Accounting for Spatial Heterogeneity in Educational Outcomes and International Migration in Mexico Edith Yolanda Gutierrez-Vazquez,Landy Lizbeth Sanchez-Peña, Silvia Elena Giorguli-Saucedo - El Colegio de Mexico

1. Accounting for Spatial Heterogeneity in Educational Outcomes and International Migration in Mexico Edith Gutierrez Landy Sanchez Silvia Giorguli El Colegio de Mexico

2. Educational Outcomes and International Migration in Mexico: A Brief Review To have in mind: Educational attainment and international migration Positive effects: remittances improve chances of school to work transition Negative effects: the “culture of migration”: migration as a better social mobility mechanism than education Mexico-US Migration is characterized by: Strong regional component due to historical trajectories since the 90’s the stream spread diversified across the country Educational achievement is also strongly diverse across México How these two spatial patterns relates? How can be captured regional differences?

3. Testing Spatial Heterogeneity Hypothesis: Classical versus Spatial approaches Classical definition for migratory regions (Durand & Massey, 2003): Based on the historical intensity of Mexico-US flows and on migration prevalence ratio Hypothesis: International migration disincentives educational achievement, regional variations depending on historic experience: stronger effects in traditional and border regions and smaller in regions where outflow started recently Regions defined by migration prevalence at a given point in time

4. Testing Spatial Heterogeneity Hypothesis: Classical versus Spatial approaches Spatial approach Based on spatial heterogeneity in the relationship between education, international migration and labor market. Hypothesis: International Migration will have negative effect on educational outcomes but the variations will be due to historical migratory trajectories and to employment and educational infrastructure: strong effects of historical migration experience regions will decrease in regions with a good labor market performance and vice versa Regions are defined based on Geographically Weighted Regression results, not solely by migration prevalence

5. Testing Spatial Heterogeneity Hypothesis: Methodological Issues Both Classical and Spatial Hypothesis imply spatial processes of: Dependence: Autocorrelation within regions between local educational outcomes and education, migration and employment trade offs Heterogeneity: Significant differences in the effects of migration or labor on educational attainment across regions Need a dependence and structural heterogeneity spatial model to decide which is the best approach to define regions

6. General Methodological strategy Both hypothesis require spatial analysis techniques and suggest a spatial dependence process: Corroborating spatial effects: OLS regression Moran’s I Local Indicators of Spatial Association Proving differences across regions: Spatial Regimes model with a spatial dependence term and a heteroskedasticity correction Migration parameter significance Chow-Wald Test Coefficients Stability Test

7. Variables

8. Educational Outcomes Moran’s I 0.3713 International Migration Moran’s I 0.6239 Results: Significant spatial dependence, heteroskedasticity issues and significant clusters across the country

9. International Migration Female Labor Low-income Workers Industrialization level

10. Traditional Regions Spatially Defined Regions

11. OLS Results: Dependence and heteroskedasticity tests Traditional Regions Spatially Defined Regions Heteroskedasticity test, both regional definitions: The Koenker-Bassett has a 1% significance level

12. Results Spatial Model with Structural Change and GroupwiseHeteroskedasticity

13. Spatially defined regions Results Spatial error Model with Structural Change and GroupwiseHeteroskedasticity

14. Spatially defined regions Results Spatial lag Model with Structural Change and GroupwiseHeteroskedasticity

15. Conclusions Negative effects of international migration on educational outcomes Results support hypothesis raised from an interaction between education, migration and labor market Regions based on spatial-varying links between dimensions studied are more appropriate to capture heterogeneity and diffusion processes than those defined previously by migration historicity Need to use proper geostatistical methods to test and develop hypotheses that imply spatial effects Regions are essential to consider how the relationships between sociodemographic variables shape geographical disparities