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Implementation of stochastic dominance: a nonparametric kernel approach

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  • Charles Moss
  • Grigorios Livanis

Abstract

The empirical application of stochastic dominance in the selection of crop alternatives under risk has typically been based on a step function specification of the empirical cumulative distribution function (cdf). This specification has questionable consequences for the analysis, particularly with regards to the tails of the distribution. This article proposes an alternative nonparametric approach based on a nonparametric regression of the cdf. The effect of this alternative specification is then demonstrated using data from Northern Florida. Results are more realistic. The first-degree stochastic dominance results are less discriminating under the new specification while the second-degree results are more discriminating.

Suggested Citation

  • Charles Moss & Grigorios Livanis, 2009. "Implementation of stochastic dominance: a nonparametric kernel approach," Applied Economics Letters, Taylor & Francis Journals, vol. 16(15), pages 1517-1522.
  • Handle: RePEc:taf:apeclt:v:16:y:2009:i:15:p:1517-1522
    DOI: 10.1080/13504850701578876
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    Cited by:

    1. Tzouramani, Irene & Karanikolas, Pavlos & Alexopoulos, George, 2008. "Risk and Income Risk Management Issues for Organic Crops in Greece," 108th Seminar, February 8-9, 2008, Warsaw, Poland 48116, European Association of Agricultural Economists.
    2. Tzouramani, Irene & Karanikolas, Pavlos & Alexopoulos, George & Sintori, Alexandra & Liontakis, Angelos E., 2008. "Modelling Economic Alternatives For Tobacco Producers: The Case Of Sheep Farming," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6695, European Association of Agricultural Economists.
    3. Dahl, Bruce L. & Wilson, William W. & Nganje, William E., 2004. "Stochastic Dominance in Wheat Variety Development and Release Strategies," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(01), April.

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