The Modified Lunn-Mcneil Model in the Assessment of Intensity of Exiting from the Unemployment
Bieszk-Stolorz Beata ()
Additional contact information
Bieszk-Stolorz Beata: University of Szczecin, Faculty of Economics and Management, Szczecin, Poland
Econometrics. Advances in Applied Data Analysis, 2019, vol. 23, issue 1, 77-89
Abstract:
The goal of the article is the assessment of the relative intensity of exiting from unemployment of long-term unemployed people with relation to their characteristics: gender, age, education, seniority and the number of subsequent registrations. The modified Lunn-McNeil model for various types of competing events: accepting the job, refusal and remaining causes of de-registration was used in the research. The modification consisted of the application of the stratified Cox model of non-proportional hazard, which allowed to assess the relative hazard after entering the state of long-term unemployment. The individual data of persons registered in the County [Powiat] Labour Office in Szczecin were used in the research. Age had the greatest impact on the change in relative hazard at the transition to long-term unemployment, while the level of education had no significant impact. The research made it possible to identify groups of people taking up work with the least intensity and refusing to take up jobs with the greatest intensity. These people should be taken into consideration during the process of creating the labour market policy.
Keywords: Lunn-McNeil model; non-proportional hazard model; competing events; long-term unemployment (search for similar items in EconPapers)
JEL-codes: C41 E24 J64 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.15611/eada.2019.1.06 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:vrs:eaiada:v:23:y:2019:i:1:p:77-89:n:2
DOI: 10.15611/eada.2019.1.06
Access Statistics for this article
Econometrics. Advances in Applied Data Analysis is currently edited by Józef Dziechciarz
More articles in Econometrics. Advances in Applied Data Analysis from Sciendo
Bibliographic data for series maintained by Peter Golla ().