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Factors associated with the mobility of college students in Brazil: an analysis using a gravity model

Abstract

The Brazilian government has adopted measures that aim to influence students’ spatial mobility. The extent and success of such measures require detailed knowledge of the mobility determinants. Gravity models are the appropriate tool for analyzing the flows of college students from their place of origin to their destination. To analyze the determinants of student flows, we estimate a negative binomial regression model with Brazilian data. The results show the deterrence effect of distance on mobility, as the total costs of entering a university increase with the distance between the place of origin and the destination institution. Places with lower living costs and smaller university centers (campuses) are attraction factors to students, as are the possibility of having non-reimbursable financing and a larger number of study programs.

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Notes

  1. As of 2017, the IBGE (Brazilian Institute of Geography and Statistics) replaces the term mesoregion with an intermediate geographic region.

  2. Foreign students were excluded from the sample, as the Census does not provide the place of origin of non-Brazilian residents.

  3. For more details, see Barbosa (2020).

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Acknowledgements

This paper is financed by National Funds of the FCT – Portuguese Foundation for Science and Technology within the project «UIDB/03182/2020.

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Correspondence to Tatiane Pelegrini.

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Appendices

Appendix

Table 4

Table 5

Table 6

Table 4 Overdispersion test
Table 5 Pearson and Hosmer–Lemeshow goodness-of-fit test

Robustness tests

According to Cameron and Trivedi (2010), the countfit command implemented in Stata 14.0 allows for a comparison of the estimates’ adequacy obtained for Poisson (PRM), negative binomial (NBR), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models. Furthermore, this command compares the four models using the BIC and AIC criteria and the Vuong test. The command guides the choice of the preferred model and provides evidence that supports the appropriate choice. Table 6 summarizes the implemented tests that support the use of the negative binomial model over the other models.

Table 6 Goodness-of-fit test

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Pelegrini, T., Sá, C. & França, M.T.A. Factors associated with the mobility of college students in Brazil: an analysis using a gravity model. High Educ 85, 203–223 (2023). https://doi.org/10.1007/s10734-022-00829-5

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