## Abstract We examine different approaches to forecasting monthly US employment growth in the presence of many potentially relevant predictors. We first generate simulated outβofβsample forecasts of US employment growth at multiple horizons using individual autoregressive distributed lag (ARDL) mo
Innovation forecasting using bibliometrics
β Scribed by Robert J. Watts; Alan L. Porter; Nils C. Newman
- Publisher
- John Wiley and Sons
- Year
- 1998
- Weight
- 181 KB
- Volume
- 9
- Category
- Article
- ISSN
- 1058-0247
No coin nor oath required. For personal study only.
β¦ Synopsis
The emerging "Information Economy" has directed attention to the value of information in the business process. Business has responded by expanding such activities as competitive technical intelligence (CTI).
The combination of access to vast collections of information and CTI interests points attention to the need for new tools to process information into knowledge. We are experimenting with techniques to exploit in-11
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Database Tomography (DT) is a textual database analysis system consisting of two major components: 1) Algorithms for extracting multiword phrase frequencies and phrase proximities (physical closeness of the multiword technical phrases) from any type of large textual database, to augment 2) interpret
## Abstract The simplicity of the standard diffusion index model of Stock and Watson has certainly contributed to its success among practitioners, resulting in a growing body of literature on factorβaugmented forecasts. However, as pointed out by Bai and Ng, the ranked factors considered in the for
## ABSTRACT Using factors in forecasting exercises reduces the dimensionality of the covariates set and, therefore, allows the forecaster to explore possible nonlinearities in the model. For an American macroeconomic dataset, I present evidence that the employment of nonlinear estimation methods ca