Skip to main content

Advertisement

SpringerLink
Log in

Educational outcomes and socioeconomic status: A decomposition analysis for middle-income countries

  • Open File
  • Published:
PROSPECTS Aims and scope Submit manuscript

Abstract

This article analyzes the factors that explain the gap in educational outcomes between the top and bottom quartile of students in different countries, according to their socioeconomic status. To do so, it uses PISA microdata for 10 middle-income and 2 high-income countries, and applies the Oaxaca-Blinder decomposition method. Its results show that students’ individual variables only explain differences in high-income countries; meanwhile, school and teacher quality, and better practices, matter even in different institutional settings. From a policy perspective, this evidence supports actions to improve school and teacher quality in order to reduce cross-country differences and differences between students at the top and bottom of socioeconomic distribution.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. The OLS estimation of educational production functions could be affected by several potential econometric caveats including multicollinearity or nonlinearities. Detailed results of the estimates and diagnostic tests are available from us upon request.

  2. Different breakpoints have been considered to define the groups. In particular, decompositions for differences between the fourth and the third quartiles, between the fourth and the second quartiles, between the fourth and the first quartiles, between the third and the second quartiles, between the third and the first quartiles, and between the second and the first quartiles have also been considered. Results, available from the authors on request, show two interesting facts: first, that greater differences in educational outcomes are associated with differences between the fourth and the first quartiles of income in all countries, and second, that the relative contribution of personal, school, and individual characteristics to explain educational outcomes are similar across the ESCS distribution.

References

  • Ammermueller, A. (2007). PISA: What makes the difference? Explaining the gap in test scores between Finland and Germany. Empirical Economics, 33(2), 263–287.

    Article  Google Scholar 

  • Ammermueller, A., Heijke, H., & Woessmann, L. (2005). Schooling quality in Eastern Europe: Educational production during transition. Economics of Education Review, 24, 579–599.

    Article  Google Scholar 

  • Arum, R. (2000). Schools and communities: Ecological and institutional dimensions. Annual Review of Sociology, 26, 395–418.

    Article  Google Scholar 

  • Baird, K. (2012). Class in the classroom: The relationship between school resources and math performance among low socioeconomic status students in 19 rich countries. Education Economics, 20(5), 484–509.

    Article  Google Scholar 

  • Barnett, R. R., Glass, J. C., Snowdon, R. I., & Stringer, K. S. (2002). Size, performance and effectiveness: Cost-constrained measures of best-practice performance and secondary-school size. Education Economics, 10(3), 291–311.

    Article  Google Scholar 

  • Bishop, J. H., & Woessmann, L. (2004). Institutional effects in a simple model of educational production. Education Economics, 12, 17–38.

    Article  Google Scholar 

  • Blinder, A. S. (1973). Wage discrimination: Reduced form and structural variables. Journal of Human Resources, 8, 436–455.

    Article  Google Scholar 

  • Boarini, R., & Lüdemann, E. (2009). The role of teacher compensation and selected accountability policies for learning outcomes: An empirical analysis for OECD countries. Revue économique de l'OCDE, 2009(1), 211–230.

    Google Scholar 

  • Burger, R. (2011). School effectiveness in Zambia: The origins of differences between rural and urban outcomes. Development Southern Africa, 28(2), 157–176.

    Article  Google Scholar 

  • Chiswick, B. R., & DebBurman, N. (2004). Educational attainment: Analysis by immigrant generation. Economics of Education Review, 23, 361–379.

    Article  Google Scholar 

  • Coleman, J. S., & Hoffer, T. (1987). Public and private high schools: The impact of communities. New York: Basic Books.

    Google Scholar 

  • Coleman, J. S., Campbell, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., & York, R. L. (1966). Equality of educational opportunity. Washington, DC: US Department of Health, Education, and Welfare.

    Google Scholar 

  • Dolton, P., & Marcenaro-Gutierrez, O. D. (2011). If you pay peanuts do you get monkeys? A cross-country analysis of teacher pay and pupil performance. Economic Policy, 26(65), 5–55.

