The generalized method of moments (GMM) is an important estimation procedure in many areas of economics and finance, and it is well known that this estimation is highly sensitive to the presence of outliers and influential observations. Case-deletion diagnostic has been studied in GMM estimation; however, it is surprised that local influence analysis is under explored. To this end, a local influence method is proposed to assess the effect of minor perturbation on GMM estimation. The local diagnostic measures of GMM estimators under the perturbations of empirical distribution and moment condition are derived to study the joint influence of observations. The obtained results are applied to efficient instrumental variable estimation and dynamic panel data model. Two real data sets are used for illustration, and a simulation study is conducted to examine the effectiveness of the proposed methodology. The advantage of local influence method is analyzed in detail through comparison with the case-deletion method.

广义矩法（GMM）是许多经济学和金融领域的重要估计程序，众所周知，此估计对异常值和影响性观测值的存在非常敏感。案例删除诊断已在GMM估算中进行了研究；然而，令人惊讶的是，正在探索地方影响力分析。为此，提出了一种局部影响方法来评估轻微扰动对GMM估计的影响。推导了GMM估计量在经验分布和矩条件扰动下的局部诊断方法，以研究观测结果的共同影响。获得的结果被应用于有效的仪器变量估计和动态面板数据模型。两个真实的数据集用于说明，并进行了仿真研究，以检验所提出方法的有效性。通过与案例删除法进行比较，详细分析了本地影响法的优势。