# Unified Container Shipping Industry Data From 1966: Freight Rate, Shipping
Quantity, Newbuilding, Secondhand, and Scrap Price††thanks:  Declarations of
interest: none

Takuma Matsuda Suguru Otani Faculty of Commerce, Takushoku University. Email:
<EMAIL_ADDRESS>of Economics, Rice University. Email:
<EMAIL_ADDRESS>
( First version: November 29, 2022
Current version: )

###### Abstract

We construct a new unified panel dataset that combines route-year-level
freight rates with shipping quantities for the six major routes and industry-
year-level newbuilding, secondhand, and scrap prices from 1966 (the beginning
of the industry) to 2009. We offer detailed instructions on how to merge
various datasets and validate the data’s consistency by industry experts and
former executives who have historical knowledge and experience. Using this
dataset, we provide a quantitative and descriptive analysis of the industry
dynamics known as the container crisis. Finally, we identify structural breaks
for each variable to demonstrate the impact of the shipping cartels’ collapse.

Keywords: container shipping industry; exemption agreement; container crisis;
shipping cartel; container freight rate

“When we think about technology that changes the world, we think about
glamorous things like the Internet. But if you try to figure out what happened
to world trade, there is a strong case to be made that it was the container …”

– Krugman, Paul.111Citigroup Foundation Special Lecture, Festschrift paper in
honor of Alan V. Deardorff, University of Michigan IPC working paper 91, 2009

“[W]ithout [the container], the tremendous expansion of world trade in the
last forty years—the fastest growth in any major economic activity ever
recorded—could not possibly have taken place.”

– Drucker, Peter F.222Innovation and Entrepreneurship, Butterworth-Heinemann,
2007 (p.28)

##  1 Introduction

###  1.1 Research background, motivation and purpose

Container shipping is a crucial component of global trade that has
revolutionized the world. According to IHS Markit and Descartes Datamyne,
container shipping accounts for 45.4% of amount-based imports to the U.S.,
21.3% of amount-based exports from the U.S., and 10.12% of quantity-based
world trade are shipped in 2021. Additionally, the container shipping industry
offers a fascinating opportunity to explore industry dynamics. Since the
industry began global shipping operations in 1966, the market’s initial state
can be determined with a significant entry and exit of firms. Furthermore,
many countries have competition laws that exempt international cartels and
consortia, which are called “shipping conferences” and “shipping
alliances”333Transport Policy Council (2007) of the Ministry of Land,
Infrastructure and Transportation in Japan defines a shipping conference as an
agreement on freight rates and other business matters to restrain competition
among container shipping lines along the same route. A consortium is a
technical agreement between several shipping lines to form a group and operate
a joint service for the diversification of services and cost reduction in the
liner service. Consortiums include alliances that are widely used.  in the
shipping industry.444There is an important difference between shipping
conferences and alliances: conferences are organized by specific routes and
directions, while alliances are formed globally. There may exist one
conference covering trade on the Transatlantic route and another covering
trade between Northern Europe and the U.S. Gulf ports. In addition, firms do
not always participate in conferences on all routes and directions they serve.
Thus, conferences are heterogeneous in their structure and membership. Despite
its significance, there is a lack of a panel dataset for the route-year-level
freight rate and shipping quantity in the container shipping industry,
particularly for the years 1966 to 1990, which limits quantitative research
during this period555As other related studies focus on the container freight
rate panel data, Luo et al. (2009) use shipping demand and freight rate data
between 1980 and 2007. As shipping demand, they used the world container
throughput reported in the Drewry Annual Container Market Review and Forecast.
The container freight rate is calculated as the weighted average of the
Transpacific, Europe-Far East, and Transatlantic trades from the same data
source. Due to data limitations, they calculated the missing period
(1980–1993) from the General Freight Index in the Shipping Statistics Yearbook
2007, using a simple statistical equation between the container freight rate
and the general freight index from 1994 to 2008.. This study provides a
unified dataset based on published books and publicly available data sources
to the extent possible, combining route-year-level data with new industry-
level data regarding shipbuilding, secondhand, and scrap prices.666The data
sources are listed in Appendix B.

To construct the freight index, we adopted the tractable imputation approach,
which involves linking multiple data sources that overlap information for some
years. This approach is simpler than formal but complicated processes or
estimation approaches that assume the AR(1) process under stationary
assumptions (Jeon 2022). We also validated our approach by presenting
interview-based evidence from ex-executive officers of shipping companies.
This confirms that our Twenty-foot Equivalent Unit (TEU)-based price data
provide a reasonable benchmark measure, even though container freight rates
were not determined by container units in the 1970s.

Using our new dataset, we have conducted an analysis of the historical
shipping price reductions in the 1980s, known as the “container crisis”
(Broeze 2002), by implementing the unknown multiple structural breaks test
(Bai and Perron 1998, 2003). It is anecdotally known that the crisis was
triggered by two events: (1) the withdrawal of Sea-Land, which was the biggest
cartel member from shipping cartels in 1980, and (2) the enactment of the
Shipping Act of 1984. The first event changed the market share of shipping
cartels, whereas the second event neutralized the shipping cartels. We also
applied the test to industry-year-level newbuilding, secondhand, and scrap
prices to determine the relationship between shipping markets and shipbuilding
markets.

Based on the test, we found that the container crisis occurred on all six
routes by 1980, which was triggered by the withdrawal of Sea-Land, although
non-U.S. routes reacted earlier than U.S. routes. Additionally, we found that
industry-year-level newbuilding, secondhand, and scrap prices displayed a
relatively stable trend during the container crisis, unlike shipping prices.
We interpret these differences as naturally capturing the distinctions between
shipping markets with shipping conferences and shipbuilding markets without
cartel groups. Thus, the container crisis was a specific event in the shipping
market.

###  1.2 Literature review

This study contributes to two strands of the literature: the historical
connection to the recent growing empirical research on the shipping industry
and the effect of an explicit cartel on the price in the shipping industry.

First, this study provides the necessary data to connect the history of the
container shipping industry from its beginning to its development after 2000,
a topic that has gained attention in the industrial organization literature
(Aguirregabiria et al. 2021). The most relevant paper in this regard is Jeon
(2022), in which she examined the relationship between demand uncertainty and
firm-market-year-level investment decisions using container shipping demand
and freight rate data for the years 1997 to 2014. To facilitate her learning-
based model, she needed to obtain the initial prices and demand in the
container industry. However, due to data limitations, she had to resort to
imputation and truncation approaches for missing shipping demand data from
1966: Q2 to 1996: Q4.777On cartel issues in a similar industry, the most
relevant paper is by Asker (2010). He studied how the presence of a cartel
affects market conduct following its dissolution and how the dissolution might
be affected by the obligations imposed on firms that seek leniency in the
tanker shipping market between 2001 and 2002. Kalouptsidi (2014), Brancaccio
et al. (2020), and Greenwood and Hanson (2015) investigated the bulk shipping
industry after 2000. Bai and Li (2021) studied the tanker market during
2017-2020 and investigated how the imbalance between the demand for and the
supply of shipping services determines congestion. Although these industries
are closely related to the container shipping industry, each of the industries
is characterized differently because the market structure and competition are
different. In addition, Kalouptsidi (2017) and Barwick et al. (2019) studied
the shipbuilding industry, which is an upstream industry for the container and
bulk shipping industries. These papers rely on the use of Clarksons Research
database and focus on the period after 2000. In the literature on
international trade, Bernhofen et al. (2016) use country-level panel data
regarding containerization adoption for the period 1962–1990. They focused on
the effect of containerization adoption on the trade quantity; therefore, they
refer to the Containerization International Yearbook only for obtaining the
first presence of container technology in each country. Rua (2014) added port-
level data to their study and investigated the diffusion of initial adoptions
of containerized transportation. Coşar and Demir (2018) exploited rich Turkish
export data and examined modal choice between containerization and breakbulk
shipping. Our study overcomes this limitation and complements the findings of
previous studies.

Second, this study examines the effect of explicit shipping cartels on
shipping prices.888The ongoing study of one of the authors of this paper
investigates the effect by constructing a structural model and focuses on the
shipping conferences as a single explicit cartel entity, and departs from the
traditional focus on tacit collusion in the literature, e.g., Porter (1983),
Bresnahan (1987), Miller and Weinberg (2017), and Byrne and De Roos (2019).
The institutional background is similar to Igami (2015)’s findings. He studied
the impact of market power on international coffee prices and evaluated the
impact of a cartel treaty on coffee prices and its global welfare consequences
under counterfactual competition regimes, that is, collusion versus
Cournot–Nash in a single homogenous good market. Shipping cartels have been
recognized in survey papers, such as Levenstein and Suslow (2006) and Asker
and Nocke (2021). Some studies, such as Morton (1997) and Podolny and Morton
(1999), examine specific shipping cartels in the U.K. in the 1800s. The most
relevant studies are Wilson and Casavant (1991), Pirrong (1992), and Clyde and
Reitzes (1998). Wilson and Casavant (1991) provided evidence of regime change
by the Shipping Act of 1984 using data on quarterly freight rates and shipping
quantities of five selected commodities only on the Transpacific route.
Pirrong (1992) tested the model prediction of the core theory surveyed in
Sjostrom (2013) using data from two specific trade routes between 1983 and
1985. Clyde and Reitzes (1998) studied the relationship between market power
and the market share of shipping conferences after the act. However, they did
not exploit cross-sectional variations, especially between non-U.S. and U.S.
routes. Our study is the first empirical research to detect the effect of
shipping cartels on the six main routes after global containerization in the
1970s, and it overcomes data limitations to complement the findings of
previous studies.

