2009

International Transport Forum 2009
TRANSPORT FOR A GLOBAL ECONOMY
Challenges and Opportunities in the Downturn

FORUM PAPERS

3

GLOBALIZATION AND FREIGHT TRANSPORTCOSTS IN MARITIME SHIPPING AND AVIATIONDavid HUMMELSNBER, Purdue University, Indiana, USA

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation

INTERNATIONAL TRANSPORT FORUM
Forum Paper 2009-3
GLOBALISATION AND FREIGHT TRANSPORT COSTS IN MARITIME SHIPPING AND
AVIATIONDavid Hummels
OECD/ITF, Paris 2009

The International Transport Forum is a global platform and meeting place at
the highest level for transport, logistics and mobility. Key figures from government
and politics, business and industry, research and civil society will meet in Leipzig
each year to debate a transport topic of worldwide strategic importance.
This document was produced as background for the 2009 International
Transport Forum, which focused on Transport for a Global Economy: Challenges
and Opportunities in the Downturn.
For more information please see www.internationaltransportfoum.org

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Forum Paper 2009-3:David Hummels
SUMMARY
This report provides evidence and analysis on how changing patterns of globalization affect transportation
demand and transport costs. Section One, “How Goods Move” provides data from Europe, North andSouth America describing which transport modes are employed for international trade and how that haschanged over time. Measured by weight, nearly all international trade with non-adjacent neighbors moves
via ocean vessels. In contrast, the value share of trade moved by air cargo is large and grew steadily from1965 through 2000. By 2000, more than half of US and Irish export value was airborne. After 2000, theair share of trade fell sharply worldwide.
A primary reason for these large shifts in modal shares is explained in Section Two, “Measures ofTransportation Costs”. The initial rise in air shipping corresponds to a period in which the relative price of
air cargo dropped by a factor of 10. Between 2000-2008, air cargo rates rose by a third. In addition toaggregate trends, Section Two describes country and product specific data on transport costs. Inlandshipping represents from 30 to 60 percent of the total door to door shipping bill, depending on the country
in question. Ad-valorem transport costs are comparable in size or larger than tariffs –transportation
expenditures represent 85 percent of the total costs (tariffs plus transportation) faced by the US as animporter, and 31-63 percent of total costs faced by Latin American Importers. Transportation costs are
considerably higher for poor countries, and vary tremendously across products and source countries. Thisimplies that transportation costs play an especially large role in altering relative prices across exporters anddetermining bilateral variation in trade.
Section Three, “What Determines Shipping Costs” adduces evidence explaining variation in freight rates
across countries, products, and over time. Technological advances in the form of jet engines for air cargo
and containerization for ocean cargo are responsible for sharp reductions in the cost of these modes.
However, these technological improvements can be swamped by significant changes in input costs. For
example, high oil prices are largely responsible for rapid increases in ocean cargo costs in the 1970s as wellas rapid increases in air cargo costs after 2000. Variation in rates across countries is driven primarily bydifferences in infrastructure quality and the strength of market power for shipping lines. Variation in rates
across products is driven primarily by differences in their weight to value ratio.
Section Four “Trends in Globalization from a Freight Perspective” provides evidence on trends inglobalization and how these trends affect freight demand. Included in this discussion is the growth inmanufacturing, variation in the weight/value ratios for trade across countries and over time, time costs, thechanging geography of trade, and the changing organization of production, including verticalspecialization/fragmentation and the growing importance of testing markets and "small value" trade flows.
Section Five “Looking Forward” provides the author’s suppositions about future trends in globalizationand transport demand in the short and long run. The key trends are these: rapid economic growth in China
and India will continue, continuing the re-orientation of trade toward Asia and pushing up demand for andprices of oil. These oil price rises will continue to disadvantage air shipping as they have done since 2000.
Enormous current account deficits in the US, which have facilitated export-led growth in Asia and led tomajor cargo imbalances, will narrow. Finally, firms and individuals will find alternative channels – trade intechnology, foreign direct investment, immigration -- other than moving goods for realizing the gains fromtrade.
1.

How Goods Move

1.A.

Trade with Non-adjacent Partners

Three-quarters of world trade takes place between countries that do not share a land border. Nearly all of
this trade moves via ocean and air modes. Bulk commodities like oil and petroleum products, iron ore,coal, and grains are shipped almost exclusively via ocean cargo. Bulk cargoes constitute the majority of© OECD/ITF, 20093

Globalisation and Freight Transport Costs in Maritime Shipping and Aviationinternational trade when measured in terms of weight, but are a much smaller and shrinking share of trade
when measured in value terms.
Manufactured goods are the largest and most rapidly growing portion of world trade. To illustrate how
they are transported, Table 1-1 (taken from Hummels 2007a, original source data reported in Table
footnotes) reports worldwide data on ocean and air shipping of non-bulk traded goods. Air shipments
represent less than 1 percent of total tons and ton-miles shipped, but are growing rapidly. Between 1975
and 2004, air tonnages grew at 7.4 percent per annum, much faster than both ocean tonnage and the valueof world trade in manufactures in this period. The relative growth of air shipping is even more apparent inlooking at ton-miles shipped, with 11.7 per annum growth rates going back to 1951.
Assessing changes in the weight of trade is important for transportation planning. Assessing changes in thevalue of trade is important for assessing the economic significance of various transportation modes andtheir role in trade. Because the heaviest goods travel via ocean, weight-based data on international tradesignificantly understate the economic importance of air shipping. The final columns of Table 1-1 report thevalue share of air shipments in US trade with non-adjacent partners. In the past 40 years, air shipments
have grown to represent a third of U.S. imports and more than half of U.S. exports with countries outside
North America.
Is the US anomalous? Countries in Latin America and Europe recently began reporting trade with transportmode detail. Table 1-2 (taken from Moreira et al 2008, original source data reported in table notes)
provides import data by mode for 11 LAC countries and the US as a comparison. For LAC trade with allcountries worldwide the modal split is similar to the US, but with somewhat lower reliance on air shippingand greater reliance on maritime transport (except for land locked Bolivia and Paraguay).

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Forum Paper 2009-3:David Hummels
Tables 1-3 through 1-6 provide similar data for EU imports and exports from all countries other than theEU1. Table 1-3 reports on import values, including modal shares in 2007, growth in those shares from
2000-2007 and the percentage growth in imports via each mode. In 2007, airborne imports were 18.1
percent of the total, down from 25.1 percent in 2000. In contrast seaborne imports were 50.3 percent of theimport value, up from 41.5 in 2000. Of course, this is a period of rising trade, so the value of imports
entering via all modes rose in this period (see last panel of Table 1-3), however airborne imports rose only
slightly while seaborne import values rose 75 percent. There is great variance across countries in theirreliance on air-borne v. ocean-borne shipments. Of course landlocked countries heavily employ airborne
shipments (presumably the residual seaborne values indicate that the shipment entered somewhere inEurope via the sea). Richer countries are also more likely to use airborne shipments.
Table 1-4 provides a similar breakout for export value. Exports are more likely to use air (25.1 percent in
2007; down from 31 percent in 2000). And the growth in exports is skewed much more to the use of rail
and road, rather than sea as was the case with imports. Note that airborne exports are especially important
for the UK and Ireland. This likely reflects commodity composition (e.g. the prevalence of electronics andpharmaceuticals in Irish exports).
Finally, Table 1-5 and 1-6 provide data on imports and exports weight by transport mode. Airborne trade isa tiny share of the weight of trade. For the EU as a whole, 70 percent of imports and exports move via
maritime routes. However, this fraction varies dramatically across countries reflecting coastal access andthe importance of trade with non-EU eastern European countries.
Note that in Table 1-1 we see the US air share of imports and exports rising steadily from 1965 until a peakin 2000 before falling in 2004. Subsequent data for the US are not available, but EU data from 2000-2007
are available. Figure 1-1 plots the air share of EU trade from 2000-2007, both imports and exports. For
both imports and exports the air share of trade has fallen rapidly since 2000.
1.B.

Trade with Neighbors

Roughly 23 percent of world trade by value occurs between countries that share a land border. This number
has been nearly constant over recent decades, though it varies significantly across continents. For Africa,
the Middle East and Asia, between 1 and 5 percent of trade by value is with land-neighboring countries; for
Latin America trade with land neighbors is 10 to 20 percent of the whole, and for Europe and North
American it is 25-35 percent of trade.
Detailed data on the value of trade with neighbors is somewhat sparse. Unlike the case with air and ocean
shipping there is no globally comprehensive sources of information on modal use but data from the US,
EU and LAC data provide some insights. The US Transborder Surface Freight Data show that in 2007
imports by weight from NAFTA countries are 39% ocean, 21% truck, 20% rail, and 20% pipeline. Imports
by value were 11% ocean, 55% truck, 18% rail, 10% pipeline, and 6% other.
The EU and LAC data are useful for seeing the importance of various land modes not just for immediately
adjacent partners but with all continental partners. The second panel of Table 1-2 shows LAC imports
from other LAC countries. Air use is lower and land use is much higher than in the US data. Table 1-7
shows the land modal shares of trade by weight for EU countries in 2006 and the change since 2000.
Unlike the customs data shown in Tables 1-3 to 1-6, these data include trade within Europe. For mostcountries, the use of road dominates.

1.

These data were downloaded from the Eurostats dataweb, "External Trade" theme. Apparently the
only data tracking modal use comes from customs data, and EU-origin trade is no longer tracked
through customs.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
1.C.

Changes in Modal Demand: Initial Lessons

Why did air transport grow so rapidly until 2000 and fall thereafter? As the next sections show, a major
factor has been the relative cost of air shipping, which fell steadily until 2000, then rose sharply after that.
But an equally important factor has been changes in the nature of trade.
To understand this point, recognize that demand for international transport is an indirect or derived demandthat primarily depends on the demand for international trade itself. An important implication fortransportation planning is that final consumers are sensitive to changes in the delivered price of products,
not to changes in the transportation price. If the cost of transportation substantially affects the delivered
price then modal choice will be driven by cost considerations. But if the transportation price is but a small
fraction of the delivered price, it will likely be trumped by other factors such as timeliness or reliability.
For example, the gains from employing air shipping are more pronounced on longer routes. Choosing airtransport from the UK to France might save a shipper 5 hours, while choosing air transport from China toFrance might save 5 weeks. An air premium may be worth paying to save 5 weeks, but not 5 hours. Thisis undoubtedly why air shipping is used far less extensively for intra-continental trade than for trade at alonger distance. It should be noted that the same lesson is true of all cost differentials related totransportation Port A may charge handling fees per container that are twice the handling fees for Port B,
but unless these differences substantially impact delivered prices of products they will have minimal
impacts on the derived demand for transportation.
Less obviously, but perhaps as important, Table 1-1 shows that a dollar of merchandise trade goods weighsmuch less today than in previous years. From 1960-2004, the real value of trade in manufactures grew
about 1.5 percent per year faster than the weight of non-bulk cargoes. If bulk commodities are included in
the calculation, the real value of all trade grew 1.8 percent faster per year than the weight of all trade.
Reductions in weight/value make it easier to shift from ocean to air shipping because it reduces the advalorem price differential between the two modes. Consider this example. I want to import a $16 bottle ofwine from France. Air shipping costs of $8 are twice ocean shipping costs of $4. Going from ocean to air
increases the delivered cost by $4 or 25 percent. Now suppose my tastes improve and I want to import a$160 bottle of wine from France so that the weight/value ratio of the product has dropped sharply. The
shipping costs are the same, but now the $4 cost to upgrade to air shipping represents just a 2.5 percent
increase in the delivered price. The consumer is much more likely to use the more expensive shipping
option when the effect on delivered price is smaller.
I will revisit these issues in Section 4 as part of a broader discussion of changes in the nature of world tradeand how these changes affect transportation demand.
2.

