products. To be profitable in the

long run, there need to be impediments or disincentives for the remaining competitors to reposition

their products to take advantage of the reduced competition in a manner that makes the price increase

unprofitable.

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138 MARY T. COLEMAN ET AL.

tion, with respect to characteristics of competitors’ offerings, there was substantial

overlap in the competitive offerings of each of the cruise lines. Both Royal Caribbean and Carnival had ships and accommodations, and itineraries that overlapped

each other and overlapped the other competitors. For some passengers, a Holland

America balcony cabin may be comparable to a Crystal ship ocean-view cabin,

while other passengers may be willing to substitute between an interior Princess

cabin and an ocean-view Royal Caribbean cabin.

The standard differentiated Bertrand model does not fit well in this industry.

Cruise lines generally sail practicably “full”, and capacity is fixed, at least in the

short term. In addition, there is not “one” price. Thus, even if an increased price for

one brand would result in significant increased demand for another brand owned

by the merged firm, at best all that the firm can hope for is that average prices will

increase. In the standard model, the increase in demand leads to additional sales

for the merged firm’s other product, while in the cruise industry, any diverted sales

would displace other (presumably lower fare) passengers so that quantity remains

unchanged. Therefore, even if there are extra profits for the other brands, these extra

profits are unlikely to offset the losses from running a ship with empty cabins. As

a result, the incentives to increase prices unilaterally as a result of a differentiated

products theory may not exist.50

In addition, the relationship between hypothetical price increases and diverted

sales was at best highly complex. For example, the variability of demand would

make it difficult for the merged firm to determine where lost passengers went after

a potential price increase.51

Finally, if the merging parties, hypothetically, were “close” competitors due

to current choices in deployments – for example, if the merging parties have an

unusually high market share in a given trade – any attempt to raise prices or reduce capacity in that area could be countered by competitors repositioning extra

capacity in that area or on that route. This extra capacity could be either an extra

50 For example, consider a merger among brands A and B, each of which currently has sales of

100 units at $200, and 100 units at $150, with zero marginal cost. Think of the high price as early

sales, and the low price as late sales. Assume that if the high price for brand A is increased to $220,

then its early sales will fall to 80, while brand B’s early sales increase to 115 (picking up 75%

of the lost sales). If brand A were on its own, this would not be profitable to follow this strategy

(variable margins would fall from $35,000 to $32,600). After the merger, this would be profitable in

the traditional differentiated product model, with the merged company’s variable margins increasing

from $70,000 to $70,600. However, if by increasing brand B’s early sales to 115 its late sales fall to

85, the merged company would see variable margins fall from $70,000 to $68,350. Even if brand A

picks up a portion of Brand B’s lost late sales, the merged entity often would not find it profitable to

increase the early price of brand A. If brand A’s late sales increase to 110 (picking up 2/3 of the lost

sales), then variable margins would fall from $70,000 to $69,850.

51 For example, if the merged firm increased prices on successive weeks and saw sales fall 10%,

one week the other line may see an increase in sales of 5%, while the other week it could see sales

fall. With this type of variability, the merged company may not be able to determine whether enough

lost sales would be recaptured to make the price increase profitable.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 139

ship, or replacing a smaller ship with a larger ship.52 Again, we found no evidence

supporting a conclusion that the number of competitors or concentration affected

the level or distribution of prices.

VII. Potential Competitive Effects: Coordinated Interaction With Respect to

Price

In a coordinated interaction theory, the merger changes competition by creating,

facilitating, or strengthening effective coordinated interaction. Obviously relevant

to the assessment of the viability of such a theory is the nature of pre-existing

competition (Scheffman and Coleman, 2003).

1. CURRENT STATE OF COMPETITION IN THE CRUISE INDUSTRY

Cruise lines market, sell, and price so as to sell out the ship. This goal is largely

achieved, even when substantial increments of capacity are added in a short period

of time.53 In addition, the cruise industry has been expanding rapidly for a number

of years, and current capacity commitments will continue this expansion for at least

the next few years. The number of lower berths across all ships has increased to

over 225,000 at the end of 2002, with over 150,000 of those berths on ships built in

the last ten years. Another 50,000 lower berths are due to be added to the world’s

cruise lines by the end of 2004.54

Prices have fallen with the rapid expansion of capacity and the introduction of

larger more efficient ships. Newer ships, aside from being larger on average, also

have more amenities and a higher portion of higher value cabins. For example,

Carnival’s Fantasy class ships, which were built Between 1990 and 1998 had 45%

inside cabins, 50% ocean view cabins, no balcony cabins, and 5% suites. Carnival’s

Spirit class ships, which were introduced in 2001, have 26% inside cabins, 9%

ocean view cabins, 60% balcony cabins, and 5% suites.

