Statistical models for measuring job satisfaction

Romina Gambacorta and Maria Iannario ()
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Maria Iannario: University of Naples Federico II

No 852, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: 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.

Keywords: job satisfaction; ordinal data modelling; CUB models (search for similar items in EconPapers)
JEL-codes: C25 J28 (search for similar items in EconPapers)
Date: 2012-02
New Economics Papers: this item is included in nep-hap and nep-lma
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Persistent link: https://EconPapers.repec.org/RePEc:bdi:wptemi:td_852_12

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