Measures of Transportation Costs

This section of the paper reports price indices for ocean and air shipping along with ad-valorem measuresof transportation costs. It draws heavily on data and discussion from Hummels (2007a). In some cases thedata series in questions offers world-wide coverage of costs, while in others the data are drawn fromsources with narrower geographic coverage. This makes it difficult to ascertain whether data patterns are
unique to the particular source in question. Where appropriate I have commented on the generality of
specific results.
2.A.

Ad Valorem Measures of Transportation Costs

International trade economists typically express transportation costs in ad valorem terms, that is, the cost of
shipping relative to the value of the good. This is useful because it describes the size of the wedge thattransportation costs drive between origin and destination prices, and because it facilitates comparison withtariff barriers. The best data for evaluating the ad valorem impact of transportation costs over time comes6© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels
from a few importers such as New Zealand, the United States, and the ALADI countries of Latin America
that collect freight expenditures as part of their import customs declarations.2

2.

An alternative approach constructs indirect measures of transportation costs using a “matched
partner” technique. In principle, exporting countries report trade flows exclusive of freight andinsurance and importing countries report flows inclusive of freight and insurance. If measured
without error, comparing the valuation of the same flow reported by both the importer and exporteryields a difference equal to transport costs. Examples of papers using this technique include
Geraci and Prewo (1977), Rose (1991), Harrigan (1993), Baier and Bergstrand (2001) and Limao
and Venables (2001). Even UNCTAD’s Review of Maritime Transport, the pre-eminent annual
publication on international transportation and trade issues, relies heavily on matched-partner datafrom the IMF to construct measures of ad-valorem shipping costs on a worldwide basis. However,Hummels and Lugovskyy (2006) show that the “matched partner” technique is subject to enormous
measurement error and in fact produces time series variation that is orthogonal to actual variationin shipping costs.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation

BOX 1
Denoting the origin price of a good as p , destination price as p * , and per unit shipping costs as f , wehave p* = p + f . International trade economists typically express costs in ad-valorem terms, that is, thepercentage change in prices induced by transportation,

p*
f
= 1+
p
p
A common but inaccurate approach is to model the f term as a constant percentage τ of value shipped, inp*= p (1 + τ )which case the ad-valorem cost is independent of the goods price, or p
These data enable us to examine ad valorem transportation costs for an individual good sold by a particular
exporter, or to calculate aggregate expenditures on transportation divided by aggregate import value. Thisaggregate measure is equivalent to an average of ad-valorem transport costs for each good, after weighting
each good by its share of value in trade. That is, define ad-valorem transport costs for an individual good
as

τk =

fk
pk

We can then calculate the aggregate ad-valorem transport costs as the aggregate expenditures ontransportation divided by aggregate import value. This is mathematically equivalent to a trade-weighted
average of the transportability for individual goods k ,good k in trade.

τ agg = ∑ k τ k s kk, where s is the value share of

Figure 2-1 reports time series variation in total freight expenditures as a share of total import value for
New Zealand and the US (omitting North America).3 The New Zealand data cover 1963-1997, a period inwhich aggregate transportation expenditures fluctuated between a low of 7 percent of import value (in1970) and a high of 11 percent (in 1974) but exhibited no clear trend. The U.S. data cover 1974-2004, a
period in which aggregate expenditures on freight declined steadily from about 8 percent of the value of
total imports in 1974 down to about 4 percent in 1997 before leveling off. However, the apparent
downward trend in the US series may be misleading. The contrast with the New Zealand data andevidence in the next section makes clear that much of the apparent decline in aggregate US transport
expenditures in this period is an artifact of the 1974 starting point and the large effect of the oil shock on
prices in that year.
While Figure 2-1 accurately measures freight expenditures, this is not necessarily an accurate picture oftransportation costs. Since the share of trade in a particular product is low when shipping costs are high,actual freight expenditures will tend to understate transportation costs faced by typical goods. In US data,
for example, unweighted averages of transportation costs in a particular year are typically 2 to 3 times
higher than the weighted average reported in Figure 2-1. Over time, a switch toward more proximate
trading partners, or toward more transportable goods, can lower the aggregate value of expenditures ontransportation even if true shipping costs are unchanged. Similarly, an increase in transport service quality
3.

8

Canada and Mexico are omitted because freight expenditures on surface shipping are measured
with much greater error.

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Forum Paper 2009-3:David Hummels
such as a switch from ocean to air shipping can raise aggregate expenditures considerably. In the sections
below, I provide measures that control for these important compositional shifts.
To get a broader perspective on the ad-valorem importance of transport costs, I next compare data from the
US and Latin America. Table 2-1 is taken from Hummels, Lugovskyy, and Skiba (2008). It provides dataon transportation costs for imports into the US and a number of Latin American countries in 2004, andmakes clear several basic facts about costs of trade. One, ad valorem transport costs are negatively
correlated with per capita income – they are 1.5-2.5 times higher for Latin American importers than for theUnited States, and systematically higher for low income exporters into a given import market.
Two, transport costs are comparable in size to, or larger than, tariffs. For the median good in US imports
transportation represents 85 percent of the total costs (transport plus tariffs) faced by an exporter. For
historical contrast, transport expenditures on the median good were half as much as tariff duties for US
imports in 1958 (Waters, 1970), and equal to tariff duties in 1965 (Finger and Yeats, 1976). For Latin
American importers, transportation costs represent from 31 to 63 percent of total costs faced by exporters
in the median good. This is not because transportation costs are lower in LAC, as the first panel in thetable makes clear. Rather, tariffs in LAC are higher as well.
Three, despite the fact that international transportation technology and the use of containerized liner
shipping is common across goods and exporters, transportation costs vary enormously. This implies thattransportation costs play an especially large role in altering relative prices across exporters and determining
bilateral variation in trade. A useful summary statistic of variability is the coefficient of variation,
calculated as the variance over observations divided by the mean. For the US and LAC data, we observe
shipping costs for each product k and exporter j, so the coefficient of variation over j,k is

COV =VAR j , k (τ j ,k )mean(τ j , k ).

For US imports, the coefficient of variation (across exporters and goods) in ad-valorem transportation costs
is 1.4, meaning that shipments with costs that are one-standard deviation above the mean have costs 140
percent greater than the mean.
Even if we hold constant the product in question there is tremendous variation in transport costs acrossexporters to a given market. This pattern can be seen by calculating ad-valorem transportation costs foreach product in US imports 2004 and sorting exporters from most to least expensive. For a typical productthe exporter one standard deviation above the mean pays shipping prices 89 percent higher than the mean.
Exporters in the 90th percentile of costs faced shipping charges that were 11 times greater than those facedby exporters in the 10th percentile. This is considerably more bilateral variation than is found in tariff rates.
Variability in Latin America is comparable to or higher than the US. Given their size and variability,transportation costs are likely to play an especially important role in changing relative prices – lowering
trade volumes in the aggregate and altering patterns of trade across goods and partners.
What explains this variation? In section 3 below, I provide detailed evidence and discussion on specificdeterminants of shipping costs that help to explain why they vary so dramatically across countries andproducts. Hummels, Lugovskyy, and Skiba (2008) provide a systematic analysis that decomposesvariation in shipping costs into component influences: product characteristics and market characteristics
including market power. For example, non-OECD exporters face shipping costs that are 38 percent higher
than OECD exporters when shipping either to the US or to LAC countries. Differences in product prices
explain 62% of this effect, (ad-valorem costs of shipping are lower for higher priced products), 7% is due
to more intensive competition (more shippers on OECD routes), and only 6% is due to longer distances
traveled. The remainder is not attributable to any specific causes, simply showing up as higher costs for
non-OECD exporters after all measurable effects are accounted for. Similarly, LAC countries pay 27
percent higher shipping costs on their imports than does the US. Higher product prices on US routes
explain 23% of this difference, more intensive competition on US routes explain 29%, shorter distances© OECD/ITF, 20099

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
explain 12%, and higher tariffs on LAC routes (which enable shipping firms to charge higher markups)
explain 44%.
2.B.

Price Indices for Air Transport

Data on international air transportation prices are sparsely reported. However, the limited data do paint aclear portrait of decline over time in air shipping prices.
The International Air Transportation Association surveys international air carriers and reports worldwide
data on revenues and quantities shipped in their annual World Air Transport Statistics (WATS). Figure 2-2(taken from Hummels 2007a) shows average revenue per ton-km shipped for all air traffic worldwide,
indexed to 100 in 2000. Over this 50-year period, this measure of costs per ton fell more than 10-fold.
Expressed in 2000 U.S. dollars, the price fell from $3.87 per ton-km in 1955 to under $0.30 from
1955-2004.
The period from 1970 onward is of particular interest, as it corresponds to an era when air transport grew
to become a significant portion of world trade, as shown in Table 1-1. In this period, more detailed data
are available.
The International Civil Aviation Organization (ICAO) published a “Survey of International Air Transport
Fares and Rates” annually between 1973 and 1993. These surveys contain rich overviews of air cargofreight rates (price per kilogram) for thousands of city-pairs in air travel markets around the world. The
Survey does not report the underlying data, but it provides information on mean fares and distance traveled
for many regions as well as simple regression evidence to characterize the fare structure. Using this data I
construct predicted cargo rates ($ per kg shipped) in each year for world-wide air cargo and for various
geographic route groups. I deflate this series in two ways: first I use the US GDP deflator to provide theprice of air shipping measured in real US dollars per kg; second I deflate using the average price ($ per kg)
for air shipped goods in US trade in this period. This second deflator then provides a rough measure of thead-valorem incidence of air cargo for each year and route group.
Results are displayed in Table 2-2 (taken from Hummels 2007a). Pooling data from all routes, prices
increase 2.87 percent annually from 1973 to 1980, and then decline 2.52 percent annually from 1980 to
1993. The increases in the first period largely reflect oil price increases. The timing of the rate reduction
also coincides well with the WATS data, which show little price change in the 1970s and more rapid
declines in the 1980s. The post-1980 price declines vary substantially over routes, with longer routes andthose involving North America showing the largest drops.
More recent air cargo price indices are only available for the US. Figure 2-3 show air freight price indicesconstructed by the US Bureau of Labor Statistics for cargoes inbound to and outbound from the UnitedStates from 1991-2008. I deflate the BLS series using the U.S. GDP deflator to provide the price of air
shipping measured in real US dollars per kilogram, and normalize the series to equal 100 in 2000. Notethat the figures include both the aggregate series, and a sub-series for flights to/from Asia. (Further
geographic aggregation has been made available only in the last two years.). The real price of outbound air
freight fell substantially from 1992-2003 before turning up sharply. By the end of the period sampled here
(second quarter 2008), rates had returned to a level not seen since 1993. Similarly, the real price ofinbound air freight fell substantially from 1990-2001, and then rose significantly thereafter. These
increases likely reflect a combination of greater security costs post 9-11 and higher oil prices. More on thisbelow.
The sharp decrease and then increase in air cargo costs undoubtedly explain much of the modal change
described in Section 1. Recall that the US imports data, which span the period of decrease then increase,exhibit air cargo usage moving inversely with prices – rising until 2000 and falling thereafter. The EU data
begin in 2000 and exhibit a sharp decline in air usage in this period.

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2.C.