52 For example, Norwegian and Royal Caribbean have both recently expanded their presence in

Alaska. Norwegian has more than doubled the number of berths in Alaska since 1999, first by replacing the smaller of its two ships, the 824 passenger Norwegian Dynasty, with the 2002 passenger

Norwegian Sky. Later, Norwegian added a third ship in Alaska. In the same time frame, Royal

Caribbean has increased its capacity in Alaska by just over 50% by adding an additional Royal

Caribbean ship and an additional Celebrity ship.

53 As discussed above, this occurred without substantial reductions in the level of prices.

54 There have been older ships, mainly former ocean liners, that have been sold for scrap over the

years, and more will likely be sold for scrap before 2004. Many of the older ocean liners need to be

retrofitted to meet new safety regulations that are being phased in through 2010. Therefore capacity

ten years ago was likely above 75,000, and overall capacity will likely increase by somewhat less

than 50,000 lower berths by 2004.

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140 MARY T. COLEMAN ET AL.

Thus the state of competition in the industry has been one of competition on

price,55 capacity, and product and service differentiation. The substantial complexity of the industry, the competition on all dimensions, the strong unilateral

incentives to set prices to fill the ships, and the strong unilateral financial incentives

to add capacity, combine to make the cruise ship industry an unlikely candidate for

anticompetitive tacit coordination with respect to price.56

No specific competitor can be credibly put forward as a relatively important

driver of the state of competition. Rather, the state of competition can be best explained as arising from the strength of the urn lateral incentives of the competitors.

Each of the cruise companies has expanded capacity significantly and added new

features and amenities. During a period of rapid growth fueled by increments in

capacity, concentration has been increasing. There are three factors underlying the

increase in concentration. First increments in capacity have changed shares over

time. Second, many smaller firms have exited the industry. Finally, there have been

previous mergers in the industry.

Thus, at the “30,000 foot level”, this is an industry that does not provide much

(if any) basis for effective coordinated interaction with respect to price. A major

focus of our empirical analyses was to look intensively at transactions-level data

to understand the nature and extent of competition and to look closely at whether

conditions were conducive to coordination and whether the merger was likely to

change the nature of competition in the market.

2. LIKELIHOOD OF PRICE COORDINATION: COMPLEXITY, TRANSPARENCY,

AND INCENTIVES

A coordinated interaction theory that involved increasing prices is complicated

by the fact that a theoretical monopolist would not find it profitable to increase

prices across the board. Therefore, a coordinated interaction theory involving

prices would require price discrimination as well. As described in the section on

market definition, a great deal of effort was made in attempting to determine if

there was some class of consumers that, after the merger, could be the focus of

a targeted price increase. However, a theory of coordinated interaction with price

discrimination adds to the complication of achieving consensus as to whom and

how prices would increase, of detecting deviations, and of designing a viable and

credible punishment mechanism.

As part of our investigation, we considered whether our detailed analyses of

transactions-level data indicated that the cruise industry was conducive to price

55 Price competition generally involves pricing to fill the ship. As we see below, the importance of

head-to-head competition on price in this industry is relatively limited, in part because to a significant

extent cruise vacations are “sold” rather than “purchased”.

56 Another indicator of the state of competition is that although this is a relatively new and rapidly

growing industry, most competitors have made substantial efforts to reduce costs, and to varying

extents across competitors those efforts have been successful.

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coordination or whether there was any evidence of current coordination on price

to some group of customers. The goal of these analyses was to determine the

following: (1) the complexity of pricing, (2) the transparency of pricing, and (3)

the extent of consistency in the cruise lines’ unilateral incentives. Several specific

analyses were performed including an analysis of the relationship of prices and

sales over the booking cycle of specific competing head-to-head cruises, an analysis of the extent that the pattern of prices and sales differed significantly across

similar cruises, an analysis of the distribution of discounts on similar cruises, and

an analysis of whether there are groups of passengers for whom pricing patterns

differed in a way that suggested less elastic demand.

A. Complexity

Reaching consensus on prices in this industry would not be an easy task due

to the complexity of pricing. At any point in time there are a large number of

cruise prices. Individual sailings open for sale twelve to eighteen months before

the ship departs. The four major cruise companies have a combined 75 ships in

their six North American brands: Carnival, Holland America, Royal Caribbean,

Celebrity, Princess, and Norwegian. If each ship were sailing approximately sevenday voyages,57 at any given time each ship would have tickets available for 50 to 75

voyages; conservatively, that would be 3,750 voyages. Each ship has ten to twenty

different cabin types, in four major categories – interior, ocean view, balcony, and

suites. Conservatively, that leads to 37,500 different products for sale at any given

time. However, there is at least twice that number of prices, since the cruise lines

have both individual and group prices for almost all cruises. At a minimum, there

are 75,000 prices at any given time, before we discuss discounting.

The cruise lines offer targeted discounts to various types of potential customers

e.g., past passengers, “affinity” customers, passengers from certain localities, etc.

