Econometric analyses rely on point estimates, standard errors, and confidence intervals, assuming the consistency and asymptotic normality of GMM or M estimators. However, in real-world applications, these assumptions may not always hold due to the finite moments of the data. This article introduces a diagnostic testing method to assess these key assumptions, using both simulated and real datasets. The proposed method aims to provide insights into the validity of econometric analyses and their applicability in various scenarios.

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