Costs of Ocean Transport

There are many price indices for tramp and liner shipping, but two reported in Figures 2-4 and 2-5 (takenfrom Hummels 2007a) stand out for their length of coverage. Figure 2-4 uses an index on tramp trip
charters originally constructed by the Norwegian Shipping News (NSN) and later continued by Lloyds
Shipping Economist. A trip charter is a contract to ship a large quantity of a dry bulk commodity between
specific ports, and may include some minimal loading and/or unloading expenses. The trip charter priceindex represents a weighted bundle of spot market prices, measured in U.S. dollars per ton, for shipping
major bulk commodities on several important routes world-wide. To evaluate the real costs of shipping
over time I deflate these indices using both the U.S. GDP deflator, and also using a price index for bulk
commodities typically shipped via tramps. Using the U.S. GDP deflator provides a constant dollar value
for the unit price of tramp shipping a given quantity of merchandise. Using the bulk commodity priceindex yields the price of shipping a bundle of goods relative to the price of that bundle, a crude measure of
the ad valorem barrier posed by shipping.
Figure 2-4 displays the price series for trip charters and shows several price spikes. The price spikes in the
1970s are clearly attributable to oil price shocks, and the price spike in the 1954-1957 period is probably
due to a combination of high demand from unexpectedly large U.S. grain exports to Europe and the Suez
Canal Crisis. Setting aside these spikes we can see two clear trends. The price of bulk shipping measured
in real dollars per ton has declined steadily over time so that it is now half as much as in 1960 and a third
the price in 1952. However, when measured relative to the commodity price deflator there are large
fluctuations but no downward trend. While the cost of shipping a ton of wheat or iron ore has steadily
declined, the cost of shipping a dollar value of wheat or iron ore has not.
Figure 2-5 reports the real price of liner shipping. It uses an index constructed by the German Ministry ofTransport that emphasizes general cargoes, including containerized shipping and manufactured
merchandise of all sorts. It also covers loading and unloading expenses, particularly relevant since
reductions in cargo handling costs are thought to be a major source of gains from containerization. This
index does not offer comprehensive geographic coverage, focusing only on those liners loading andunloading in Germany and Netherlands. As with the tramp index, I deflate the index to get the real price ofshipping, using both the German GDP deflator, and a composite traded goods price index for Germany.
Measured relative to traded goods prices, liner prices rise steadily against German import prices before
peaking in 1985. Measured relative to the German GDP deflator liner prices decline until the early 1970s,
rise sharply in 1974 and throughout the late 1970s, spike in the 1983-1985 period (likely due to the rapid
real depreciation of the DM which made German purchases of all international goods and services more
expensive), then decline rapidly thereafter.
The rapid increases in liner prices facing Germany in the 1970s were wide-spread. Throughout the 1970s,
UNCTAD’s annual Review of Maritime Transport reported price changes announced by shipping
conferences, with annual nominal increases of 10-15 percent being common across nearly all routes. The
RMT also reports the ad valorem shipping rates for a small number of specific commodities and routes
from 1963-2004: examples include rubber shipped from Malaysia to Europe, cocoa beans shipped fromeither Ghana or Brazil to Europe, and tea shipped from Sri Lanka to Europe. Converted to real dollars perquantity shipped, these liner prices increased by 67 percent in the 1970s.
2.D.

Constructing Price Indices from Regression Evidence.

Index numbers attempt to measure changes in the price of a non-changing bundle of services. The
difficulty with using these numbers is that they frequently lack comprehensive coverage, and users do nothave the option to inspect or re-construct the bundles of goods included in the index. Further, attempts toconstruct ad-valorem equivalents of the index numbers will be crude at best. One solution to this problem
is to use a regression approach to control for compositional change, thereby creating a kind of pseudo-priceindex.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
Hummels (2007a) shows how to use detailed data on shipping costs taken from customs data along with aregression approach to control for changes in the composition of trade. The data on shipping costs aretaken from the U.S. Imports of Merchandise data for 1974-2004. These data provide extremely detailed
shipment characteristics including transport mode, weight, value, freight and insurance charges, and duties
for each exporter with commodities disaggregated to the five-digit SITC level. The regression relates thead valorem air freight cost in logs for commodity k, shipped from exporter j, at time t. The independent
variables include a separate intercept for each exporter-commodity shipped, the weight/value ratio in logs
for each shipment, and year dummy variables. The exporter-commodity intercepts control for the fact thatiron-ore from Brazil has higher transportation costs in every period than shoes from Taiwan, and theweight/value ratio controls for compositional change over time within an exporter-commodity such as
Taiwan shipping higher quality shoes.
The dashed line in Figure 2-6 (taken from Hummels 2007a) reports an unadjusted measure of ad valorem
air shipping costs: that is, aggregate expenditures on air shipping divided by the value of airborne imports.
(This is very similar to Figure 2-1, except that only air shipping data are employed.) This line trends down
slowly, dropping only 2 percentage points over 30 years. As discussed earlier, measures of aggregatetransportation expenditures calculated in this way do not take into account changes in the mix of trade
partners or products traded. The solid line in Figure 2-6 reports the fitted trend in air shipping costs and isequivalent to ad valorem transportation expenditures after controlling for compositional change. Oncechanges in the trade partner and product mix have been taken into account, the fitted ad valorem cost
exhibits a greater absolute decline in air transportation costs.
Figure 2-7 (taken from Hummels 2007a) provides a parallel picture for ocean shipping. Again, the dashedline shows aggregate expenditures on ocean shipping divided by total value of ocean shipping in each year.
It shows an initially rapid decline in transportation expenditures, followed by a 25 year period in whichrates fluctuate but do not otherwise decline. The solid line represents ad valorem ocean shipping costs after
controlling for exporter-commodity composition and changing weight/value ratios. The fitted rates decline
initially, then increase through the mid-1980s, then decline for the subsequent 20 years.
Moreira et al (2008) used a similar approach to calculate pseudo price indices for ad-valorem ocean and air
shipping costs for Latin American imports. These results are reported in Figure 2-8 for air cargo and Figure
2-9 for ocean cargo. Note that their data for LAC includes years 1995 and 2000-2005 (so the 1995-2000
trend is interpolated). The air cargo series shows, on average, a decline from 1995 to 2000 though themagnitude varies from roughly constant (for Chile) to steep declines in air cargo prices for Argentina. After
2000-2001 air cargo prices turn up sharply. In contrast, ocean cargo expenses decline from 1995-2003(with a blip up in 2001) before increasing from 2003-2005.
2.E.

Door-to-door costs: inter-modal cost data

One difficulty with assessing international transportation costs is that most available data sources offer
coverage that begins at the exit port and ends at the entry port. The result is the omission of a crucialcomponent of costs: getting goods to and from the ports. This inland component is plausibly a very large
fraction of the overall bill.
Two large data exercises provide some cross-country perspective on the magnitudes of these inland
costs. The World Bank Doing Business database provides data on costs of inland movements, broken out
into various components: inland transport, ports, and other (customs, and assembly). Figure 2-3 provides
an aggregation of these costs for each broad region (with country data weighted by populations to constructregional averages). Costs are much lower for East Asia than for other regions, and highest for Sub-SaharanAfrica. The distribution of these costs also varies considerably across regions; inland costs being very low
for East Asia and much higher elsewhere.
De (2008) systematically extracted shipping cost quotes from the Maersk-Sealand shipping cost databasefor many city pairs within Asia. This allowed him to assess the relative importance of the inland relative to

12© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels
the ocean segment for each city-pair, which can then be aggregated into country pairs, or aggregated into
shipping costs for a country as a whole. An extract of this data is shown in Figure 2-4, which reports theaverage inland and ocean shipping costs for seven major Asian exporters. The total freight bill varied
widely from $1284 per TEU for Malaysia up to $3488 for India. The inland share of freight also varied
widely, with China at the low end (28%) and Thailand at the high end (60%). Also noteworthy: theexpensive of moving a container through Indian's interior is equal to the expense of the entire trip for
Thailand.
3.

What determines shipping costs?

Section 2 makes clear that transportation costs vary substantially across products, across countries, andover time. In this section, I discuss evidence on the determinants of shipping costs to help explain thisvariation. I begin with air cargo, and discuss the role of technology, policy, shipment characteristics, andcost shocks. I proceed next to a discussion of the changes in ocean cargo, including changes in technology
and institutions, input costs, port infrastructure, scale effects, and market power.
3.A.

Air Cargo

3.A.1.

Technological and Institutional Change

Commercial aviation has undergone rapid technological change, including improvements in avionics, wing
design, materials, and most importantly the adoption of jet engines. Compared to the piston engines they
replaced, jet engines are faster, more fuel efficient and reliable, and require much less maintenance.
Gordon (1990) calculates price indices for aircraft that adjust for these quality changes and finds dramatic
declines in real prices after jet engines were introduced. From 1957-1972, the period in which jet engine
usage became widespread, quality-adjusted real prices fell at a rate of 12.8 to 16.6 percent per year,
depending on the method of calculation. Quality change in commercial aviation slowed considerably after
1972, but quality-adjusted aircraft prices were still dropping by 2.2 to 3.8 percent per year from 19721983.
The timing of these changes are closely reflected in the WATS data reported in Figure 2-2. As with
Gordon’s measure of quality-adjusted aircraft prices, declines in air transport prices are especially rapid
early in the period. Average revenue per ton-km declined 8.1 percent per year from 1955-1972, and 3.5
percent per year from 1972-2003.
More recently there have been are two significant shocks to institutions that affect both air travel and air
cargo. The first, as documented in Micco and Serebrisky (2006) is the signing of agreements to liberalize
trade in air services. They discuss a series of 50 "Open Skies Agreements" by the US beginning in 1992.
These agreements, which apply to passenger, cargo, and combination air transport include several key
provisions, including: free competition (no restrictions on number of airlines, their capacity or service
frequency); pricing determined by market forces (as opposed to government imposed fares); and fair andequal opportunity to compete (freedom of airlines to establish sales offices and ground handling services).
Micco and Serebrisky (2006) use data on air cargo expenses for the US to estimate that signing OSA's
reduce air transport costs by 9%.
Finally, tighter security associated with the 9-11 terrorist attacks may have increased costs both for air
cargo and for air passengers, though most of the relevant evidence focuses on reduced quantities rather
than direct information on costs. For example, Blalock et al (2007) estimate that tighter screening
procedures introduced after 9-11 reduced passenger volumes by 6-9 percent. That said, it is possible to getat some of the higher air transport costs associated with 9-11. The Air Transport Association publishes costindices for the air industry, breaking out detailed cost factors such as fuel, labor, maintenance,
communications, and insurance. Insurance is especially interesting. Between 2001Q3 and 2002Q1, the costof insuring the aircraft itself tripled. In that same period, non-aircraft insurance for the airlines (i.e. insuring© OECD/ITF, 200913

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
everything other than the aircraft itself) rose five-fold. In both cases, insurance costs have subsequently
dropped, but remain roughly double what they were before the attacks.
Figure 3-1 shows a time series graph for air passenger fares taken from Cristea (2008), with these last two
events superimposed. The signing of open skies agreements correlate to sharp reductions in air prices, atrend that continues until the fourth quarter of 2001.
3.A.2.

Regression Evidence: Distance, Oil Prices.

