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in grade 9, while tenth grade students were unaffected. This provides a natural experiment for analyzing the impact on schooling achievements and educational choice. We find negative effects on grades in mathematics, but no effects in German literature. More- over, a significant share of females were found to delay university enrollment. JEL classification: I21, J18, C21. Keywords: Student performance; schooling quality; educational choice; learning intensity; natural experiment. 1. INTRODUCTION With the intention of enabling the earlier labor market participation

. Barro R., Lee J. W. (2001), Schooling Quality in a Cross-Section of Countries , “Economica”, V ol. 68, No. 272, pp. 465-488, DOI: 10.1111/1468-0335.d01-12. 5. Battese G. E., Coelli T. J. (1995), A Model for technical inefficiency effects in a stochastic frontier production for panel data , “Empirical Economics”, No. 24, pp. 325-332, DOI: 10.1007/BF01205442. 6. Bourdieu P., Passeron J. C. (2006), Reprodukcja. Elementy teorii systemu nauczania , Wydawnictwo Naukowe PWN. 7. Czyżewski B., Brelik A. (2016), Modelowanie społeczno-ekonomicznych determinant jakości

a production function framework.7 Thus a priori it seems that empirical analyses can at best reveal whether there is a positive education externality at all, but not by how much such an externality may differ from a benchmark value of one-third that considers the prevailing level of education subsidies. 3. EMPIRICAL RESULTS 3.1. Main variables and measures of schooling quality We begin our empirical analysis with a basic sample of 82 countries8 for which we have data on the variables specified in equation (9), mainly for the base year 1995. Our data on GDP per

.1016/0167-2231(94)90002-7. Barro, R.J. & Lee, J.W. (1996). International measures of schooling years and schooling quality. American Economic Review, 86(2), 218-223. Barro, Robert J. & Lee, J.W. (2013). A new data set of educational attainment in the world, 1950–2010, Journal of Development Economics.104,184–198. DOI: 10.1016/j.jdeveco.2012.10.001. Becker, G.S. (1964). Human Capital. Princeton, N.J. Princeton University Press. Becker, G.S. (2007). Health as human capital: synthesis and extensions. Oxford Economic Papers. 59, 379–410. DOI:10.1093/oep/gpm020. Chow, G. (1993). Capital formation

among public school teachers Journal of Human Resources 37 4 892 912 Available at: . Barro, R., Lee, J. W., 2001. Schooling Quality in a Cross-Section of Countries. Economica (68), pp. 465-488. Available at: . Barro R. Lee J. W. 2001 Schooling Quality in a Cross-Section of Countries Economica 68 465 488 Available at: . Benesova, I., Sanova, P., Laputkova, A., 2015. Public Expenditures on Education – Comparison of EU States. [Proceedings Paper

Communities. Vol. II, Part 4: 383-404. Barro R.J., 1998. Human capital and growth in cross-country regressions. Working paper, Harvard University. Barro R.J., Lee J.W., 1996. International measures of schooling years and schooling quality. American Economic Review Papers and Proceedings 86: 218-223. Barro R.J., Lee J.W., 2000. International data on educational attainment: Updates and implications. CID working paper 42, www.cidwp/042.htm (accessed 15 December 2011). Barro R.J., Lee J.W., 2010. A new data set of educational attainment in the world, 1950-2010. NBER working

the local labour force”, since individuals with higher levels of education and working experience can better contribute to the development and growth of a society. Therefore, highly educated people may improve AC of a region ( Feldman 2000 ). Schillaci et al. suggest that knowledge and skills of a territory can be measured by average years of schooling, quality of schooling, R&D employees in firms and employees training at the firm level. The authors raise the critical role played by human capital at the broader context of a region. In doing so, they propose

. While this hypothesis has been comparatively less investigated, some results from the above-mentioned studies have already pointed to an effect of schooling quality. For example, it was found that different school tracks (e. g. technology, social science, economics) were differentially related to intelligence (Cliffordson & Gustafsson, 2008). However, this study did not control for possible differences in baseline intelligence across the tracks studied. In another study, baseline intelligence was controlled for, and differential track effects appeared nevertheless

-Country Regressions.” Swedish Economic Policy Review 6(2):237–77. Barro, R.J., and J.W. Lee. 1996. “International Measures of Schooling Years and Schooling Quality.” American Economic Review 86(2):218–23. Barro, R.J. 1997. Determinants of Economic Growth: A Cross-Country Empirical Study . Cambridge: MIT Press. 10.3386/w5698 Barro, R.J., and X. Sala-i-Martin. 1995. Economic Growth . New York: McGraw-Hill. Benhabib, J., and M.M. Spiegel. 1994. “The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data.” Journal of Monetary Economics 34

sliding into poverty of those most unfortunate. General anti-poverty measures and support of those hit hardest by COVID-19 allow to prevent a spike in poverty and inequality, which is a goal in itself, and on top of that attenuate the risk of a surge in the risk of political violence. When it comes to preventing the depletion of human capital, it is important to put much emphasis and priority on making sure that universal school access is guaranteed. In current policy debates schooling quality and access is often seen as a less urgent and forefront matter during the