i have applied two step system gmm in my paper. A reviewer commented ''It is not clear whether time effects have been included'' on given results. Can you help me how to handle his comment please.
Furqan Ullah
Define your variables: First, define the variables you want to include in your model. You will typically have a dependent variable and one or more independent variables. Specify your model: Next, specify your model with the appropriate time effects included. This will depend on the nature of your research question and the variables you are using. One common approach is to include lagged dependent variables as additional independent variables. Estimate your first-step GMM model: Once you have specified your model, estimate your first-step GMM model. This involves estimating a set of moment conditions that capture the orthogonality conditions between the instruments and the errors in your model. The resulting estimates are used to obtain the efficient GMM estimates of the coefficients in the second step. Test for overidentifying restrictions: After estimating your first-step model, you should test for overidentifying restrictions. This involves comparing the number of moment conditions used in the estimation to the number of degrees of freedom in your model. If the number of moment conditions is greater than the number of degrees of freedom, then you have overidentifying restrictions. Estimate your second-step GMM model: If the test for overidentifying restrictions is passed, estimate your second-step GMM model using the efficient GMM estimates obtained from the first step. This involves using a set of moment conditions that are orthogonal to the instruments and the errors in your model.
o include time effects in a two-step system GMM, you can follow these general steps:
By including time effects in your two-step system GMM, you can account for time-varying relationships between your variables and obtain more reliable estimates of the coefficients in your model. However, it is important to carefully specify your model and test for overidentifying restrictions to ensure that your estimates are valid.
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