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The role of age‐structured education data for economic growth forecasts
Author(s) -
Cuaresma Jesús Crespo,
Mishra Tapas
Publication year - 2011
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.1171
Subject(s) - econometrics , dimension (graph theory) , model selection , sample (material) , bayesian probability , economics , regression , economic forecasting , computer science , statistics , mathematics , artificial intelligence , chemistry , chromatography , pure mathematics
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 selection 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. Copyright © 2009 John Wiley & Sons, Ltd.