4. A model relating a person's wage to experience is: where is the natural logarithm of individual is hourly wage and is the number of years of experience. In this model 100* measures: a. The unit change in hourly wage given another year of experience holding all other factors fixed. b. the percentage change in hourly wage given another year of experience, holding all other factors fixed. c. the unit change in hourly wage given a 1% increase in experience. holding all other factors fixed. d. the percentage change in given another year of experience. holding all other factors fixed. Suppose that average worker productivity at manufacturing firms () depends on two factors, average hours of training () and average worker ability (): Assume that this equation satisfies the Gauss-Markov assumptions and that and are expected to have a positive impact on. If grants have been given to firms whose workers have less than average ability, so that and are negatively correlated, how does omitting the relevant variable from the model affect the estimated effect of the training program ()? a on average, across different random samples, the simple regression estimator associated to the training program (is unbiased b. on average across different random samples, the simple regression estimator underestimates the effect of the training program c. on average, across different random samples, the simple regression estimator overestimates the effect of the training program d. on average, across different random samples, the simple regression estimator associated to the training program ( does not change when is omitted from the model. 4. A model relating a person's wage to experience is: where is the natural logarithm of individual is hourly wage and is the number of years of experience. In this model 100* measures: a. The unit change in hourly wage given another year of experience holding all other factors fixed. b. the percentage change in hourly wage given another year of experience, holding all other factors fixed. c. the unit change in hourly wage given a 1% increase in experience. holding all other factors fixed. d. the percentage change in given another year of experience. holding all other factors fixed. Suppose that average worker productivity at manufacturing firms () depends on two factors, average hours of training () and average worker ability (): Assume that this equation satisfies the Gauss-Markov assumptions and that and are expected to have a positive impact on. If grants have been given to firms whose workers have less than average ability, so that and are negatively correlated, how does omitting the relevant variable from the model affect the estimated effect of the training program ()? a on average, across different random samples, the simple regression estimator associated to the training program (is unbiased b. on average across different random samples, the simple regression estimator underestimates the effect of the training program c. on average, across different random samples, the simple regression estimator overestimates the effect of the training program d. on average, across different random samples, the simple regression estimator associated to the training program ( does not change when is omitted from the model