The remainder of this paper is organized as follows. Section 2 summarizes the
data and institutional background of the container shipping industry. Section
3 presents interview-based evidence from an ex-chairperson and an ex-vice
chairperson to demonstrate the consistency of our recovered data. Section 4
implements structural break tests to detect price reductions in market
variables. Finally, Section 6 presents our conclusions, and Appendix B
presents the details of data construction.

##  2 Data and Institutional Details

We provide details of the data source in Section 2.1. Next, we provide
graphical interpretations in Section 2.2 and summary statistics for the
variables in Section 2.3. We also introduce institutional details. For
clarification, in this industry, a market refers to a non-directional location
pair. For instance, if a firm operates a container ship in the eastbound of
the transpacific, it should also operate the ship in the westbound. A route
refers to a directional round-trip between two locations. For example, both
the westbound and eastbound of the transpacific. An industry refers to the
entire market consisting of all six routes.

###  2.1 Data source

We constructed route-year-level and industry-year-level data for the container
shipping industry.999Based on the firm-level data, each route is divided into
conference and non-conference routes. For example, the Transatlantic eastbound
conference route is a single route and the Transatlantic conference market is
a single market. A conference market is a market where all conference firms
conducted collusive behavior under the shipping conferences before the
Shipping Act, but have competed since the act, whereas a non-conference market
is a market where all non-conference firms have competed throughout the whole
period. In the interview with ex-practitioners in shipping companies, they
told that container freight rates for nonmember carriers are 20% to 30% lower
than conference firms on the same routes. However, as far as we know, there
was no data available on the trends in freight rates offered by the non-
conference carriers. In addition, although we checked The Japan Maritime
Daily, the newspaper of the maritime industry, we could not find any articles
that continuously reported on the level of freight rates offered by the non-
conference carriers.  First, we collected route-year-level data on container
freight rates and shipping quantities. Collecting data, particularly before
1994, was not trivial because no single data source covers the period from
1966 to 1993. Thus, we needed to carefully combine data from multiple sources
carefully.101010For reference, we merge “Issues of Our Ocean Shipping”
(“Wagakuni no Gaikou Kaiun Ni Tsuite,” in Japanese), Global Container Markets
Drewry Shipping Consultants, Review of Maritime Transport, Containerization
International 1973, World Sea Trade Service, Container transportation cost and
profitability 1980/2000, The Container Crisis 1982, World Container Data 1985,
and World’s sea trades. Then, we converted merged data into TEU-based data. In
Appendix B, we provide the data source and a detailed guide with some
assumptions on data construction for each container freight rate and shipping
quantity on the six major routes: mainhaul and backhaul (separately) on the
Transpacific (Asia and North America), Transatlantic (North America and
Europe), and Asia-Europe routes. Finally, we used price and quantity data from
the six routes between 1966 and 2009. The price was adjusted according to the
CPI in the U.S. in 1995. To check the accuracy and validity of our data, in
Section 3, we provide interview-based evidence on the consistency of our
recovered data with the historical experience of industry experts, Akimitsu
Ashida and Hiroyuki Sato.

Second, we utilized industry-year-level data for newbuilding, secondhand, and
scrap prices.111111For reference, we merged Review (1971-1998) and Lloyd’s
Shipping Economist (1983-1990). Then, we converted merged data into TEU-based
data. Specifically, we used newbuilding and scrap prices per TEU between 1966
and 1998 and the secondhand price per TEU between 1968 and 1998. These prices
were adjusted to the CPI in the U.S. in 1995.

It is worth noting that recent data on newbuilding, secondhand, and scrap
prices after 1998 and shipping prices and quantities after 2009 are available
for purchase from companies such as Clarksons and IHS Markit. While our data
can be merged with proprietary data, this study does not include such data in
order to provide public access to our data.

###  2.2 Graphical interpretation

####  2.2.1 Route-year-level shipping price and quantity data

Figure 1 illustrates the nonstationary trends in container freight rates and
shipping quantity between 1966 and 1990. The container freight rate decreased
with fluctuations, and suddenly dropped significantly, with the transition of
freight rates on the Asia-Europe eastbound and westbound routes being more
unstable than those on Transpacific and Transatlantic routes in the 1970s and
1980s. This was mainly due to the reopening of the Suez Canal in 1976, which
increased the supply of container shipping services (Saito et al. 2022).
Additionally, freight rates for the Asia to Europe trade were higher than for
other trade routes, possibly due to the strong influence of shipping
conferences on Asia to Europe trade in the 1970s and early 1980s. The figure
shows a sharp decline in freight rates in the second half of the 1980s,
possibly because of the significant impact of the conferences’ loss of power
in the early 1980s.121212In the interview with an ex-executive of a Japanese
shipping company, he pointed out the difference between conferences.
Conferences related to Asia-Europe had a strict membership screening process,
and the number of voyages by member companies was clearly defined (closed
conference). In addition, some members in the conference pooled their freight
and then redistributed them. In contrast, the conferences for Transpacific
routes were free to join or leave (open conference), and freight pooling was
explicitly prohibited under the Shipping Act of 1916 in the U.S.

The shipping quantity on all routes increased monotonically between 1973 and
1990 due to the increase in containerized cargo and the increase in the size
of ships.131313When Sea-land began container transport services in 1966, 226
35-foot containers were deployed. In the 1970s, with the development of
international maritime container transport, container vessels began to
increase in size, with vessels of approximately 2000 TEU becoming the mainstay
of liner services. Owing to increased competition following the Shipping Act
of 1984, shipping companies wanted to introduce even larger vessels. In 1988,
American President Lines (APL) opened a 39.1-meter wide, 4300 TEU vessel, the
first container vessel that could not pass the Panama Canal. Further, in the
1990s, 6000TEU-class vessels come into the container shipping market. In
response to the rapid increase in cargo exported from Asian countries,
especially China, to Europe and the U.S., the number of vessels deployed on
the Trans-Pacific East and Asia-Europe East routes has increased exponentially
since 2000. Jeon (2022) has examined these characteristics in detail since
2000.

The enactment of the Shipping Act of 1984 in the U.S. sharply divided the
conference market regime into two periods, before and after 1984, as
illustrated by the trend of the container freight rate in Figure 1. The
Shipping Act of 1984 in the U.S. made it much easier to form shipping
conferences. As a result, after 1984, the Transpacific and Transatlantic
routes saw significant price reductions due to market competition.141414This
is consistent with an interview article to ex-executives of Japanese shipping
companies (Ishida and Sato 2006) that were in charge of container trades in
the 1980s. The change in the market regime played a significant role in
shaping the container crisis.

(a) Price

(b) Quantity

Figure 1: Trends in route-year-level shipping prices and quantities.

Note: Container freight rates before 1992 refer to conference prices. The
container freight rates after 1993 are unified prices based on conference and
non-conference prices, and the difference between them is known to vanish
because of the Shipping Act of 1984. The latter are standard data often used
in the literature, such as Jeon (2022). Prices were adjusted to the CPI in the
U.S. in 1995.

####  2.2.2 Industry-year-level newbuilding, secondhand, and scrap prices data

Figure 2: Trends in industry-year-level newbuilding, secondhand, and scrap
prices.

The data span 33 years (1966-1998) for the entire container shipping industry.
The data cover newbuilding and scrap prices between 1966 and 1998 and
secondhand prices between 1968 and 1998. All prices were adjusted according to
the CPI in the U.S. in 1995.

Figure 2 illustrates the transitions of newbuilding, secondhand, and scrap
prices. First, we observe four peaks in the newbuilding price in 1974, 1980,
1987, and 1991, indicating that the newbuilding price peaks at similar times
to the shipping price. Surprisingly, the shipping price, after adjusting CPI,
did not decrease significantly, which means that the trend of the newbuilding
price did not decrease unlike the shipping price. This is a new finding
because it is commonly known that vessels themselves were expensive in the
1970s and the shipbuilding price per TEU decreased in the 1990s due to the
gradual increase in the size of ships. We find that the increasing CPI
corresponds with a seemingly decreasing shipbuilding price in the nominal
sense.

