In its 1999 report, the federal Marine Transportation System (MTS) Task Force expressed concern that fast-growing demand in marine freight and passenger travel will challenge the capacity and functioning of this transportation system. It noted that “the total volume of domestic and international marine trade is expected to more than double over the next 20 years” (DOT 1999, viii). This estimate, equivalent to growth on the order of 3 to 4 percent per year, was derived largely from extrapolations of recent trends and near-term forecasts of the tonnage of waterborne cargo moved into and out of the country in international trade (DOT 1999, 25–28). However, significant variations were expected in the rate of growth among different freight segments. The fastest growth,

3.5 percent per year on a tonnage basis, was predicted for goods moved in international trade (DOT 1999, 26). In comparison, bulk cargoes moved domestically on the inland waterways were projected to grow at 1.3 percent per year (DOT 1999, 27).

In this chapter, these and other demand projections are reviewed in more detail to gain a better understanding of where the most dynamic growth in marine transportation demand is expected. In particular, consideration is given to forecasts of demand for the following freight sectors:

• Containerized cargoes shipped overseas, consisting primarily of manufactured and processed goods, as well as other kinds of general cargo moved in intermodal containers;

• Liquid bulk cargoes shipped overseas, consisting primarily of petroleum and chemicals moved by tankers;

• Dry bulk cargoes shipped overseas, consisting largely of agricultural products, coal, and iron ore; and

• Cargoes shipped domestically on the inland rivers and Great Lakes, consisting largely of dry bulk and liquid bulk commodities, much of it moved by barge.

The discussion begins with an overview of current traffic volumes in each of these freight sectors. The major sources of long-range forecasts of traffic demand in each of these sectors are then examined. The chapter concludes with an assessment of possible implications of this forecast demand on the capacity and functioning of the MTS.

The most commonly used measure of marine freight is tonnage. More than 2,300 million tons of cargo moved through the MTS, domestic and international, during 2000 (the latest year for which complete data are available). The breakdown by freight sector is shown in Table 2-1.

On the basis of tonnage moved, barge traffic on the inland rivers represents the largest sector of the MTS; it accounts for about 30 percent of total tonnage transported. Most of the freight moved on the inland rivers consists of heavy bulk commodities, which leads to the high tonnage totals for this segment of the MTS. More than half the tonnage moved on the rivers, for instance, is from shipments of coal and petroleum. Bulk commodities are also predominant on the Great Lakes and in domestic ocean and coastwise shipping. The former consists of shipments of iron ore and coke, while the latter includes the traffic moved domestically along the Gulf Coast and between Alaska, Hawaii, and the U.S. mainland—much of it petroleum.

Another way to measure traffic is by cargo value. Table 2-2 shows both the value and tonnage of cargo moved over the oceans in U.S. international trade. As might be expected, vessels carrying containers, which are used to transport high-value manufactured and processed items, account for a much higher proportion of traffic on the basis of value (about 67 percent) than on the basis of tonnage (less than 15 percent).

Presenting an accurate picture of demand for marine freight transportation is complicated by differences in the kinds of freight moved, some of

which are more easily and aptly measured by weight and others by value. Even more difficult is forecasting how demand for marine freight will change over time, particularly over the course of a decade or more. In the following discussion, some of the approaches used in forecasting demand and the major sources of these forecasts are reviewed. The forecast results are then reviewed, and their assumptions and uncertainties are considered.

The accuracy of longer-term projections of marine transportation demand hinges not only on an understanding of the basic drivers of demand, such as growth in the national economy and in international commerce, but also on many other factors that can be even more difficult to predict, such as changes in legislation and transportation technology. Such factors will, in time, have measurable effects on both the level and nature of transportation demand. Forecasters of marine transportation demand in the early 1950s, for instance, could not foresee the advent a decade later of containerization, which would quickly transform the way general cargo is transported and help spur even greater international trade.

