The role of age-structured education data for economic growth forecasts

This paper utilizes for the first time age-structured human capital data for economic growth forecasting. We concentrate on pooled cross-country data of 65 countries over six 5-year periods (1970-2000) and consider specifications chosen by model election criteria, Bayesian model averaging methodologies based on in-sample and out-of-sample goodness of fit and on adaptive regression by mixing. The results indicate that forecast averaging and exploiting the demographic dimension of education data improve economic growth forecasts systematically. In particular, the results are very promising for improving economic growth predictions in developing countries.

KEYWORDS: Economic growth; Education data; Forecasting; Adaptive regression; Bayesian model averaging

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