Vol. 8 No. 78 (2026): April
Artículos

Pillars of development: Macroeconomic factors, unemployment, and completion of education

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  • Susana Amanda Vilchis Camacho,
  • Efraín Jaramillo Benhumea,
  • Minerva Martínez Ávila
Susana Amanda Vilchis Camacho
Universidad Autónoma del Estado de México
Efraín Jaramillo Benhumea
Universidad Autónoma del Estado de México
Minerva Martínez Ávila
Universidad Autónoma del Estado de México
DOI: https://doi.org/10.51896/rilcods.v8i78.1212

Published 2026-05-08

Keywords

  • Higher Education,
  • Completion of Education,
  • Macroeconomic Factors,
  • Public Policies,
  • Teacher Compensation

How to Cite

Vilchis Camacho, S. A., Jaramillo Benhumea, E., & Martínez Ávila, M. (2026). Pillars of development: Macroeconomic factors, unemployment, and completion of education. Desarrollo Sustentable, Negocios, Emprendimiento Y Educación, 8(78), 33–51. https://doi.org/10.51896/rilcods.v8i78.1212
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

The effect of macroeconomic factors on higher education completion in Mexico during the period 2000-2023 is analyzed to understand the influence of per capita income, inequality, and GDP, as well as the impact of teacher compensation. Regarding higher education completion, the importance of working towards educational equity stands out. Significant investments have been made; however, school dropout rates remain prevalent, especially in marginalized communities. There is a gap in research on economic and social factors that analyze teacher compensation. A quantitative approach is used with multiple linear regression models and data from reliable sources such as the World Bank and CONEVAL, considering theories of social stratification, work incentives, and human development, to analyze the interaction between macroeconomic and educational variables. The importance of implementing redistributive policies and transfer programs to promote higher education is emphasized. The relationship between unemployment, per capita income, GDP, and the Gini coefficient with educational completion is explored through a correlational and multivariate research design, using census data, to analyze the relationship between the variables. Keywords: Higher Education, Completion of Education, Macroeconomic Factors, Public Policies, Teacher Compensation.

