Collinearity and the use of latent root regression for combining GNP forecasts


Journal Article

In combining economic forecasts a problem often faced is that the individual forecasts display some degree of dependence. We discuss latent root regression for combining collinear GNP forecasts. Our results indicate that latent root regression produces more efficient combining weight estimates (regression parameter estimates) than ordinary least squares estimation (OLS), although out‐of‐sample forecasting performance is comparable to OLS. Copyright © 1989 John Wiley & Sons, Ltd.

Full Text

Duke Authors

Cited Authors

  • Guerard, JB; Clemen, RT

Published Date

  • January 1, 1989

Published In

Volume / Issue

  • 8 / 3

Start / End Page

  • 231 - 238

Electronic International Standard Serial Number (EISSN)

  • 1099-131X

International Standard Serial Number (ISSN)

  • 0277-6693

Digital Object Identifier (DOI)

  • 10.1002/for.3980080308

Citation Source

  • Scopus