Forecasting the Diffusion of Innovations: Implications for Time-Series Extrapolation

By Nigel Meade, Towhidul Islam. 2001

77 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/0412ae48b9188914d83074c1d8b53fa7ed9b1aba

Citations in the corpus

• Findings from Evidence-Based Forecasting: Methods for Reducing Forecast Error (2006, unknown): “Meade and Islam (2001), in their review of the accuracy of alternative methods, found that no one diffusion model dominated and that relatively simple diffusion models were about as accurate as more complex diffusion models.”
• Simple versus complex forecasting: The evidence (2015, unknown): “    24  ”
• Extrapolation for Time-Series and Cross-Sectional Data (2009, unknown): “However, as Meade and Islam (2001) showed, various sophisticated and well-thought-out formulations often do not improve accuracy. That said, some degree of realism should aid accuracy. For example, economic behavior is typically best represented by multiplicative (exponential) rather than additive (”
• Forecasting for Marketing (2005, unknown): “Morwitz, V. (2001), “Methods for forecasting from intentions data,” in J. S. Armstrong (Ed.)”