Earnings functions, whereby the log of earnings is regressed on years of education, years of on the job training, and individual characteristics, have been studied for a variety of reasons. Some studies have focused on the returns to education, others on discrimination, union non-union differentials, etc. For all these studies, a major concern has been the fact that ability should enter as a determinant of earnings, but that it is close to impossible to measure and therefore represents an omitted variable.
Assume that the coefficient on years of education is the parameter of interest. Given that education is positively correlated to ability, since, for example, more able students attract scholarships and hence receive more years of education, the OLS estimator for the returns to education could be upward biased. To overcome this problem, various authors have used instrumental variable estimation techniques. For each of the instruments potential instruments listed below briefly discuss instrument validity.
(a)The individual's postal zip code.
(b)The individual's IQ or testscore on a work related exam.
(c)Years of education for the individual's mother or father.
(d)Number of siblings the individual has.

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The Answer of Earnings functions, whereby the log of earnings is regressed on years of education, years of on the job training, and individual characteristics, have been studied for a variety of reasons. Some studies have focused on the returns to education, others on discrimination, union non-union differentials, etc. For all these studies, a major concern has been the fact that ability should enter as a determinant of earnings, but that it is close to impossible to measure and therefore represents an omitted variable.
Assume that the coefficient on years of education is the parameter of interest. Given that education is positively correlated to ability, since, for example, more able students attract scholarships and hence receive more years of education, the OLS estimator for the returns to education could be upward biased. To overcome this problem, various authors have used instrumental variable estimation techniques. For each of the instruments potential instruments listed below briefly discuss instrument validity.
(a)The individual's postal zip code.
(b)The individual's IQ or testscore on a work related exam.
(c)Years of education for the individual's mother or father.
(d)Number of siblings the individual has.

Earnings Functions, Whereby the Log of Earnings Is Regressed on Years