Estimation of regression coefficients of interest when other regression coefficients are of no interest: The case of non-normal errors

This note considers the problem of estimating regression coefficients when some other coefficients in the model are of no interest. For the case of normal errors, Magnus and Durbin [1999. Estimation of regression coefficients of interest when other regression coefficients are of no interest. Econometrica 67, 639–643] and Danilov and Magnus [2004. On the harm that ignoring pretesting can cause. J. Econometrics 122, 27–46] studied this problem and established an equivalence theorem which states that the problem of estimating the coefficients of interest is equivalent to that of finding an optimal estimator of the vector of coefficients of no interest given a single observation from a normal distribution. The aim of this note is to generalize their findings to the large sample non-normal errors case. Some applications of our results are also given.