Resource information
Conservation auctions are increasingly being used to procure publicenvironmental goods on private land. In the absence of demand-sideprice information, the majority of conservation auctions in Australia havebeen designed without a reserve price. In these instances bids have beenaccepted in order of cost-effectiveness until the budget constraint binds. Itis widely recognised that in situations where auctions are run repeatedlya reserve price strategy could allow for a more efficient allocation of fundsacross multiple rounds, both spatially and temporally.This paper provides a brief overview of methods for determining areserve price for application in conservation auctions. It is concluded thatinformation deficiencies and the high transaction costs involved in theapplication of these methods to conservation auctions often render themunsuitable for application to real-world auctions.This paper presents an empirical approach to determining a reserveprice using data obtained during an auction - the supply curve. Theapproach stems from the C4.5 algorithm, developed in the field ofdata mining to construct decision trees from training data using theconcept of information entropy. The algorithm establishes a reserve priceby determining the cut-off price that results in the ”best fit” of twonormal distributions to the frequency distribution of bid-price per unitenvironmental benefit.Empirical data from conservation auctions in Victoria is used todemonstrate the algorithm and compare auction results obtained usingthe algorithm and traditional ”budget” methods. The paper presents adiscussion on the situations where the algorithm could be appropriatelyused, and advantages and limitations of the approach are identified. Thepaper concludes that the use of the algorithm can result in efficiency gainsover the traditional budget method in situations where alternative reserveprice strategies are impractical.