Hummels (2007a) examines air cargo prices from US imports data, relating the cost of shipping good kfrom exporter j to various determinants. Ad-valorem air transportation costs are increasing in theweight/value ratio of the good, the distance shipped, and jet fuel expenses. I will return to the importanceof weight/value below, but first consider the role of distance. Interestingly, the effect of distance is steadily
eroding over time. In 1974 the elasticity of air transportation costs with respect to distance was 0.43, but
had dropped to 0.16 by 2004. To better understand the impact of this change, we can calculate the air
shipping price paid by an exporter 14,000 kilometers from the US compared to an exporter 2,000
kilometers away. The distant exporter would have paid air shipping prices that were 2.3 times that of theproximate exporter in 1974, but only 1.3 times that of the proximate exporter in 2004.
Fuel prices are an important determinant of costs. Several studies have examined the elasticity of aviation
costs with respect to fuel prices (hereafter: fuel elasticity). Using the 1974-2004 time series and a CobbDouglas cost structure, Hummels (2007a) estimates that a fuel elasticity of 0.26. To the extent that thetechnology for passenger aviation and cargo aviation is similar, other studies focused on passenger aviation
may be useful. Caves et al (1984) estimate translog cost functions for US passenger airlines from 19701981, and find a direct fuel elasticity ranging from .166 to .196.4 Chua et al (2005) provide similar
estimates on quarterly data from 1994-2001, and find a direct fuel elasticity ranging from .11 to .126. Oumand Yu (1998) examine worldwide passenger aviation from 1986-1993 and estimate a direct fuel elasticity
of 153.
Thus we have cost estimates ranging from .11 to .26, depending on the functional forms employed, thetime period, and whether the data sample uses cargo v. passenger aviation. These numbers imply that
doubling oil prices, say from $50 to $100 a barrel, would result in aviation cost increases of 11 to 26
percent. However, these estimates significantly understate the cost increases experienced by passenger
aviation in the last few years.
Figure 3-2 displays data on airline (passenger and mixed use passenger/cargo) operating costs taken fromthe Air Transport Association. It shows aggregate measures of operating costs (indexed to 100 in 2000),along with an index of fuel costs, and the share of fuel costs in overall operating expenses. Airline
operating costs have risen 89 percent since 2000 and much of that increase can be ascribed to fuel cost
increases. Recall that the BLS cargo price indices in Figure 2-3 rose sharply sometime after 2001. In thefirst quarter 2002, the fuel price index was at 79, the overall cost index was at 110, and fuel costs
represented just 9.9% of operating costs. By first quarter 2008, the fuel cost index was at 358.7, the overall
cost index had reached 229, and fuel represented 29.4% of airline operating expenses.
These numbers allow for a simple back of the envelope calculation of the fuel elasticity. Dividing the (log)
percentage change in total costs by the (log) percentage change in fuel prices, we get a fuel elasticity of

4.

Translog cost functions include interactions between each input cost and other inputs. To evaluate
the total effect of an input cost shock on total fares it is necessary to evaluate the partial
derivatives of the cost function at the means of the other variables. Unfortunately, the Caves et al,
Chua et al, and Oum and Yu studies cited here do not report other variable means so only the
direct effects can be calculated.

14© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels⎛ 228 ⎞ ⎛ 358.7 ⎞ln ⎜⎟ / ln ⎜⎟ = .48⎝ 110 ⎠ ⎝ 79.7 ⎠That is, a doubling of fuel prices leads to a nearly 50 percent increase in aviation costs.
3.B.

Ocean shipping

3.B.1.

Technology and Institutional Change -- Containerization and Open Registries

Ocean shipping has undergone several important technological and institutional changes in the post-war
era including the growth of open registry shipping and the introduction of containerization. Open registry
shipping is the practice of registering ships under flags of convenience – for example, Liberia or Panama-to circumvent higher regulatory and manning costs imposed by wealthier nations. Open registry fleetscomprised 5 percent of world shipping tonnage in 1950, 31.1 percent in 1980, and 48.5 percent in 2000.
(OECD, Maritime Transport, for 1950; UNCTAD Review of Maritime Transport, various years). Tolofari(1989) estimates that vessel operating costs for open registry ships are from 12 to 27 percent lower than
traditional registry fleets, with most of the estimated savings coming from manning expenses.
Containerized shipping is thought by many specialists to be one of the most important transportation
revolutions in the twentieth century. (Levinson 2006) The use of standardized containers provides costsavings by allowing goods to be packed once and moved over long distances via a variety of transportmodes--truck, rail, ocean liner, rail, then truck again--without being unpacked and repacked. This reduces
direct port costs such as storage and stevedoring (port labor) as well as indirect costs incurred during
lengthy port stops (the rental rate on unused capital while a ship sits idle in port). The indirect costs are
critical: estimates place break-bulk (non-container) cargo ships’ time in port at one-half to two-thirds of the
ship’s life (UNCTAD, Unitization of Cargo). Containerization also creates savings on the ocean leg.
Larger and faster ships substantially reduce the price per ton-mile while the ship is steaming, but they incur
higher indirect port costs (idle time) in proportion to their increased capital expense.(Gilman, 1983).
Because containerships spend more time steaming, investments in larger, faster ships become feasible.
Containerized shipping was first introduced in the United States in the 1960s, then on U.S.-Europe andU.S.-Japan routes in the late 1960s and into the 1970s, then to developing countries from the late 1970s
onward. The reason behind this seemingly slow pattern of diffusion lies in the large fixed costs ofadoption, and the differential cost savings containers yield. To make full use of containerization requires
container-ready ocean liners and ports adapted to container use, which requires specialized cranes, storage
areas, and rail-heads. As a result, containerization was first adopted on the most heavily traded routes.
Developing nations were especially slow to adopt, both because of lower scale and because of factor
prices. In countries where capital is scarce and labor abundant, the capital cost of building container ports
is higher, and the port labor cost savings of containers much lower.
How big are the cost savings from adopting containerization? Blonigen and Wilson (2006) use the US
Waterborne Trade Database 1990-2004 to estimate that doubling the share of trade that is containerized
lowers shipping costs by 5 percent. Hummels (2007) uses a longer time series (1974-2004) that spans theperiod in which adoption of containerization was underway and in which there is a much more pronounced"before and after" effect of adoption to measure. He finds that, for a given exporter and commodity,
doubling the percentage of cargo that is containerized leads to a reduction in shipping costs of 13.4 percent.
3.B.2.

Other Input Costs.

Figure 2-5 shows that ocean liner freight rates were rising sharply in the period shortly after the
introduction of containerization to European liner trades. If containerization and the associatedproductivity gains led to lower shipping prices, as Levinson (2006) qualitatively documents, and BlonigenWilson (2006) and Hummels (2007a) estimate, why does the effect not show up in price indices capturing© OECD/ITF, 200915

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
the cost of liner shipping?
In the period during which containerization was spreading, other input costs including fuel, ship prices, andport costs, were skyrocketing. An UNCTAD (1977) study, “Port Problems,” revealed port cost increases in
the 1970s ranging from 10 to 40 percent per annum, resulting in an overall increase in liner conference
costs of as much as 7.5 percent per annum. Sletmo and Williams (1981) report that rising steel and laborcosts resulted in sharply higher shipbuilding prices in the 70s and that liner operating costs rose 14-18
percent per annum in the 1970s as a result of the oil price shocks.
This historical experience is relevant because it suggests that congestion and fuel prices can swamp
technological advances. Recall that Figures 2-6 and 2-7 show steady downward trends in US ocean and air
shipping prices. However, part of this apparent decline may be due to the fact that the US data series starts
in 1974 when oil prices – a critical transportation input – were unusually high. Using the historical data,
Hummels (2007a) estimates an elasticity of ocean cargo costs with respect to fuel prices between .23 and.32. Ocean bunker fuel prices rose four-fold in real terms between 1973 and 1974. Combining this with themeasured elasticity of 0.232 implies a 92 percent increase in ocean shipping costs in this year. That
estimate matches very closely to estimates of fuel-related cost increases constructed from shipping fleet
micro data (Sletmo and Williams, 1981). Taking the average fitted value of ocean shipping costs in 1974
from Figure 2-7 (9.9 percent ad-valorem) and using this implied cost shock gives 1973 ad-valorem ocean
costs of 5.2 percent – a level comparable to rates in 2000.
As noted in the discussion of aviation costs, recent increases in oil prices resulted in substantial increases
in the cost of cargo and passenger aviation. Were there similar increases for ocean shipping? Table 3-1
reports crude oil prices and liner rates ($ per TEU) for major liner routes at quarterly frequencies between
1998 and 2008. The liner data are collected and reported online by Containerisation International. Between
2002Q1 and 2004Q4, oil prices doubled. Freight rates also increased, by an average of 25 percent acrossall routes. This implies an elasticity of freight rates with respect oil prices of .25, quite similar to theestimate from Hummels (2007a). Between 2004Q4 and 2008Q1 oil prices doubled again, but liner rates
only increased by 11 percent on average, for an implied elasticity of .11.
Note however that rates of change differ substantially across routes. For example, from 2002Q1 to
2004Q4 routes outbound from the US experienced declines in rates, while routes outbound from Asia andEurope experienced very large increases -- as much as 71 percent for cargos outbound from Asia to
Europe. Two explanations for this variable response to large fuel price increases come to mind. First, thefuel intensity of liner service depends on the length of route. On short hauls time spent in port and port
costs comprise a larger share of operating expenses, while on longer hauls such as Asia-Europe trade port
charges are less important and fuel prices figure more prominently in overall costs. Second, capacity
constraints may lead to lead to sharply rising prices when volumes increase, as well as unbalanced rates asa function of unbalanced trade. For example, Asia to the US rates are double the reverse, likely reflecting
the large imbalance in trade volumes driven by US trade deficits. A consequence is that, while higher fuelcost do show up in higher rates, the correspondence is much weaker than is seen in aviation.

16© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels

3.B.3.

Scale Effects and Market PowerThe rise in world trade may have had significant impacts on shipping prices through scale effects. In
periods of rapidly rising demand, shipping capacity becomes scarce, ports become congested, and spot
shipping prices rise quickly. This is readily apparent from inspection of Table 3-1. Imbalances in tradelead to large differences in rates on the same trade route, depending on the direction of the flow. Similarly,
at the height of the US business cycle in 1999-2000 shipments from Asia ran as high as $2203 per TEU.
These rates dropped nearly 50% by the low point of the US recession in 2001-2.
Over longer periods however, rising demand for shipping may actually lower shipping prices, especially insmaller countries with low trade volumes. To explain, the capacity of a modern ocean-going liner vessel islarge relative to the quantities shipped by smaller exporting nations. As a consequence, vessels may stop ina dozen ports and in different countries to reach capacity. As trade quantities increase, it is possible to more
effectively realize gains from several sources. First, a densely traded route allows for effective use of hub
and spoke shipping economies – small container vessels move quantities into a hub where containers areaggregated into much larger and faster containerships for longer hauls. Second, larger trade volumes allow
for the introduction of specialized vessels (reefers, ro-ros) and larger ships that enjoy substantial costsavings relative to older smaller models still in use. Third, larger trade volumes induce investment in port
infrastructure, and better port infrastructure is highly correlated with lower shipping costs (Limao and
Venables (2001), Clark et al (2004), Fink et al (2002), and Haveman et al 2008).
Hummels, Lugovskyy, and Skiba (2008) systematically examine the effect of market power in shipping,
and their arguments and evidence are worth reviewing in depth. First, trade growth along a route promotes
greater entry by shipping lines: In 2006 one in six importer-exporter pairs was served by a single liner
service, and over half were served by three or fewer. Figure 3-3 (taken from Hummels et al 2008) displays
the number of shipping lines on a trade route graphed against exporter GDP -- large countries enjoy more
firms competing for their trade.
To show how market power works, Hummels et al (2008) model the shipping industry as a Cournot
oligopoly and determine optimal shipping markups as a function of the number of carriers and theelasticity of transportation demand faced by carriers. A key insight of the model is that transportation is notconsumed directly; instead carriers face transportation demand derived indirectly from import demand.
This implies that the impact of an increased shipping markup on the demand for transportation depends on
the share of transportation costs in the delivered price of the good, and elasticity of import demand.
To make plain the intuition behind the model, suppose the marginal cost of shipping either of two goods
equals $10, and carriers are considering adding a $5 markup. The first good has a factory price of $10, so
the markup will increase the delivered price by 25%. The second good has a factory price of $90, so themarkup increases the delivered price by 5%. The same shipping markup has a much larger effect on thedelivered price of the $10 good because shipping costs represent a larger share of the delivered price.
Further, when considering the impact of shipping prices on the delivered price of goods, it is necessary to
examine product prices inclusive of tariffs. Raising the tariff on a good raises its price inclusive of thetariff, lowers the percentage impact of a given transportation charge on the delivered price, and therefore
increases the optimal shipping markup. This suggests a particularly deleterious role for tariffs in limiting
trade. Tariffs raise foreign goods prices directly by taxing them, and indirectly by inducing higher shipping
prices, and both reduce trade flows.
A second key point of the Hummels et al model relates to the responsiveness of trade to increased prices.
Returning to our example above, now suppose we have two traded goods with a factory gate price of $90
and marginal costs of shipping equal to $10, so that a markup of $5 will yield an equal 5% increase in thedelivered price of each good. The first good is a differentiated product and faces an import demand
elasticity equal to 1.1. Here, a markup that yields a 5% increase in delivered price reduces traded
quantities, and therefore demand for transportation services, by only 5.5%. The second good is a highly© OECD/ITF, 200917

