Alaska’s economy was built around fossil fuel use at a time when it was inexpensive. Since then, key Alaska industries such as fishing, mining, tourism, transportation, and subsistence have grown to depend directly on liquid fossil fuels. In addition, Alaska’s urban service economy depends heavily on the low cost of living and doing business that has historically been assisted by cheap transportation fuels.
These conditions are changing rapidly and perhaps permanently. In 2005, Alaska consumed 40% more fossil fuel than any other state, according to the Energy Information Administration (EIA, 2012). By 2010, Alaskans consumed almost three times more energy than the national per capita average.
Alaska’s higher per capita energy consumption results from a variety of factors. Alaska’s remoteness and dispersed populations combined with a limited road system results in a dependence on air travel. In addition, our role as a major world air cargo and transportation hub, oil producer, and marginal refiner also contributes. This acute energy dependence creates a higher vulnerability to energy price volatilities and shocks. For state policy makers and industry, this vulnerability necessitates a better understanding of how energy prices and legislation impact transportation patterns and efficiency.
Since 2009, the Institute of Social and Economic Research (ISER) at the University of Alaska Anchorage has worked with AUTC to develop a model of Alaska’s transportation sectors to assess what might happen if fuel prices suddenly change. Titled, “Model of Alaska Transportation Sector to Assess Energy Use and Impacts of Price Shocks and Climate Change Legislation,” the project is helping illustrate and quantify the interactions between energy use, energy prices, and economic activity in Alaska.
Given its geography, Alaska has long relied on aviation and marine transportation to move people and goods. Although Alaska is the largest state in the U.S., it has the fifth-lowest road mileage in the nation, leaving 82% of its communities unconnected to a state road system (Schultz, 2012). Residents of these areas primarily use expensive air passenger and consumer goods transportation. Their needs also drive demand for liquid fuels and construction materials that have both high initial and storage costs.
The reasons for Alaska’s limited road system are many, and its unusual dependence upon efficient inter-modal transportation will no doubt continue. Extreme weather, rugged terrain, vast distances, low population density, and scattered islands make future construction initiatives difficult and extremely costly when compared with the number of end users (ADOT&PF, 2008). Consequently, the major changes in Alaska’s transportation system have been primarily technological improvements within each transportation mode rather than major system changes.
In Alaska’s more populated areas, inter-modal reliance looks quite different. More than half of Alaska’s population resides within the Railbelt region, served by the Alaska Railroad and the state highway system, and a few other small urban areas in Southeast Alaska. This region, as a result, has competing transportation modes, services, and economies of scale for freight and passengers.
From an economist’s perspective, understanding Alaska’s highly inter-modal transportation system requires a focus on inputs and outputs that are specific to that system, especially energy resources.
The journey of freight goods to Alaska consumers is a good illustration. Most of Alaska’s food, household, and consumer goods that are shipped from the continental U.S. begin their journey from the manufacturing plant or distribution facility. Loaded onto trucks destined for ports in either Tacoma or Seattle, Washington, the goods travel to these locations where they are loaded onto a container ship, barge, or roll-on, roll-off vessel which sails to Alaska ports. If bound for a community connected to the highway system, the freight often completes its journey in trucks. It may also transport north or south from or to the Port of Anchorage via the Alaska Railroad. Freight destined for towns off the road system is flown from either Anchorage or Fairbanks to a remote community. Then it is either driven by pickup truck if there is a regional road system or loaded onto smaller aircraft or boats for shipment to outlying villages. Quite often in remote areas, freight makes the final leg of the journey in sleds pulled by snow machines or on four-wheelers (ADOT&PF, 2008) (Figure 2). Each leg of this journey involves a specific mode and energy resource, like liquid fuel.
Quantifying the energy needs of this intricate network requires a methodology informed by diverse data sources.
Understanding trends of an inter-modal transportation system requires multi-modal data. Marine shipping, barge, and trucking firms provided figures on their operations between 2006 and 2010. We also added information on Aviation modes provided by the U.S. Department of Transportation, Research and Innovative Technology Administration (RITA), Bureau of Transportation Statistics (BTS). This aviation data helped us model fuel consumption and costs per passenger mile and ton mile by aviation fleet type (U.S. DOT, RITA, BTS, 2010). Enhancing our data on maritime and rail modes, the Alaska Marine Highway System (AMHS), Interisland Ferry Authority (IIFA), and Alaska Railroad Corporation all offered statistics on their respective operations as well. Augmenting this data set, we also received information from individual companies, which we used in conjunction with secondary data to model the barge and trucking subsectors—both major Alaska industries.
Three primary types of analysis are being conducted as part of this research. We are developing broad energy use statistics for each transportation subsector such as estimated total annual energy and fuel use, carbon emissions, fuel use per ton mile and passenger mile, and cost of fuel per ton mile and passenger mile. We are conducting economic input-output analysis, which estimates the employment and output of each transportation subsector in the Alaska economy. Input-output modeling assumptions will be adjusted to reflect fuel price shocks/changes and/or emissions taxes to estimate the potential impact of these changes on industry output and employment in the Alaska economy. In addition, we will conduct statistical analyses of the data to estimate changes in use patterns, efficiency and potential mode shifts across the industry during the studied time interval, including extensive fuel price volatility.
These results will give Alaska decision makers a better understanding of the state’s energy use, vulnerability to price shocks, and the kinds of transportation patterns, efficiency, and mode shifts that may accompany them.
By: Ginny Fay, AUTC Researcher; Assistant Professor of Economics
Institute of Social and Economic Research
University of Alaska Anchorage
NOTE: This story originally appeared in AUTC’s latest newsletter. Read other stories at AUTC’s publications page, here.
ADOT&PF, 2008, Let’s Get Moving 2030: Alaska Statewide Long-Range Transportation Policy Plan, Alaska Department of Transportation and Public Facilities, February.
EIA, 2012, U.S. Department of Energy, Energy Information Administration, State Energy Data System, June 29, 2012. http://www.eia.gov/state/seds/hf.jsp?incfile=sep_sum/html/rank_use_per_cap.html
Schultz, Caroline, 2012, The Span of Alaska’s Railroads, Alaska Economic Trends, Alaska Department of Labor and Workforce Development, Research and Analysis Section, Volume 32, Number 3, March.
U.S. DOT, RITA, BTS, 2010, U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics, Aviation Library: http://www.transtats.bts.gov/databases.asp?Mode_ID=1&Mode_Desc=Aviation&Subject_ID2=0
U.S. Environmental Protection Agency, 2008, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 to 2006.