Statistical Models for Measuring Job Satisfaction

50 Pages Posted: 29 Mar 2012

See all articles by Romina Gambacorta

Romina Gambacorta

Bank of Italy

Maria Iannario

University of Naples Federico II

Date Written: February 23, 2012

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 modeling, CUB models

JEL Classification: J28, C25

Suggested Citation

Gambacorta, Romina and Iannario, Maria, Statistical Models for Measuring Job Satisfaction (February 23, 2012). Bank of Italy Temi di Discussione Working Paper No. 852, Available at SSRN: https://ssrn.com/abstract=2030802 or http://dx.doi.org/10.2139/ssrn.2030802

Romina Gambacorta (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy

Maria Iannario

University of Naples Federico II ( email )

via Cinthia, 4
Naples, Caserta 80126
Italy

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