Conclusion
The local grain industry in North Dakota includes 440 elevators, two Class I rail carriers, three short line railroads, several local processors, 3,858 rail miles, 106,514 road miles, and thousands of farmers. In looking to the future of North Dakota's local grain industry infrastructure it is important to (1) view the local infrastructure as a part of global grain marketing network (2) determine, with the best current knowledge, what resources the local segment of that much larger network will require, and (3) rationally allocate available resources to maximize returns to the local segment of the network. huttle rail rates are, in today's grain industry, the railroad's most competitive rate. Shuttle rates are available to shippers equipped to meet specific volume, transaction, and operational commitments. Investment in shuttle facilities and the ability of these facilities to utilize the more competitive rates in attracting grain has the potential to strongly influence future local grain flow patterns. As these local grain flow patterns adjust to new market signals, demands on the local grain gathering system will need to be addressed. The objective of this study was to provide a market-based synopsis of the potential impact of shuttle train shipments on North Dakota's local grain industry. Secondary objectives were to (1) profile the local grain procurement network, (2) develop alternative network scenarios to analyze the influence of shuttle trains, and (3) provide framework for understanding the longer-term implications of shuttle trains for North Dakota's grain processing industry, infrastructure, and rural communities.
Facility infrastructure requirements, economic incentives, investment requirements, and financing packages are unique to each shuttle venture. Based on an earlier UGPTI study, a $6 million green field facility required approximately 10 million bushel handle for profitable returns. Discussions with grain companies and railroads suggest a target of 12 to 15 million bushels for a shuttle facility. This bushel requirement compares to the current average annual handle of 1.2 million bushels for the North Dakota elevator population, and average annual handle of 5.6 million bushels for the state's largest elevators. Therefore, redistribution of bushels in the local elevator industry seems imminent.
Spatial analysis was used to estimate producer delivery patterns for alternative rail rate and producer truck cost scenarios. Grain production and draw area spans were used as quantitative measures in discussing the delivery patterns. An economic decision model was employed to illustrate the impact of changes in elevator rail rates and producer trucking costs on the relative competitiveness of local processors. HRS wheat, durum, barley, and corn were considered in this economic analysis of shuttle rail rates on the local grain marketing. In the base case, wheat, the area included in the 10 shuttle facility boundaries accounted for approximately 45 percent of the total North Dakota land area. Regarding production, approximately 88.6 million bushels of HRS wheat and 32.9 million bushels of durum were contained in the estimated shuttle draw areas. The 10 draw areas encompassed about 38 percent of North Dakota HRS wheat production and 39 percent of the state's durum production. In the cases of barley and corn, shuttle facilities have the potential to accumulate 26.5 million bushels (24 percent of average North Dakota production) and 14.2 million bushels (19 percent of average North Dakota production), respectively, based on the estimated draw areas.
Considering these four crops, the 10 shuttle facility draw areas have the potential to originate about 162 million bushels. In relative terms, 2 percent of the elevators may originate up to 32 percent of the average annual production of wheat, barley, and corn. This market share of North Dakota production translates to an average 16.5 million bushels per facility. This potential concentration of bushels has implications for local roads, short line railroads, bridge infrastructure, local processors, local communities, and the North Dakota elevator industry.
References
Berwick, Mark, Denver Tolliver, and Kimberly Vachal, 2000 Farm Truck Survey, Report to be Published, Upper Great Plains Transportation Institute, North Dakota State University, Fargo.
Berwick, Mark and Frank Dooley, Truck Costs for Owner Operators, MPC Report No. 97-81, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. October 1997.
Bobb, Stevan, Vice President, Agricultural Commodities Business Unit, Burlington Northern Santa Fe, "Presentation to the North Dakota Public Service Commission," Bismarck, ND, 1999.
Burlington Northern Santa Fe, Published Tariff Rate Item 43521, http://www.bnsf.com/ June 2000.
"Grain Transportation Report," Shipper and Exporter Assistance Program, United States
Department of Agriculture, Washington, D.C. Various Weeks.
North Dakota Agricultural Statistics Service, North Dakota Annual Statistics, 1999, Fargo, ND. June 1999.
Ming, Dennis and William W. Wilson, The Evolving Country Grain Marketing System in North Dakota, UGPTI Publication No. 49, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. July 1983.
North Dakota Grain and Oilseed Shipment Statistics, Upper Great Plains Transportation Institute, North Dakota State University, Unpublished, Various Years.
North Dakota Public Service Commission, http://www.psc.state.nd.us/ June 2000.
Tolliver, Denver, The Effects of Local and Regional Railroads on Intermodal and
Intramodal Competition,UGPTI Publication No. 77, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. November 1989.
United States Department of Commerce, Bureau of Economic Analysis, Regional Economic Analysis Division, June, 1999.
Upper Great Plains Transportation Institute, North Dakota State University. ND Public Service Commission Grain Movement Data. Various Years.
Upper Great Plains Transportation Institute, North Dakota State University, "2000 North Dakota Elevator Industry Transportaiton & Rail Service Survey Results," April 2000.
North Dakota Grain and Oilseed Shipment Statistics, Upper Great Plains Transportation Institute, North Dakota State University, Unpublished, Various Years.
Upper Great Plains Transportation Institute, North Dakota State University, 1999 ND Elevator Survey Results, May 1999.
Upper Great Plains Transportation Institute, North Dakota State University, 2000 ND Elevator Survey Results, April 2000.
Upper Great Plains Transportation Institute, North Dakota State University, 2000 ND Farm Truck Fleet Survey Results, to be Published.
Vachal, Kimberly and Charlie Cooper, 1998-99 North Dakota Grain and Oilseed
Transportation Statistics, UGPTI Publication No. 133, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. October 1999.
Vachal, Kimberly, Denver Tolliver, John Bitzan, and Bridget Baldwin, Marketing Hard Red Spring Wheat in 100-Car Trains, MPC Report No. 98-93, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. August 1998.
Vachal, Kimberly, Mike Saewert, and John Bitzan, North Dakota Wheat Producer Marketing, MPC Report No. 96-57, Upper Great Plains Transportation Institute, North Dakota State University, Fargo. February 1996.
| HRS Wheat | Durum | Corn | Barley | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PNW | Gulf | Total | PNW | Gulf | Total | PNW | Gulf | Total | PNW | Gulf | Total | |
| 1990 | 45% | 44% | 259,573 | 4% | 27% | 79,721 | 21% | 71% | 2,080,438 | 24% | 5% | 128,570 |
| 1991 | 41% | 51% | 288,093 | 4% | 43% | 43,619 | 18% | 75% | 1,752,116 | 38% | 10% | 66,665 |
| 1992 | 33% | 56% | 395,060 | 2% | 31% | 60,815 | 15% | 80% | 1,691,804 | 25% | 12% | 85,550 |
| 1993 | 43% | 44% | 380,973 | 3% | 43% | 49,013 | 15% | 78% | 1,553,410 | 30% | 7% | 63,815 |
| 1994 | 65% | 21% | 267,168 | 15% | 68% | 39,348 | 11% | 83% | 1,330,564 | 14% | 4% | 69,618 |
| 1995 | 56% | 25% | 317,523 | 2% | 63% | 36,814 | 26% | 67% | 2,329,833 | 68% | 11% | 62,126 |
| 1996 | 48% | 27% | 321,915 | 1% | 57% | 31,932 | 21% | 73% | 2,006,439 | 68% | 10% | 35,989 |
| 1997 | 53% | 31% | 250,132 | 0% | 55% | 45,017 | 26% | 71% | 1,589,131 | 54% | 0% | 55,996 |
| 1998 | 53% | 24% | 247,426 | 5% | 57% | 32,140 | 11% | 78% | 1,545,109 | 79% | 0% | 25,646 |
| 1999 | 55% | 26% | 230,692 | 3% | 59% | 39,714 | 17% | 73% | 1,967,320 | 82% | 0% | 25,366 |
| 90-94 Avg. | 45% | 43% | 318,173 | 6% | 42% | 54,503 | 16% | 77% | 1,681,666 | 26% | 8% | 82,844 |
| 95-99 Avg. | 53% | 27% | 273,538 | 2% | 58% | 37,123 | 20% | 73% | 1,887,566 | 70% | 4% | 45,025 |
| Source: Agricultural Marketing Service, USDA, Grain and Feed Weekly Summary and Statistics, various issues. Note: Percents to not sum to 100, due to exports through others ports. Total (in 1,000 bushels) reflects exports through all ports. | ||||||||||||
Appendix B. Individual Commodity Production Densities
Figure 22. Production Density for North Dakota HRS Wheat Production, Avb. 1994-1999
Figure 23. Production Density for North Dakota Durum Production, Avg. 1994-1999
Figure 24. Production Density for North Dakota Barley Production, Avg. 1994-1999
Figure 25. Production Density for North Dkota Corn Production, Avg. 1994-1999