Migration and academic performance in higher education: evidence for Colombia

ABSTRACT

We study the relationship between academic performance of students in higher education and the decision to migrate. We focus on the case of Colombia due to the good availability of data on standardised tests for students in higher and secondary education. We exploit this information following an empirical strategy that allows us to identify the existence of negative effects associated with the decision to migrate, controlling for potential academic benefits of migration, such as belonging to better social networks in the receiving cities of migrants. These negative effects are associated with the psychological and financial costs that students face when migrating. Similarly, we follow a novel strategy by controlling for potential commuter students who are not identified in the sample, or who may be misclassified as migrants. These robustness exercises show that the result found previously is maintained, which is favourable to the hypothesis of the existence of negative effects associated with migration on academic performance. This result is relevant for the elaboration of educational policies in developing countries.

KEYWORDS:

• higher education
• academic performance
• migration

JEL:

• I21
• I29
• R23

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in Open Science Framework at http://doi.org/10.17605/OSF.IO/UY9V5

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1 We did not include city fixed effects because these are absorbed by the HEI programme fixed effects. INSE (índice de nivel socioeconómico) results from the principal components analysis were applied to a broad set of socio-economic variables of the students. Therefore, it captures the joint variability of this comprehensive set of variables, including the socio-economic stratum. However, in Colombia, the inequality of monetary income is high. Therefore, income will likely be a relevant predictor of student performance. The INSE alone does not allow for capturing this high-income inequality. Including the socio-economic strata and other characteristics of the students’ households will enable us to control more explicitly for this aspect.

2 We adopt this argument from Beine et al. (2014) about the presence of country nationals at the destination.

3 For the complete version of this table, see Table A2 in Appendix A in the supplemental data online.

4 The magnitude of the estimated coefficient for migration presents a substantial change between OLS-SB and IV-SB. We instrument an endogenous dummy variable with a ‘continuous’ variable in a linear reduced form. Therefore, variance of the predicted values of the first stage in IV is substantially different from the variance of endogenous dummy variable (Zhong et al., 2022). This substantial change in variances implies that the magnitudes of the coefficients estimated with OLS and IV are different. We assume the linear reduced form since we include a large set of fixed effects, which represent a substantial computational burden to estimate a probability model, probit or logit. The sign of the estimated coefficient is not affected. Therefore, we show evidence of adverse effects but not of the size of the adverse effects.