Computational Methods for Measuring the Difference of Empirical Distributions

13 Pages Posted: 21 Apr 2020

See all articles by Gregory L. Poe

Gregory L. Poe

Cornell University

Kelly Giraud

University of New Hampshire - Department of Resource Economics and Development

John Loomis

Colorado State University, Fort Collins - Colorado State University

Date Written: May 2005

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.

Keywords: bootstrapping, contingent valuation, endangered species, measuring differences of distributions, scope testing

Suggested Citation

Poe, Gregory L. and Giraud, Kelly and Loomis, John, Computational Methods for Measuring the Difference of Empirical Distributions (May 2005). American Journal of Agricultural Economics, Vol. 87, Issue 2, pp. 353-365, 2005, Available at SSRN: https://ssrn.com/abstract=3581104 or http://dx.doi.org/10.1111/j.1467-8276.2005.00727.x

Gregory L. Poe (Contact Author)

Cornell University

Kelly Giraud

University of New Hampshire - Department of Resource Economics and Development ( email )

15 College Road
Durham, NH 03824
United States

John Loomis

Colorado State University, Fort Collins - Colorado State University

Department of Economics
Fort Collins, CO 80253-1771
United States

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