Optimization of prediction methods for patents and trademarks in Spain through the use of exogenous variables Antonio Hidalgo a, * , Samuel Gabaly b a Dept. Business Administration, Universidad Politécnica de Madrid, c/José Gutiérrez Abascal, 2, 28006 Madrid, Spain b Gabaly Diseño S.L., Madrid, Spain Keywords: Patent time series Trademark time series Intelligent transfer function model Exogenous variables Polynomial distributed lag abstract An accurate forecast of patent and trademark application filings is strategic for resource planning at the Spanish Patents and Trademarks Office and other patent offices, national and supranational. The need for reliable forecasts of patents and trademarks application filings has been accentuated by the current situation of budgeting rationalization imposed by the economic crisis. In this study we have evaluated the suitability and effectiveness of different methodologies for advanced data analysis to predict the number of national patent and trademark applications in the short and medium terms (2011e2014), including the use of exogenous variables or predictors which help to understand the changes in these variables. The inclusion of exogenous variables which explain the behavior of patent and trademark application filings, in particular the investment in R&D and GDP, and the use of advanced predictive analysis techniques, amongst which the most notable are Polynomial Distributed Lags and Intelligent Transfer Function models, have all achieved an improvement upon the prediction and modeling power possessed by the models formerly used to predict trademark and patent series based only on the analysis of time series. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction The Spanish Patents and Trademarks Office (SPTO) requires accurate analyses and predictions regarding the changes in demand for its services, especially in terms of national patent and trademark applications, in order to ensure high-quality, properly dimensioned service for its clients. Given the current situation of budgeting rationalization imposed by the economic crisis, this factor is highly relevant because prior knowledge of changes in patent and trade- mark applications may contribute to an optimization of planning, an improvement in cost rationalization and greater efficiency in providing services to clients in the coming years. With this objective in mind, in 2010 the Spanish Office of Patents and Trademarks promoted a research project aimed at developing a methodology for predicting changes in the number of national patent and trademark application filings. The methodology used consists of three stages: the objective of the first stage (developed in 2010) was to predict the changes in the number of national patent and trademark applications for a time horizon of one to four years (short and medium term), using regression models of trends and advanced time series models; the second stage (developed in 2011) sought the same time objective, but using advanced econo- metric methods to identify indicators correlated with the changes in the national patent and trademark applications; last of all, the third stage (pending development) is oriented towards predicting the long-term changes (with a horizon of more than five years) using data at the company and sector levels, as well as identifying potential transfer functions through the use of multiple techniques, such as surveys among patent applicants, long-term econometric models and signals analysis. The results found in the first stage of research made it clear that it is feasible to model the series of national patent and trademark applications with different models of time series and that the advanced time series models, in particular ARIMA (Auto-Regressive Integrated Moving Average) [1], are better adjusted to the real values of the series than the regression models of trends with satisfactory results in terms of the fit of models and relatively low error levels [2]. In fact, a comparison of the prediction of patent and trademark applications performed using real data from the year of 2010 displays a high level of reliability, as demonstrated by the data in Table 1 . The goal of this study (second stage) is to evaluate the suitability and effectiveness of different methodologies for advanced data * Corresponding author. Tel.: þ34 913363210. E-mail addresses: ahidalgo@etsii.upm.es (A. Hidalgo), sgabaly@gmail.com (S. Gabaly). Contents lists available at SciVerse ScienceDirect World Patent Information journal homepage: www.elsevier.com/locate/worpatin 0172-2190/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.wpi.2012.12.009 World Patent Information 35 (2013) 130e140