Abstract
We propose a finite mixture latent trajectory model to study the behavior of firms in terms of open-ended employment contracts that are activated and terminated during a certain period. The model is based on the assumption that the population of firms is composed by unobservable clusters (or latent classes) with a homogeneous time trend in the number of hirings and separations. Our proposal also accounts for the presence of informative drop-out due to the exit of a firm from the market. Parameter estimation is based on the maximum likelihood method, which is efficiently performed through an EM algorithm. The model is applied to data coming from the Compulsory Communication dataset of the local labor office of the province of Perugia (Italy) for the period 2009–2012. The application reveals the presence of six latent classes of firms.
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Acknowledgments
We acknowledge the financial support from the grant “Finite mixture and latent variable models for causal inference and analysis of socio-economic data” (FIRB - Futuro in ricerca - 2012) funded by the Italian Government (grant RBFR12SHVV). We also thank the Province of Perugia (Direction for “Work, Training, School and European Policies”) for permitting to extract specific data from the “Compulsory Communication database of the Employment Service Centers”.
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Bacci, S., Bartolucci, F., Pigini, C., Signorelli, M. (2016). A Finite Mixture Latent Trajectory Model for Hirings and Separations in the Labor Market. In: Di Battista, T., Moreno, E., Racugno, W. (eds) Topics on Methodological and Applied Statistical Inference. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-44093-4_2
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DOI: https://doi.org/10.1007/978-3-319-44093-4_2
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