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
• Data Transmission Network(Scoular
grain)- high FM band transmission to
elevators/ vendors
Farm Newsletters
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•
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Kiplinger Ag Letter
Pro Farmer
Brock & Associates
Others-FGL,etc.
* These provided advice plus information
Market Information History
• Radio
• * College station ISU- futures price
broadcast/ updated on the hour
• * WHO ( Worthington,MN) –updated
information
• * WCCO- update several times/day
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
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
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
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
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
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 websiteregional basis in Minnesota, decision aids
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
Early Spatial Price Maps
• W. Nefstead/Kurt Collins- U. of Minnesota1998
• 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
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
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
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.
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.
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
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.
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.
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.