    Article  Google Scholar 

  • Entorf, H., & Minoiu, N. (2005). What a difference immigration policy makes: A comparison of PISA scores in Europe and traditional countries of immigration. German Economic Review, 3, 355–376.

    Article  Google Scholar 

  • Fay, R. E. (1989). Theoretical application of weighting for variance calculation. In Proceedings of the Section on Survey Research (pp. 212–217). Alexandria: American Statistical Association.

  • Feinstein, L., & Symons, J. (1999). Attainment in secondary education. Oxford Economic Papers, 51, 300–321.

    Article  Google Scholar 

  • Ferreira, F., & Gignoux, J. (2011). The measurement of educational inequality: Achievement and opportunity. Discussion paper. Bonn: Institute for the Study of Labor.

    Book  Google Scholar 

  • Fertig, M. (2003). Who’s to blame? The determinants of German students’ achievement in the PISA 2000 study. Discussion paper. Bonn: Institute for the Study of Labor.

    Google Scholar 

  • Frenette, M. (2007). Are youth from lower-income families less likely to attend university? Evidence from academic abilities, parental influence, and financial constraints. Ottawa: Statistics Canada, Ministry of Industry.

    Google Scholar 

  • Fuchs, T., & Woessmann, L. (2007). What accounts for international differences in student performance? A re-examination using PISA data. Empirical Economics, 32(2–3), 433–462.

    Article  Google Scholar 

  • Hanushek, E. A. (1986). The economics of schooling. Journal of Economic Literature, 24, 1141–1177.

    Google Scholar 

  • Hanushek, E. A. (2003). The failure of input based schooling policies. Economic Journal, 113, 64–98.

    Article  Google Scholar 

  • Hanushek, E. A., & Luque, J. A. (2003). Efficiency and equity in schools around the world. Economics of Education Review, 22, 481–502.

    Article  Google Scholar 

  • Hanushek, E. A., Kain, J. F., Markman, J. M., & Rivkin, S. G. (2003). Does peer ability affect student achievement? Journal of Applied Econometrics, 18, 527–544.

    Article  Google Scholar 

  • Hanushek, E. A., & Woessmann, L. (2011a). How much do educational outcomes matter in OECD countries? Economic Policy, 26(67), 427–491.

    Article  Google Scholar 

  • Hanushek, E. A., & Woessmann, L. (2011b). The economics of international differences in educational achievement. In E. A. Hanushek, S. Machin, & L. Woessmann (Eds.), Handbook of the economics of education, vol. 3 (pp. 89–200). Amsterdam: North Holland.

  • Haveman, R., & Wolfe, B. (1995). The determinants of children’s attainment: A review of methods and findings. Journal of Economics Literature, 33(4), 1829–1878.

    Google Scholar 

  • Heyneman, S. P., & Loxley, W. A. (1983). The distribution of primary school quality within high- and low-income countries. Comparative Education Review, 27(1), 108–118.

    Article  Google Scholar 

  • Krueger, A. B. (2003). Economics considerations and class size. Economic Journal, 113, 34–63.

    Article  Google Scholar 

  • Lee, J.-S. (2012). The effects of the teacher-student relationship and academic press on student engagement and academic performance. International Journal of Educational Research, 53, 330–340.

    Article  Google Scholar 

  • Marks, G. N. (2008). Accounting for the gender gaps in student performance in reading and mathematics: Evidence from 31 countries. Oxford Review of Education, 34(1), 89–109.

    Article  Google Scholar 

  • Meunier, M. (2011). Immigration and student achievement: Evidence from Switzerland. Economics of Education Review, 30(1), 16–38.

    Article  Google Scholar 

  • Mislevy, R. J., & Sheehan, K. M. (1987). Marginal estimation procedures. In A. E. Beaton (Ed.), The NAEP 1983–84 technical report, National Assessment of Educational Progress (pp. 293–360). Princeton, NJ: Educational Testing Service.

    Google Scholar 

  • Mislevy, R. J., & Sheehan, K. M. (1989). Information matrices in latent-variable models. Journal of Educational Statistics, 14, 335–350.

    Article  Google Scholar 

  • Nieto, S., & Ramos, R. (2013). Decomposition of differences in PISA results in middle-income countries. Background paper for the 2013 Education for All Global Monitoring Report. Paris: UNESCO.

