Teachers' Sickness Absence in Primary Schools: A Panel Data Multilevel Analysis
This paper uses longitudinal employer–employee data and multilevel models to examine both observed and unobserved variation of the probability and length of certified and self-certified sickness absence for Norwegian primary school teachers. We argue that self-certified absences are particularly prone to moral hazard. We find that most of the observed teacher, school and municipality characteristics are significantly associated with the probability and the length of sickness absence. However, most of the unexplained variation is attributed to teacher factors rather than influenced by variation at the school or municipality levels. Teacher characteristics that may be associated with less attachment to the workplace increase the probability of self-certified absences. Moreover, the unexplained variation in schools and at municipality level is higher for self-certified than for certified sickness absence. There may be some scope for reducing self-certified absence by improving work conditions or changing administrative practices, but our main policy conclusion is that to reduce sickness absence, the main focus must be on individual health and the incentives to report sick.
|Date of creation:||01 Jun 2010|
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- Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number mimus2, November.
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