GMM Estimation of Count-Panel-Data Models With Fixed Effects and Predetermined Instruments
提出一种针对固定效应计数面板数据模型的广义矩估计方法，即使解释变量为预定变量也能得到一致估计，并应用于专利与研发支出、技术转移等研究。
The "traditional" approach to the estimation of count-panel-data models with fixed effects is the conditional maximum likelihood estimator. The pseudo maximum likelihood principle can be used in these models to obtain orthogonality conditions that generate a robust estimator. This estimator is inconsistent, however, when the instruments are not strictly exogenous. This article proposes a generalized method of moments estimator for count-panel-data models with fixed effects, based on a transformation of the conditional mean specification, that is consistent even when the explanatory variables are predetermined. Two applications are discussed, the relationship between patents and research and development expenditures and the explanation of technology transfer.