  • Noell, J. (1982). Public and Catholic schools: A re-analysis of public and private schools. Sociology of Education, 55, 123–132.

    Article  Google Scholar 

  • Ñopo, H. (2008). An extension of the Blinder–Oaxaca decomposition to a continuum of comparison groups. Economics Letters, 100, 292–296.

    Article  Google Scholar 

  • Oaxaca, R. (1973). Male–female wage differentials in urban labor markets. International Economic Review, 14(3), 139–148.

    Article  Google Scholar 

  • OECD [Organisation for Economic Cooperation and Development] (2009). Technical report 2006. Paris: OECD.

    Google Scholar 

  • OECD (2010). PISA 2009 results: Overcoming social background—Equity in learning opportunities and outcomes, vol. 2. doi:10.1787/9789264091504-en.

  • Opdenakker, M. C., & Van Damme, J. (2006). Differences between secondary schools: A study about school context, group composition, school practice, and school effects with special attention to public and Catholic schools and types of schools. School Effectiveness and School Improvement, 17(1), 87–117.

    Article  Google Scholar 

  • Ramos, R., Duque, J. C., & Nieto, S. (2012). Decomposing the rural-urban differential in student achievement in Colombia using PISA microdata. Discussion paper. Bonn: Institute for the Study of Labor.

  • Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools and academic achievement. Econometrica, 73(2), 417–458.

    Article  Google Scholar 

  • Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.

    Book  Google Scholar 

  • Sander, W. (1996). Catholic grade schools and academic achievement. Journal of Human Resources, 31(3), 540–548.

    Article  Google Scholar 

  • Somers, M. A., McEwan, P. J., & Willms, J. D. (2004). How effective are private schools in Latin America? Comparative Education Review, 48(1), 48–69.

    Article  Google Scholar 

  • Smith, J., & Naylor, R. A. (2005). Schooling effects on subsequent university performance: Evidence for the UK university population. Economics of Education Review, 24, 549–562.

    Article  Google Scholar 

  • Stevans, L. K., & Sessions, D. N. (2000). Private/public school choice and student performance revisited. Education Economics, 8(2), 169–184.

    Article  Google Scholar 

  • Ulrick, S. W. (2012). The Oaxaca decomposition generalized to a continuous group variable. Economics Letters, 115, 35–37.

    Article  Google Scholar 

  • Vandernberghe, V., & Robin, S. (2004). Evaluating the effectiveness of private education across countries: A comparison of methods. Labor Economics, 11(4), 487–506.

    Article  Google Scholar 

  • Woessmann, L. (2010). Families, schools, and primary-school learning: Evidence for Argentina and Colombia in an international perspective. Applied Economics, 42(21), 2645–2665.

    Article  Google Scholar 

  • Woessmann, L. (2011). Cross-country evidence on teacher performance pay. Economics of Education Review, 30(3), 404–418.

    Article  Google Scholar 

  • Zhang, L., & Lee, K. A. (2011). Decomposing achievement gaps among OECD countries. Asia Pacific Education Review, 12(3), 463–474.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universitat Oberta de Catalunya, Avda Tibidabo 39-45, 08035, Barcelona, Spain

    Sandra Nieto

  2. AQR-IREA, University of Barcelona, Avda Diagonal 690, 08034, Barcelona, Spain

    Raúl Ramos

Authors
  1. Sandra Nieto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raúl Ramos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sandra Nieto.

Additional information

This article builds on Nieto and Ramos (2013). We are grateful to the members of the EFA Global Monitoring Report team and the editors and referees of Prospects for their constructive and helpful comments and suggestions. We especially acknowledge Manos Antoninis, Kwame Akyeampong, and Pauline Rose.

Appendix

Appendix

See Table 2.

Table 2 Variable definition
Full size table

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nieto, S., Ramos, R. Educational outcomes and socioeconomic status: A decomposition analysis for middle-income countries. Prospects 45, 325–343 (2015). https://doi.org/10.1007/s11125-015-9357-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11125-015-9357-y

Keywords

Search

Navigation