Despite such uncertainty, long-range demand forecasting is not a futile exercise. As long as transportation services require large-scale capital investments by the public and private sectors, demand forecasting will be required to support decision making. Forecasts are required for planning port facilities, making vessel and terminal investments, and regional and national economic planning. The key to using this information is understanding the sensitivities of forecasts to demand drivers and understanding how the forecasts themselves can go awry. In these

respects, long-range demand forecasting has advanced a great deal since the 1950s as computational capacity, modeling techniques, and information sources have improved.

Basic kinds of forecasting methods are described in Box 2-1. Each has strengths and weaknesses. Some of the simpler methods that are based on few variables have the advantage of flexibility; decision makers find them easy to use for “what-if” scenario analyses. They may not be especially accurate, but they are capable of providing “ballpark” estimates for the initial stages of decision making. At the other end of the spectrum are complex forecasting models designed to provide detailed projections across many economic sectors and regions with a high degree of internal consistency (e.g., imports equal exports for all commodities on a global basis). They may be used to inform national policy making. Such complex multivariate modeling systems require large amounts of data and computer processing and a substantial amount of time from the modeler.

Because the quantity of marine traffic is heavily influenced by international commerce, forecasts of international trade are especially important inputs in most marine freight forecasts. Similarly, projections of domestic and international energy demand, as well as the demand for agricultural commodities, are important.

The major commercial and government suppliers of long-term trade and commodity forecasts tend to use the most sophisticated forecasting methods described in Box 2-1, which incorporate time series, constrained demand, and multivariate modeling approaches. These suppliers include

• Global Insight, Inc.,¹ which forecasts trade in all major physical commodities (i.e., nonphysical commodities, such as electricity and services, are not included), across nearly all countries, and in detail by commodity, trade route, and vessel type (e.g., container, tanker, dry bulk);

• The Energy Information Administration (EIA) of the U.S. Department of Energy, which publishes the Annual Energy Outlook containing long-term forecasts of U.S. energy balances, including projected imports and exports of specific energy commodities (e.g., crude oil, coal, petroleum products, natural gas); and

• The Institute of Water Resources (IWR) of the U.S. Army Corps of Engineers (USACE), which projects demand for transportation on the nation’s waterways, including the inland waterways. Because bulk cargoes are the chief source of demand for inland waterways, IWR employs specialty consulting firms to develop long-range forecasts of agricultural products, minerals, energy, and other commodities moved in large quantities on inland waterways.

Several forecasts from the preceding sources are examined in this section. They offer insight into the factors that can influence demand, and they illustrate the kinds of information that decision makers in the public and private sectors have at their disposal to plan for the future. Results from the latest (at the time of this study) 20-year forecasts from Global Insight, EIA, and USACE are presented at different levels of aggregation and across different demand sectors, starting with forecasts of all U.S. international trade and then focusing on specific categories of freight, including containerized cargo, energy, and agricultural commodities.

Global Insight’s forecasts are developed from dynamic trade models of supply and demand that cover more than 75 physical commodity types in each trading region of the world (currently encompassing 54 major countries and 16 regions). Factored into the models are current and projected exchange rates, price deflators, demographic trends, expected production capacities, and other relevant variables such as transportation costs. Forecasts for U.S. international trade in all commodity sectors are

shown in Table 2-3. The forecasts, which are based on tonnage, anticipate an average annual growth rate of 1.9 percent per year from 2000 to 2020. Total trade volume is thus projected to increase by nearly 50 percent over the forecast period.

Global Insight also forecasts growth in trade sectors. The firm’s most recent forecasts for U.S. containerized exports and imports are presented in Table 2-4. Cargo exported in containers, measured in 20-foot equivalent units (TEUs), is expected to grow an average of 3.4 percent per year, while containerized imports are expected to grow an average of 5 percent per year. Containerized traffic overall is expected to grow 4.4 percent per

year. At this pace, traffic would double in about 15 years and increase by more than 135 percent over two decades.

