Assessing risk perception by means of ordinal models

Paola Cerchiello, Maria Iannario and Domenico Piccolo
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Paola Cerchiello: University of Pavia, Department of Statistics and Applied Economics “L.Lenti”
Maria Iannario: University of Naples Federico II, Department of Statistical Sciences
Domenico Piccolo: University of Naples Federico II, Department of Statistical Sciences

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2010, pp 75-83 from Springer

Abstract: Abstract This paper presents a discrete mixture model as a suitable approach for the analysis of data concerning risk perception, when they are expressed by means of ordered scores (ratings). The model, which is the result of a personal feeling (risk perception) towards the object and an inherent uncertainty in the choice of the ordinal value of responses, reduces the collective information, synthesising different risk dimensions related to a preselected domain. After a brief introduction to risk management, the presentation of the CUB model and related inferential issues, we illustrate a case study concerning risk perception for the workers of a printing press factory.

Keywords: risk perception; CUB models; ordinal data (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-88-470-1481-7_8

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DOI: 10.1007/978-88-470-1481-7_8

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