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Estimating Economic Impacts of Goods Movement Disruptions

As long as commodities and goods move as part of a nation’s supply chain, providing reliable and cost effective transportation capability is embedded in the supportive nature of transportation to economic productivity. When such capability is disrupted, either by man-made or natural means, economic losses—to the companies and individuals dependent on the supply chain as well to the broader society—could be significant.

Hurricane Sandy is just the most recent example of the impacts that extreme weather events can have on entire regions of the country. From the perspective of goods movement, Hurricane Sandy disrupted both interstate and local freight flows as transport systems were damaged and fuel supplies were crippled. Weeks after the storm itself the freight logistics system was still trying to recover.

Other examples of disruptions in the United States include numerous other hurricanes, major labor strikes such as the one affecting the West Coast ports in 2002, the closure of northern rail lines during the winter of 2006 for almost two weeks due to snow, the 2008 fuel price spike, freezing temperatures and flooding, the shutdown of the national aviation system during 9/11, and stoppages on critical transportation links such as the Baltimore rail tunnel fire. Internationally, disruptions in supply chains have also been caused by health concerns, such as the avian flu.

Key Factors in Understanding the Economic Impact of Goods Network Disruptions

Several factors can affect the economic consequences of disruptions to the nation’s goods network. For example, the spatial or geographic scale of the disruption itself will likely have a direct bearing on the magnitude and incidence of the economic impact. Thus, for example, the closing of a major port or key links in a land transportation network could have negative impacts throughout the supply chain, assuming little resiliency in moving goods on alternate paths. A disruption could affect the entire freight system of an area or affect a specific mode. In the situation where a single mode is disrupted, shipments are likely to transfer to alternative modes.

Generally speaking, the longer, more geographically extensive, and the more breaks in the supply chain, the more extensive are the likely economic impacts. Shorter and less widespread disruptions, covering fewer supply chain/transport links are likely to entail limited economic impacts, mainly in transport and inventory costs. Much more extensive and longer lasting disruptions will likely begin to affect productive economic activities, such as product assembly and manufacturing, or product distribution.

Different types of disruption could have a range of direct and indirect economic impacts. For example, the removal of one critical link in a network could create a bottleneck that might or might not have important consequences to goods flow. On the other hand, widespread network disruption (e.g., due to floods and hurricanes) could have a multitude of overlapping and connected economic impacts.

Whether goods can be shipped economically via other modes depends, in addition to the availability of service, on the value and nature of the cargo itself. High value commodities or commodities that are otherwise time sensitive, such as air cargo, may not economically be shifted to slower modes.

Modeling Economic Impacts 

Various types of modeling approaches can help estimate the potential for losses due to a disruption in the supply chain. These range from simple logical frameworks to complicated dynamic economic simulations. What the approaches share in common is a need to link supply chain responses to economic impacts.

Box 1 shows the general categories of models that are available for estimating supply chain response to disruptions and resulting economic impacts.

Diversion models are often quite simple, and can be based on the assumption that in the case of a transportation network disruption cargo is diverted to the least cost alternative route. This diversion leads to some direct impacts in terms of increased transportation costs (e.g., fuel, operator salaries, operations and maintenance, etc.) and certain indirect impacts (e.g., increased inventory costs imposed by the relative uncertainty of deliveries through the detour, lost shipper profit, etc.).

Freight network simulation models are complicated versions of simple diversion models. Generally, GIS-based platforms that replicate the complex network of routes through which freight flows occur either represent movement on a single mode (such as truck over the road network) or over multiple modes. As with the simple cargo diversion models, a least cost (including time cost) or shortest route approach is applied to analyze freight flows in various scenarios.

Business supply-chain optimization models aim to optimize business operations including the flow of goods (raw materials, intermediate and finished products) through a specific industry supply chain. Business and industry decisions regarding sourcing, inventory levels, and the transportation network or route choice form key components of the supply chain, and are all vulnerable to impacts of major disruptions.

