Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/23479 
Year of Publication: 
2001
Series/Report no.: 
Staff Paper No. SP 2001-05
Publisher: 
Cornell University, Charles H. Dyson School of Applied Economics and Management, Ithaca, NY
Abstract: 
This paper develops a statistically unbiased and simple method for measuring the difference of independent empirical distributions estimated by bootstrapping or other simulation approaches. This complete combinatorial method is compared with other unbiased and biased methods that have been suggested in the literature, first in Monte Carlo simulations and then in a field test of external and internal scope testing in contingent valuation. Tradeoffs between methods are discussed. When the empirical distributions are not independent a straightforward difference test is suggested.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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