Second, the secondhand price sharply decreased between 1974 and 1979. However,
after 1980, it remained relatively stable compared to shipping and newbuilding
prices. In the 1970s, when full container vessels started operating on liner
routes, the number of vessels was insignificant, leading to a small number of
vessels traded in the secondhand market, which resulted in more fluctuation in
secondhand prices. However, since the 1980s, the number of vessels traded in
the secondhand market has increased, leading to more stable secondhand freight
rates and a more significant correlation with new building prices.

Third, the scrap price remained stable, without significant fluctuations
relative to other price variables. Moreover, the scrap price level was smaller
than that of the newbuilding and secondhand prices because the scrap price is
linked to the input price, such as the steel price. Thus, the trend in scrap
price reflects the dynamics of the input price.

###  2.3 Summary statistics

####  2.3.1 Route-year-level shipping price and quantity data

Table 1: Summary statistics.

| N | mean | sd | min | max
---|---|---|---|---|---
Price ($ per TEU): $P_{rt}$ | 240 | 2105.35 | 1250.84 | 561.86 | 6654.79
Quantity (1 mil TEU): $Q_{rt}$ | 240 | 2.34 | 2.75 | 0.00 | 17.70
(a) Route-year-level variables (1966-2008)

| N | mean | sd | min | max
---|---|---|---|---|---
Newbuilding price ($ per TEU): $P_{t}^{new}$ | 33 | 20633.82 | 5555.70 | 13186.28 | 31966.62
Secondhand price ($ per TEU): $P_{t}^{second}$ | 31 | 18371.82 | 14502.46 | 7020.96 | 46792.94
Scrap price ($ per TEU): $P_{t}^{scrap}$ | 33 | 609.97 | 196.54 | 334.25 | 1098.38
(b) Industry-year-level variables: $(P_{t}^{new},P_{t}^{scrap})$ (1966-1998)
and $P_{t}^{second}$ 1968-1998)

Note: Panel (a) of the six routes covers a data span of 44 years (1966-2009).
The Transatlantic routes opened in 1966, Transpacific routes opened in 1967,
and Asia-Europe routes opened in 1971. The shipping prices before 1992 in
Panel(a) refer to conference prices, while the shipping prices after 1993 are
unified prices based on conference and non-conference prices. The difference
between them vanished because of the Shipping Act of 1984. The latter are
standard data that are often used in the literature such as Jeon (2022). Panel
(b) of the container shipping industry covers a data span of 33 years
(1966-1998). The data cover newbuilding and scrap prices between 1966 and
1998, and secondhand prices between 1968 and 1998. All prices were adjusted
according to the CPI in the U.S. in 1995.

Panel (a) in Table 1 presents the summary statistics of the route-year-level
variables for the shipping price $P_{rt}$ and quantity $Q_{rt}$. The data
cover the Transatlantic routes that opened in 1966, the Transpacific routes
that opened in 1967, and the Asia-Europe routes that opened in 1971.151515For
Table 1, the shipping prices before 1992 refer to conference prices, while the
shipping prices after 1993 are unified prices based on conference and non-
conference prices, while the difference between them vanished in the
Containerization International Yearbook. Thus, we observe the full history of
the conference market. On average, the shipping price was $2105.35 per TEU and
the shipping quantity was 2.34 million TEUs.

####  2.3.2 Industry-year-level newbuilding, secondhand, and scrap prices data

Panel (b) in Table 1 shows the summary statistics of industry-year-level
variables for the newbuilding price $P_{t}^{new}$, scrap price $P_{t}^{scrap}$
between 1966 and 1998, and secondhand price $P_{t}^{second}$ between 1968 and
1998. The average newbuilding price per TEU was $ 20633.82. The average
secondhand price per TEU was $18371.82, which was less than the newbuilding
price after 1971. The average scrap price per TEU was $609.97.

###  2.4 Institutional details

Here, we introduce the institutional background of the shipping conference,
the early history of the container shipping industry, and two key events
triggering the change in competition regime.

Table 2 summarizes the historical events of the liner shipping industry before
and after global containerization.

Table 2: The historical background of the liner shipping industry.

Timing / Period | Event | Related Study
---|---|---
1875 | the first liner shipping conference (The U.K.-Calcutta) established | Morton (1997)
|  | Podolny and Morton (1999)
1916 |  The Shipping Act of 1916 prohibited deferred rebate |
1918 | The end of WW1 | Deltas et al. (1999)
1936 | U.S. Maritime Commission established |
1945 | The end of WW2 |
1956 | The world’s first container ship sailed |
1961 |  The 1961 Amendment enacted |
|  Federal Maritime Commission (FMC) established |
| Technical Committee on Cargo Containers established (ISO/TC104) |
1964 | ISO adopted seven sizes of containers as ISO standards |
1966 | The first Full-container (FC) ship sailed the Transatlantic route |
1967 | The first FC ship sailed the Transpacific route |
1971 | The first FC ship sailed the Asia-Europe route |
1973 | Oil shock |
1974 | The UNCTAD Code of Conduct for Liner Conferences adopted | Fox (1992, 1995)
1980 | Withdrawal of Sea-Land from shipping conferences | Sjostrom (1989)
1983\. April | The UNCTAD Code of Conduct for Liner Conferences accomplished |
1984\. June |  The Shipping Act of 1984 in the U.S. enacted, conference breakdown | Clyde and Reitzes (1995, 1998)
|  | Wilson and Casavant (1991)
|  | Pirrong (1992)
1985.Sep | Yen appreciation due to the Plaza Accord |
1991 | Strategic alliance boom started |
1998\. Oct |  The Ocean Shipping Reform Act (OSRA) of 1998, effective in 1999 | Reitzes and Sheran (2002)
|  | Fusillo (2006, 2013)

  * a

Note: This table is based on unified survey papers such as Sjostrom (2004,
2013) and Martin (2012) and specific papers (Clyde and Reitzes 1995, 1998).
Industry and legislative changes after 1990 are beyond the scope of this
study. For reference, see Reitzes and Sheran (2002), which states that “OSRA
alters the role of the Federal Maritime Commission as a cartel enforcer. Under
the Shipping Act of 1984, all carriers, both conference carriers, and
independent carriers, had to file their tariffs with the FMC. The FMC then
policed these rates, issuing fines to carriers that engaged in secret
discounting, known as “rebating.” Under the OSRA, carriers are obliged to make
their freight rates publicly available, but the FMC’s enforcement obligations
are eliminated. OSRA’s elimination of tariff-filing requirements and rate
enforcement by the Federal Maritime Commission raises the cost of monitoring
their members’ pricing activities. (page 56).”

####  2.4.1 Shipping conferences

The world’s first shipping conference, the “Calcutta Conference,” was formed
in 1875 on the route between England and Calcutta to establish a unified
freight rate.161616In this subsection, we refer to The Actual State of
Competition in Oceangoing Shipping and Problems with Competition Policy
(“Gaikoukaiun no Kyousoujittai To Kyousouseisakujou no Mondaiten ni Tsuite,”
in Japanese) reported by Study Group on Government Regulation and Competition
Policy (2006) of the Japan Fair Trade Commission, Branch and Stopford (2013),
and Sjostrom (2013). In particular, Sjostrom (1989) discusses the economic
insights of the shipping conferences from an historical viewpoint. Morton
(1997) provide detailed historical evidence on British shipping industry
before 1900. In 1879, the Chinese Alliance, the ancestor of the Far East
Freight Conference, was formed on routes between Asia and
Europe.171717Sjostrom (2004) conducted a survey on shipping conferences, and
pointed out that systems similar to shipping conferences had existed in
Atlantic shipping and British coastal shipping before the Calcutta Conference.
The shipping conferences appeared 15 years before the enactment of the Sherman
Antitrust Act in 1890, one of the first competition laws in the modern world,
so cartels themselves were not illegal at that time. Table 2 summarizes the
history of the liner shipping industry before 2000, with related studies and
key legislative changes.

##### Internal mechanism to conference firms.

The internal mechanism of conference firms is mainly aimed at market
stabilization by controlling entry via excess capacity (Fusillo 2003),
predatory pricing (Morton 1997, Podolny and Morton 1999), price discrimination
(Fox 1992, Clyde and Reitzes 1998), and loyalty contracts (Marin and Sicotte
2003), among other things. To achieve this, shipping conferences agreed on
various matters, in addition to freight rates. The content of the agreements
covered: (1) alternatives to suppress freight rate competition among member
shipping companies, (2) alternatives to prevent shippers from moving to non-
conference shipping companies, and (3) alternatives to directly exclude non-
conference vessels.

To avoid freight rate competition, rate agreements and vessel allocation
agreements were concluded among the member shipping companies. Rate agreements
are signed by members to agree on rates for each product and to update the
rates jointly. Vessel allocation agreements adjust the amount of tonnage to be
allocated, the number of voyages, ports of call, operation schedules, and
cargo to be loaded. These features were modeled as price and quantity-fixing
cartels.181818For example, Clyde and Reitzes (1998) model the market with the
shipping conference as a collusion equilibrium.

