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Computational Methods for Measuring the Difference of Empirical Distributions

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  • Gregory L. Poe
  • Kelly L. Giraud
  • John B. Loomis

Abstract

This paper presents a simple computational method for measuring the difference of independent empirical distributions estimated by bootstrapping or other resampling approaches. Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate. Copyright 2005, Oxford University Press.

Suggested Citation

  • Gregory L. Poe & Kelly L. Giraud & John B. Loomis, 2005. "Computational Methods for Measuring the Difference of Empirical Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 353-365.
  • Handle: RePEc:oup:ajagec:v:87:y:2005:i:2:p:353-365
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2005.00727.x
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