The role of age-structured education data for economic growth forecasts
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 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
249-267
Cuaresma, Jesus
da080c94-5ead-4deb-a03d-e787c2840e4d
Mishra, Tapas
218ef618-6b3e-471b-a686-15460da145e0
2011
Cuaresma, Jesus
da080c94-5ead-4deb-a03d-e787c2840e4d
Mishra, Tapas
218ef618-6b3e-471b-a686-15460da145e0
Cuaresma, Jesus and Mishra, Tapas
(2011)
The role of age-structured education data for economic growth forecasts.
Journal of Forecasting, 30 (2), .
(doi:10.1002/for.1171).
Abstract
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
Text
Mishra-JFore.pdf
- Version of Record
Restricted to Repository staff only
Request a copy
More information
Published date: 2011
Organisations:
Southampton Business School
Identifiers
Local EPrints ID: 380205
URI: http://eprints.soton.ac.uk/id/eprint/380205
ISSN: 0277-6693
PURE UUID: 100dd2d8-6289-4b9d-831b-a7ce117ea178
Catalogue record
Date deposited: 04 Sep 2015 13:16
Last modified: 15 Mar 2024 03:51
Export record
Altmetrics
Contributors
Author:
Jesus Cuaresma
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
