Estimating the Innovation Function from Patent Numbers: GMM on Count Panel Data

Bruno Crépon and Emmanuel Duguet

Journal of Applied Econometrics, 1997, vol. 12, issue 3, 243-63

Abstract: The purpose of this paper is to estimate the patent equation, an empirical counterpart to the 'knowledge-production function'. Innovation output is measured through the number of European patent applications and the input by research capital, in a panel of French manufacturing firms. Estimating the innovation function raises specific issues related to count data. Using the framework of models with multiplicative errors, we explore and test for various specifications: correlated fixed effects, serial correlations, and weak exogeneity. We also prevent a first extension to lagged dependent variables.

Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (99)

Downloads: (external link)
http://qed.econ.queensu.ca:80/jae/1997-v12.3/ Supporting data files and programs (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jae:japmet:v:12:y:1997:i:3:p:243-63

Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252

Access Statistics for this article

Journal of Applied Econometrics is currently edited by M. Hashem Pesaran

More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().