##### External mechanism for non-conference firms.

The conference tariff rates, or freight rates, determined by these agreements
had been publicly noticed, and no entry restrictions imposed non-conference
container shipping market. The market was, however, subject to competition
from non-conference vessels and new entrants. Consequently, shipping
conferences introduced the Dual Rate System, the Fidelity Rebate System, and
the Differed Rebate System to ensure effectiveness of freight rate agreements
and prevent shippers from flowing to non-conference shipping companies that
offer lower rates than the conferences’ rates.191919In the Dual Rate System, a
shipper and a shipping conference conclude an exclusive patronage
contract/loyalty agreement and provide transportation service for the specific
route. The contract rate is lower than the spot rate on the condition that the
shipper uses only conference member carriers’ service within a specific
contract period. The Fidelity Rebate refunds a portion of the freight if the
shipper uses only the conference carriers within a specified period (4-6
months). The Differed Rebate System is also an incentive to use conference
carriers. Under the system, if a shipper had used only members’ services for a
specified refundable period (4-6 months), and if it does not use any non-
conference members’ service for the deferment period following the refundable
period, a certain amount of money is refunded upon the shipper’s request. The
refund amount was usually around 10% of the freight. Fox (1992) uses the U.S.
port pair-level data in 1977 to examine the effect of the dual rate contract
and consumer loyalty. These entry deterrents promoted the stability of freight
rates and liner services.202020For instance, Marin and Sicotte (2003) examine
the economic effects of exclusive contracts of ocean shipping cartels during
the 1950s between firms and the ultimate consumers of their product. They
record that, “During the congressional investigations of shipping conferences
in the late 1950s and early 1960s documents obtained from an ocean carrier
contained an admission that ‘the entire contract system is a fighting measure
to get rid of outside competition’ ” (p.198).

Conferences also utilized “fighting ships,” which are vessels that temporarily
put into service at a similar schedule as non-conference shipping companies
and at lower rates.212121See Marshall and Marx (2014) (page 148) and
Harrington Jr et al. (2018) for reference to put the strategy of shipping
conferences in general cartel literature. Harrington Jr et al. (2018) classify
the general response of cartels to the expansion of noncartel supply into four
strategies: takeover, starvation, coercion, and bribery. The fighting ships
are classified into coercion strategy. Fighting ships were used to force non-
conference shipping companies to leave routes, and all members shared the
associated operational losses.

Since the 1960s, the nature of shipping alliances have changed. Technological
innovation centered on containerization, and pro-competitive amendments to
shipping laws in the United States, particularly, have had an impact on the
functioning of shipping alliances and market competition in the shipping
market.

####  2.4.2 The inception of the container shipping industry

The history of container shipping began with Malcolm P. McLean, the founder of
the U.S. Land Transportation Company Sea-Land Service.222222Bernhofen et al.
(2016) and Rua (2014) explain the detailed history of the container shipping
industry from the viewpoint of the global trade and country-level development.
Levinson (2016) provides an overview of the industry with anecdotal and
qualitative evidence. The world’s first container ship sailed from the Port of
Newark, New Jersey, to the Port of Houston, Texas in 1956. The first
international container ship was employed by Sea-Land Service for the
Transatlantic Route in 1966, and for the Transpacific route in 1967. However,
for the Asia-Europe route, the first international semi-container ship,
Cornelia Maersk, was employed in 1967. The first international full-container
ship, Kamakura-maru, was delayed in 1971.

Global containerization induced several market changes between 1966 and 1990,
including transforming the cost structure, lowering barriers to entry,
stimulating the rise of non-conference shipping companies in developing
countries, shifting from “closed” conferences to “open” conferences, and
forming a consortium. Appendix A provides further details on each of these
changes.

####  2.4.3 Withdrawal of Sea-Land from shipping conferences in 1980

In the late 1970s, the increase in competition for Transpacific routes led to
pressure on shipping rates. To address this, Sea-Land introduced eight SL-7
high-speed container vessels with a speed of 33 knots. However, the high
operation costs of these vessels negatively impacted the company’s
profitability. Consequently, Sea-Land withdrew from shipping conferences to
avoid tonnage-based cargo allocation imposed by the conferences and secure
profitability. Former executives of a Japanese shipping company stated that
Sea-Land had to increase loaded cargo but could not achieve its goals without
leaving the conference that set freight rates and that it felt it had no
choice but to become a non-alliance carrier and establish its own freight rate
to retain customers (Ishida and Sato 2006).

After Sea-Land’s withdrawal from shipping conferences, shippers with contracts
with conference carriers hesitated paying the penalty to switch to Sea-Land
under the conference’s Dual Rate System. Sea-Land focused on import shippers
and intermodal cargoes not covered by the double-freight rate system. The
company also paid the freight cost of returning inland containers to the port
instead of passing them on to shippers, decreasing freight rates.

####  2.4.4 The Shipping Act of 1984 in the U.S.

In June 1984, the United States enacted the new Shipping Act as part of the
Reagan administration’s deregulation policy to allow member carriers to make
individual agreements with shippers on freight rates and services, and to
unbind shippers from shipping conferences to enable them to make more
appropriate choices in shipping companies. This drastically changed the
competition regime.232323Wilson and Casavant (1991) provide anecdotal evidence
and a case study of the effect of the Shipping Act of 1984.

The Shipping Act of 1984 included the right to Independent Action (IA),
allowing member firms to define freight rates or services that deviate from
the conference tariff rates and guaranteeing of members carriers in the
shipping conferences to set their own rates or services.

It required conferences to allow the right to form service contracts (SCs),
which are contracts in which the shipper commits in advance to load a specific
quantity or more of cargo to the shipping company during a specific period.
Under this contract, the shipping company reserves the space necessary to
carry cargo and applies discounted freight rates242424The minimum number of
containers promised by the shipper to the shipping company is called the MQC
(Minimum Quantity Commitment)..

The act explicitly prohibited the Dual Rate System and the shipping conference
lost its binding power over shippers, and individual shipping companies
frequently exercised their right to independent action, which encouraged
competition and led to a significant decline in freight rates on U.S.-related
routes.252525Japan Maritime Center (2008) pointed out that the Dual Rate
System was the most effective way in which shipping companies kept their
shippers when the conference system was functioning.

##### Stabilization agreement.

Containerization and the Shipping Act of 1984, weakened the price-binding
power of shipping conferences by increasing contracts based on IAs and SCs.
Shipping companies thus set their freight rates, leading to intense price
competition and sharp drops in Transpacific freight rates. To stabilize
shipping routes, conference shipping companies formed a “stabilization
agreement” inviting most shipping companies, including non-conference ones.

Agreements shared information on supply and demand trends and agreed
guidelines for rate restoration and surcharges, but binding power on rates.
The Transpacific Stabilization Agreement (TSA) was formed in 1989 by 13
shipping companies to stabilize shipping routes from Asia to North
America.262626TSA was dissolved in 2018.

##  3 Interviews

In this section, we provide interview-based evidence on the consistency of our
recovered data on container freight rates with the historical experience of
industry experts, Akimitsu Ashida and Hiroyuki Sato.272727We obtained
additional interview-based evidence. Mikio Tasaka, who belonged to the Nittsu
Group and worked in the U.S. in the 1980s, stated that there was no
discrepancy in the development of freight rates. In addition, Carolyn Almquist
experienced pricing and conference division in the container shipping business
at American President Lines, stated that provide a reasonable basis for
analysis. Professor Yutaka Yamamoto (University of Nagasaki), who had 20 years
of experience in the container shipping business at American President Lines,
stated that the trend was generally reasonable. We also received responses
from Kwon Oh In who worked for 40 years at Korea Maritime Transport Company, a
major Korean container shipping company. He said that our graphs seemed
convincing as a general trend of the container shipping industry during that
period.

###  3.1 Akimitsu Ashida, an ex-chairperson of Mitsui O.S.K Lines

Concerning the increase in freight rates in Transatlantic and Asia-Europe
routes in the 1980s, Mr. Akimitsu Ashida, former chairman of Mitsui O.S.K.
Lines (MOL), answered about the situation on liner routes. He served as the
company’s European Division Manager from 1985-86 and responded to our e-mail
inquiry on February 28, 2022. We asked him about his thoughts and related
memory on the figures and tables.

Regarding Shipping Quantity in Asia-Europe routes
Ashida: Unlike Transpacific routes (where U.S. Customs publishes data),
European routes did not have a system whereby customs authorities published
statistics on container transport volumes. Therefore, the FEFC did not have to
compile and notify its members of actual container transport volumes.
Consequently, it is not easy to find the data even today.