– and give special deals to various travel agencies. The cruise lines also often use

upgrades as a form of discounting. Many passengers buy their plane tickets through

the cruise lines that purchase blocks of seats from the airlines. Since the cruise lines

often “charge” significantly above or below their negotiated price with the airlines

(in terms of the implicit airline price in a bundled offering), the prices that the

cruise lines charge for the airfare allows them to increase or decrease the effective

prices of the cruise for passengers flying from every different airport. In effect, this

could lead to almost 200 times as many prices on any given day.58

Any coordinated interaction theory would require reducing the complexity of

this large set of prices to a manageable level, both in reaching consensus on what

the collusive prices should be, and in monitoring them to detect cheating. One

focus of our empirical analyses was whether there were systematic relationships in

57 The average voyage length for sailings in our data is just under 7 days, with 52% of cruises 7

days, 31% less than 7 days, and 17% over 7 days.

58 The Travelocity website will give prices for cruises and airfares from 189 different airports in

the United States and Canada.

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pricing that might reduce the number of prices about which consensus regarding

coordination would be necessary. One possibility was to find groups of prices that

were highly correlated. For example, if there were fixed premiums for different

categories of interior cabins across sailings, then the firms would only need to

coordinate one price for interior cabins. While the premiums for higher quality

cabin categories were fairly consistent in the brochure prices, for the sailings that

we analyzed there was substantial variation in relative transactions prices across

types of berths. Another possible example would be if consecutive sailings could

be combined to reduce the number of prices. However, the pricing and booking

patterns can vary substantially for two cruises of the same ship sailing the same

itinerary one week apart.

To assess the complexity of the booking cycle, we looked at booking curves

(fill rates and average prices over time) for many individual cruises. While it might

seem likely, a priori, that transactions prices fall over the booking cycle, this is

not generally true. Although on average across all cruises in a given season later

prices are lower than earlier prices, on any given cruise, transactions prices can fall

or rise, or go up and down through the booking cycle. This is shown in Figure 1,

which is just one example of the lack of a consistent pattern of prices through

the booking cycle.59 Thus, yield management in the cruise line industry is much

more complex than starting with high prices and then, if necessary, lowering them

through the booking cycle so as eventually to fill the ship. While most sailings had

lower average prices later in the booking cycle, the distribution of discounts and

premiums also varied dramatically. As demonstrated in Figure 1, prices late in the

booking cycle ranged from 55% below the early prices to 35% above the early

prices.

B. Transparency

Lack of transparency would make detection of cheating difficult. Although each

firm publishes brochures listing prices for the various types of cabins for the various

itineraries it plans to sail, most passengers do not pay these prices. Furthermore,

many passengers will buy a bundle that includes airfare or land-based add-ons,

which may or may not be priced in the brochure. The cruise line can set the price

of the air add-on to raise or lower the effective price of the cruise. Many passengers

also receive free upgrades, which is another way for cruise lines to discount prices

on higher quality cabins. Another complicating factor is that discounts on group

sales are not always transparent. Furthermore, it is possible for travel agents, which

sell most tickets, to rebate a portion of their commission to close a sale.

59 Since we are limited to presenting public information, these figures are from

David Scheffman’s presentation to the ABA M&A Committee on November 21, 2002

(http://www.abanet.org/antitrust/committees/clayton/programs.html). The entire presentation is

available at http://www.ftc.gov/be/hilites/ftcbeababrownbag.pdf, where larger color versions of

these charts are available.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 143

Figure 1. Relative pricing before and after 120 days for all cruises.

Cruise ship transactions prices are generally not available on computer reservation systems. With the large number of prices at any given time, it would be

extremely difficult for cruise lines to track them all. Furthermore, while some

prices are visible to competitors, such as brochure prices or prices at Internet travel

agents, there are many other prices that are not easily accessible. Therefore, unless the prices that are not transparent are highly correlated with some transparent

price, overall prices will not be transparent. For example, if average prices were

consistently at a fixed discount from brochure prices, then a competitor would only

need to know the brochure price. However, our analyses did not support this type

of relationship between various types of prices. Competitors also cannot determine

with any accuracy the fill rate on competitors’ individual cruises or in aggregate

over the booking cycle or year.

The cruise lines do expend significant effort to track at least some prices of

their competitors for particular sailings. They will receive information from travel

agents telling them about specials being offered by competing cruise lines and they

will also do some of their own research on pricing through mock bookings. This

data collection, however, only gives them sporadic information on pricing about a

subset of cabins and price offerings. The information is not consistently used to

respond to the pricing of competitors but appears to be a piece of information used

by the cruise lines to understand the pattern of bookings that they are observing for

particular sailings.

C. Incentives

The incentives of the various cruise lines to participate in any collusive equilibrium

would differ. One reason is that the products offered by the various cruise lines are

differentiated in many ways, such as in the quality and configuration of their ships

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144 MARY T. COLEMAN ET AL.

and the itineraries that they sail. These differences will make it much more difficult

for the firms to agree on which prices to increase since each firm will differ in the

fraction of customers of any given type. For example, over 40% of Princess’ cabins

are balcony cabins while only about 20% of Carnival’s cabins are balcony cabins.

