[Cross-posted here as well: https://stats.stackexchange.com/questions/330619/non-classical-measurement-error]
I have a question similar to this thread. Although there was one answer, it did not capture the essence of the poster's question.
In essence, I am trying to estimate y = a + bx* + e. Unfortunately, I do not observe x*, but rather a proxy x = x* + v. I know that in such cases, the model suffers from endogeneity (classical error-in-variables.
In my case, however, v ≥ Ø and so E[v] ≠ Ø.
The question is can I still use traditional instrumental variable techniques, or why not? If not, what options do I have? How can I implement this in Stata?
Thanks,
Panos
I have a question similar to this thread. Although there was one answer, it did not capture the essence of the poster's question.
In essence, I am trying to estimate y = a + bx* + e. Unfortunately, I do not observe x*, but rather a proxy x = x* + v. I know that in such cases, the model suffers from endogeneity (classical error-in-variables.
In my case, however, v ≥ Ø and so E[v] ≠ Ø.
The question is can I still use traditional instrumental variable techniques, or why not? If not, what options do I have? How can I implement this in Stata?
Thanks,
Panos
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