For the level model, once usually wants to difference the instruments. A key system GMM assumption is that those first-differenced instruments are valid instruments for the level model (i.e. uncorrelated with the unobserved group-specific effects, which are still present in the level error term). For the differenced model, you may or may not difference the instruments as well; both is possible. Often, no differencing of the instruments is applied for the differenced model.
The one-step and two-step (system) GMM estimators differ in the way that the two-step estimator uses an optimal estimate of the weighting matrix, while the one-step estimator uses a pre-specified weighting matrix which is typically not optimal (in an asymptotic variance minimizing sense). Estimating this weighting matrix can be very inaccurate when the sample size is small and/or the number of instruments is large.
In dynamic panel models, the main idea is to use lagged variables as instruments (rather than other variables excluded from the model), assuming that those lags do not have a direct effect on Y but through their serial correlation over time affect the unlagged X regressors. The particular way of transforming the model and/or instruments then ensures that those instruments are uncorrelated with the error term, especially the group-specific component in the error term.
GMM-type instruments are typically used for endogenous variables, but technically IV-type instruments are just collapsed versions of GMM-type instruments. What really matters is to use the right lags and transformations to ensure the endogeneity of those instruments, irrespective of whether they are in GMM-type or IV-type format.
-
Login or Register
- Log in with
Leave a comment: