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Incorporating Spatial Grain Price Information in Marketing Plans: A Minnesota Example

Incorporating Spatial Grain Price Information in Marketing Plans: A Minnesota Example. Ward E.Nefstead Associate Professor& Extension Economist University of Minnesota. Brief History- Market Price Information. Print media: *Newspaper- futures and local price information

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Incorporating Spatial Grain Price Information in Marketing Plans: A Minnesota Example

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  1. Incorporating Spatial Grain Price Information in Marketing Plans: A Minnesota Example Ward E.Nefstead Associate Professor& Extension Economist University of Minnesota

  2. Brief History- Market Price Information • Print media: *Newspaper- futures and local price information • Data Transmission Network(Scoular grain)- high FM band transmission to elevators/ vendors

  3. Farm Newsletters • Kiplinger Ag Letter • Pro Farmer • Brock & Associates • Others-FGL,etc. • * These provided advice plus information

  4. Market Information History • Radio • * College station ISU- futures price broadcast/ updated on the hour • * WHO ( Worthington,MN) –updated information • * WCCO- update several times/day

  5. DTN Extends to Farms • DTN developed network to sell to farms • Captive terminals allowed selective distribution of content • Additional pages could be added such as newsletters/ local price information

  6. Research in Marketing Information/Grain Marketing • U. of Minnesota- Rob King/ W. Lazarus/Stan Stevens • Marketing club software/ option-based futures projection • Annual market price outlook- fall

  7. Farm Market Advisory Research • First Nat’l Bank-Bloomington, Ill.- 1970’s • AgMAS project- U. of Illinois • Merrill Lynch- Chicago office-futures marketing plan based on advisory information

  8. Early Grain Basis Research • W. Anthony( U. of Minnesota)- used Mpls terminal prices minus a transportation differential to estimate local basis • Charting and basis charts prepared by marketing clubs- some Adult Farm Mg’t • Manual charts became computer-based with the advent of microcomputers and spreadsheets

  9. Internet Influence on Grain Price Information • DTN moved information to internet site • Real time or delayed information now fed to receiver • Website development fosters unique collection and presentation of information

  10. Websites featuring grain price information/analysis • Farms.com • AgDayta.com • Other sites- FarmDoc(U. of Illinois) regional basis in Illinois, supply-demand historic information,other • Newer sites- W. Nefstea/faculty website- regional basis in Minnesota, decision aids

  11. Access to Local Grain Price Information • Creation of National Corn and Soybean Indices- by Minneapolis Grain Exchange. • Indices are used for hedging,etc • Data collection on spot elevator prices by DTN

  12. Early Spatial Price Maps • W. Nefstead/Kurt Collins- U. of Minnesota- 1998 • Used UROP grant to purchase spatial software & project maps based on data. • Paper presented at AAEA meeting on nature of local grain price distributions and incorporation of sampling from distributions in marketing plan spreadsheets

  13. Spatial Grain Price Projects • K. McNew- Montana State U.- publication of monthly spatial maps based on NCI/NSI/Other data • K. DuyVetter- Kansas State U.- AgManager series shows monthly basis maps and projections for multistate area • B.Babcock- Iowa State University- added maps on CARD

  14. How To Use Spatial Price Information • Corresponds to dilemma in precision agriculture- how do we use field maps • Precision-based marketing is a refinement of basic marketing plans • Spatial price variation affects “ where” and “when” to sell

  15. Spatial Price Information Decisions to Sell • “where” to market- spot sales- will generate a return over transportation costs in excess of $.17 per bu on corn and $.23 per bu. On soybeans. Faculty website-Wnefstead contain weekly maps and transportation algorithm plus spreadsheet marketing plan software.

  16. Spatial Price Information also affects” When” to sell • Price maps show basis changes over time by local area so storage decisions/ hedging/forward contracting decisions are also affected. • Basis maps show relationships to flat price series. Higher prices have shifted to different areas of the state.

  17. Commercial Products Related to Spatial Prices • AgDayta has experimental program-called Optimizer • Internet-based marketing plans are also available from the same vendor and in beta form elsewhere

  18. Case Farm-SW Minnesota • Near Marshall, Minnesota • 300 acres- 150 used for corn; 150 used for soybean production. • Expected crop production- 2004- 12,000 bu. Corn and 4,000 bu. Soybeans • Prices view in 45 mile radius. • Price variation within area- $.48 corn and $1.18 soybeans.

  19. Case Farm Example • Net gain of $5700 for corn and $4720 for soybeans on this farm • This gain is the result of increased spot and delayed delivery prices. • The software consisted on website and spreadsheet-based decision aids.

  20. Future research and programs • Modification of mechanical marketing strategies to incorporate price forecast and spatial data • Refinement of spatial price information to include other delayed prices.

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