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- In addition, we observe children once they are in first grade and ideally we would like to have birth records to perform our analysis. Data from official vital statistics (MINSAL 1996, 1997, 1998) show that the number of births is about 21K each month for the years we study. If we exclude the 7% of those children (who enroll in the private schools), then we get very close to our sample of 19K per month. In addition, the same source indicates that the number of births was evenly distributed by month of birth (taking into account the different number of days each month has), as we also find in our data with first grade enrollment.
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Rubio-Codina, M., Araujo, M. C., Attanasio, O., Muñoz, P., and Grantham-McGregor, S. (2016). Concurrent validity and feasibility of short tests currently used to measure early childhood development in large scale studies. PLoS One, 11(8):e0160962. Appendices i A Appendix: Robustness A.1 Density of Running Variable We test for differences in unobserved characteristics by examining whether there is manipulation of birth dates near the cutoffs in our data. For example, it could be the case that more motivated parents planned the timing of their children’s birth in order for them to be older when enrolling in primary school. If parents consider school starting age rules when timing conceptions or births dates by scheduling C-sections, for instance, our results would be subject to manipulation and sample selection bias.
- We test for manipulation using a nonparametric test of discontinuity in the density of students born at each side of the eligibility rule, provided by Cattaneo et al. (2018). The manipulation test is -0.3668, with a p-value of 0.7138, which indicates that there is no statistical evidence of systematic manipulation of the running variable.
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