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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

10. Explaining the Patenting Propensity: A Regional Analysis Using EPO-OECD Data

verfasst von : Claudio Cozza, Francesco Schettino

Erschienen in: Geographical Labor Market Imbalances

Verlag: Springer Berlin Heidelberg

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Abstract

The aim of this chapter is to conduct an empirical study of the patenting propensity at the European regional level using the OECD-REGPAT dataset. We use patent applications by inventor’s region as, in this case, linkage to the territory is stronger than using applicant’s region. Data analysis reveals the existence of a deep, uneven distribution of patent applications, R&D expenditure and human capital. Richer regions show higher levels of both private and public R&D expenditure as well as a consistent share of the total European patent applications. Starting from the analysis of these key variables, we proceed explaining the determinants of patenting propensity. The results substantially confirm the significant role of R&D expenditure on patenting activity: mainly the business enterprises, but also the government sector component. Human capital variables show similar positive effect, while average enterprise size seems not to play a determining role in patent applications.

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Vorheriges Kapitel Do FDI in Business Services Affect Firms’ TFP? Evidence from Italian Provinces
Nächstes Kapitel Family Origin and Early School Leaving in Italy: The Long-Term Effects of Internal Migration
Fußnoten
1
Among others, Caballero and Jaffe (1993), Henderson et al. (2005), Jaffe et al. (2005) and Schettino (2007).
 
2
See Harhoff et al. (1999), Lanjouw and Schankerman (2004) and Hall et al. (2007).
 
3
EU27 + EFTA countries, NUTS 2 level.
 
4
OECD-REGPAT database, June 2012—includes patent applications to the EPO (derived from PATSTAT, April 2012) and international PCT (Patent Cooperation Treaty) patents (derived from the OECD patent database, including patents published up to May 2012). Note that the regional breakdown refers to the latest revision to NUTS. The dataset covers regional information for most OECD countries and the EU27, plus the BRICs. We thank Helene Dernis for providing the data.
 
5
Fractioned following Narin and Breizman (1995).
 
6
The choice of inventor rather than applicant is discussed in Sect. 10.3.
 
7
Selection made at the NUTS 2 level.
 
8
We refer to the case of an inventor commuting daily from region of residence to workplace region. This would lose the connection to the territory of the invention (workplace region), overestimating the region of residence only.
 
9
The test performed on Gini2000 and Gini2010 excludes a statistically significant difference between the indexes.
 
10
The number of observations fluctuates across the years (282–300) because although the number of regions per country is generally constant over time, the regional structures of eastern European countries have changed in recent years.
 
11
Both BERD and GOVERD have been calculated in PPS, 2,000 prices.
 
12
We apply Moran’s test to the whole sample (2000–2010) and to 1 year (2008). In both cases, the test confirms that we can accept the null hypothesis that there is zero spatial autocorrelation present in the variable considered (Moran I (2000–2010) = 0.011; Moran I (2008) = 0.004).
 
13
GMM estimations were performed by using the xtabond2 for Stata 10 (see also Roodman 2006).
 
14
See Hall et al. (2003).
 
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Metadaten
Titel
Explaining the Patenting Propensity: A Regional Analysis Using EPO-OECD Data
verfasst von
Claudio Cozza
Francesco Schettino
Copyright-Jahr
2015
Verlag
Springer Berlin Heidelberg
Buch
Geographical Labor Market Imbalances

Print ISBN: 978-3-642-55202-1

Electronic ISBN: 978-3-642-55203-8

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-642-55203-8_10