Forecasting Innovations [electronic resource] : Methods for Predicting Numbers of Patent Filings / edited by Peter Hingley, Marc Nicolas.

Background -- A research programme for improving forecasts of patent filings -- From theory to time series -- An assessment of the comparative accuracy of time series forecasts of patent filings: the benefits of disaggregation in space or time -- Driving forces of patent applications at the European Patent Office: a sectoral approach -- Time series methods to forecast patent filings -- International patenting at the European Patent Office: aggregate, sectoral and family filings -- Micro data for macro effects -- Improving forecasting methods at the European Patent Office.

This is a practical guide to solutions for a case study of forecasting demand for services and products in international markets - and so much more than just another listing of dry theoretical methods. Leading experts present studies on improvements to methods for forecasting numbers of incoming patent filings at the European Patent Office. Studies are presented from econometric, survey and systems theory viewpoints. A recurring theme is the extent to which it is worthwhile to break down the components of the forecasting problem into classes based on geography, technical descriptions and sub-products. The contributions are reviewed by the practitioners of the existing methods, who seek to establish how to make use of the results and discover that it may not always be wise to put complete trust in established regression approaches. Along the road the reader will learn more about the patent system, debatably the best way for society to harness the forces of human invention. .