These differences give each firm different incentives and reduce the likelihood that

they would be able to reach consensus on how to change prices.

Variability of demand also creates differences in the incentives of cruise lines.

This raises another difficulty in reaching consensus since any collusive agreement

would need to decide how to react to unanticipated changes in demand. If demand

falls, the firms will need to decide when to cut prices and how far. Furthermore,

since demand is unlikely to fall evenly, it is unlikely that the firms could reach

consensus ahead of time on how to react to the many different ways that demand

could change. Since the demand changes are uneven, the firms would also have

different incentives to deviate from the original collusive arrangement.

3. SPECIFIC ANALYSES RELEVANT TO ASSESSMENT OF THE POTENTIAL FOR

COORDINATED INTERACTION EFFECTS ON PRICE ARISING FROM THE

PROPOSED MERGERS

We conducted many different empirical analyses to determine whether the market

conditions were conducive to coordinated interaction on price, either before or after

the merger.60

These analyses often shed light on more than one of the above elements. Some

examples of these analyses are presented below.

A. Head-to-Head Cruises

We conducted many of analyses of the prices and “fill-rate” over the booking cycle

of head-to-head cruises, i.e., specific cruises of the four major competitors that had

similar ships on these cruises, leaving on the same day with approximately the same

itinerary. Figure 2 provides one example of this analysis. The lines track average

prices each month (the months are “months before sailing”) of the booking cycle

60 We describe some of those analyses in what follows, including some examples. Although we

had more than 100 gigabytes of data, the data were quite complex (involving transactions data files

from a number of companies), and the market setting greatly added to the complexity. There was a

fundamental tradeoff between taking account of very important market complexities and the complexity of the data and the utility of simple (or complex) regression models. Although we performed

various regression analyses, we found that for the purpose of assessing the potential for coordinated

interaction in this complex market setting, relatively straightforward data analyses such as cross-tabs,

summary statistics, and innumerable graphical depictions of the data were generally the most useful.

However, we only had a few months to develop data analyses during the period of the investigation.

(This is a fundamental issue for FTC economists: the need to develop with useful, reliable analyses

using very messy data in a complex setting under tight time constraints). We hope that this paper will

stimulate further ideas on quantitative analyses that can be useful in the analysis of the potential for

coordinated effects arising from a merger.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 145

Figure 2. Average gross per Diem and bookings by month prior to sailing for four ships

departing the same port on the same day sailing similar itineraries (category X cabins).

for a specific cabin type and the bars plot the sales for each month. For example,

the average price per day for ship A for passengers that purchased their ticket five

months prior to sailing was just over $125, and 10% of the passengers on that

sailing purchased their tickets that month. Figure 2 shows that the pattern of prices

and booking is quite different across the head-to-head cruises.

It is quite striking how relatively unrelated are these head-to-head prices. These

same patterns occurred whether regardless of the number of competitors with headto-head sailings. This analysis indicates that pricing decisions for an individual

sailing are not primarily driven by competitors’ pricing. Given the details of the

generation of sales, this is not surprising. Cruises are sold by travel agents, and

across most of the country. Prices differ to some extent across some locations at

a given time (but with no consistent pattern over different cruises or seasons). A

given cruise line may be working with travel agents in Cleveland in a given week

or month to push sales, whereas a competing cruise line with a head-to-head cruise

might be working with travel agents in Atlanta.

What we found from our many empirical analyses of transactions prices was

consistent with what we learned from the cruise lines documents and executives:

Pricing decisions during the booking cycle are determined by a number of complex

factors. Finally, we also ran regression models to test more systematically whether

prices on individual sailings reacted to prices on other sailings of similar cruises.

The approach was to model the relationship between price changes for a particular

sailing and the competitor prices as well as other factors such as how full the ship

was at the time relative to historic levels. The results indicated that competitors’

prices did not have a significant impact on prices for individual sailings. The regresCase 1:20-cv-22945-RNS Document 285-23 Entered on FLSD Docket 04/25/2022 Page 26 of

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sions indicated that pricing during the booking cycle was very difficult to explain

or predict. For example, there was not a strong, consistent relationship between

prices and fill rates.

This suggests that the incentives faced by various competitors at any point in

time with regard to pricing would differ, making coordination quite difficult because of problems in achieving consensus, the great complexity of pricing, and

lack of transparency. Figure 2 and many similar analyses also indicate the relative

lack of importance of head-to-head competition in pricing, which, itself, raises

questions about the importance of the loss of head-to-head competition on pricing

between the parties to the merger. Put simply, on any given itinerary and date

of departure, the competing cruise lines are trying to fill up their ships over the

booking cycle, and competitors’ prices are just one factor influencing how any

particular cruise line is going to price or change its prices over the booking cycle.