EIA’s latest Annual Energy Outlook (2003) contains petroleum import and export forecasts for the next two decades. The 2020 forecasts are shown in Table 2-5. The largest gains are expected for petroleum product imports, which are projected to grow 4 to 5 percent per year. Crude oil imports, which account for most of the petroleum trade, are expected to grow less than 2 percent per year on average, resulting in a 40 percent increase in import levels from 2000 to 2020. The quantity of petroleum exports is relatively small and is not expected to change much during the period.

EIA 20-year forecasts of imported and exported natural gas (which is moved mostly in liquefied natural gas tankers) and coal are shown in Table 2-6. Natural gas imports are forecast to grow at a rate of about

3.2 percent per year during the period, which would lead to a near doubling. In comparison, the quantity of coal exported is expected to decline in absolute terms as more of the country’s domestic production is used internally (coal imports are insignificant and are expected to remain so).

USACE projections of freight traffic on the inland waterway system (to 2020) are summarized in Table 2-7. These projections, made in 1995 and 1998, are cited in the 1999 MTS Task Force report (DOT 1999). They anticipate 1.3 percent annual growth in the total volume of cargo transported on the inland waterways. The tonnage of all types of cargoes is expected to grow at a rate of 1 to 2 percent per year. Total annual tonnage moved on the inland waterways is expected to increase by 26 percent during the 20-year period.

More recent forecasts were released by USACE in July 2002. These forecasts, shown in Table 2-8, are for shipments only on the Upper Mississippi River. The magnitude of predicted change (23 percent) in traffic volumes is consistent with the 1995 and 1998 USACE forecasts for the inland waterway system as a whole.

Table 2-9 summarizes the results of these major forecasts of marine transportation demand to 2020. What is most apparent from this comparison is the expectation for continued high rates of growth in container traffic. Much more modest growth is anticipated for the dry and liquid bulk commodities shipped overseas and on the inland waterways.

A common assumption of models forecasting high growth in container traffic is that international commerce will flourish, populations will

increase, and incomes will rise worldwide, all of which will cause trade in manufactured goods to grow. Most forecasts assume that the U.S. economy will expand at an average annual rate of 3 percent during the period, causing gross domestic product to nearly double. In its middle-series estimates, the U.S. Bureau of the Census projects the national population to increase by 50 million between 2000 and 2020.² By themselves, the assumed increases in national income and population explain a great deal of the expected growth in international trade and thus the anticipated strong growth in container trade. Of course, other assumptions are embedded in the forecast models. Some are especially difficult to model, including the following:

• The occurrence of “shocks,” such as enduring droughts, political upheaval, and war. Although such shocks do occur, their timing, magnitude, and effects are largely unpredictable; hence, long-range forecasts do not take them into account. Rapid and large-scale changes in the political and economic systems of China, for instance, could yield such “shocking” effects on international commerce, and thus on the demand for marine transportation.

• The introduction of new technologies that have transforming effects on the pattern and level of marine transportation demand. Complex demand models do assume that evolutionary changes in technologies will make transportation services less expensive over time. The models, however, do not have good ways of accounting for the occurrence and impact of dramatic technological changes. The widespread introduction of intermodal containers in the 1960s (sometimes referred to as the “container revolution”) is a good example of how technological change can transform marine transportation demand.

• Major changes in consumer preferences. The fundamentals of consumer behavior are well understood; for instance, consumers tend to purchase more of a good as its price falls. Nevertheless, preferences for

particular goods can change, causing some to become more or less in demand over time. The most complex demand models tend to work on a life-cycle basis that incorporates consumer sentiment indices to account for changing consumer preferences. However, consumer preferences can change in unanticipated ways. As an example, during the 1970s, Americans began purchasing foreign-made automobiles and electronics at much higher rates than previously. Many factors accounted for this change, including greater acceptability of foreign-made goods as perceptions of poor product quality diminished.

• Major changes in trade policies. Substantial changes in tariffs or trade embargoes with major trading countries are examples of government policies that could have direct impacts on the demand for marine transportation services. Such changes, and the precipitating factors, can be unpredictable.

