Forecasting the Europe 2020 headline target on education and training: A panel data approach Report as inadecuate




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Abstract

This analysis aims at proposing simple econometric models that can be used to forecast early leavers from education and training and tertiary education attainment benchmarks up to year 2020. The models are built on the theoretical framework of human capital and optimal schooling decisions and then estimated in a panel setting to better deal with a limited dataset. By looking back at the time period of enrolment and graduation, our approach could be seen as an attempt to identify the determinants that shape the education decisions of young individuals.We construct the forecasts under very simple assumptions about the expected adults’ education attainment and given the determinants of schooling decisions uncovered by our empirical analysis. The forecasts tell us how early school leaving and tertiary education attainment are likely to develop over the next years if nothing changes in terms of policy measures. This very strong assumption provides scope for policy action especially for those countries where the expected developments of model’s determinants are not enough to foresee a positive outcome.



Item Type: MPRA Paper -

Original Title: Forecasting the Europe 2020 headline target on education and training: A panel data approach-

Language: English-

Keywords: education; human capital investment; panel data; forecasting;-

Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - GeneralI - Health, Education, and Welfare > I2 - Education and Research Institutions > I20 - GeneralJ - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J24 - Human Capital ; Skills ; Occupational Choice ; Labor ProductivityJ - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J30 - General-





Author: Dragomirescu-Gaina, Catalin

Source: https://mpra.ub.uni-muenchen.de/68664/







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