Estimating compulsory schooling impacts on labor market outcomes in Mexico

A well-known problem in this analysis is the endogeneity between schooling and labor market outcomes due to unobservable characteristics that could jointly determine them. There is also heterogeneity in the empirical evidence of the effectiveness of such schooling policies among developing and developed countries, perhaps because of the different contexts and identification strategies used. Some studies use instrumental-variables (IV) and difference-in-differences (D-i-D) methods to tackle endogeneity issues. Most analyses use a regression discontinuity design (RDD) approach with different order polynomials of the year of birth (for example, cubic or quartic order), whereas few studies use birth month for more accurate and robust estimates because it allows more schooling variation within a year.

The impact of the Mexican policy is analyzed in this study through a fuzzy RDD approach with the use of Stata for the period 2009 to 2017. It addresses endogeneity by exploiting the age cohort discontinuities in birth month, for more robust estimation, as an exogenous source of education variation. Fuzzy RDD then compares schooling and labor market outcomes among the birth cohorts exposed with those not exposed to the reform. The fuzziness accounts for the imperfect compliance by using the random assignment of the exposure to the policy.

Stata allows plotting discontinuity graphs between cohorts as well as the McCrary test to validate the use of this methodology. It also facilitates parametric and nonparametric analyses. The empirical evidence suggests that the 1993 compulsory schooling law, although raising average school attendance, was an insufficient policy to impact labor market outcomes in Mexico. The analysis contributes to the limited literature on the returns to compulsory schooling that uses a rigorous RDD methodology in developed and developing countries.