Education-growth nexus in middle-income countries: an empirical examination for schooling rates

Abstract

The goal of this paper is to examine the education-growth nexus for 5 middle-income countries (Malaysia, Mexico, South Africa, Thailand, and Turkey) using schooling rate as the indicator of education over the period 1987-2015. The paper first performs cross-sectional dependence and heterogeneity tests and then employs the bootstrap panel Granger causality test developed by Konya (2006). According to the findings, while there is unidirectional causality from schooling rate to GDP in Thailand, there is unidirectional causality from GDP to schooling rate in South Africa. The findings of the paper indicate that schooling rate is not a good proxy for human capital. Theoretical and policy implications are discussed in the conclusion part.

Keywords

• middle-income trap,human capital,education,schooling rate,PISA test,panel data

References

1. Acemoglu, D. (2009). Introduction to modern economic growth. New Jersey: Princeton University Press.
2. Afzal, M., Rehman, H. U., Farooq, S., & Sarwar, K. (2011). Education and economic growth in Pakistan: a cointegration and causality analysis. International Journal of Educational Research, 50, 321-335.
3. Agenor, P. R., Canuto, O., & Jelenic, M. (2012). Avoiding middle-income growth traps. The World Bank Economic Premise, 98.
4. Barro, R. J. (1991). Economic growth in a cross section of countries. The Quarterly Jour-nal of Economics, 106(2), 407-443.
5. Barro, R. J., & Lee, J. W. (1993). International comparisons of educational attain-ment. Journal of Monetary Economics, 32(3), 363-394.
6. Barro, R. J. (2001). Human capital and growth. The American Economic Review, 91(2), 12-17.
7. Breton, T. R. (2011). The quality vs. the quantity of schooling: what drives economic growth?. Economics of Education Review, 30(4), 765-773.
8. Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.

