Computational Methods for Measuring the Difference of Empirical Distributions
- Gregory L. Poe, associate professor,
- Kelly L. Giraud, assistant professor and
- John B. Loomis, professor
- Department of Applied Economics and Management, Cornell University
- Department of Resource Economics and Development, University of New Hampshire
- Department of Agricultural and Resource Economics, Colorado State University
- Received October 1, 2001.
- Accepted May 1, 2003.
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.
Key words
- bootstrapping
- contingent valuation
- endangered species
- measuring differences of distributions
- scope testing
JEL codes
- Copyright 2005 American Agricultural Economics Association
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