Regarding Freight Rates in Asia-Europe routes
Ashida: Freight rates were rising regularly in nominal terms. One of the
reasons was that shipping conferences had relatively strong power on Asia-
Europe routes. In addition, surcharges such as the Bunker Adjustment Factor
(BAF) and Currency Adjustment Factor (CAF) were collected without fail. Under
these circumstances, the Plaza Accord of 1985 raised the yen-dollar exchange
rate from 240 yen to approximately 140 yen. This caused dollar-based freight
rates to rise sharply, especially for cargoes originating in Japan. Non-
Japanese carriers earned even higher profits because their yen-based costs
were relatively small.

The Reason Why the Shipping Conferences Were Still Functioning on the Asia-
Europe Routes
Ashida: One reason is that there were no powerful non-conference member
shipping lines. At that time, Japanese shippers avoided non-conference members
when exporting cargo from Japan. The exports accounted for 50 % of all cargo
shipped from Asia. Therefore, the export cargo was mainly assigned to
conference member firms. This trend was disrupted by the introduction of large
newly built vessels by non-conference members from 1990 onward.

I recall that about 35 % of cargo on the Asia-Europe routes was handled
through forwarders, unlike the Transpacific routes. Furthermore, the Asia-
Europe routes were less active in discount negotiations than the Transpacific
routes because the inland transport distances were shorter and lower ocean
freight rates would reduce the profit for the company.

###  3.2 Hiroyuki Sato, an ex-vice president of Mitsui O.S.K Lines

We interviewed Mr. Hiroyuki Sato, former vice president of MOL, about the
shipping conferences in the Transpacific routes and the situation in liner
routes in the 1970s and the 1980s. He had been in charge of sales for Asia-
Europe service routes from 1969 and Transpacific service routes from 1974. We
conducted onsite interview with Mr. Sato on November 17, 2021 and our e-mail
inquiries were responded by him on December 15, 2021 and February 28, 2022. We
asked him about his thoughts on the figures and tables used in this study.

Regarding Freight Rate
Sato: In the 1970s, containerization was progressing on all routes, but
freight rates were determined based on weight or measured in the same way as
conventional vessels, instead of box rates (rates per container). There was
also an arrangement called “minimum revenue per container.” In addition, a few
percent of discounts were applied to long-term contract shippers using a
double freight contract with the shipper.

In the 1980s, there was a shift to box rates; the enactment of the Shipping
Act of 1984 was a significant reason for this shift. The period after the Act
was when space charters were no longer viable, leading to the formation of
alliances in the 1990s.

##  4 Results of Structural Breaks Test

We test multiple unknown structural breaks for each route using Bai and Perron
(1998, 2003), to confirm anecdotal evidence of container crises between the
1970s and the 1980s, documented in Broeze (2002), and to find when the
container crisis started and how long it lasted. Methodologically, we follow
Bai and Perron (2003) to address the problem of estimating the break dates and
the number of breaks and present an efficient algorithm.282828The most
relevant paper is Fan and Yin (2016), which applies Bai and Perron (2003)’s
method to the semi-annual data on the newbuilding price index, the time
charter rate index, and the second-hand price index for each ship size (i.e.,
Feeder, Feedermax, Handy, Sub-Panamax, and Panamax) between October 1996 and
July 2013. They focus on the unknown structural breaks in the relationship
between the three abovementioned global-level indices, whereas we are
interested in the unknown structural breaks in the route-level container
freight rate corresponding with competition regime changes.

We consider a multiple linear regression with $k$ breaks ($k+1$ regimes) as
follows:

$\displaystyle y_{t}=z_{t}^{\prime}\delta_{j}+u_{t}\quad
t=T_{j-1}+1,\ldots,T_{j}$ (1)

for $j=1,\ldots,k+1$. In this model, $y_{t}$ is the targeted price at time
$t$, $z_{t}(q\times 1)$ is a vector of $q$-dimensional covariates,
$\delta_{j}(j=1,\ldots,k+1)$ is the corresponding vector of coefficients, and
$u_{t}$ is the disturbance at time $t$. We allow serial correlation in the
errors and variances of the residuals across segments. The indices
$\left(T_{1},\ldots,T_{k}\right)$, that is., the breakpoints, are explicitly
treated as unknown (we use the convention that $T_{0}=0$ and $T_{k+1}=T$ ).

The purpose of this section is to estimate the unknown regression coefficients
together with the breakpoints and the number, therefore we specify $z_{t}=1$
as the simplest case. Bai and Perron (2003) suggested that the trimming
parameter $\varepsilon=h/T=0.10$ holds where $h$ is the minimum distance
between each break. Following Bai and Perron (2003), we assume a minimum
length equal to 10% of the sample size, given that we allow for a maximum of
four breaks. Our data specify $T=40$ (i.e., yearly data between 1966-2007),
thus we impose $h=4$ for the route-year-level analysis of the shipping price.
For consistency, we also impose $h=4$ for the industry-year-level analysis of
newbuilding, secondhand, and scrap prices.

###  4.1 Route-year-level shipping price data

|  BIC: $m$ = 0 |  $m$ = 1 |  $m$ = 2 |  $m$ = 3 |  $m$ = 4 |  $m$ = 5 |  $m$ = 6 |  $m$ = 7 |  $m$ = 8
---|---|---|---|---|---|---|---|---|---
Transatlantic westbound | 647.86 | 555.88 | 538.08 | 538.10 | 538.89 | 538.95 | 545.65 | 552.91 | 560.26
Transatlantic eastbound | 685.71 | 620.56 | 596.29 | 582.23 | 581.03 | 584.06 | 587.28 | 592.78 | 598.48
Transpacific westbound | 679.59 | 609.32 | 592.63 | 568.14 | 568.96 | 573.59 | 579.50 | 586.58 | 593.87
Transpacific eastbound | 714.70 | 640.64 | 599.18 | 592.70 | 592.22 | 595.82 | 600.01 | 606.82 | 614.56
Asia to Europe | 684.17 | 620.42 | 593.91 | 567.82 | 571.46 | 576.96 | 584.01 | 591.20 | 627.68
Europe to Asia | 631.38 | 581.33 | 553.76 | 539.17 | 545.08 | 551.75 | 558.62 | 566.59 | 588.79

Figure 3: The estimated breakpoints and 95 % confidence intervals with BIC.

  * a

Note: Each segment shows the estimated breakpoints and the 95% confidence
intervals for $\hat{T}_{i}$ for $i=1,\cdots,4$. Following Bai and Perron
(2003), the number of breakpoints is selected by minimizing BIC, as shown in
the bottom table. The estimated parameters $\hat{\delta}_{j}$ and standard
errors for all $j=1,\cdots,k+1$ for all possible numbers of breakpoints are
omitted. We use the sample between 1968 and 2008 for the Transatlantic and
Transpacific routes and the sample between 1971 and 2008 for the Asia-Europe
routes. We used the strucchange R-package developed by Zeileis et al. (2002).

Figure 3 illustrates the estimated breakpoints $\hat{T}_{j}$ and 95%
confidence intervals for route-year-level analysis of shipping freight rates.
The bottom table shows BIC for all possible number of breaks under $h=4$,
where the minimizer of the BIC is the optimal break number $\hat{k}$. First,
we find that the 95% confidence intervals of the structural break cover the
period between 1979 and 1980 on the U.S. routes (left and center panels),
whereas the intervals cover the period between 1976 and 1978 on the non-U.S.
routes (right panels). This indicates that the container crisis occurred on
all six routes by 1980, triggered by the withdrawal of Sea-Land, although
non-U.S. routes reacted earlier than U.S. routes. The reason for the response
in non-U.S. routes may be related to the reopening of the Suez Canal in 1976,
which increased the supply of container shipping services (Saito et al. 2022).

Second, we find remarkable differences between U.S. routes and non-U.S. routes
between 1984 and 1990. The 95% confidence intervals of the structural break
cover some period between 1984-1990 on the U.S. routes, whereas there were no
breaks on the non-US routes in the period. This implies that the enactment of
the Shipping Act of 1984 generated some structural breaks in the treatment
group — the U.S. routes. Surprisingly, we also find that the container crisis
lasted heterogeneously, even along the U.S. routes. For example, Transpacific
routes seemed to recover in 1986, whereas Transatlantic routes remained sour
until 1990. This result may support the fact that the supply-demand
relationship on the Transpacific and Transatlantic routes changed differently
in the late 1980s. The substantial change in exchange rates after the Plaza
Accord in 1985 led to a recovery in the demand for transportation on the
Transpacific route. However, no such situation was observed between Europe and
the U.S.

###  4.2 Industry-year-level newbuilding, secondhand, and scrap prices data

|  BIC ($m$ = 0) | 1 | 2 | 3 | 4 | 5 | 6 | 7
---|---|---|---|---|---|---|---|---
Newbuilding | 668.72 | 668.35 | 665.16 | 661.39 | 663.70 | 667.99 | 674.65 | 694.26
Secondhand | 687.91 | 610.21 | 609.25 | 606.64 | 612.79 | 619.02 | 625.65 | -
Scrap | 448.16 | 446.64 | 440.37 | 443.81 | 440.36 | 446.38 | 452.99 | 470.14

Figure 4: The estimated breakpoints and 95 % confidence intervals with BIC.