B. Similar Cruises of the Same Company

In another set of analyses, we looked at the pattern of prices over the booking

cycle of what appeared to be similar cruises of the same cruise line. For example,

one analysis looked at whether the same ship sailing on successive weeks had

similar pricing patterns. Figure 3 provides an example of this type of analysis.

This chart represents prices and sales for four individual cruises on the same ship

sailing similar itineraries in consecutive weeks. As in Figure 2, the lines plot the

average prices each month before sailing for one category of cabin, while the bar

charts represent the sales during that month. Figure 3 demonstrates that the pattern

of prices and bookings varies significantly across these four proximate sailings.

This analysis shows that similar sailings cannot be grouped together to reduce the

complexity of pricing in the cruise ship industry.

C. Brochure or “Early” Price Theories

The number of prices and the complexity of coordination could be reduced if there

was a predictable distribution of discounting off some set of transparent “early”

prices. One problem with this (and most theories of targeted price discrimination) was that most early bookings cancel without penalty. Consumers can and

do arbitrage over time, and the cruise lines are quite cognizant of this fact.

One potential theory we pursued was whether prices could be elevated if there

was some sort of tacit coordination with respect to brochure prices61 and if later

transactions prices were significantly related to brochure prices. There were a number of issues in testing this theory. First, even early bookers typically pay less

– often significantly less – than the brochure prices. Second, it is not clear how

the merger would affect the ability to coordinate these prices. If competitors were

“signaling” through pre-season brochure prices, why would the merger change

anything? In any event, the above analysis shows that this theory was unlikely

61 Brochures are typically produced prior to the beginning of the booking cycle.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 147

Figure 3. Average gross per Diem and bookings by month prior to sailing on similar itineraries

for four consecutive weeks (category X cabins).

to be viable since the overall distribution of prices varied so much from sailing to

sailing and therefore was not correlated to brochure prices.

After rejecting a brochure price theory, we turned to an “early” price theory.

The idea here was that transactions prices early in the booking cycle might provide

some sort of “anchor” for later prices. To examine the relationship between early

and later prices,62 we analyzed transactions prices for consecutive sailings of the

same ship, as well as the sailings of the same ship in the same week in consecutive

years, to see if the distribution of “discounts” off the “early” prices were consistent.

Figure 4, which is one example, demonstrates that the relationship between early

and later prices shows no stability over four consecutive sailings of the same ship

on similar itineraries. The figure shows the percentage of passengers for a single

cabin type that purchased tickets at various levels of discounts.63 Figure 5, which

is one example, demonstrates that the amount of “discounting” varied significantly

during the same week in three consecutive years. The absence of consistent patterns

or numbers of people paying the “early” price led us to reject the early price theory.

D. “Early” versus “Late” Bookings

Another theory of how the firms could coordinate to increase prices to a subset of

consumers was that firms could increase prices to passengers that booked their

cruise early.64 The logic was that passengers that booked early could be more

62 We used various definitions of “early” prices.

63 These “discounts” were rounded to the nearest 5%. Some passengers paid “premiums” relative

to “early” pricing on some sailings.

64 A significant issue with this theory was that there were usually no cancellation penalties for

early bookers. Thus, the cruise line would have to be able to keep early bookers from “rebooking” to

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148 MARY T. COLEMAN ET AL.

Figure 4. Distribution of passengers paying rounded percentage of “early” price for four

consecutive sailings of ship A, for a 7 day cruise, category 1 cabins.

Figure 5. Distribution of passengers paying rounded percentage of “early” price, for three

identical sailings of ship A, in three consecutive years, category 1 cabins.

inelastic since they wanted to make sure that they got tickets for their desired

vacation. One problem with this theory was the absence of cancellation penalties so that arbitrage would be a significant issue. This strategy would require the

firms to lower prices later in the booking cycle if the firms still attempted to sail

full. Increasing the price early could drive some passengers out of the market, but

the lower prices. This might occur if information on lower prices were not readily available, if there

were some cost to passengers of waiting to book (such as lower likelihood of obtaining a preferred

cabin), or if lower prices were offered only to passengers that were booking geographic areas where

there were low current booking rates.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 149

Figure 6. Distribution of percent of capacity filled at 120 days before sailing across all sailing.

combined with increases in discounts later on would also give passengers an added

incentive to book closer to sailing. Pushing passengers to book later would also

increase the uncertainty that the firms face with respect to what the actual demand

is for their cruises.

One analysis that we did to see if this theory was plausible was to examine

average prices early and late, as well as the number of passengers that booked

in these periods. If the pattern of discounting and the number of passengers that

booked early versus late was fairly consistent, then coordination might be possible. However, the number of passengers that booked early varied dramatically.

