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Thanks; this clarifies the issue. Note that my simple example resulted from removing many complications in the model that I am actually interested in. In that model, I could not find good starting values at all (i.e., values that lead to convergence), even though a grid search indicated where the op...

Thanks for your answer. I still find it problematic that Eviews does not give the right estimate for such a simple problem. I hope you understand my worries after reading the following comments on your note. 1) The relevance of the starting value for c(1), as you correctly noticed, was something tha...

Thanks a lot for your serious answer. It is informative about the interpretation of grid results. Notwithstanding this, I still think there is a bug. Let us forget about the grid search. The code I enter is equation a.GMM yy = C(1) + @logit(C(2)) * yy(-1) @ yy(-1), so just simple linear panel regres...

Well, a grid search makes clear that the objective function is perfect (single minimum, smooth, ... ). I think an estimation procedure without bugs should be able to find the minimum in this model. For completeness, the model is equation a.GMM yy = C(1) + @logit(C(2)) * yy(-1) @ yy(-1). As you see: ...

The attached program tries to estimate a simple regression model with 1 regressor and a nonlinearity in the parameter, using a slightly unbalanced panel data set. Although the GMM objective function has just one minimum and is perfectly differentiable (as suggested by the grid search in the program)...