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Measuring the Difference ( X — Y ) of Simulated Distributions: A Convolutions Approach
Author(s) -
Poe Gregory L.,
SeveranceLossin Eric K.,
Welsh Michael P.
Publication year - 1994
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1243750
Subject(s) - resampling , normality , confidence interval , mathematics , empirical research , econometrics , empirical distribution function , statistics , statistical hypothesis testing , interval (graph theory) , valuation (finance) , computer science , economics , combinatorics , finance
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.