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
substitutable commodity and faces an import demand elasticity of 10. Here, the markup raises prices by
5% but lowers quantities traded and demand for transportation services by 50%! In the latter case theidentical markup reduces import (and therefore transportation) demand to a much greater degree, limiting
the carrier’s optimal markup.
Hummels et al (2008) show that the market power of shipping firms is extremely high when they are
moving goods with inelastic import demand, and when marginal costs of comprise a small fraction of theoverall delivered price. In these cases, it is easy to generate examples where optimal markups could be anorder of magnitude higher than the marginal cost of shipping. However, entry by rival liner companies canvery quickly erode this pricing power. Using typical values for shipping costs and import demand
elasticities, a monopoly shipper would charge a markup 6 times marginal costs of shipping, while entry bya single rival would cut this markup in half. Hummels et al (2008) provide strong empirical evidence forthe theoretical claims: shipping prices are higher when (a) goods prices are high; (b) tariffs are high; (c)import demand elasticities are low; and (d) the number of rival firms are low. They claim that these effects
generate the majority of variation in transport prices observed in the data.
4.

Trends in Globalization from a Freight Perspective

In the preceding sections we document significant changes in modal usage and in freight costs. Toalarge extent freight costs move in response to changes in technology and shocks to input costs (oil,shipbuilding, port congestion). But freight costs are also affected by what is being traded, and that haschanged over time. Similarly, modal usage responds to changes in relative prices – when air shipping falls
in price more firms employ air cargo. But the benefit derived from air shipping depends on what is traded,
and that has changed over time. In this section I discuss trends in globalization and how they affect freight
demand. I focus on changes in the commodity composition of trade, changes in the organization of
production, and changes in the partner composition of trade.
4.A.

The Changing Commodity Composition of Trade

4.A.1.

Growth in Manufacturing.

Table 1-1 shows that from 1955-2004 trade in manufactured goods grew 27-fold in real terms from $222
bn to $6022bn, roughly four times faster than all other trade. The shift from trade in agricultural andextractive goods to trade in manufactured goods affects transportation demand in (at least) six ways. I
briefly summarize them here, and develop many of these themes in greater depth in the following sections.
First, it raises the demand for air transport relative to other modes. This is because manufactured goods
have, on average, a lower weight/value ratio than do commodities, and because they are more time
sensitive. Second, manufactured goods are containerized to a much greater extent than bulk commodities,
allowing the use of standardized vessels. Third, as just argued in the section on market power in shipping,transportation demand is a derived demand and depends on product characteristics, including weight/value
and the import demand elasticity for goods. Both are lower for manufactures than for commodities
resulting in, ceteris paribus, greater market power for shipping firms. Fourth, production of manufactures ismuch more footloose than is trade in commodities: countries can develop a comparative advantage intextile production, but they are either endowed with oil and iron ore, or they are not. This means thatlogistics capabilities become an important source of comparative advantage – firms can compete ondelivery time and price. Fifth, and related, production of manufactures can be fragmented into stages andthe ability to move goods (and people) in a timely and coordinated manner between stages is paramount.
Sixth, manufactured goods proceed through life cycles of introduction and then slow maturation, which
implies that demand for manufactures is initially uncertain and firms must experiment with potentiallysuccessful goods. This implies a life-cycle of transportation demand as well, with early stages requiring
flexibility, and subject to low scale.

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Forum Paper 2009-3:David Hummels
4.A.2.

The weight to value ratio of trade

Transportation specialists are accustomed to thinking of transportation costs in per unit terms, the cost oftransportation services necessary to move grain a ton-km or to move one TEU container from Los Angeles
to Hong Kong. International trade specialists who pay attention to shipping costs as an impediment to tradeare accustomed to thinking of these costs in ad-valorem terms, the cost of transportation services necessary
to move a dollar of grain or microchips between two points. The distinction is important because even if
the cost of moving one TEU container remains constant over time the ad-valorem cost and the implied
impediment to trade will change as the contents of the container grow more valuable.
To see this, suppose we sell one kilogram of a good at a price per kg of p, and pay shipping costs f per kg
shipped. Note that the price per kilogram, p, is just the value/weight ratio, that is, the inverse of theweight/value ratio. If the shipping price per kg f is independent of the goods price per kg, the ratio ofdestination to origin prices is(0.1)

p * ( p + f )qfweight== 1+ = 1+ f (
)
p
pq
p
value

If the container holds scrap metal, p is low (weight/value is high), and the ratio p*/p is high. That is,shipping charges drive a large wedge between the prices at the origin and destination. If the container holds
micro chips, p is very high (weight/value is very low), the ratio p*/p is close to 1, and shipping charges
drive only a small wedge between prices at the origin and destination.
Of course, the shipping charge f may be increasing in the value of the container’s content because higher
value goods require more careful handling and a larger insurance premium. The shipping charge f may also
be increasing because optimal markups are rising in p, as discussed in the market power section (3.b.3)
βabove. We can then write the per kg shipping charge as f = p X , where X represents other costs shifters
such as distance, port quality and so on. In this case we havep * / p = 1 + p1− β X = 1 + X ((0.2)

weight β −1)
value

Unless β = 1 the weight/value ratio of a product will be an important determinant of the transportation
expenses incurred when trading that product. Hummels and Skiba (2005) and Hummels, Lugovskyy and
Skiba (2007) examine the dependence of shipping costs on product weight/value. They estimate that a 10
percent increase in product weight/value leads to a 4-6 percent increase in shipping costs measured advalorem, i.e. relative to the value of the good shipped. Further, since there is tremendous variation acrossproducts in weight/value ratios, weight/value explains far more variation in observed transportation costs
than do other observables including: the distance goods are shipped, the technology with which they areshipped, the quality of port infrastructure, or the intensity of competition between carriers on a trade route.
To see how this calculation works, take Hummels' (2007a) estimate that the elasticity of air shipping costswith respect to weight/value is 0.492. By measuring goods prices in units of price/kilogram, we can use thecoefficient on weight/value to calculate the freight charges faced by high- and low-priced goods. For
example, a volume of shoes that is worth $100 per kilogram will face much lower ad valorem costs of air
shipping than shoes worth $10 per kilogram:f $100 / f $10 = ($100 / kg 0.494−1)= .31$10 / kgAs Schott (2003) notes, the variance of U.S. import prices within a particular product category has grownover time. As the spread between high-priced and low-priced goods in each product category widens, thetransportation cost advantage enjoyed by high-end goods is growing over time.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
Figure 4-1 provide data on the weight/value ratio (kg/$ -- in constant year 2000$) for the imports andexports of several EU countries from 1988-2007. These data are calculated by collecting the weight /value
ratio of each shipment, and aggregating. More specifically, denote the reporting country as i, their partner
as j, the product shipped (CN 8) as k, and the year as t. Then the weight/value ratio of the shipment is

ϖ i , j , k ,t =( weight in kg )i , j ,k ,t( value in 2000$ )i , j ,k ,tWe can then aggregate the weight/value ratio for a particular country and year by summing the weight overall shipments divided by the value over all shipments,

ϖ i ,t =∑ ( weight in kg )∑ ( value in 2000$ )
j ,k

j ,k

i , j , k ,ti , j , k ,twhich is equivalent to multiplying the weight/value ratio of each shipment by its share in trade for thatcountry and time period, and summing.

ϖ i ,t = ∑ j ,k ϖ ijkt s jk
Figure 4-1 shows no obvious trend over time in weight/value ratios for the included country. However itdoes reveal several interesting facts. First, with the exception of Greece and France, imports are heavier
than exports, a likely indication that trade costs on imports exceed those on exports. Second, the weight ofexports is especially low for Ireland and for the UK, which explains why these countries rely on air
shipping of exports to a far greater extent than do other EU countries.(see Table 1-4).
Figure 4-2 calculates aggregate weight/value ratios similarly, except that it aggregates over all EU
countries but disaggregates by continental partner. This shows how EU trade with Asia and North America
differs from trade with Latin America and Africa. Trade with Asia and North America, both imports andexports, is extremely light. Imports from all other sources are much heavier, reflecting the importance ofbulk commodities in trade with the continents.
Contrast this with data calculated for Asian trade in Hummels (2008). Figure 4-3 reports time series onweight/value measured in kg per constant year (2000) US dollars for each Asian country’s imports (solidline) and exports (dashed line) in Figure 1. Several patterns are notable. One, a dollar of exports weighs
far less for the developed market economies (Japan, Korea, Taiwan, Hong Kong, Singapore) than for the
emerging market economies. Indonesia is a notable outlier in the weight of its exports, which are almost 40
times heavier per dollar than those of Singapore or Japan. Two, most of these Asian economies (with the
exception of Malaysia and Indonesia) are net importers of weight, that is, their import bundles weigh far
more than do their export bundles. Three, China’s imports are getting heavier and exports are getting
lighter as China imports raw materials, transforms them, and shifts increasingly to high value exports.
In addition to affecting the ad-valorem transportation charge, reductions in weight/value make it easier toshift from ocean to air shipping because it reduces the ad-valorem price differential between the twomodes. Consider this example. I want to import a $16 bottle of wine from France. Air shipping costs of $8
are twice ocean shipping costs of $4. Going from ocean to air increases the delivered cost by $4 or
25 percent. Now suppose my tastes improve and I want to import a $160 bottle of wine from France so thatthe weight/value ratio of the product has dropped sharply. The shipping costs are the same, but now the $4
cost to upgrade to air shipping represents just a 2.5 percent increase in the delivered price. The consumer ismuch more likely to use the more expensive shipping option when the effect on delivered price is smaller.
If we arrange goods along a continuum from heaviest to lightest, goods at the heaviest part of thecontinuum tend to be ocean shipped, and those at the lightest part tend to be air shipped. This pattern canbe seen in the level of the ad valorem freight expenditures in Figures 2-7 and 2-8, where ocean shipping

20© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels
appears to be much more expensive than air shipping. It is not: the higher costs incurred for ocean shipping
are due to the fact that the average ocean-shipped manufactured good is 25 times heavier than the average
air shipped manufactured goods. As the relative price of air/ocean shipping falls, goods at the margin shift
from ocean to air shipping (Harrigan (2005) provides a formal model of this process). This point helps us
to explain several patterns of modal use shown in Tables 1-3 and 1-4. There we see that the UK and Ireland
use a very high ratio of air relative to sea transport. An important reason for that is that the weight/value
ratio of their trade is lower than other EU countries.
As a final point, recent research has shown clearly that, within product categories, high income households
buy higher quality goods. The result is that higher income countries import higher quality goods5. Risingincomes affect demand for transport in three ways. One, higher quality goods have higher prices andtherefore a lower ad-valorem transportation cost for reasons just discussed. Two, as consumers grow richer,so does their willingness to pay for precise product characteristics.6. That in turn puts pressure on
manufactures to produce to those specifications, and be rapidly adaptable. Three, delivery speed is itself an
important characteristic of product quality, and will be in greater demand as income grows.
4.A.3.