Dynamic supply-chain simulation models aim to capture supply-chain responses dynamically and allow for ongoing assessment of raw material sources, factory locations and processes, distribution centers, transportation links, outsourcing, inventory and related costs, and constraints. These models are generally very demanding in terms of data requirements and skill levels of the modelers, and are as yet in the early stages of development as far as their use in common practice goes.

Static/input-output models of varying complexity focus on transport costs (on the monetary value of time and other resource costs). The most widely used tools are input-output (I-O) modeling tools, which can be applied to analyze primarily two situations: 1) economic damages to freight transportation infrastructure, such as the costs incurred directly within a port (e.g., when dock workers are laid off), and the spin-off impacts to industries and enterprises that supply goods and services to the port; and 2) economic damages associated with supply-chain disruptions, and cargo diversions or bottlenecks that disrupt freight flows.

Dynamic economic simulation models are statistically estimated, simultaneous equation representations of the aggregate workings of an economy. They have forecasting capabilities that can be helpful in determining the potential impacts of a future event or in distinguishing the actual activity of an economy from what it would have been like in the absence of a shock. Econometric models have their own established set of criteria for model validation that are more rigorous than those for input-output models. The downside of these models is their high level of complexity and user skill requirement.

A Simplified Impact Template
The research project culminated in development of both a process for analysis and a template providing users with typical values that can be used to estimate economic losses given a set of assumptions about supply chain behavior.

The Process

A five-step decision model, shown in Box 2 on the following page, was developed to provide an analytic framework for application of methodologies. The process proceeds through the following major steps:

  1. Define the freight network. What is the freight network? What are its routes, paths, modes, branches? Where are alternative paths?
  2. Identify freight network flows. What are volumes of good that move across the disruption? What modes? What types of cargoes or commodities are moving across the network?
  3. Define the supply-chain characteristics. Where is production located? What are the transport characteristics of moving goods from initial point of production to local distribution to final customers?
  4. Supply-chain response: how does the supply chain adapt? Are alternative networks or modes available and practical to use? Is the supply chain flexible enough to respond? Is production halted as goods are held in storage or ships anchor outside the harbor until the port is reopened?
  5. Economic impact modeling: given steps one through four, and especially step four, what are the economic impacts? Were goods moved by other routes or modes, minimizing economic consequences, or were industries or regions compelled to reduce or stop production or shift production to other less optimal locations? What are the impacts on local, regional, and global markets? Are prices affected? Did output cease, and can the industries rebound later on?



Impact Rules of Thumb

Together with the framework, the research provided freight stakeholders with a series of impact values which, in the absence of more extensive or in-depth modeling, could be used for quick response analysis of economic impacts. Impact rules of thumb were provided covering:

  1. Direct transportation cost impacts: increases in the direct cost of transporting goods per ton-mile.
  2. Inventory costs: the “time penalty” associated with delayed delivery of goods to final or intermediate markets, also including the additional costs of retaining inventory in warehouses or in stores or factories per ton-mile.
  3. Direct regional economic output losses: losses to regional or state output, employment, wages, and GDP, resulting from a contraction or halt to production or sales and multiplier impacts.
  4. Indirect regional economic output losses: lost output, employment, income, and GDP due indirectly to higher transport costs and increased delay. Are transport cost penalties significant enough to reduce quantity demanded for the output of a given area?
  5. Impacts on major transportation facilities: losses in employment and earnings to a region when a major facility, such as an international port or major intermodal freight rail network, cannot operate.

Summary

Whether from natural or man-made causes, disruptions to freight movement are likely to characterize transportation system performance in future years. This research has identified the critical components of both the short- and long-term economic impacts of such disruptions, and the types of models that can be used to estimate the magnitude. Such information will be useful for identifying where in the supply chain steps can be taken to minimize such impacts as well as estimating the cost to society and to industry of not taking such steps. This is the type of information often needed by both public and private sector officials when considering steps to protect the nation’s freight and logistics network, and as was seen most recently with Hurricane Sandy, the information desired when reporting on the economic costs associated with network disruptions.

 

Image Header Source: Federal Emergency Management Agency (Creative Commons)