Artikel
Modelling the occupational and educational choices of young people in Poland using Bayesian multinomial logit models
Binomial logit models are commonly used in the analysis of the situation of respondents on the labour market. Consequently, in most cases researchers consider two states: of being unemployed and employed or economically inactive and active. This paper focuses on the situation of young people aged 18 to 29 on the labour market in Poland. A major part of the people who comprise the studied group are still in education or combine education with work. Therefore, the participants of the research were divided into the following groups: the employed and not learning, those combining education with work, the unemployed, learners/students only, and those economically inactive and not at school. The model allowing an analysis which includes both the most common division into working and non working persons as well as the division proposed in this study is a nested logit model. This model has a hierarchical structure and is a special case of a multinomial logit model. In this paper, all models were estimated within the Bayesian approach. The findings show that continuing education by young people may result from their problems with finding a job; moreover, combining work with education is not the preferred form of professional activity. In addition, the study examines the inequalities observed on the Polish labour market.
- Language
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Englisch
- Bibliographic citation
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Journal: Statistics in Transition New Series ; ISSN: 2450-0291 ; Volume: 22 ; Year: 2021 ; Issue: 3 ; Pages: 175-191 ; New York: Exeley
- Subject
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young people
labour market
education
multinomial logit model
Bayesian approach
- Event
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Geistige Schöpfung
- (who)
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Grzenda, Wioletta
- Event
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Veröffentlichung
- (who)
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Exeley
- (where)
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New York
- (when)
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2021
- DOI
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doi:10.21307/stattrans-2021-033
- Handle
- Last update
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10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Grzenda, Wioletta
- Exeley
Time of origin
- 2021
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