Measuring the Difference (X — Y) of Simulated Distributions: A Convolutions Approach

Gregory Poe, Eric K. Severance-Lossin and Michael P. Welsh

American Journal of Agricultural Economics, 1994, vol. 76, issue 4, 904-915

Abstract: Resampling or simulation techniques are now frequently used in applied economic analyses. However, significance tests for differences between empirical distributions have either invoked normality assumptions or have used nonoverlapping confidence interval criteria. We demonstrate that such methods generally will not be appropriate, and we present an empirical test, based on the method of convolutions, for assessing the statistical significance between approximate empirical distributions created by resampling techniques. The proposed convolutions approach is illustrated in a case study involving empirical distributions from dichotomous choice contingent valuation data.

Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (73)

Downloads: (external link)
http://hdl.handle.net/10.2307/1243750 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:76:y:1994:i:4:p:904-915.

Access Statistics for this article

American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().