As demonstrated in Figure 6, the number of passengers that booked more than 120

days prior to sailing varied from 0% to 100%. For example, the chart shows that

for 7% of sailings, 45% of passengers booked at least 120 days prior to sailing,

while for 3.5% of sailings, only 20% of passengers booked at least 120 days prior

to sailing. Since the natural variation in the number of passengers is this high, there

does not appear to be a predictable group of passengers that will book early that

could be discriminated against. Furthermore, this variation in the number of passengers that book early will make it very difficult for a cruise line to determine if its

ship is suffering reduced demand due to normal variation or due to its competitors’

cheating and lowering early fares.

4. PRICE COORDINATION CONCLUSIONS

The many empirical analyses we conducted demonstrated that there was very substantial unsystematic variation in transactions prices that makes the achievement

of the required consensus, detection, and punishment required for a viable coordinated interaction theory very difficult. Reducing the number of competitors

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150 MARY T. COLEMAN ET AL.

is unlikely to change this outcome. Not only is the demand for cruises (across

the season and across any particular booking cycle) variable, demand does not

appear to vary evenly across firms, or even across sailings of the same ship or cruise

line. Indeed, the demand for individual cruises appears to be highly idiosyncratic.

As shown in Figure 2, prices for cruises that one would expect to be very close

substitutes do not appear to be highly correlated. Therefore, if a company sees that

its sales on a particular voyage are lower than expected, it may be very difficult to

determine whether the lower sales are due to a competitor cheating on the collusive

agreement or the reduced sales are due to some idiosyncratic change in demand.

As a result, a firm’s own sales cannot be used to detect cheating.

VIII. Potential Competitive Effects: Capacity Coordination

1. OVERVIEW

In addition to considering whether coordination directly on price was likely, we

considered whether capacity coordination was feasible as a means to increase

prices currently or at some point in the near future. That is, could the major cruise

lines reduce capacity and cause prices to rise either by reducing future capacity

additions or repositioning current capacity? Several elements are relevant to both

a future capacity reduction theory or a repositioning theory. First, transparency is

not as significant an issue. New ship orders and ship itineraries are announced well

in advance, and the information about such orders and itineraries are readily available. Thus, firms would likely be able to detect deviations from the coordination

outcome.

Second, as discussed previously, demand as a whole for cruising appears to be

relatively elastic (with a best-estimate elasticity of at least −2). Thus, a significant

amount of capacity would have to be removed to have a meaningful impact on

pricing. This means reducing capacity by a sufficient number of ships to cause

prices to increase significantly (likely at least 15 ships averaging 1500 passengers

to have a 5% impact). Determining exactly how such a reduction would occur and

in what trades and by which companies would be complex.

2. FUTURE CAPACITY REDUCTION THEORY

An important issue in assessing whether capacity coordination with regard to future capacity reductions was likely was to consider whether firms would have the

incentive collectively or individually to reduce capacity in the foreseeable future.

Capacity had been expanding in the industry at a rapid pace with limited impact on

price, and there were significant new capacity expansions on the way. In addition,

new ships with expanded amenities provided news for the industry and helped to

increase demand. These factors suggest that continued expansion, at least in the

near term, was likely to be profitable for the industry.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 151

To address the incentives of cruise firms to expand, we developed pro forma financial models for the profitability of adding a new ship for the industry as a whole

and for individual cruise lines, taking into account the impact on pricing from

existing ship orders and the cannibalization effect on pricing from the addition of a

ship. As inputs into this model, we used financial data on revenues and costs from

actual experiences of new ships in the recent past and assumptions on the impact

of additional capacity on prices. That is, we adjusted the revenues from the actual

experience of previous new ships downward to take into account that the possible

new ship under consideration would be launched when there was substantial other

new capacity in the market. We also subtracted from the new ship’s revenues the

loss in revenues for other ships owned by the firm under consideration (or all other

ships if we looked at the industry as a whole) caused by the addition of the capacity

of the new ship.

Our analysis showed that adding a new ship was profitable not only for individual firms in the industry but for the industry as a whole.65 While clearly at some

point, new ship additions would not be profitable for the industry, this analysis suggested that the current marginal incentives are to add capacity. Thus, firms would

have a substantial incentive to cheat on any coordination scheme, particularly since,

as noted, punishment would be difficult (and not very timely) and building new

ships is a way of differentiating oneself from competitors.66

In addition, given the long-term nature of the theory of competitive concern,

entry and expansion by the fringe (which includes, among others, Disney) was

an important issue, particularly since reducing future ship orders would release

space at shipyards for other firms. Smaller cruise line competitors have added

new ships and have plans for additional expansion. In addition, cruise lines that

had traditionally targeted European passengers had announced plays to seek more

North American passengers, not only when they sailed in the Caribbean but also

when they sailed in Europe. Expansion or entry would only undermine a coordinated outcome; even if such entry or expansion could not entirely offset a capacity

reduction by the main cruise lines, it would make a reduction less profitable and

thus coordination less stable.