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References

  1. Aghion, P., Akcigit, U., Bergeaud, A., Blundell, R., & Hemous, D. (2021). Innovation and Top Income Inequality. Review of Economic Studies, 88(1), 1-35. https://doi.org/10.1093/restud/rdaa043
  2. Banco Mundial. (2023). World Development Report 2023: Education for Social Mobility. World Bank Publications.
  3. Banerjee, A., & Duflo, E. (2019). Good Economics for Hard Times. PublicAffairs.
  4. Barro, R. J. (1991). Economic Growth in a Cross Section of Countries. Quarterly Journal of Economics, 106(2), 407-443. https://doi.org/10.2307/2937943
  5. Bell, D. N. F., & Blanchflower, D. G. (2020). Youth Unemployment in Advanced Economies in Europe and the United States. IZA World of Labor. https://doi.org/10.15185/izawol.486
  6. Bloom, D., Canning, D., & Chan, K. (2006). Higher Education and Economic Development in Africa. World Bank. https://doi.org/10.1596/978-1-4648-0426-3
  7. Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–1294.
  8. Bryman, A. (2015). Social Research Methods (5th ed.). Oxford University Press. de Vaus, . (2013). Surveys in Social Research (6th ed.). Routledge.
  9. Card, D., & Krueger, A. B. (1995). Myth and Measurement: The New Economics of the Minimum Wage. Princeton University Press.
  10. CEPAL. (2021). Panorama Social de América Latina 2021. Comisión Económica para América Latina y el Caribe. https://www.cepal.org/es/publicaciones/47616-panorama-social-america-latina-2021
  11. Deaton, A. (2015). The Great Escape: Health, Wealth, and the Origins of Inequality. Princeton University Press.
  12. De Gregorio, J., & Lee, J. W. (2002). Education and Income Distribution: New Evidence from Cross-Country Data. Review of Income and Wealth, 48(3), 395-416. https://doi.org/10.1111/1475-4991.00060
  13. Durbin, J., & Watson, G. S. (1951). Testing for serial correlation in least squares regression. Biometrika, 38(1/2), 159–178.
  14. Easterly, W. (2001). The Elusive Quest for Growth. MIT Press.
  15. Fiszbein, A., & Schady, N. (2009). Conditional Cash Transfers: Reducing Present and Future Poverty. World Bank Policy Research Report. https://doi.org/10.1596/978-0-8213-7352-1
  16. Fondo de las Naciones Unidas para la Infancia (UNICEF). (2023). The State of the World’s Children 2023: For Every Child, Education. UNICEF Publications.
  17. Girón, A. (2015). Austeridad, Inequidad y Desigualdad. Problemas del Desarrollo. Revista Latinoamericana de Economía. 46 (181), 1-8 https://doi.org/10.1016/j.rpd.2015.03.011
  18. Hanushek, E. A., Schwerdt, G., Wiederhold, S., & Woessmann, L. (2020). Returns to Skills around the World: Evidence from PIAAC. European Economic Review, 103, 212-234. https://doi.org/10.1016/j.euroecorev.2020.103675
  19. Hayashi, F. (2000). Econometrics. Princeton University Press.
  20. Heckman, J. J., Lochner, L., & Todd, P. E. (2006). Earnings Functions, Rates of Return, and Treatment Effects: The Mincer Equation and Beyond. Handbook of the Economics of Education, 1, 307-458. https://doi.org/10.1016/S1574-0692(06)01007-5
  21. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. Springer.
  22. Kraft, M. A., Blazar, D., & Hogan, D. (2021). The Effect of Teacher Coaching on Instruction and Achievement: A Meta-Analysis of the Causal Evidence. Review of Educational Research, 91(4), 612-651. https://doi.org/10.3102/0034654320974205
  23. Krugman, P. (1994). The Age of Diminished Expectations. MIT Press.
  24. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2004). Applied Linear Statistical Models. McGraw-Hill.
  25. Lazear, E. P. (2000). Performance Pay and Productivity. American Economic Review, 90(5), 1346-1361. https://doi.org/10.1257/aer.90.5.1346
  26. Lavrakas, P. J. (2018). Encyclopedia of Survey Research Methods. SAGE Publications.
  27. Loayza, N. V., Schmidt-Hebbel, K., & Servén, L. (2017). Economic Growth in Latin America: Sources and Trends. Journal of Economic Perspectives, 31(2), 29-49. https://doi.org/10.1257/jep.31.2.29
  28. Menard, S. (2008). Handbook of Longitudinal Research: Design, Measurement, and Analysis. Academic Press.
  29. Organización para la Cooperación y el Desarrollo Económicos (OECD). (2021). Education at a Glance 2021: OECD Indicators. OECD Publishing.
  30. Organización para la Cooperación y el Desarrollo Económicos (OECD). (2022). How’s Life? Measuring Well-being. OECD Publishing.
  31. Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura (UNESCO). (2022). Global Education Monitoring Report 2022: Inclusion and Education. UNESCO Publishing.
  32. Piketty, T. (2014). Capital in the Twenty-First Century. Harvard University Press.
  33. Psacharopoulos, G., & Patrinos, H. A. (2018). Returns to Investment in Education: A Decennial Review of the Global Literature. World Bank Policy Research Working Paper. https://doi.org/10.1596/1813-9450-8402
  34. Punch, K. F. (2014). Introduction to Social Research: Quantitative and Qualitative Approaches (3rd ed.). SAGE Publications.
  35. Schultz, T. W. (2019). Transforming Traditional Education through Economic Perspectives. Cambridge University Press.
  36. Sen, A. (1999). Development as Freedom. Oxford University Press.
  37. OECD. (2023). Education at a Glance 2023: OECD Indicators. OECD Publishing. https://doi.org/10.1787/eag-2023-en
  38. Organización para la Cooperación y el Desarrollo Económicos (OECD). (2023). Educational Outcomes in Mexico: Progress and Challenges.
  39. Secretaría de Educación Pública (SEP). (2024). Beca Universal "Rita Cetina Gutiérrez".
  40. Rawls, J. (1971). A Theory of Justice. Harvard Universito Press.
  41. Ramsey, J. B. (1969). Tests for specification errors in classical linear least-squares regression analysis. Journal of the Royal Statistical Society: Series B, 31(2), 350–371.
  42. Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611.
  43. Stock, J. H., & Watson, M. W. (2020). Introduction to Econometrics (4th ed.). Pearson.
  44. Sen, A. (1999). Development as Freedom. Oxford University Press.
  45. Tilak, J. B. G. (2020). Higher Education, Public Good and Markets: The State, Privatization and Markets in Education. Springer.
  46. UNESCO. (2015). Education for All 2000-2015: Achievements and Challenges.
  47. UNESCO Publishing. https://doi.org/10.15220/978-92-3-100085-0UNESCO. (2022). Global Education Monitoring Report 2022: Inclusion and Education.
  48. UNESCO. (2023). Global Education Monitoring Report 2023: Inclusion and Education. UNESCO Publishing.
  49. White, H. (1980). A heteroscedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity. Econometrica, 48(4), 817–83
  50. World Bank. (2021). The State of the Global Education Crisis: A Path to Recovery. World Bank Group. https://doi.org/10.1596/978-1-4648-1736-2
  51. World Bank. (2022 a). Learning Losses during COVID-19: Global Estimates. World Bank
  52. World Bank. (2022 b). World Development Report 2022: Education for Growth. World Bank Group. https://doi.org/10.1596/978-1-4648-1736-2
  53. World Bank Group. (2024 a). Education Statistics Database. Retrieved from https://datacatalog.worldbank.org/
  54. World Bank Group. (2024 b). World Development Indicators.

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