Statistical models for measuring job satisfaction
In this paper we present two statistical approaches for discussing and modelling job satisfaction based on data collected in the Survey on Household Income and Wealth (SHIW) conducted by the Bank of Italy. In particular, we compare two different classes of model for ordinal data: the Ordinal Probit Model and the more recent CUB 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, allowing us to control for the effect of uncertainty and shelter choices in the response process.
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