  * a

Note: Each segment shows the estimated breakpoints and the 95% confidence
intervals for $\hat{T}_{i}$ for $i=1,\cdots,4$ for each route. Following Bai
and Perron (2003), the number of breakpoints is selected by minimizing BIC, as
shown in the bottom table. The estimated parameters $\hat{\delta}_{j}$ and the
standard errors for all $j=1,\cdots,k+1$ for all possible numbers of break
points are omitted. We use samples from 1968 to 1998 and the strucchange
R-package developed by Zeileis et al. (2002).

Figure 4 illustrates the estimated breakpoints $\hat{T}_{j}$ and 95%
confidence intervals for industry-level analysis of newbuilding, secondhand,
and scrap prices. First, we find that 95% confidence intervals of the
structural break cover the period between 1974 and 1976 for newbuilding and
secondhand prices. These results correspond with the shipping price trend in
the Asia-Europe market. Second, downward structural breaks in prices were not
detected between 1984 and 1990. These results imply that, unlike route-level
shipping prices, the container crisis did not significantly decrease industry-
level prices in the shipbuilding market. We interpret these differences as
naturally capturing the differences between shipping markets with shipping
conferences and those without cartel groups.

##  5 Practical Implications, Discussion, and Future Research

###  5.1 Practical implications

Our study makes an important contribution to the development of consistent
data on the history of the container shipping industry and policy discussions
for practitioners. The data contribution enables practitioners to obtain
empirical knowledge on the main container transport markets, as well as to
develop a methodology to construct container market trends on other routes,
where information such as freight rates and vessel volumes deployed is only
partially available. For example, container transport market trends on routes
between the Indian subcontinent, Africa and Europe, South East Asia and the
U.S. are important information for manufacturing companies to establish their
supply chains and respond to specific policies, but the available information
is fragmented. Thus, our data contribution sheds light on the calculation of
partially known logistics costs for shippers.

###  5.2 Discussion

We summarize the potential concerns for the data and structural break tests.
First, our imputation approach is ad hoc, which potentially makes the data
sensitive to other imputation approaches or assumptions. However, we believe
that our approach is the best alternative among feasible approaches because
other data-driven imputation approaches require a large sample size, several
overlapping years, and the no-structural-break assumption of the data, which
our data does not satisfy (discussed in Section 2.4 and Appendix B). Second,
we may face a small sample problem for the structural breaks tests because we
use route-year-level data between 1968 and 2008. If route-quarter-level data
for a longer period can be consistently constructed, the results of the
structural breaks may change.

Regarding the possibility of combining our data with data from 2009 and
beyond, we have a couple of reasons for not doing so. First, our main data
source, Review of Maritime Transport, only provides route-level price data up
until 2009. Second, there are some challenges with merging our data with
Drewry’s data for a fee since their price data is based on a different
observation unit than ours. Drewry’s data includes monthly port-to-port level
price data, while our data is route-year-level. Third, the industry
experienced significant changes around 2009, such as the Global Financial
Crisis and the Repeal of the EU’s competition law exemption for shipping
conferences in October 2008. These industry changes not only make it
inappropriate to simply merge data from 2009 and beyond with our existing
data, but they can also contaminate the results of structural break tests.
These concerns are beyond the scope of this study and are left for future
research.

###  5.3 Future research

Our data are useful for understanding the related historical policy debates in
the container shipping industry. In ongoing research, one of the authors merge
our data with the firm-market-level shipbuilding data between 1966 and 1990 ;
then construct a dynamic structural model of firms’ entry, exit, and
shipbuilding investment decisions in homogenous good markets under collusive
and perfect competition regimes, which are exogenously determined by the
enactment of the Shipping Act of 1984. Understanding the effect of shipping
conferences based on the structural model makes the specific features of the
inner allocation mechanism of shipping conferences contributable to the
general literature on competition law and industrial policy which have been
investigated in the shipbuilding and shipping industry (Kalouptsidi 2017,
Barwick et al. 2019). Thus, our data sheds light on the historical questions
of future research in the container shipping industry.

Our data are also useful for understanding the current policy debates in the
container shipping industry. For example, we merge our data with post-1990
firm-market-level shipbuilding data to evaluate the effects of EU competition
law exemptions (by Regulation (EEC) No 4056/86) for liner shipping firms,
which terminated in 2008, on merger waves after 1990. Jeon (2022) uses data
from 2006 to 2014 and conducts counterfactuals with respect to competition and
industry consolidation by simulating the industry under a multi-plant
monopolist and a merger of the top two firms. Kalouptsidi (2017) and Barwick
et al. (2019) investigated the Asian shipbuilding market in the 2000s to study
China’s expansion. Thus, our data fill the gap between prior studies focusing
on the 2000s and the 2010s and future research examining the 1980s and the
1990s.

Our data provides a historical benchmark of shipping prices for updated issues
in the container shipping industry. First, our data enables us to make
quantitative comparisons between price increase during Covid period and
historical prices that were under active shipping conferences. For instance,
during the Covid period, the highest peak of shipping prices per TEU from
Shanghai to Los Angeles was recorded in February 2022, adjusted according to
the CPI in the U.S. in 1995, and amounted to $4462. This level is comparable
to the highest peak of cartel prices observed in the Transpacific eastbound
route, as illustrated in Figure 1. This will offer valuable insights into how
prices have evolved over time, as well as how significant the shipping price
increase during Covid was. Second, our 1966–2009 data provides a helpful
benchmark for predicting the impacts of significant industry changes that are
expected to occur, such as the updates to the EU competition law exemption for
consortium in 2024 and the breaking of the 2M alliance between Mediterranean
Shipping Company (MSC) and Maersk in 2025. By using our data, we can gain a
better understanding of the potential effects of these changes on shipping
prices.

##  6 Conclusion

This study provides a new unified panel dataset of route-year-level freight
rate and shipping quantities for the six major routes and industry-year-level
newbuilding, secondhand, and scrap prices from 1966 (beginning of the
industry) to 2009. The data provide a fundamental basis for understanding the
container shipping industry. The data and structural break tests provide
historical insights into the nonstationary dynamics of these price variables,
known as the container crisis. We find that the container crisis was a
specific event in the shipping market. Our data shed light on the industry
dynamics of shipping cartels. We leave a detailed analysis based on these data
for future work.

Acknowledgement
We benefited from anonymous referees and participants at the International
Association of Maritime Economists 2022. We thank Akimitsu Ashida and Hiroyuki
Sato for sharing industry knowledge and expertise as ex-chairperson in the
1980s. And we thank Mikio Tasaka, Yasuhiro Fujita, Jong-khil Han and Yutaka
Yamomoto for professional comments. This study was supported by JSPS KAKENHI
Grant Numbers 20K22129 and 22K13501.

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Container freight rate | Year | Source | Measured Units | Note
---|---|---|---|---
| 1965,1970,1975,1979 | Issues of Our Ocean Shipping | dollars per 100 tons-mile | Liner sector, three main cargo
| 1973-1976 | Current status of marine transportation | converted dollars per TEU | Revenue and quantity on only Transpacific and Asia-Europe routes
| 1976-1994 | Global Container Markets Drewry Shipping Consultants | dollars by FEU | Missing 1976-1989 in Asia-Europe
| 1994-2009 | Review of Maritime Transport | dollars by TEU | All market-level info is available
Liner freight rate |  |  |  |
| 1965-2009 | Review of Maritime Transport | index rate based on 1995(=100) | Global liner freight rate
Quantity |  |  |  |
| 1966-1972 | Containerization International 1973 | TEU | Aggregate carrying capacity for each route
| 1970,1974,1978,1980 | The Container Crisis 1982 | 1 million ton | Aggregate quantity for each route
| 1975,1978,1981,1984,1987,1990 | Container transportation cost and profitability 1980/2000 | 1000TEU | Aggregate quantity for each route
| 1985-1997 | World Sea Trade Service | 1000TEU | All market-level info is available
| 1994-2009 | Review of Maritime Transport | 1000TEU | All market-level info is available
| (1970,1975,1977,1978,1979) | *Issues of Our Ocean Shipping | D/W tons | Aggregate quantity for each route
| (1973) | *Containerization International 1975 | 1000TEU | Aggregate quantity for each route
| (1978,1981) | *The Container market to 1990 | TEU | Aggregate carrying capacity for each route and container type
| (1983) | *World Container Data 1985 | 1000TEU | Aggregate quantity for each route

  * a

Note: The data sources with ($*$) are used for reference to check the
consistency of the trend.

Table 3: Overview of data sources.

Figure 5: The observed and imputed variable cells for market-level data.