Fulfilling the punishment prong of the consensus/detection/punishment requirements is problematic for long-lived capacity additions. Finally, this theory

65 We have not provided details of our analysis because it contains confidential information that

cannot be revealed.

66 We also analyzed the commitments to new capacity that existed, whether such commitments

could be modified, and when the impact of capacity coordination (if it were to occur) would happen.

We found that there were substantial commitments to new capacity that would be coming in the next

several years and more were announced during the course of our investigation. These commitments

would be difficult to cancel. Thus the theory would involve a reduction in orders in the future for

ships not yet planned and that would not be launched for at least 4–5 years. Moreover, to have a

significant impact on price, several fewer new ships would have to be ordered, further making it

difficult to achieve a coordinated outcome. Any such theory was considered far too speculative to

provide the basis for challenging the merger.

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anticipates an effect in the future when ships not currently under order would have

been built but for the hypothesized coordination, come on line, and affect pricing.

The farther in the future is the potential effect, the more speculative becomes the

argument.

3. CAPACITY REPOSITIONING THEORY

The capacity repositioning theory considered whether the major North American

cruise lines would move capacity out of North America (to Europe or Asia) to

target non-North American passengers, thus raising prices in North America. As a

starting point, any such repositioning would be very complex as it would involve

coordination over which ships to move from which trades and to where. Given that

a significant number of ships would have to move, accomplishing this would not

be easy. However, abstracting from these issues, we tried to assess whether such

repositioning would be profitable.

To do so, we conducted a variant of a critical loss analysis. That is, we modeled

the net impact on profits from moving ships, determined by (1) the gain in profits

on the ships remaining in North America; (2) the lost profits on the ships moved

(taking into account the impact on prices at the new location of adding significant

new capacity); and (3) the lost profits on ships already in the area where the repositioned ships will be moved. This analysis first assumed no repositioning of ships

by other cruise lines back to North America.67 The important components for this

analysis included: (1) the number of ships that would have to move to achieve a

small but significant price increase; (2) the margins in the two areas currently; (3)

the size of the capacity increase in the new area that would result from moving

ships into that area; and (4) the impact of this capacity increase on prices in that

area.

Our analysis showed that a repositioning that would have a meaningful impact

on price in North America would not be profitable.68 There are several reasons why

this is so. For instance, at least nine average size ships69 would have to move to result in a 5% price increase. Second, North American capacity is much greater than

capacity elsewhere. It is approximately 21

2 times greater than capacity in Europe

and over ten times greater than capacity in Asia. Thus a 10% reduction in capacity

in North America equates to a 25% increase in capacity in Europe or over a 100%

capacity increase in Asia. Even if we assume that margins and elasticities in North

America, Europe, and Asia are the same currently, such a movement would result

in a substantial reduction in margins in these areas – over 12% for Europe and over

50% for Asia. Finally, the major North American cruise lines already have (as a

67 We also assessed the impact of such repositioning.

68 Again, we do not provide details of this analysis because it incorporates confidential information.

69 The average ship in the North American fleet carries 1681 passengers. Using an elasticity of

−2, a 5% price increase would require a 10% capacity reduction, or 15,800 berths.

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ECONOMIC ANALYSES OF MERGERS AT THE FTC 153

group) significant capacity in Europe and Asia. Thus, reducing margins in those

areas not only affects the profits of the ships to be repositioned but also the profits

of ships already in those areas. Moreover, the ownership of capacity varies across

the cruise lines, and thus the incentives for repositioning capacity will differ. This

result does not indicate that firms will never move ships among their lines – they

will seek what look to be the most profitable locations for their ships. However, it

is unlikely that firms could profitably coordinate to reposition ships to achieve a

meaningful price increase in North America.

Making repositioning more unlikely is the ability of firms to expand by building

more ships or European firms to reposition their own ships. Most European lines

already have a number of North American passengers on their existing itineraries.

They could undermine a coordination outcome by targeting more North American passengers and sailing on more North American itineraries. These types of

transfers have occurred in the past. For example, Star has transferred ships from

Star, its Asian cruise line, to Norwegian, its North American cruise line.70 Royal

Olympic Cruise Lines has also moved some of its ships to North America and

attempted to market them to North American passengers. In addition, such firms

(as well as smaller North American firms) could build more ships and undermine

the coordination. Moreover, even the members of the coordination group could

undermine the coordinated outcome through building new ships and putting them

in North America.

IX. Conclusion

This paper should provide a better understanding of the sorts of analyses that

FTC economists conduct in connection with FTC merger investigations.71 The

70 The Norwegian Sun and the Norwegian Dawn were originally part of the Star Cruises fleet,

which is marketed to Asians, but were transferred to the Norwegian fleet, which is marketed to North

Americans, after Star purchased Norwegian in 2000. After September 11, Star cancelled the transfer

of the Norway from the Norwegian fleet to the Star fleet since the Asian market was weaker than

the North American market. Star was also going to transfer a smaller ship to its Orient line, which is

marketed to North Americans, but the net effect was to keep capacity in the North American market

that it had planned to move to the Asian market.

