✦ LIBER ✦

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

✍ Scribed by John B. Guerard Jr.; Robert T. Clemen

Publisher: John Wiley and Sons
Year: 1989
Tongue: English
Weight: 472 KB
Volume: 8
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980080308

No coin nor oath required. For personal study only.

✦ Synopsis

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. O w 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.

📜 SIMILAR VOLUMES

Combining classification and regression

Combining classification and regression approaches for the quantification of highly overlapping capillary electrophoresis peaks by using evolutionary sigmoidal and product unit neural networks

✍ Cesar Hervás; Pedro Antonio Gutierrez; Manuel Silva; Juan Manuel Serrano 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 247 KB 👁 1 views