In recent years, the debate on flexible employment has been at the center of political and scientific discussion in Europe. Findings on mobility from flexible to permanent employment can be severely biased due to measurement error, usually present in the data used for analysis. The aim of this paper is to use a mixed hidden Markov model (MHMM) to study the effect of measurement error on the role of flexible employment in the life course. Specifically, we employ a MHMM with two indicators for the employment contract, coming from linked data from the Labour Force Survey and the Employment Register of the Netherlands for the period 2007-2015.

Patterns of flexible employment careers. Does measurement error matter? / Pavlopoulos, Dimitris; Garnier-Villarreal, Mauricio; Varriale, Roberta. - (2023), pp. 985-990. (Intervento presentato al convegno Statistical Learning, Sustainability and Impact Evaluation SIS 2023 tenutosi a Ancona).

Patterns of flexible employment careers. Does measurement error matter?

Roberta Varriale
2023

Abstract

In recent years, the debate on flexible employment has been at the center of political and scientific discussion in Europe. Findings on mobility from flexible to permanent employment can be severely biased due to measurement error, usually present in the data used for analysis. The aim of this paper is to use a mixed hidden Markov model (MHMM) to study the effect of measurement error on the role of flexible employment in the life course. Specifically, we employ a MHMM with two indicators for the employment contract, coming from linked data from the Labour Force Survey and the Employment Register of the Netherlands for the period 2007-2015.
2023
Statistical Learning, Sustainability and Impact Evaluation SIS 2023
mixed hidden Markov model; latent variable model; multisource data; employment careers
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Patterns of flexible employment careers. Does measurement error matter? / Pavlopoulos, Dimitris; Garnier-Villarreal, Mauricio; Varriale, Roberta. - (2023), pp. 985-990. (Intervento presentato al convegno Statistical Learning, Sustainability and Impact Evaluation SIS 2023 tenutosi a Ancona).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1703878
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