Abstract
This article introduces a Kolmogorov-type test for the shortfall order (also known in the literature as the right-spread or excess-wealth order) against parametric alternatives. In the case of the null hypothesis corresponding to the negative exponential distribution, this provides a test for the new-better-than-used-in-expectation and for the new-worse-than-used-in-expectation properties. Such a test is particularly useful in reliability applications, as well as duration and income distribution analysis. The theoretical properties of the testing procedure are established first for uncensored data, and then for censored and truncated data. Simulation studies reveal that the test based on a bootstrap procedure performs well, even with moderate sample sizes. Applications to real data (chief executive officer compensation data, flight delay data, and throttle failure data) illustrate its empirical relevance.
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