Suppose you detect heteroskedasicity and or auto correlated, Ask an Expert

Economics

Suppose you detect heteroskedasicity and /or auto correlated errors in your regression. What is the difference between (I) calculating robust errors versus (ii) conducting a weighted least squares or feasible generalized least squares analysis. What are the pros and cons of each approach? Give an example of when each might be preferred over the other.

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Business Economics, Economics

Category:- Business Economics
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