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Migration and Self-selection: An Agent-Based Model

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Computational Statistics and Mathematical Modeling Methods in Intelligent Systems (CoMeSySo 2019 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1047))

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Abstract

We construct an agent-based economic model that is capable of reproducing the mechanisms of internal migration of workers by focusing on the auto-selective characteristic of the subject-matter. Our model considers the potential of people to migrate as well as those who do migrate. Thus, the model introduces a pre-selection stage into the act of migrating. This is mainly performed using a hypothesis, which was previously discussed in other theoretical works covering the dynamics of migration, but rarely tested. To migrate, an individual must have a certain profile and a real pecuniary gain primarily sought through highly probable hiring strategies.

We use an agent-based model to simulate individuals’ migration. Two types of agents are considered: Individuals and Regions. We describe each type of agents by a set of equations. We also consider many variables to introduce Individuals’ and Regions’ properties and heterogeneity.

The use of agent-based model allows for the consideration of a high heterogeneity of agents while at the same time permitting us to test the effect of individuals ‘self-selection’. The obtained results show the importance to take self-selection aspect and heterogeneity in migration analysis.

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Notes

  1. 1.

    Labour market tension measures the ability of the labour market to absorb new entrants into the labour market. It equals to the ratio between vacancies and the number of new unemployed.

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Correspondence to Samira Boulahbel-Bachari .

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Boulahbel-Bachari, S., El Saadi, N. (2019). Migration and Self-selection: An Agent-Based Model. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Computational Statistics and Mathematical Modeling Methods in Intelligent Systems. CoMeSySo 2019 2019. Advances in Intelligent Systems and Computing, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-31362-3_28

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