Estimating the Impact of Schooling and Labor Market Experience on Wages, Assignments of Statistics

Download Estimating the Impact of Schooling and Labor Market Experience on Wages and more Assignments Statistics in PDF only on Docsity! Economics 105 Davidson College Aug -Dec 2008 Mark C. Foley Graded Homework #221 Suppose you were interested in estimating the impact of years of schooling and labor market experience on wages. To do so, you estimate an equation of the form iiii ESwages εβββ +++= 210ln , where S is years of schooling and E is years of experience in the labor market. The data are in an Excel file P:\Economics\Eco 105 (Statistics)\gh22_data.xls. (a) Estimate 0β , 1β , and 2β . Write out the sample regression function and interpret each coefficient. (b) What fraction of the variance in log wages is explained by the two explanatory variables? (c) Test the hypothesis that the return to education (“the effect of schooling on wages”) is greater than 10% using a 5% significance level. (d) At what significance level can you reject the hypothesis that schooling has no impact on wages? (e) At what significance level can you reject the hypothesis that the effect of schooling on wages (“the return to education”) does not equal 5%? (f) Now estimate the model iiiii EESwages εββββ ++++= 2 3210ln , where 2E is the square of the number of years of labor market experience. Why would you include a quadratic expression of this type in the model? At what number of years of experience is earnings maximized? 1 Example is taken from problem 11.3 of Ashenfelter, Levine, and Zimmerman (2003), Statistics and Econometrics: Methods and Applications.