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The Risks to Global Trade


There are many risks to global trade patterns due to their underlying complexity. Trade relationships are often facilitated by free trade agreements (FTAs). For example, the North American Free Trade Agreement (NAFTA) was a landmark agreement aimed at strengthening the trade relationship between the United States, Canada, and Mexico, and the efforts to enact its replacement are ongoing. Global trade patterns are also demand driven. Developing economies and population growth create emerging markets and shift production and consumption patterns around the globe. For example, Asia is expected to contain two thirds of the world’s middle class by 2030 (compared to almost half in 2015) and half of global GDP by 2050 (compared to one-third in 2017). Finally, all trade is dependent on the transportation system and is impacted by the associated costs and technological advancements. For example, increasing the share of trade that is containerized has contributed to lower shipping costs (Hummels, 2007). In this light, global trade patterns can be seen as a complex result of interactions between policies, technologies, economies, and infrastructure. These complex interactions subsequently create risks to potential freight volumes and difficulty in determining optimal infrastructure investment strategies.


This research should identify the threats and opportunities that can substantively affect shipping costs and/or the economies that are tightly coupled with global trade now and in the future, and provide quantitative estimates of their potential impacts on specific infrastructure (e.g., gateways, corridors, or ports) or trade and freight volumes. Potential risk factors may include:

  • The influence of political events (e.g., trade disputes, Brexit)
  • Safety and security concerns (e.g., Container Security Initiative)
  • Shifting demand patterns due to emerging markets (e.g., China, India)
  • Transport developments and technologies (e.g., new trade routes, terminal technologies)

  • Cyclical economic events (e.g. recessions, surging emerging economies)

  • Other potential risks (e.g., impacts of climate change, global energy prices)

Research aimed at improving the methodologies by which risks to global trade and transportation are quantified are also needed. In particular, the practical methods that could be used to study the above risks can be furthered by taking advantage of unique and growing datasets [e.g., OECD’s international trade indicators (OECD, 2018), UN Comtrade Database (United Nations, 2017), World Input-Output Database (WIOD, 2018), etc.], developing new or extended methodologies (e.g., considering stochasticity), and by conducting rigorous validation efforts of current approaches.

Related Research:

Global trade forecasts are typically short-run in nature. For example, the OECD Economic Outlook provides an analysis of trends and prospects for the next two-years, including a trade in goods and services forecast for OECD member countries as well as selected non-member countries (OECD, 2018b). National forecasts are similarly short-run in nature. For example, Economic Development Canada’s Global Export Forecast analyzes the sales outlook by sector for the two coming years (EDC, 2018). These short-run forecasts are useful for industries and market analysts but are not sufficient for making long-run infrastructure investment decisions. Hence, it is difficult to invest in infrastructure in such a way that maximizes the resiliency of the transport system toward variability in future global trade patterns.

The two most common tools used for analyzing trade scenarios are gravity models and computable general equilibrium (CGE) models. Gravity models are often used in an ex-post analysis, to help understand the impact of a previous policy or change. For example, Coughlin and Wall (2003) study the impact of NAFTA on the pattern of state exports in the United States using a gravity model. However, gravity models are subject to the Lucas critique: econometric models estimated under a specific set of conditions cannot be used to analyze a different set of conditions because the parameters of an estimated model embody the conditions under which the observed data were generated. Hence, the impact of NAFTA as determined by Coughlin and Wall (2003), or any other gravity model, cannot be generalized to other times, places, or FTAs.

A CGE model is a system of equations that describes an entire economy, representing both macroeconomic constraints on the economy as a whole and the individual microeconomic behavior of interactions between its parts. CGE models are often used for ex-ante analyses, to help understand the potential impact of future policies or changes based on information available at the time of forecast. For example, Bachmann (2017) uses a CGE model to determine the trade and transportation impacts of the Comprehensive Economic and Trade Agreement (CETA) between Canada and the European Union (EU). The main advantage of CGE models is that they try to capture how economies actually work, with every change affecting a range of other parts of the economy. In other words, the models reach equilibrium, considering all of the feedbacks between various agents and their decisions, while maintaining the circular flow of money. However, the validation of CGE models has not been rigorous and previous efforts have shown their validity is sensitive to their assumptions. For example, Kehoe (2005) uses data on actual changes in trade flows among Canada, the US, and Mexico, to evaluate the performance of three CGE models that were used in the early 1990s to estimate the impacts of NAFTA, finding these models severely underestimated the impact of NAFTA on North American trade due to their structures.