71 The cruise ship investigation demonstrated how cooperation on data issues can be beneficial to

the investigation. Working with the parties to see what types of data are kept, what format is easiest

to produce the data, and what format the Commission could receive the data, helped ease the data

requests in this investigation. Without the detailed transactions level data submitted early in the investigation (well before compliance with the FTC’s second request), many of the analyses presented

here would not have been possible before the Commission needed to make a decision. Negotiating

the data requests also helped create a dialogue about economic analyses between the parties and the

Commission staff as the Commission staff attempted to explain why certain types of data would be

useful, and the parties attempted to explain how they use the data in the ordinary course of business.

Furthermore, since both sides were working from common data, later substantive discussions were

more useful. (See http://www.ftc.gov/be/bestpractices.pdf and http://www.ftc.gov/be/ftcbebp.pdf for

a discussion of suggested best practices).

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investigation concluded that cruise ships would be a novel and complex product

market. Furthermore, to support the market, the hypothetical monopolist needed

to be able to price discriminate. While a cruise ship product market would be

highly concentrated post-merger, these product market weaknesses affected the

assessment of potential competitive effects of the proposed mergers – particularly

since the evidence rejected the viability of a unilateral effects theory. Put simply,

although the product market was based on a presumption that a monopolist could

successfully engage in anticompetitive price discrimination relative to the status

quo, this presumption was not supported for an industry that would have three major and a number of smaller competitors, post-merger. A large number of analyses

of voluminous transactions data, along with a great deal of qualitative evidence, led

to a conclusion that the mergers were not likely to lead to anticompetitive effects

via coordinated interaction either with respect to prices or capacity.

More generally, there is much more work to be done by economists to develop

reliable useable analyses – particularly quantitative analyses – for the assessment

of the potential competitive effects of mergers. Another important line of research

is to conduct retrospective analyses of past mergers in order to assess the efficacy

of past enforcement decisions. FTC economists are conducting a number of such

analyses.

References

Carlton, Dennis W., and Jeffrey M. Perloff (2000) Modern Industrial Organization, 3rd edn. Reading,

MA: Addison-Wesley.

Church, Jeffrey, and Roger Ware (2000) Industrial Organization: A Strategic Approach. Boston:

Irwin McGraw-Hill.

Dick, Andrew R. (2002) ‘Coordinated Interaction: Pre-Merger Constraints and Post-Merger Effects’,

http://www.crai.com/Agenda/Dick.pdf.

Grimes, Warren S., and John E. Kwoka (2003) ‘A Study in Merger Enforcement

Transparency: The FTC’s Ocean Cruise Decision and the Presumption Governing High Concentration Mergers’, The Antitrust Source 2(5), 1–14; available at

http://www.abanet.org/antitrust/source/may03/metstudy.pdf

Harris, Barry C., and Joseph J. Simons (1989) ‘Focusing Market Definition: How Much Substitution

is Necessary?’, Research in Law and Economics, 12, 207–226.

Katz, Michael, and Carl Shapiro (2003) ‘Critical Loss: Let’s Tell the Whole Story’, Antitrust, 17,

49–56.

Kreps, David M., and Scheinkman, Jose’ A. (1983) Quantity Precommitment and Bertrand Competition Yield Cournot Outcomes’, The Bell Journal of Economics, 14, 326–337.

Langenfeld, James, and Wenqing Li (2001) ‘Critical Loss in Evaluating Mergers’, Antitrust Bulletin,

46, 299–337.

O’Brien, Daniel P., and Abraham L. Wickelgren (forthcoming) ‘A Critical Analysis of Critical Loss

Analysis’, Antitrust Law Journal.

Scheffman, David (2002) ‘Cruise Investigation: Empirical Economic & Financial Analyses’, available at http://www.ftc.gov/speeches/other/021024mergeenforcement.htm.

Scheffman, David (2003) ‘Sources of Information an Evidence in Merger Investigations: An FTC

Economist’s View’, available at http://www.ftc.gov/speeches/other/sourcesofinfobrussels03.pdf.

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Scheffman, David, and Mary Coleman (2003) ‘Quantitative Analyses of Potential Competitive Effects from a Merger’, George Mason University Law Review (forthcoming)

(http://www.ftc.gov/be/quantmergeranalysis.pdf).

Simons, Joseph J. (2002) ‘Merger Enforcement at the FTC’, available at

http://www.ftc.gov/speeches/other/021024mergeenforcement.htm.

Werden, Gregory J. (1998) ‘Demand Elasticities in Antitrust Analysis’, Antitrust Law Journal, 66,

363–414.

Woodbury, John R., and William H. Page (2003) ‘Paper Trail: Working Papers and Recent Scholarship’, The Antitrust Source, 2(5), 1–5; available at

http://www.abanet.org/antitrust/source/may03/papertrail.pdf

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