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Cascade Sensitivity Measures

Pesenti, S. M., Millossovich, P. ORCID: 0000-0001-8269-7507 and Tsanakas, A. ORCID: 0000-0003-4552-5532 Cascade Sensitivity Measures. .

Abstract

Sensitivity measures quantify the extent to which the distribution of a model output is affected by small changes (stresses) in an individual random input factor. For input factors that are dependent, a stress on one input should also precipitate stresses in other input factors. We introduce a novel sensitivity measure, termed cascade sensitivity , which captures the direct impact of the stressed input factor on the output, as well as indirect effects via other input factors that are dependent on the one being stressed. In this way, the dependence between inputs is explicitly taken into account. Representations of the cascade sensitivity measure, which can be calculated from a single Monte Carlo sample, are provided for two types of stress: a) a perturbation of the distribution of an input factor, such that the stressed input follows a mixture distribution, and b) an additive random shock applied to the input factor. These representations do not require simulations under different model specifications or the explicit study of the properties of the model’s aggregation function, making the proposed method attractive for practical applications, as is illustrated through numerical example.

Publication Type: Monograph (Working Paper)
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
Q Science > QA Mathematics
Departments: Cass Business School > Management
URI: http://openaccess.city.ac.uk/id/eprint/20808
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