Time Costs

Delivery speed is an important characteristic of transportation quality, and increasingly, an importantcharacteristic of the quality of the delivered good. Time in transit doesn’t matter much for bulk
commodities and simple manufactures. But for goods like fresh produce and cut flowers, lengthy travel
times lead to spoilage. More generally, if there is uncertainty in demand plus lags between production andfinal sales, firms may face a mismatch between what consumers want and what the firm has available tosell. In the case of apparel, for example, firms are unable to predict in advance which fashions will beespecially popular, making the ability to respond quickly to revelation of market information an important
advantage. Evans and Harrigan (2003) show that clothing lines with high re-stocking rates are more likely
to be obtained from exporters closest to the US market. Aizenman (2004) argues theoretically and Schaur(2006) shows empirically that the use of airplanes is an alternative solution to the timeliness problem when
foreign demand is uncertain. By using a mix of ocean and air shipping firms can respond rapidly todemand shocks, essentially using airplanes as a real hedge for market volatility.
Hummels and Schaur (2008) estimate the value of time saving using US imports data that report the priceand quantity of air shipping relative to ocean shipping as well as time delays associated with ocean
shipping. The idea is that a firms’ willingness to pay for more expensive air shipping is increasing in thenumber of days saved with airplanes, and decreasing in the premium paid to air ship. The sensitivity of air
shipment to these factors can then be used to calculate a per day valuation for time savings that is productspecific.

τCall this per day valuation for an product k, k . Table 4-1 (taken from Hummels, Minor, Reisman, Endean2007) reports Hummels-Schaur estimates for various goods. As with the weight / value ratio we can thencalculate the aggregate time sensitivity of a country’s trade bundle by multiplying the product specific time
cost by the share of that product k in the trade bundle. Since these shares differ across countries, the time
sensitivity of their trade bundle will also vary. Table 4-2 (taken from Hummels, Minor, Reisman, Endean2007) reports the per day equivalents for the import and export bundles of various regional groupings.
Table 4-3 (taken from Hummels 2008) report the time sensitivity of the import and export bundle for anumber of Asian countries. The values are written in ad-valorem equivalents per day. A value of 0.77 for
Chinese exports means that each day of delay in transit is equivalent to a tariff of 0.77 percent, so that a 4
day delay is equivalent to a tariff of just over 3 percent ad-valorem.
Two things are notable about these figures. First, time sensitivity is much more important for the developed
5.
6.

Hallak (2005), Choi et al (2007).
Hummels and Lugovskyy (2005).

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviationcompared to the emerging market economies. Second, the time sensitivity of the import and export bundles
are considerably different – developed markets export goods that are more time sensitive than the import,
while the emerging market do the reverse. Note that the import bundles of India and Indonesia are twice astime sensitive as their exports. Of course, the numbers on time sensitivity in the last two columns of Table
4-1 are intended to capture aggregate tendencies, and do not reflect the sensitivity of particular sectors.
Malaysia, for example, ships extremely time sensitive products to the US as demonstrated by the very highshare of air shipping shown in the first two columns of Table 4-1.
Finally, Table 4-4 (taken from Hummels, Minor, Reisman, Endean 2007) reports the time costs of varioustransport delays (calculated by the World Bank Doing Business Survey) and compares these to the applied
tariffs for each region. Total time costs are typically larger than tariffs, and arise from a combination ofdelays at ports, customs, and inland transit. Note that these numbers entirely omit costs associated with theinternational leg of the journey.
4.B

The Changing Geography of Trade

The geography of trade, in this context, means both which partners a country trades with and what parts ofa country (internal v. external) engage in trade. Partner composition matters for two important reasonsFirst, whether a country trades with neighboring or perhaps continental partners. Second, whether
a country trades with near or distant partners.
Trading with neighboring or continental partners matters enormously because it enables the use of landbased transport modes (rail, truck, pipelines). The revealed preference for land over other modes isapparent in Table 1-2 which shows the prevalence of land use, when feasible, for Latin America and the
US. There are likely three reasons for this revealed preference. One, it is less expensive. For US imports
from Canada and Mexico it is possible to directly compare the cost of land, air, and ocean modes, and landbased shipping incurs a smaller ad-valorem cost. Two, and perhaps related, land-based modes allow for amore granular transportation network with direct connections between production origin and consumption
point. Three, land-based modes allow for smaller consignments. US imports data make clear that shipment
sizes are smaller and shipment frequencies are higher when land-modes are used. This is critical in cases
where initial scale is small or where demand is uncertain (more below).
Trade with near v. distance partners also matters for the choice of ocean v. air shipping when land-basedmodes are not an option. Suppose I am trying to decide between air and ocean shipping in reach two
foreign markets, the first proximate to and the second distant from my exporter. How does the distanceaffect my calculation of the appropriate mode to use? Exporters consider two costs, both rising in distance.
The first is the direct cost of transport, and the second is the time cost.
To measure the direct distance cost, one should compare the elasticity of air shipping costs with respect todistance to the elasticity of ocean shipping costs with respect to distance. Hummels 2007 estimates that, in
1974, the distance elasticity for air shipping costs was almost three times that of ocean shipping (.44compared to .15). In that year, doubling distance raised air shipping prices by 44 percent while only
raising ocean shipping prices by 15 percent. In other words, the direct effect of distance on the cost of
shipping represented a rising penalty on air shipping. However, Hummels 2007 also estimates that theelasticity of air shipping costs with respect to distance fell steadily so that by 2004 it was virtually equal tothat of ocean shipping. In this case, both air and ocean costs are rising in distance at the same rate so that
distance does not affect the relative price.
Regrettably data to perform this calculation are not available after 2004. I surmise that the changing
distance elasticity has much to do with the very high oil prices in 1974 and the lower prices faced
thereafter. That is, the distance elasticity for air will be higher when oil prices are high. If this is correct,
then I would expect that very high fuel prices from 2004-2008 would result in a distance elasticity similar
to that in the 1970s.

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Forum Paper 2009-3:David Hummels
The other cost of distance is the time cost. Choosing air transport from the UK to France might save ashipper 5 hours, while choosing air transport from China to France might save 5 weeks. How does ashipper balance the direct cost against the time costs? The answer is product specific and provided by
Hummels and Schaur (2008) – see above. However, a general statement is that an air premium may be
worth paying to save 5 weeks, but not 5 hours. That is, at short distances the direct cost wins out while atlonger distances (and for time sensitive goods) the time cost dominates. This is likely why air shipping isused far less extensively for intra-continental trade than for trade at a longer distance.
As a final point, geographic remoteness of another kind can be overcome by using airplanes. Ocean port
cities act as entrepots for interior regions of their own countries. These entrepot cities can be a bottleneckchoking off trade, especially for geographically large countries with economically important interior
regions. This becomes more pronounced in cases where ports vie for land and coastal access that retains
significant value for housing and public amenities. Trucks arriving at and departing these facilities also
compete with other users of roadways, leading to major highway congestion and significant pollution
effects. Air cargo that overflies congested ports can be an effective way to reach remote interior regions.
This can be seen clearly in US data, where the share of coastal facilities is shrinking in favor of directtransport into the US interior7.
4.C.

The Changing Organization of Production.

4.C.1.

Vertical Specialization and Global Supply Chains.

A hallmark of recent trade growth is the fragmentation of international production processes, also known
as vertical specialization, slicing up the value chain, or unbundling supply chains8. What it is called, it
simply means that production of certain manufactured goods takes place in multiple distinct stages andthese stages are increasingly geographically dispersed.
How important is this phenomenon? One way to measure the fragmentation process is to look at the shareof trade that occurs in goods labeled “parts and components”. This approach has been widely employed
and is useful, but it also leaves out intermediate goods (e.g. chemicals) that do not contain the “parts andcomponents” label. An alternative approach introduced in Hummels, Ishii and Yi (2001) is to employ
input-output tables that track use of imported intermediate inputs. Hummels and Puzzello (2008) use thisapproach in conjunction with the Asian Input-Output data produced by IDE-JETRO for 1975-2000. Table
4-5 taken from their work, shows the growth in input trade from 1975-2000, both relative to gross output
and relative to total trade. The use of imported inputs as a share of gross output has grown enormously –more than 300% in Malaysia, Thailand, and the Philippines. Input trade as a share of total trade is now 6070 percent for most of Asia.
Scholars have provided several theoretical explanations for the growth in fragmentation. Broadly speaking,these theoretical treatments argue that each country enjoys a comparative advantage in a different stage of
production (R&D, production of various parts and components, assembly) and so in a world of frictionlesstrade, each country would specialize in that stage. However, if moving goods (and people and ideas)
around is costly, then fragmentation will be costly. This creates a tension for firms – separating stages canlower production costs for each stage but raise the costs of transport and coordination. When comparativeadvantage is strong the first force wins out and fragmentation increases. When trade costs rise the second
force wins out and fragmentation decreases. Yi (2003) notes that because products engage in “roundtripping” – with inputs being shipped multiple times as components of complex manufactures are graduallybuilt up into an assembled final product – the impact of transport costs are multiplied by the number oftimes a component in shipped. As a result, small reductions in costs over time can yield large increases infragmentation and trade as a whole.
7.
8.

Haveman and Hummels (2004)
The phenomenon appears to have as many names as authors writing about it.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
It should be said, however, that empirical evidence on the causes of rising fragmentation is fairly weak.
The most direct evidence (that this author knows of) comes from Hummels and Puzzello (2008), who
control for variation in expenditures by using industry to show that input trade is vastly more "homebiased" than final goods trade. In addition, input trade is far more likely to take place with neighboring
countries and with partners that share a common language. However, all these effects were quite strong
from 1975-1995, they have weakened substantially from 1995-2000.
More speculatively, I would point to three key factors explaining the rise in fragmentation. First,
information technology makes it easier for firms to communicate information between stages of
production. This information could take the form of blue prints, quality validation, or inventory
management. Second, coordinating production requires moving managers and engineers between far flung
production plants, and this is greatly aided both by lower air passenger rates (through 2000), and by agreater density of air connections. Third, timeliness in delivery is critical as entire factories can be
shuttered by the absence of key components and achieving timeliness in delivery is greatly assisted bylower air cargo costs (again, through 2000).
These three points suggest that fragmentation puts a much larger strain on transport and trade infrastructure
than other types of production arrangements. Put another way, fragmentation is extremely transportationintensive. Fragmented products move multiple times rather than once. Fragmented products use airplanes
more intensively than container ships. Fragmented production processes require frequent shuttling ofexecutives and engineers around the globe. As such, these processes may be quite sensitive to rising fuelcosts after 2000 and greatly curtailed by it, though it will be some time before data are available to test thishypothesis.
4.C.2.