To analyze the associated transportation impacts, the above trade models can be linked to freight transport models. However, the difference between trade flows (in value), commodity flows (in weight), and vehicle flows (in ships, trucks, or rail cars, etc.) makes for a difficult translation, not only due to the necessary data needed for conversion, but also because of the presence of transshipment points and vehicle routing patterns. For example, Jahangiriesmaili, Roorda, Bachmann, and Allen (2018) combine several US and Canadian datasets in order to estimate the multi-modal impacts of CETA in Canada. As new data are increasingly available, the modeling process by which vehicle flows are calculated from trade flows can be enhanced.

Hence there is a need to develop methodologies that maximize the resiliency of infrastructure investments in light of risks and uncertainty in global trade patterns; to extend and validate existing methodologies aimed at quantifying global trade risks; and to identify and quantify the opportunity and threats posed by contemporary issues with these methodologies.


Bachmann, C. (2017). Modeling the impacts of free trade agreements on domestic transportation gateways, corridors, and ports. Transportation Research Record: Journal of the Transportation Research Board, 2611, 1-10. http://dx.doi.org/10.3141/2611-01

Coughlin, C. C., & Wall, H. J. (2003). NAFTA and the Changing Pattern of State Exports. Papers in Regional Science, 82(4), 427-450. https://doi.org/10.1007/s10110-003-0122-x

EDC (2018). Global Export Forecast. https://www.edc.ca/EN/Knowledge-Centre/Economic-Analysis-and-Research/Pages/global-export-forecast.aspx

Hummels, D. (2007). Transportation costs and international trade in the second era of globalization. Journal of Economic Perspectives, 21(3), p. 131–154. https://doi.org/10.1257/jep.21.3.131

Jahangiriesmaili, M., Roorda, M. J., Bachmann, C., & Allen, R. (2018). Assessment of Canada’s transportation system under the Comprehensive Economic and Trade Agreement (CETA). Forthcoming in Transportation Research Record: Journal of the Transportation Research Board.

Kehoe, T. J. (2005). An evaluation of the performance of applied general equilibrium models of the impact of NAFTA. In T. J. Kehoe, T. N. Srinivasan, & J. Whalley (Eds.): Frontiers in Applied General Equilibrium Modeling: In Honor of Herbert Scarf (pp. 341-377). Cambridge: Cambridge University Press https://doi.org/10.1017/CBO9780511614330.014

OECD (2018a). International trade: Indicator group. https://data.oecd.org/economy.htm#profile-International%20trade

OECD (2018b). Trade in goods and services forecast (indicator). https://doi.org/10.1787/0529d9fc-en

United Nations (2017). UN Comtrade Database. https://comtrade.un.org/

WIOD (2018). World Input-Output Database. http://www.wiod.org/home


Undertake research to address and provide greater insight and understanding of the objectives. Such tasks could include:

  • Identification of risk factors on international shipping costs, including maritime and air modes.
  • Quantification of cargo value changes for risk factors.
  • Quantification of cargo volume changes for risk factors.
  • Quantification of direct and indirect financial impact (at the port level up to the gateway region) for risk factors.
  • Analysis of longevity of impact for risk factors.

The ongoing negotiation of trade agreements between the US, Canada, and Mexico in addition to trade disputes makes it important to demonstrate the importance of international trade and the potential risks to trade levels.

Sponsoring Committee:AT020, International Trade and Transportation
RNS Developer:Daniel Hackett
Source Info:This would make an excellent research paper for the Standing Committee on International Trade and Transportation
Date Posted:01/11/2019
Date Modified:01/24/2019
Index Terms:International trade, International transportation, International compacts, Freight transportation support businesses, Freight transportation, Risk assessment,
Cosponsoring Committees: 
Marine Transportation
Freight Transportation
Planning and Forecasting

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