In addition to these uncertainties, demand modelers must make assumptions about a range of other factors, such as rates of borrowing and savings and demographic trends. Given the size and complexity of world trade, the influence of any one of these “macro” factors can have far-reaching effects on forecast accuracy. Moreover, the compounding effects of even small variations in rates of growth can have large effects on the aggregate growth levels predicted over time. For example, an actual growth rate in container trade that is just one-quarter of a percentage point lower or higher than the forecast rate can lead to predictions of traffic growth that are off by tens of millions of TEUs in a matter of 20 years.

Finally, the human element of forecasting must be taken into account, because published forecasts are often influenced by perceptions of what seems reasonable. Sometimes forecast results, no matter how well modeled, do not appear realistic to decision makers, causing forecasters to make adjustments. Often, the adjustments are intended to reduce the forecast rate of growth; however, they can also be made to increase it. As an example of the former, in 1987 the Ports of Long Beach and Los Angeles

(as part of the San Pedro Bay 2020 Plan for capital development) cosponsored projections of total U.S. oceanborne trade for 1985 to 2000, as well as forecasts of containerized trade. These forecasts, performed by WEFA for the period 1985 to 2000, are shown in Table 2-10. They are compared with actual traffic volumes during the period. The 1987 forecasts substantially underestimated traffic growth, especially for container movements. More than 15 years later, it is difficult to know all the factors contributing to this inaccuracy. However, participants in this forecasting effort recall initial growth projections that were considerably higher (and of a magnitude comparable with actual levels). These high-growth forecasts were not used out of concern that they would be viewed as too high to be credible.³ Because they necessarily involve many assumptions and uncertainties, all forecast models present a series of scenarios from which policy makers must choose in making long-range plans and decisions.

Most forecasts are accompanied by sensitivity analyses to provide a range of possible outcomes. Moreover, the development and refinement

of forecasting models compel evaluation of the many factors that can influence marine transportation demand, including differing constraints on the supply of marine transportation services and capacity. Although the understanding gained from modeling can never be comprehensive, it can help inform both public and private decision making.

The 1999 MTS Task Force report raises concern that a doubling of demand for marine freight during the next two decades will severely tax the capacity of the MTS. Long-range forecasts, however, suggest the importance of focusing on different components of demand. Rising incomes and escalating trade in manufactured goods are factors driving demand for the movement of marine containers. Of all the segments of the MTS, the container segment has the greatest potential for growth. Forecasts indicate that international container traffic could continue to grow at a rate of 4 to 5 percent annually, which would cause a doubling during the next two decades. It could grow at an even faster rate. The capacity of the MTS to handle such growth is therefore likely to become a greater concern for both industry and government.

Growth in international container traffic at the rate forecast could necessitate new physical infrastructure, which will take many years to complete, as well as improvements in the management and efficiency of these assets. Traffic in bulk shipments moved on the inland rivers and lakes is expected to grow at a more modest pace of 1 to 2 percent per year. However, much of the infrastructure on these systems is old and, in some cases, outmoded. Even relatively modest growth in traffic levels on these systems—producing 20 to 40 percent increases in volumes in 20 years— will further tax many parts of this federal infrastructure system.

Many factors have the potential to influence marine transportation demand, including some that cannot be predicted or planned for. History suggests the importance of adaptability and flexibility in meeting marine transportation demand.

BTS Bureau of Transportation Statistics

DOT U.S. Department of Transportation

EIA Energy Information Administration

USACE U.S. Army Corps of Engineers

BTS. 2002. Maritime Trade and Transportation ‘02. U.S. Department of Transportation, Washington, D.C.

DOT. 1999. An Assessment of the U.S. Marine Transportation System—A Report to Congress. Washington, D.C., Sept.

EIA. 2003. Annual Energy Outlook 2003. Report DOE/EIA-0383. U.S. Department of Energy, Washington, D.C.

USACE. 2002. Interim Report for the Restructured Upper Mississippi River–Illinois Waterway System Navigation Feasibility Study. Washington, D.C., July.