Nonlinear Arellano-Bond GMM for Dynamic Panel Data

Nonlinear Arellano-Bond GMM extends the classic Arellano-Bond difference-GMM framework to panel models where the conditional mean function is nonlinear in parameters or variables. It uses lagged levels of the dependent variable as instruments after first-differencing to remove individual fixed effects, yielding consistent estimates in short dynamic panels with nonlinear specifications such as count, duration, or multiplicative models.