"Small value" trade and Testing Markets

Recent theoretical and empirical research in international trade has begun to emphasize the importance ofextensive and intensive margins of trade expansion. A country can expand exports by trading larger
quantities of a given set of goods (the intensive margin), or by expanding set of goods that are traded (theextensive margin). Higher trade costs can affect both margins9.
For example, suppose that exporting firms must pay a fixed cost of trade (for example, the cost ofcollecting information about foreign markets or setting up distribution networks) and marginal costs oftrade (proportional to quantities traded). In this case, firms must sell a sufficiently high volume of exports
to justify paying the fixed costs. A fall in marginal costs of trade lowers delivered prices and expands
quantities demanded abroad. This has two effects: existing exporters can sell larger quantities (an increasein the intensive margin), and more firms can now cover their fixed costs of trade and begin exporting forthe first time (an increase in the extensive margin). In contrast, a drop in fixed costs of trade leads to trade
expansion only along the extensive margin.

9.

See Hummels and Klenow (2005) on extensive and intensive margin expansion and Hillberry and
Hummels (2007) and Eaton, Kortum, and Kramarz (2004) on the role of geographic frictions.

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Forum Paper 2009-3:David Hummels
Which of these are most important? In order to decompose trade growth in this manner, write the aggregate
value of a country c’s exports at time t as
(0.3)

N cjktX tc = N cjkt X cjkt
is the number of unique shipments of products k (measured at the 6 digit level of the Harmonized

Xc

System) to destinations j from exporter c at time t, and jkt is the average value per unique shipment. If cships 10 distinct products apiece to each of 5 destination markets the number of unique shipments is 5010.
Exports could increase over time because country c ships more goods, has more export destinations pergood or higher average value per shipment. (Note that it is also possible to separate N into the number of
products and number of destinations per product. However, at this 6 digit HS level of aggregation we seevery little growth in number of products traded in this period. As a result, changes in the number of unique
shipments for these countries and this time period are driven almost entirely by expansions in the numberof markets with which trade occurs.)
We can then express the log percentage change in total exports over time as the sum of the log
changes in the components, that isln

N cjkt +1
X cjkt +1
X tc+1
=
ln
+
ln
X tc
N cjktX cjktThis is useful because we can then assess the percentage contribution of each component to the totalchange.
Table 4-6 provides this decomposition for Mexico's very rapid export expansion from 1991-2004. In thisperiod Mexican exports to the US increased dramatically, a log percentage change of 1.374. How did thisgrowth occur? If we define goods using the HS 6 classification, the answer is: primarily along the intensive
margin. The mean value per shipment grew by 1.145 log points, and number of goods grew by only .228
log points. That is, 83 percent (=1.145/1.374) of export growth was along the intensive margin and 17
percent was along the extensive margin. However, if one disaggregates down to 10 digit categories, thenthe extensive margin growth becomes much more apparent. In this case, almost 30 percent of the growth isin new products.
Table 4-7 (taken from Hummels 2008) provides a similar decomposition separately for imports and exportsof each Asian country. For simplicity I report only the log change in each variable. For example, the log
change in Chinese exports between 1995 and 2005 is ln(675/161)=1.43. Of this 1.43, 0.80 came from anincrease in the number of unique shipments, and 0.63 came from an increase in average value pershipment. Contrast this mixed growth with Thailand and Malaysia where almost all growth came via an
increase in the number of shipments rather than an increase in the average shipment. Conversely, almost all
the growth for Hong Kong and Japan came through an increase in average shipment size rather than anincrease in the number of unique shipments.
The calculation of the changes in average shipment size can be misleading – the average can rise because
all existing shipments get larger, or it could be that shipment size grows differentially at different points inthe size distribution. To show this distinction Table 4-7 also reports growth in the size of the median and90th percentile shipment. By comparing these to growth in the mean shipment we can understand wheretrade growth is occurring.
Consider Chinese exports, where the number of shipments and mean shipment size are growing rapidly, as
are 90th percentile shipments, but median shipment sizes are falling. This indicates that China has
10.

One could further decompose this into the number of products multiplied by the average number ofdestinations per product.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
experienced a tremendous growth in new shipments but these tend to be very small, pushing down the
median shipment size. At the same time, established flows that were already large (90th percentile) in 1995
have grown larger still, and this increased the mean shipment size. The pattern across all reported countries
is similar – median shipment sizes are falling while mean shipment sizes are rising (or in some cases, bothare falling but medians are falling faster).
What do we learn from this exercise? For most of these countries we have export expansion occurring in
two very different ways – there are large and existing flows that are the principal drivers of aggregate trade
growth, but there are also a very large number of new entrants that, to date, do not yet represent a large
fraction of overall trade. This distinction matters for several reasons. One, the infrastructure needs of small
and medium size firms may be considerably different than those of large firms. They typically lack theinternal capacity for facilitating trade and must work through trade intermediaries to gather information
about foreign market opportunities, and to handle trade finance, transportation and distribution functions.
Two, small firms face higher shipment costs because they are unable to negotiate bulk discounts. Three, if
we take the fixed v. marginal cost view of trade costs, these new flows associated with small and medium
size firms are highly tenuous. Small increases in trade costs could kill off many exporting firms quickly.
Now, one could view this as a minor concern – these flows are small and their loss could be absorbed withlittle impact on aggregate numbers – but this ignores the dynamic nature of new flows. Besedes and Prusa(2003,2004) use survival analysis to show that new trade flows suffer high failure rates, but those that dosurvive go on to ever-larger trade shares. That is, today’s success story was yesterday’s fragile newborn.
Putting all this together it suggests that nations are increasingly growing their exports by shipping new
goods to new markets. What are the characteristics of these new markets? Most firms begin producing only
for a local market, slowly expand sales within their own country, and some small fraction of thesegradually expand sales abroad. Of these who go abroad, they initially look to neighboring countries.
Because of this process, new and unexploited markets tend to be further away. When serving these distantmarkets, firms face tremendous uncertainty about demand, quantities sold are likely to be very low
initially, and most trading relationships fail in a few years. All of these characteristics, initially small
quantities of uncertain demand in distant markets, are precisely the characteristics that make air shipping
particularly attractive. This suggests that airplanes may be an especially effective tool for firms wishing totest new markets11.
5.

Looking Forward: Future Trends in the Short and Long Run

Guessing at future trends is always hazardous. I will start with the recent short term disruptions
due to the financial crisis and economic slowdown of 2008. I will then turn to long run trends and discuss
their implications for transportation prices and demand. It should be understood that this forward look is
not based on any formal forecasting model but rather based on the author’s qualitative evaluation of trends.
5.A.

Short Run Trends

As this report is being written in Fall 2008, a severe financial crisis in the US has rippled outwards withsignificant effect on world financial markets. At the same time, economic growth on the real side of theeconomy is slowing. How will this affect trade and transportation demand?
Trade and the Business Cycle
Simply put, trade drops during recessions as income falls and the consumption share of income drops. Thiscan have a pronounced effect on those countries whose exports are tied closely to a single importing
market. For example, Mexico’s exports to the US tripled from 1994-2000, but declined for three years as a
11.

Aizenman (2003) and Schaur (2006) examine the use of airplanes in hedging demand volatility.
Evans and Harrigan (2005) and Harrigan and Venables (2004) discuss the importance of demand
volatility in determining comparative advantage and industrial agglomerations.

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Forum Paper 2009-3:David Hummels
consequence of the 2001 recession in the US. These effects are more likely to be pronounced when therecession is global, rather than isolated in a single country. When a country slides into recession by itself,
there is a quick remedy in the form of currency depreciation and export growth to stimulate aggregate
demand. But when multiple economies slide into recession simultaneously the prospects for an export-led
recovery are dimmed. This effect may be exacerbated by the tendency for economies sliding into recession
to look for any and all available means to boost output for their domestic industries. This makes short term
protectionist measures very attractive.
Oil Prices
Output responses will be more muted when prices adjust. Falling demand shows up in falling prices, andnowhere is this more apparent than in the precipitous drop in oil prices in the second half of 2008. While
this channel should indirectly boost trade and transportation demand, it is clearly a second order effectrelative to the first order income shocks.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
The Composition of Trade
Two of the recent trade trends outlined above become more problematic when output is contracting andincome is dropping. First, Alessandria, Kaboski and Midrigan (2008) show theoretically and empiricallythat “small value” trade, and the extensive margin of trade, is especially sensitive to demand declines. Thatis, demand declines cause trade to contract, but the effect is especially pronounced for firms that had small
trade volumes prior to the contraction. They are focused primarily on the effect of large real exchange rate
depreciations but the point goes through for recessionary contractions. Second, speed is a luxury good.
Overnight delivery of goods may be an easy thing to give up when income is tight. This seems likely totranslate into a reduction in the demand for express air transport.
5.B.

Long Run Trends

China and India will continue to growIn the last decade China and India have experienced dramatic economic growth that has fueled atremendous rise in trade volumes within Asia and the rest of the world. The major drivers of that growth,
factor accumulation and technological progress, show no signs of abating. It is possible that China inparticular will rely less on export-led growth, but the scope for inward-looking growth is large as
development and infrastructure continues to spread inland. This may result in slower growth in export
volumes, but Chinese demand for imported commodities necessary for infrastructure development should
continue. This translates into demand for bulk carriers to move those commodities from production sourcesin Asia, Latin America and Africa.
Oil prices will continue to rise
Barring discovering of major new oil reserves or alternative energy sources, rising consumption of energy
will push prices steadily upwards. The “International Energy Outlook 2008” produced by the US Energy
Information Agency forecasts a 50 percent rise in world energy consumption, with an 85 percent rise for
non-OECD countries. This outlook forecasts roughly linear increases in demand and supply, but withdemand growing faster. The result is forecasted to be rising oil prices, reaching as high as $186 by 2030.
(This forecast was authored prior to the dramatic run up in oil prices in the second quarter of 2008; it is notknown how that experience would translate into differences in the forecast.)
In short, this forecast calls for the steady increase in oil prices experienced between 2000-2007 (see Table
3-1) to continue for the next 25 years. This scenario includes no provision for rising taxation of fossil fuels.
Were global efforts to limit greenhouse gas emissions to result in significant fuel taxes one would expect
these price increases to be even greater.
Recalling the discussion in section 3, rising fuel prices result in higher transportation costs regardless ofmode. However, the elasticity of transportation costs with respect to fuel prices is much higher forcommercial aviation than for ocean-borne cargo. This means that, absent some unseen technologicalinnovation, rising fuel prices will continue to increase the relative price of airborne cargo.

US current accounts must come back into balance.
The US has for almost three decades run current account deficits, and these deficits have grown tohistorically unprecedented magnitudes: over $800billion in each year from 2005, 2006, 2007. It is hard tofind an international economist who believes this situation can continue. At some point, net foreign capital
flows into the US will slow (perhaps aided by an increased perception of risk in US capital markets), theUS dollar will fall in value and the massive trade gap will narrow. This process is already underway in2008, but seems likely to accelerate.

