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Measuring Job Satisfaction with CUB Models
Author(s) -
Gambacorta Romina,
Iannario Maria
Publication year - 2013
Publication title -
labour
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 34
eISSN - 1467-9914
pISSN - 1121-7081
DOI - 10.1111/labr.12008
Subject(s) - job satisfaction , statistics , econometrics , computer science , psychology , mathematics , social psychology
In this paper we present two statistical approaches for discussing and modelling job satisfaction based on data collected in the S urvey on H ousehold I ncome and W ealth ( SHIW ) conducted by the B ank of I taly. In particular, we analyse these data by means of a mixture model introduced for ordinal data and compare results with the O rdinal P robit model. The aim is to establish common outcomes and differences in the estimated patterns of global job satisfaction, but also to stress the potential for curbing the effects of measurement errors on estimates by using CUB models [a C ombination of discrete U niform and (shifted) B inomial distributions], allowing control for the effect of uncertainty and shelter choices in the response process.