9. Bulut, U., & Bulut, A. S. (2015). The role of schooling in struggling with the middle-income trap: dynamic panel data analysis. Journal of Social and Administrative Sciences, 2(4), 205-215.
10. Chen, S., & Luoh, M. (2010). Are mathematics and science test scores good indicators for labor-force quality?. Social Indicators Research, 96(1), 133-143.
11. Cohen, D., & Soto, M. (2007). Growth and human capital: good data, good re-sults. Journal of Economic Growth, 12(1), 51-76.
12. Delgado, M. S., Henderson, D. J., & Parmeter, C. F. (2014). Does education matter for economic growth?. Oxford Bulletin of Economics and Statistics, 76(3), 334-359.
13. Doppelhofer, G., Miller, R. I., & Sala-i-Martin, X. (2000). Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. NBER Working Paper, 7750.
14. Durlauf, S. N., Kourtellos, A., & Tan, C. M. (2008). Are any growth theories robust?. The Economic Journal, 118(527), 329-346.
15. Easterly, W., & Levine, R. (1997). Africa's growth tragedy: policies and ethnic divi-sions. The Quarterly Journal of Economics, 112(4), 1203-1250.
16. Eichengreen, B., Park, D., & Shin, K. (2013). Growth slowdowns redux: new evidence on the middle-income trap. NBER Working Paper, 18673.
17. Felipe, J., Abdon, A., & Kumar, U. (2012). Tracking the middle-income trap: what is it, who is in it, and why?. Levy Economics Institute of Bard College Working Paper, 715.
18. Gill, I. S., Kharas, H. J. (2007). An east asian renaissance: ideas for economic growth. World Bank Publications. http://documents.worldbank.org/curated/en/517971468025502862/An-East-Asian-renaissance-ideas-for-economic-growth. Accessed 01.07.2018.
19. Glewwe, P., Maiga, E., & Zheng, H. (2014). The contribution of education to economic growth: a review of the evidence, with special attention and an application to Sub-Saharan Africa. World Development, 59, 379-393.
20. Hanushek, E. A., & Kimko, D. D. (2000). Schooling, labor-force quality, and the growth of nations. American Economic Review, 90(5), 1184-1208.
21. Hanushek, E. A., & Woessmann, L. (2008). The role of cognitive skills in economic de-velopment. Journal of Economic Literature, 46(3), 607-668.
22. Hanushek, E. A., & Woessmann, L. (2009). Schooling, cognitive skills, and the Latin American growth puzzle, National Bureau of Economic Research, 15066.
23. Hanushek, E. A. & Woessman, L. (2010). Education and economic growth. In P. Peterson, E. Baker, B. McGaw (Eds.), International Encyclopedia of Education (Vol. 2) (pp. 245-252). Oxford: Elsevier.
24. Hanushek, E. A., & Woessmann, L. (2012). Do better schools lead to more growth? Cog-nitive skills, economic outcomes, and causation. Journal of Economic Growth, 17(4), 267-321.
25. Henderson, D. J. (2010). A test for multimodality of regression derivatives with applica-tion to nonparametric growth regressions. Journal of Applied Econometrics, 25(3), 458-480.
26. Islam, N. (1995). Growth empirics: a panel data approach. The Quarterly Journal of Eco-nomics, 110(4), 1127-1170.
27. Karahasan, B. C., & Lopez-Bazo, E. (2013). The spatial distribution of human capital: can it really be explained by regional differences in market access? International Re-gional Science Review, 36(4), 451-480.
28. Kharas, H., & Kohli, H. (2011). What is the middle income trap, why do countries fall into it, and how can it be avoided?. Global Journal of Emerging Market Economies, 3(3), 281-289.
29. Konya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978-992.
30. Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3-42.
31. Mankiw, N. G., Romer, D., & Weil, D. N. (1990). A contribution to the empirics of eco-nomic growth. The Quarterly Journal of Economics, 107(2), 407-437.
32. Mathur, V. K. (1999). Human capital-based strategy for regional economic develop-ment. Economic Development Quarterly, 13(3), 203-216.
33. Nonneman, W., & Vanhoudt, P. (1996). A further augmentation of the Solow model and the empirics of economic growth for OECD countries. The Quarterly Journal of Economics, 111(3), 943-953.
34. OECD, https://www.oecd.org/pisa/. Accessed 1 July 2018.
35. Perotti, R. (1993). Political equilibrium, income distribution, and growth. The Review of Economic Studies, 60(4), 755-776.
36. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence. CESifo Working Paper, 1229.
37. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127.
38. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large pan-els. Journal of Econometrics, 142(1), 50-93
39. Psacharopoulos, G., & Arriagada, A. M. (1986). Educational composition of the labour force: an international comparison. The World Bank Discussion Paper, 38.
40. Pritchett, L. (2001). Where has all the education gone?. The World Bank Economic Re-view, 15(3), 367-391.
41. Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Econo-my, 94(5), 1002-1037.
42. Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Econo-my, 98(5), 71-112.
43. Ranis, G., Stewart, F., & Ramirez, A. (2000). Economic growth and human develop-ment. World Development, 28(2), 197-219.
44. Soubbotina, T. P., & Sheram, K. (2000). Beyond economic growth: meeting the challenges of global development. Washington, DC: World Bank Publications.
45. Swamy, P. A. (1970). Efficient inference in a random coefficient regression mod-el. Econometrica, 38(2), 311-323.
46. Tho, T. V. (2013). The middle-income trap: issues for members of the association of Southeast Asian nations. Asian Development Bank Institute Working Paper, 421.
47. Van Zyl, G., & Bonga-Bonga, L. (2009). Fiscal stimulation of human capital and resultant economic growth in South Africa. SA Journal of Human Resource Management, 6(3), 1-6.
48. World Bank Database. http://data.worldbank.org/. Accessed 1 July 2018.
49. Yu, C. H., DiGangi, S., & Jannasch-Pennell, A. (2012). A time-lag analysis of the relation-ships among PISA scores, scientific research publication, and economic perfor-mance. Social Indicators Research, 107(2), 317-330.
50. Zeng, J., & Fang, Y. (2014). Between poverty and prosperity: China’s dependent devel-opment and the ‘middle-income trap’. Third World Quarterly, 35(6), 1014-1031.