Schooling is Not Learning - the Impact of the Learning-Adjusted Years of Schooling on Growth in a Dynamic Panel Data Framework
48 Pages Posted: 7 Jul 2020
Date Written: December 1, 2019
Abstract
Schooling is not the same as learning. Nonetheless, many cross-country studies still use the mean school years, that is, a purely quantitative measure, to control for human capital. Thus, they ignore that the learning outcomes of two countries can differ dramatically even if they have the same average years of schooling. The concept of the learning-adjusted years of schooling (LAYS), introduced by the World Bank in 2018, tries to mitigate this problem by combining quantitative and qualitative components of education. However, so far, the impact of the LAYS has only been analyzed in a cross-sectional framework, ignoring several potential problems such as endogeneity, omitted variable bias, unobserved country heterogeneity, and measurement error. Our paper is the first to provide a country-level LAYS database covering up to 5 periods. Analyzing the impact of the LAYS on growth within a dynamic panel data framework (using system GMM estimation methods) enables us to take advantage of the time series variation in the data and to control for the problems listed above. We find that the LAYS have a highly significant positive impact on economic growth, even when controlling for institutional quality, investment ratios, trade openness, and government expenditures. Moreover, we compare the LAYS measure to the traditional measures of education. Our findings suggest that the LAYS appear to be a better predictor of economic outcome than the standard educational measures. Finally, we also investigate the interrelationship between institutional quality and human capital. Our evidence suggests that human capital and ‘good’ institutions serve as substitutes in the growth process, meaning that the positive effect of the LAYS on growth is smaller in countries where institutions are already strong than in countries with poorly functioning institutions. Our results are robust for many different specifications and have important policy implications, since investments in human capital and institutional quality are both costly measures, especially for developing countries.
Keywords: human capital, education, learning, economic growth and development, schooling, test scores, dynamic panel data model, system GMM, institutions
JEL Classification: O11, O15, I21, I25, E24
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