  * a

Note: In the yellow X cells, the route-level variables are recorded in data.
In the green Y cells, the route-level variables that cannot identify the
eastbound and westbound routes are recorded, so that we assign the values
based on the fixed ratio of the eastbound to the westbound in the closest
period. In the orange Z cells, although route-level variables are not
recorded, ship-level variables with targeted routes are available, so that we
convert firm-level information into route-level variables based on the fixed
ratio in the closest period. The red cells are missing values. Thus, we impute
the values via interpolation based on the observed points in each route and
global liner freight rate.

##  Appendix A Details of global containerization (Not for publication)

##### Transforming the cost structure.

In the 1960s, the volume of cargo movement on ocean liners and port handling
costs increased, putting pressure on the management of shipping companies.
However, in the U.S., the cargo was loaded into standardized containers for
transport, which not only eliminated the need for onboard cargo handling
equipment but also enabled cargo handling in the rain. In addition, cargo
handling in container shipping has saved a significant amount of work done by
workers. Furthermore, they significantly reduce the time and cost required for
cargo handling at ports. However, containerization has made the industry more
capital-intensive.

##### Lowering barriers to entry.

The development of containerization has dramatically lowered barriers to entry
for new shipping companies. Prior to the development of containerization,
large and small cargoes had to be loaded and unloaded individually, which
required skilled stacking techniques and expertise to prevent cargo collapse
during the voyage and a significant amount of time and workforce for cargo
handling and management. As containerization has progressed, cargo sizes have
been standardized, and many stacking techniques and expertise have become
unnecessary, significantly reducing the time and labor required for cargo
handling.

##### Rise of (non-conference) shipping companies in developing countries.

Several national and local governments competed to build container terminals,
which resulted in the loss of technological and equipment advantages of
existing shipping companies. Thus, barriers to entry for new shipping
companies that did not have the technology or bases for loading and unloading
dropped significantly.292929Further, containerization has made it possible to
quickly reload cargo onto freight trains and trailers, which has led to the
rapid development of international intermodal transportation. In the past,
shipping companies were contracted to transport goods only by sea between
ports and were not involved in inland transportation. The relationship between
inland and vessel transportation is investigated by Bernhofen et al. (2016)
and Levinson (2016) explained it anecdotally.  In parallel with the
development of containerization, developing and socialist countries began to
develop the ocean shipping business as a core industry, and state-owned
shipping companies in these countries began to enter the market as non-
conference members.

##### Shifting from “closed” conferences to “open” conferences.

Furthermore, conferences came to be strongly perceived as an impediment to the
entry of the shipping industries of developing countries into the world trade
market, mainly in the UNCTAD arena. In response to this trend, the United
Nations Convention on a Code of Conduct for Linear Shipping Conferences was
concluded in 1974. This convention allows shipping companies from trading
parties to participate in shipping conferences. Moreover, when a conference
determines the ratio of cargo transportation by shipping companies, the ratio
of origin-destination shipping companies to third-country shipping companies
should be 4:4:2. In the 1980s, conferences related to European routes began to
ask non-conference companies to join conferences to prevent their market share
from declining.303030Theoretically, in the 1970s, the potential entrants in
the conference markets consisted of non-containerized liner shipping companies
in the shipping conferences. In the 1980s, the potential entrants added non-
conference firms. However, the number of non-conference firms joining shipping
conferences is marginal.

##### Forming a consortium.

As containerization progressed, container routes required considerable
investment in ship construction and container terminal ownership. Therefore,
multiple companies began to form consortiums to reduce the scale of investment
while maintaining a certain level of service.313131For example, these
consortia include the TRIO Group, formed by European shipping lines, and the
Ace Group, consisting of Japanese, Korean, French, and other shipping lines.
Specifically, consortiums are engaged in business co-operation such as space
chartering, joint use of container terminals, and coordination of operation
schedules.323232 Major container shipping companies are forming global
alliances such as THE Alliance and the Ocean Alliance. They are utilizing a
consortium framework. Both “conference” and “consortium” are defined as
concerted actions by competition laws in various countries, which then require
exemptions from competition laws. However, member companies at a conference
agree on freight rates, and consortium members do not have any consent.
Individual shipping companies in the consortium determine freight rates and
sales activities. Thus, the consortium is not treated as a single firm.

##  Appendix B Data construction (Not for publication)

The container shipping industry is a fascinating laboratory for investigating
industry dynamics. Because the industry started global shipping in 1966, we
can determine the initial state of the market’s dynamic structure. There is
also substantial firm entry and exit in the industry, which makes it ideal for
studying industry dynamics in the global markets. Finally, the markets observe
the dynamics of shipping alliances, mergers, and consolidations.

Despite its significance, a panel dataset regarding the container freight rate
and shipping quantity on the three major trade routes (front-haul and back-
haul separately) between 1966 and 2009 was not available.333333Similar to
related papers focusing on the container freight rate panel data, Luo et al.
(2009) use shipping demand and freight rate data between 1980 and 2007. As for
shipping demand, they used the world container throughput reported in the
Drewry Annual Container Market Review and Forecast. The container freight rate
is calculated as the weighted average of Transpacific, Europe-Far East and
Transatlantic trades from the same data source. Because of the data
limitation, they calculated the missing period (1980–1993) from the General
Freight Index in the Shipping Statistics Yearbook 2007, using a simple
statistical equation between the container freight rate and the general
freight index from 1994 to 2008. Although, unified instructions and guidance
to construct the dataset are provided by published books and available data,
the construction and merging processes involve conversion and imputation
errors from multiple datasets. Table 3 presents the data sources. Instead of
manually constructing the freight index from the commodity-level freight rate
via formal but complicated processes, we adopted at tractable imputation
approach, which links multiple data sources that overlap information for a few
years. The corresponding code is also provided to ensure that an interested
researcher can replicate the construction.

Collecting data on container freight rates and shipping quantity, particularly
before 1994, is not trivial because there is no single data source. In the
subsequent subsections, we provide detailed data construction for each
container freight rate and shipping quantity.

###  B.1 Container freight rate

To construct the data regarding the container freight rate, we refer to the
data sources presented in Table 3 and the liner freight rate before global
containerization.

####  B.1.1 Shipping conference and Liner freight rate

The liner shipping industry has traditionally formed shipping conferences
including explicit cartels. Until 1984, shipping conferences played an
important role in the container-shipping market. For example, in February
1967, a container shipping firm, Matson, started an operation on the Atlantic
route under the freight rate contracted with one of conferences, the TPFC.
Thus, the container freight rate was determined by liner shipping conferences.

This unique feature allows us to use the liner freight rate to approximate the
container freight rate. Figure 6 compares the liner freight rate with the
container freight rate recorded since 1995. In particular, “Issues of Our
Ocean Shipping” recorded that in 1978, 76.0% of U.S. liner transports, 66.4%
of European liner transports, and 68.8% of Asian and Australian liner
transports were containerized. Therefore, more than two-thirds of the liner
freight rate was determined by the container freight rate in the 1970s and the
1990s.

Figure 6: The trend of the liner freight rate.

  * a

Note: Source: Review of Maritime Transport, published annually by UNCTAD. The
measure of the price index is not explicitly mentioned in the Review of
Maritime Transport.

####  B.1.2 Container freight rate between 1966 and 1975

Data on freight rates between 1966 (i.e., the beginning of the industry) and
1975 were missing from a single data source. Thus, we need to infer and impute
data from multiple sources and information in subsequent years. Fortunately,
we can use the institutional knowledge in Section B.1.1, the liner freight
rate, and the published data that overlap the data in subsequent years in
multiple data sources.

The “Issues of Our Ocean Shipping” (“Wagakuni no Gaikou Kaiun Ni Tsuite”, in
Japanese) records the freight rate of liner shipping on three major routes in
1965, 1970, 1975, and 1979. The freight rates for the three types of cargo
(electric appliances, clothes, and ceramic products) are available. The
freight rates were measured in dollars for 100 tons per mile. Shipping miles
between specific ports are listed.343434For the Transpacific and Asia-Europe
routes, the shipping miles between specific ports, Japan-Hamburg and Japan-San
Francisco routes are mentioned. However, only for the transatlantic route, the
specific ports were not mentioned. Thus, we take the average of the shipping
miles for Hamburg-San Francisco (i.e., west coast) and Hamburg-Halifax routes
(i.e., east coast). Using this information, we can recover route-level
container freight rates for 1965, 1970, and 1975. Finally, we assumed that the
proportions of liner and container freight rates for each route were fixed
before 1975. Under this assumption, we recovered and interpolated the
eastbound and westbound container freights for each route based on the fixed
proportion of the liner and container freight rates and that of subsequent
years, which overlaps container freight rates in multiple data
sources.353535The overlapped information in 1979 is key for merging multiple
data before and after 1975. However, the freight rate swung irregularly and
non-proportionally in both data sources. For making the smooth transition of
the freight rate in the merged dataset, we calculated the conversion rate
based on the freight rate of 1975 from the Issues of our ocean shipping and
that of 1976 from Global container markets year.

