
ContinuousTime Markov Model for Transitions Between Employment and NonEmployment: The Impact of a Cancer Diagnosis

Type de document

Articles dans des revues scientifiques 
Titre original du chapitre

ContinuousTime Markov Model for Transitions Between Employment and NonEmployment: The Impact of a Cancer Diagnosis 
Auteurs physiques

Joutard, X., Paraponaris, A., Sagaon Teyssier, L., Ventelou, B. 
Date d'édition

2012 
Revue

ANNALS OF ECONOMICS AND STATISTICS ; 107/108 : 239265 
Résumé du document en anglais

This article investigates whether a cancer diagnosis can cause a persistent loss in employability.
We estimate continuoustime Markov transition processes, between employment statuses, to study
and compare the labor market dynamics in two populations: 1) individuals diagnosed with cancer,
and 2) individuals selected in the general population. The consequences of cancer diagnosis
were measured by the significant deviation in the transition matrix for cancer survivors in
comparison to the prior matrix standardized according to the general population. We accounted
for the probability that some individuals in the control group (i.e., the general population)
could be diagnosed with cancer which is a keyissue in casecontrol studies. The absence of
detailed information about the health statuses of the individuals in the control group required
the implementation of the EM algorithm for maximizing the adapted likelihood function. We
jointly estimated the probability of being diagnosed with cancer in the control group and the
parameters of our model. Given that individuals are exposed differently to cancer depending
on their activities, we stratified the dataset by socioeconomic status (SES) with two objectives:
1) to clearly distinguish between the cancerspecific effects, and 2) to account for the other
stigmatizing factors in the labor market that are inherent to the examined subpopulations (i.e.,
low and highSES groups). We also considered the systematic differences in the subjects’
socioeconomic statuses and their abilities to return to work, and then, we determined whether
these differences are related to illness (e.g., cancer sites or prognosis) or occupation (e.g., physical
demands).* 
Code bibliographique

12_S56 
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