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Analysing Farmers’ Use of Price Hedging Instruments: An Experimental Approach

  • Friederike Anastassiadis , Jan-Henning Feil EMAIL logo , Oliver Musshoff and Philipp Schilling


This paper analyses the influencing factors of farmers’ use of price hedging instruments (PHIs) based upon a discrete choice experiment with German grain farmers. A mixed logit model is used to determine whether farmers’ choices of PHIs against cash sales are influenced by their price expectation, their risk attitude and their available storage capacities. The results show that farmers with a price expectation below the actual price level have a higher preference for using PHIs against cash sales in general and that the individual degree of risk aversion can have a significant impact on farmers’ choices of a specific PHI. A generally lower preference of farmers with available storage capacities for using PHIs as assumed in many theoretical contributions in the literature, however, cannot be confirmed.


We would like to thank the anonymous referees and the editors for their helpful comments and suggestions. We gratefully acknowledge financial support from the German Research Foundation (DFG).

Appendix 1: Decision-making situation and choice-sets of the experiment

The online survey was put online during January 2012 and was brought to farmers’ notice through online newsletters of two agricultural consulting companies. In addition, students from the University of Göttingen were also asked to make farmers aware of the experiment.

All participating farmers made the six choice-sets of the DCE in one sitting, although they had the possibility to interrupt the experiment. Farmers were not offered an incentive or compensation to participate in the experiment. In addition, any feedback was provided.

The choice-sets differed only in the actual spot market price which the farmer was asked to assume while deciding between the marketing instruments. To avoid an order effect when presenting the choice-sets to the farmers, the sequence of the choice-sets was randomly chosen by the computer. In the following, the DCE is presented.

The six following choice-sets are presented to the respondent in a random order:

Appendix 2: Stata 12 code

In addition to the independent variables depicted in Table 2 of the article, the dependent variable “Choice” specifies the choice made by a farmer in a specific choice occasion. This variable is dummy-coded with 1 = alternative is chosen and 0 = alternative is not chosen. Furthermore we need two other variables: “Number” and “Occasion”. “Number” is a numeric identifier for the farmers (range from 1 to 136). In this way it is taken into account that the farmer answer six choice-sets. “Occasion” is a numeric identifier for the choice occasions (range from 1 to 6).

To integrate independent variables which do not vary over alternatives into the model it is necessary to generate interaction terms with the alternative specific constants. This procedure leads to four variables per independent variable (cf. the above-mentioned command for STATA).

For more information regarding the STATA-command “mixlogit” readers are referred to the STATA help-file.



























rand(asc_forward asc_managed asc_futures asc_option)

group(occasion) id(number) nrep(500)


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Published Online: 2014-12-2
Published in Print: 2014-1-1

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