Estimating the Parameter of Dynamic Panel Data Model Using Arellano-Bond Method
Abstract
The dynamic panel data model is based on the concept of dynamics, when a variable is not only determined by other variables at the same time, but is also determined by the variables in the previous time. The dynamic model contains lagged dependent variable, which is correlated with the error term, as an explanatory variable. It causes the Ordinary Least Square (OLS) estimator is biased and inconsistent. Therefore, other estimation methods are needed, one of them is the Arellano-Bond method. This method is based on the Generalized Method of Moments (GMM), and provides an unbiased, consistent, and efficient estimator. Having obtained the estimator, then we estimate the individual effects using OLS method.
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