ESTIMATING THE INNOVATION FUNCTION FROM PATENT NUMBERS: GMM ON COUNT PANEL DATA
用法国制造业企业的欧洲专利申请数作为创新产出、研发资本作为投入，估计知识生产函数，并处理计数数据中的内生性、固定效应和序列相关等问题。
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. © 1997 John Wiley & Sons, Ltd.