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Forum Paper 2009-3:David Hummels
Consider the difference in freight rates on routes to and from the US displayed in Table 3-1. Rates on Asia
to US routes are more than double rates for the return voyage. Rates on Europe to US routes are roughly
50 percent greater than rates on the return voyage from the US to Europe. While there may be additional
factors that drive this enormous disparity, the enormous US trade deficit seems a likely primary cause.
Indeed, the trade deficit may actually understate the imbalance in ocean cargoes, as US exports are
significantly more air-intensive than are US imports. Data on capacity utilization on US inbound v.
outbound routes were not available to this author. However, the macroeconomic facts on the trade deficit
along with the very large differences in rates on these routes suggests that containerships inbound to the
US steam at full capacity with significant slack capacity on return routes.
If, then, the US dollar were to depreciate and the US trade deficit to narrow or even reverse itself, the result
would necessarily be a size-able rebalancing on the cargo front. The obvious effect would be to equalize
the rate differential between inbound and outbound cargos. Less obviously, and perhaps more
speculatively, I expect that a narrowing of the US trade deficit would allow a reduction in ship capacity
deployed on these routes. To explain, consider a simple example. Suppose the US has 15m containers ofgross trade, with 10m containers imported and 5m containers exported through the combined Los
Angeles/Long Beach facilities. The imports would require 2000 round trips by 5000 TEU containerships,with those same ships returning on westbound routes half empty. Now, suppose the US were to balance
trade, with 7.5m containers imported and exported, for the same 15m containers of gross trade. The samegross volume of trade could be handled with 1500 visits of 5000 TEU ships for a 25% reduction inshipping capacity.
Protection
There is ample evidence to show that reductions in tariff barriers to trade have resulted in sharp increases
in trade volumes. For example, Mexican exports to the US tripled in the 6 years after signing NAFTA, andChina’s exports to the world quadrupled in the 5 years after its WTO accession.
However, the forecast for further liberalization seems cloudy at best with the Doha round of WTO talks
now entering its eighth year of negotiation, and several preferential trade agreements similarly stalled. And
barriers once removed can easily become barriers reinstated. While it is hard to imagine many countries
pulling out of existing agreements, there is no shortage of disputes that could provide a pretext foradministered protection for governments so inclined. A short list of examples would include disputes overproduct health and safety, intellectual property protection, and labor and environmental standards.
Predicting what will happen in this area is extremely difficult, but it would not surprise this author were weto see significant backsliding on the trade liberalization front.
Firms and persons will pursue alternative channels for realizing gains from trade.
International trade economists point out that there are frequently multiple ways for an economy to enjoy
the gains from trade without actually engaging in merchandise trade itself. Consider some examples.
Countries with high capital/labor ratios will have a lower cost of capital and can gain from trade byexporting capital-intensive goods while importing labor-intensive goods. Alternatively, the same gains
from trade can be accomplished by capital flows or migration than narrow gaps in capital/labor ratios.
Countries may also have a comparative advantage in certain goods because their firms enjoy a productivity
advantage in their production. Similarly, much trade is driven by consumer and firm love of variety, that is,
enjoyment of distinct differentiated goods produced around the world. In both cases firms can produce
those goods in their home markets and export them to consumers worldwide. Alternatively, they can trade
the technology itself (selling blueprints, engaging in FDI) so that the goods can be produced in the
consumers’ home markets anywhere in the world.

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
The broad point here is that there are many ways to engage in international arbitrage, and firms will tend to
pursue the channel that is most efficient. Three factors point toward growth in channels other thanmerchandise trade. First, starting with the Uruguay round of the GATT/WTO new trade agreements havefocused more on liberalization of investment, services trade, and intellectual property protection than onliberalizing merchandise trade. Second, dramatic improvements in information technology allow firms toshare technology and coordinate production worldwide. Third, trade costs for merchandise trade seem
likely to rise, both transportation costs (due to oil prices) and political barriers to trade such as tariffs. A
consequence is that countries will enjoy the benefits of trade without physically moving merchandise.

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Finger, J.M. and Yeats, Alexander (1976), “Effective Protection by Transportation Costs and Tariffs: A
Comparison of Magnitudes”, Quarterly Journal of Economics, 169-176.
Fink et al., 2002 C. Fink, A. Matoo and I.C. Neagu, Trade in international maritime services: how muchdoes policy matter?, World Bank Economic Review 16 (2002) (1), pp. 81–108.
Geraci, Vincent J. and Prewo, Wilfried (1977), “Bilateral Trade Flows and Transport Costs”, Review of
Economics and Statistics, v59 n1, pp. 67-74
Gilman, Sidney (1983), The Competitive Dynamics of Container Shipping, University of Liverpool Marine
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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
Glick and Rose, 2001 Glick, R., Rose, A., 2001. Does a currency union affect trade? The time series
evidence. National Bureau of Economic Research Working Paper 8396, Washington, DC.
Gordon, Robert, (1990) The Measurement of Durable Goods Prices, University of Chicago Press.
Harrigan, James (1993),” OECD Imports and Trade Barriers in 1983” Journal of International Economics;
v35 n1-2, pp. 91-111
Harrigan, James (2005) “Airplanes and Comparative Advantage” NBER 11688
Harrigan, James and Venables, Anthony (2004) “Timeliness, Trade and Agglomeration” NBER 10404
Haveman, Jon, Ardelean, Adina, and Thornberg, Christopher (2008), "Trade Infrastructure and trade costs:
A study of select Asian Ports" in Infrastructure's Role in Lowering Asia's Trade Costs: Building for Trade.
Edward Elgard Publishers 2008. Douglas H. Brooks and David Hummels, eds.
Hillberry, Russell and Hummels, David (2008) “Trade Responses to Geographic Frictions: A
Decomposition Using MicroData”, European Economic Review 52 (2008) pp. 527-550
Hummels, David, (2007a) "Transportation Costs and International Trade In the Second Era of
Globalization”, Journal of Economic Perspectives 21 (2007) pp. 131-154.
Hummels, David (2008) "Trends in Asian Trade: Implications for Transport Infrastructure and Trade
Costs" in Infrastructure's Role in Lowering Asia's Trade Costs: Building for Trade. Edward Elgard
Publishers 2008. Douglas H. Brooks and David Hummels, eds.
Hummels, David, Ishii, Jun, and Kei-Mu Yi, (2001) "The Nature and Growth of Vertical Specialization in
World Trade", Journal of International Economics, 54 pp 75-96.
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Economic Review 95 (2005) 704-723.
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Power in International Shipping” forthcoming Journal of Development Economics.

32© OECD/ITF, 2009

Forum Paper 2009-3:David Hummels
Hummels, David and Lugovskyy, Volodymyr, (2006) “Are Matched Partner Trade Statistics Usable
Measures of Transportation Costs?”, Review of International Economics 14 (2006).
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Ideal Variety” forthcoming, Journal of Money, Credit, and Banking
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Equivalents for Time in Trade" USAID/Nathan Associates.
Hummels, David, and Puzzello, Laura, (2008), "Some evidence on the nature and growth of input trade"mimeo, Purdue University
Hummels, David and Schaur, Georg (2008), "Time as a Trade Barrier"Hummels, David and Skiba, Alexandre (2004) “Shipping the Good Apples Out: An Empirical
Confirmation of the Alchian-Allen Conjecture” Journal of Political Economy 112 (2004) 1384-1402.
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1013-20.

© OECD/ITF, 200933

Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
List of Tables and Figures
Section 1

How Goods Move

Table 1-1

World Trade Cargo Modes

Table 1-2Latin American Imports: Transport Mode

Table 1-3

European Import Values by Transport Mode

Table 1-4

European Export Values by Transport Mode

Table 1-5

European Import Weights by Transport Mode

Table 1-6

EU Export Weights by Transport Mode 2000-2007

Table 1-7

Modal Shares Within Europe

Figure 1-1

Airborne share of EU imports and exports 2000-2007

Section 2

Measures of Transportation Costs

Table 2-1

Ad-valorem Transportation Costs for the US, Latin America and the Caribbean

Table 2-2

Changing Air Fares by Region

Table 2-3

Inland Costs of Transporting One TEU Container

Table 2-4

Inland and Ocean Freight in Asian Trade

Figure 2-1

Ad-valorem freight expenditures in US and New Zealand Imports

Figure 2-2

Worldwide Air Revenue per Ton-Km

Figure 2-3

US air cargo price indicesFigure 2-4

Ocean cargo price indices, trip charters

Figure 2-5

Ocean cargo price indices, liner shipping

Figure 2-6Aggregate and Fitted Ad-valorem Air Freight for US

Figure 2-7

Aggregate and Fitted Ad-valorem Ocean Freight for US

Figure 2-8

Trend in Import Air freight, US and Selected LAC countries, 1995-2005

Figure 2-9

Trend in Import Ocean freight, US and Selected LAC countries, 1995-2005

Section 3

What determines shipping costs?

Table 3-1

Liner Rates on Major Trade Routes 1998-2008

Figure 3-1

Airfare Trend for US Inbound Travel (Economy Class Services) and Volume of Business
Air Travel

Figure 3-2

Trends in Airline Costs

Figure 3-3

Number of Shippers on the Route to the US

Section 4

Trends in Globalization from a Freight Perspective

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Table 4-1

Value of Time Saving and Share in World Trade for Selected Products

Table 4-2

Per-day Costs of Time Delays, Tariff Equivalents

Table 4-3

Time Sensitivity of Asian Trade

Table 4-4 Tariff Equivalents of Time Delays vs. Applied Tariffs
Table 4-5 Relative Importance of Inputs, Traded Goods in Asia
Table 4-6

Decomposing Mexican Export Growth to US 1991-2004

Table 4-7

Decomposing Asian Trade Growth 1995-2005

Figure 4-1

The weight/value ratio of EU trade, by EU country

Figure 4-2

The weight/value of EU trade, by partner region

Figure 4-3

The weight/value of Asian trade 1995-2005© OECD/ITF, 200935

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Table 1-7 Modal Shares within Europe

EU 15
Austria
Belgium
CyprusDenmark
FinlandFranceGermany
GreeceIceland
IrelandItaly
LatviaLithuania
Luxembourg
Malta
Netherlands
PolandPortugal
Romania
Slovenia
Spain
SwedenUnitedKingdom

Shares in 2006
Road
Rail
79.1
14.4

IWW
6.5

Change in shares 1990-2006
Road
Rail
IWW
5.8
-3.9
-1.9

63.2
71.2
100.0
91.8
72.7
80.9
65.9
98.1
100.0
98.8
90.1
39.0
58.4
91.5
100.0
63.6
70.4
94.9
70.5
78.2
95.4
64.5

33.8
14.0
0.0
8.2
27.1
15.7
21.4
1.9
0.0
1.2
9.9
61.0
41.6
4.6
0.0
4.1
29.4
5.1
19.4
21.8
4.6
35.5

3.0
14.7
0.0
0.0
0.2
3.4
12.8
0.0
0.0
0.0
0.0
0.0
0.0
4.0
0.0
32.3
0.2
0.0
10.0
0.0
0.0

14.2
-2.0
0.0
0.8
-2.2
7.6
7.3
2.3
0.0
9.1
3.0
16.6
31.0
16.6
0.0
3.4
37.6
3.1
34.3
24.4
6.1
6.4

-11.1
-2.4
0.0
-0.8
3.3
-7.2
-3.2
-2.3
0.0
-9.1
-3.0
-16.0
-30.4
-11.9
0.0
0.9
-37.1
-3.1
-41.7
-24.4
-6.1
-6.4

-3.1
4.2
0.0
0.0
-1.1
-0.5
-3.9
0.0
0.0
0.0
-0.1
-0.6
-0.6
-4.5
0.0
-4.3
-0.5
0.0
7.4
0.0
0.0
0.0

88.1

11.8

0.1

-1.9

1.9

0.0

*

*

*
*
*
*
*
*

*
*

*

*

* First period of data is 1991.
Source: Eurostats42© OECD/ITF, 2009

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Figures 2-8 & 2-9

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Globalisation and Freight Transport Costs in Maritime Shipping and Aviation
Figure 4.3. Weight/Value of Trade 1995-2005

HKG

IDN

IND

JPN

KGZ

KOR

MYS

PHL

SGP

THA

TWN

0

1

2

3

4

0

1

2

3

4

0

1

2

3

4

CHN

1995

2000

2005 1995

2000

2005 1995

2000

2005 1995

2000

2005

year
imports

exports

Graphs by wbcode

62© OECD/ITF, 2009