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    Model misspecification in peaks over threshold analysis

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    Classical peaks over threshold analysis is widely used for statistical modeling of sample extremes, and can be supplemented by a model for the sizes of clusters of exceedances. Under mild conditions a compound Poisson process model allows the estimation of the marginal distribution of threshold exceedances and of the mean cluster size, but requires the choice of a threshold and of a run parameter, KK, that determines how exceedances are declustered. We extend a class of estimators of the reciprocal mean cluster size, known as the extremal index, establish consistency and asymptotic normality, and use the compound Poisson process to derive misspecification tests of model validity and of the choice of run parameter and threshold. Simulated examples and real data on temperatures and rainfall illustrate the ideas, both for estimating the extremal index in nonstandard situations and for assessing the validity of extremal models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS292 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Weathering the Storm of Business Climate Rankings

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    This paper explores current usage of the term business climate. It discusses multiple definitions and measures of what constitutes a region's business climate. It also examines how usage of the term varies over time and geography. Finally, it addresses some issues related to business climate rankings, their role in economic development policy, and whether the multiplicity of published state rankings contribute consensus or confusion to the meaning of the term business climate.
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