####  B.1.3 Container freight rate between 1976 and 1994

The data on the freight rate between 1976 and 1994 were recorded in the Global
Container Markets Drewry Shipping Consultants. The recording of the freight
rate started in 1976 for the transatlantic and Transpacific routes and in 1990
for the Europe-Asia route. Thus, data on the freight rate of the Europe-Asia
route between 1976 and 1989 are missing.363636Global Container Markets Drewry
Shipping Consultants stated that, “the Europe-Far East trade is the least well
documented of the axial routes (page 109)”.

For the imputation of the missing data, we assumed that the proportion of
liner and container freight rates for eastbound and westbound Asia-Europe
routes were fixed between 1976 and 1990. This assumption implies that there is
no time-varying difference between the eastbound and westbound Asia-Europe
routes. Under this assumption, we recovered the container freight rates of the
eastbound and westbound Asia-Europe routes.

####  B.1.4 Container freight rate after 1995

The freight rate data were recorded in the Review of Maritime Transport which
refers to the Containerization International Yearbook. The recording of
freight rates began in June 1994.373737Jeon (2022) stated: “The first dataset
on firm-level investment and capital is therefore supplemented with the
historical price and quantity data compiled from the Review of Maritime
Transport published by the United Nations that goes back to 1997.” (p. 9).
However, we confirm that the data in 1994 are available in Containerization
International Yearbook. The Containerization International Yearbook mentioned
that “the information is derived mainly from confidential reports provided by
some of the main carriers and other public sources.” Review of Maritime
Transport is often used because of the consistency of data sources and public
availability. For example, Jeon (2022) used quarterly freight data.

The above steps generate time-series data of the container freight rate for
each route between 1966 and 2009. Figure 7 shows the trend of the container
freight rate (CPI-adjusted to 1995) with the liner freight rate depicted in
Figure 6. In particular, the recovered and imputed data points in the 1960s
and the 1970s quantitatively capture anecdotal and institutional evidence.
First, for the transatlantic and Transpacific routes, a peak in 1976 and a
sharp declining trend in 1979 were observed. Second, the container freight
rate on each route corresponds to fluctuations in the liner freight rate.

Figure 7: The trend of the container freight rate.

###  B.2 Shipping quantity

To construct data on container trade volume, we refer to the five data sources
shown in Table 3.

####  B.2.1 Shipping quantity between 1966 and 1975

Official data on shipping quantities between 1966 and 1969 were not available.
However, we could keep track of the development of the container vessels
during this period. First, data regarding vessel capacity were recorded in
Containerization International 1973.383838“Theory and Practice of Container
Shipping” (“Container Yusou no Riron to Jissai”, in Japanese) contains
information about the launch of container ships owned by the United States’
four main firms, Moore-McCormack, U.S. Lines, SeaLand, and CML (American
Export Isbrandtsen). This helps us to identify the exact launch year of full-
container ships by the largest players, that is, United States’ container
shipping companies. We use the data source only to check institutional
evidence. This information identifies the carrier composition of the
Transatlantic, Transpacific, and Asia-Europe routes between 1966 and 1972.

Second, the Review of Maritime Transport (1971) summarizes the relationship
between annual global container carrying capacity and container capacity in
1969 and 1970 on the transatlantic route. We assume that container capacities
were fully exploited during this period. This assumption is not restrictive,
because the demand for container shipping was considerably high during this
period. Under this assumption, the shipping quantity is recovered by
calculating the total shipping quantity from the container capacity and
invariant conversion rate.

Third, the data on shipping quantity in 1970 and 1974 were recorded in The
Container Crisis 1982, and the data for 1973 were recorded in Containerization
International 1975. However, data for 1971 and 1972 were missing. The data
contains regional levels of container shipping, that is, container traffic in
Asia, North America, and Europe. One alternative is the imputation approach,
which employs external data that provide information about missing
data.393939Jeon (2022) stated that: “We set the start date for firms”
information as the second quarter of 1966, which is the date of the first
international container voyage. Then, we employed quarterly data on the value
of trade by origin-destination pair from the IMF Direction of Trade Statistics
database to impute the missing data on demand states from 1966: Q2-1996: Q4.”
(p. 25), and “To translate the value of trade to the quantity of container
trade, the demand state for the 1997–-2014 period was regressed on the de-
trended value of trade. Then, the demand states for periods with missing data
are constructed as predicted values from the regression. For the 1997–-2014
period, actual demand states are used.” (footnote 37). We assign the recorded
trade volume to each route in proportion based on subsequent
years.404040Alternatively, we could assign the aggregate container shipping
quantity to westbound and eastbound routes based on the data on the value of
trade by origin-destination pair from the IMF Direction of Trade Statistics
database. We did not take the full-imputation approach because the value of
trade includes goods transported by the bulk shipping service. For missing
years, we interpolated the trade volume using the observed data points.

####  B.2.2 Shipping quantity between 1976 and 1994

Data on shipping quantity between 1976 and 1994 were recorded in World Sea
Trade Service, Container transportation cost and profitability 1980/2000, The
Container Crisis 1982, and World Container Data 1985. World Sea Trade Service
started recording data in 1985, whereas the other data sources recorded the
data before 1985 but irregularly. Specifically, the quantity data for 1971,
1972, 1973, 1976, 1977, and 1979 were missing for all routes, and the quantity
data for 1970, 1974, 1980, 1982, and 1983 were recorded in the total shipping
quantity, summing the eastbound and westbound for each market.

####  B.2.3 Shipping quantity after 1995

Data on shipping quantity after 1995 were recorded in the Review of Maritime
Transport and World’s sea trades. The former refers to World Sea Trade Service
Review, various issues, 1996; Journal of Commerce, various issues, 1996; and
Containerization International, various issues, 1996. As in Section B.1.4,
shipping quantity data are easily constructed from a single data source, the
Review of Maritime Transport. Before merging the data before and after 1995,
we confirm that the discrepancy between the two data sources is marginal for
almost all market-year observations. However, only the quantities on the
transatlantic eastbound and westbound routes in 1995 were somewhat different.

The above steps generate time-series data of container shipping quantity
measured by 1000 TEU for each route between 1966 and 2009. Figure 8
illustrates the trend in the container shipping quantity. Shipping quantity on
all routes increased monotonically between 1973 and 2000. After 2000, this
trend increased exponentially, particularly on the Transpacific eastbound and
Europe-to-Asia routes.

Figure 8: The trend of the container shipping quantity. The trend before 1976
is based on ship-level carrying capacity information on each route.

###  B.3 Newbuilding, Secondhand, and Scrap prices

We provide recommendations for constructing newbuilding, secondhand, and scrap
prices for container ships from 1967. Our data were collected from a series of
Review (1971-1998) published by Fearnley and Lloyd’s Shipping Economist
(1983-1990) published by Lloyd’s of London Press.

####  B.3.1 Newbuilding prices

We collected industry-year-level newbuilding prices per 18000 DWT bulk ships
from Review (1971-1998)). Using the overlapped year, we converted prices into
consistent prices under the assumption that the conversion rate is invariant
across years. Then, we divided the price per 12000 dwt by 10 to convert it to
the price per 1200 TEU and then converted it into the price per TEU. Finally,
we convert bulk prices into container prices based on Lloyd’s Shipping
Economist (1983-1990).

####  B.3.2 Secondhand prices

We collected industry-year-level secondhand prices per 16000 DWT CSD (liner
type) ships from Review (1971-1998). Using the overlapped year, we converted
prices into consistent prices under the assumption that the conversion rate is
invariant across years.

We assume a fixed depreciation rate ($=X$) and a fixed conversion rate ($=a$)
for 1981 and 1983 and observe the following:

$\displaystyle 1981:2.7+2X$ $\displaystyle=16.0a\quad\text{(18-year
depreciation)}$ $\displaystyle 1983:0.8+0X$
$\displaystyle=11a\quad\text{(20-year depreciation)}$

We solved the equations for $X$ and $a$. To obtain the price per
$1600dwt+15X$, we multiplied the above price by 12000/16000 and obtained the
price per 12,000dwt. We then divided the price by 10 to convert it to the
price per 1200TEU. We then converted it into the price per TEU of 5 years ship
by dividing it by 1200. Finally, we converted liner prices into container
prices based on Lloyd’s Shipping Economist (1983-1990).

####  B.3.3 Scrap prices

We collected industry-year-level scrap prices per LTD in the Far-East. Using
the overlapped year, we converted prices into consistent prices under the
assumption that the conversion rate is invariant across years. We then divided
each LTD by four to obtain the price per dwt, multiplied it by 10, and
converted it into the price per TEU.414141The rate is based on
https://nippon.zaidan.info/seikabutsu/2002/00264/contents/030.htm.