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Published in:
2006 | OriginalPaper | Chapter
Modeling Probabilities of Patent Oppositions in a Bayesian Semiparametric Regression Framework
Published in: Economic Analyses of the European Patent System
Publisher: DUV
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In this paper, we apply a semiparametric approach described in Fahrmeir & Lang (2001
b
) and Brezger & Lang (2005) to analyze the determinants and the effects of patent oppositions in Europe. This approach replaces linear effects
χ′β
of metrical covariates
χ
by smooth regression functions
f
(
χ
). Within a Bayesian framework we apply MCMC-methods for estimation purposes. In order to analyze the benefits from applying semi-parametric models we compare our specification to the results of a simple linear probit model employed by Graham et al. (2002) using their dataset on EPO patents from the biotechnology/pharmaceutical and semiconductor/computer software sector.