Bidding for Timber
6 Pages Posted: 23 Jun 2009
A forestry analyst must review the recent bidding history of 103 timber trees in order to prepare bids for future timber auctions. A regression analysis to predict highest competing bid and a decision analysis to select a bid to maximize expected profit might be used to prepare the case. Students are required to build their own linear models.
BIDDING FOR TIMBER
In the 1970's, the United States National Forest Service (NFS) sold timber rights through a series of regularly scheduled auctions. These auctions were conducted by one of two methods: (1) sealed bid, in which each bidder submitted a confidential, sealed bid and the highest bidder won the timber rights at the price bid, or (2) oral, in which bidders submitted bids orally (heard by all other bidders) in ever increasing amounts until one winning bidder remained to pay the last (highest) amount bid.
The winning party received the right to harvest any or all timber on the tract for a specified period of time, usually five years, after which the rights expired. Prior to each auction, interested bidders could survey the tract offered in order to estimate the value of its timber.
Clifford Walsh, forestry analyst for Northwest Pacific (NP), had been given the task of analyzing the recent competitive bidding behavior in Oregon's Douglas and Lane counties. NP was experiencing an unexpected increase in demand for its lumber and paper products in late 1977 and had decided to expand into new territories. The company had selected areas in the two counties as promising. NP had yet to submit a bid for a tract in this new area, however, and management was anxious for the results of Walsh's analysis so that they could move quickly.
Exhibit 1 contains the information available to Walsh on 103 completed timber auctions in Douglas and Lane counties in 1977, and Exhibit 2 defines each of the Exhibit 1 variables. Note that NP went to the expense of estimating the value to it of each of these tracts of timber. This estimated value differs from the NFS estimate because the NFS estimate is for the value of the end products while the NP estimate is for the value of the raw timber. The NFS estimate also does not take into account firm specific factors affecting the value NP would place on both the timber and the resulting end products.
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Keywords: bargaining/bidding, decision analysis, linear programming, regression analysis
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Bidding for Timber
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