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Cognitive skills and economic performance: evidence from the recent international student assessment tests

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Abstract

This paper examines the empirical relationship between the quality of educational attainment and economic growth. It uses country scores from the recent international student assessment tests as a proxy for education quality and cognitive skills of the labor force along with data on education quantity (schooling) and several control variables. The student assessment data set includes two widely used international tests, PISA and TIMSS, spanning the periods 2000–2015, and 1995–2015, respectively. Empirical results from OLS and IV estimations indicate that cognitive skills component of human capital has a robust positive effect on growth performance whereas the impact of average years of schooling, after conditioning on test scores, is statistically insignificant. Results suggest that to improve the quality of human capital stock and spur economic growth, countries should focus more on developing national education policies designed to enhance students’ cognitive skills rather than merely increasing the number of schools.

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Notes

  1. A separate branch of literature focuses on the relationship between individual skills and innovation. It has been shown that soft-skills and hard-skills in the labor force are positively associated with individual-level innovativeness (see, for example, Hendarman and Cantner 2017). Hard-skills are mostly related to technical knowledge and cognitive skills which can be improved by education and training.

  2. See Altinok et al. (2014) and Altinok and Aydemir (2016) for a detailed explanation related to the process of country mean score adjustment with respect to US performance at NAEP assessment.

  3. The KOF globalization index has been used by numerous studies to examine the impact of globalization on economic growth, human development, and inequality. Examples include Dreher and Gaston (2008), Cieslik (2014) and Yay et al. (2016). Also see Potrafke (2015) for a comprehensive literature review on globalization.

  4. We did not estimate the model using all PISA subjects together in our regressions due to the high degree of multicollinearity. As can be seen from the correlation matrix in Appendix, PISA math, science, and reading scores are highly correlated with each other with correlation coefficients 0.97 or higher. Similarly, the correlation coefficient between TIMSS science and reading subjects is 0.95.

  5. We also estimated the models using robust regression methods. The results are not reported as they were qualitatively similar.

  6. They use several factors that aim to measure institutional quality of school systems as well as non-school factors such as families, peers, and ability. These variables include catholic share in the population, the centralization of decision-making, relative teacher pay, and the share of privately operated schools (for details see Hanushek and Woessmann 2012) We do not consider all potential IVs because of data inavailability. We also note that IV-2SLS and LIML methods are large-sample estimators that may not behave as expected in small samples.

  7. We use their data on this variable (exit) in the following IV estimations.

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Authors and Affiliations

  1. Department of Economics, Yildiz Technical University, Davutpasa Campus, Istanbul, Turkey

    Hüseyin Taştan & Selin Erdoğan

Authors
  1. Hüseyin Taştan
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  2. Selin Erdoğan
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Correspondence to Hüseyin Taştan.

Appendix

Appendix

See Tables 8, 9, 10 and 11.

Table 8 Sources of data used in the analysis
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Table 9 List of countries
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Table 10 Cross-correlation table: PISA sample 2000–2015
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Table 11 Cross-correlation table: TIMSS sample 1995–2015
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Taştan, H., Erdoğan, S. Cognitive skills and economic performance: evidence from the recent international student assessment tests. Eurasian Econ Rev 8, 417–449 (2018). https://doi.org/10.1007/s40822-018-0099-z

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