ESTIMATING THE INNOVATION FUNCTION FROM PATENT NUMBERS: GMM ON COUNT PANEL DATA (replication data)

DOI

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 present a first extension to lagged dependent variables.

Identifier
DOI https://doi.org/10.15456/jae.2022313.1256494695
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:776403
Provenance
Creator Crépon, Bruno; Duguet, Emmanuel
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 1997
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics; Social and Behavioural Sciences