Research tasks 1. (7 points) You are given a dataset in an Excel format. Figure out how to load this dataset in R. Provide your R-commands to load the data. In particular, be clear about which R-package you install and use. (Hint: use the Internet. There are several different ways of doing it.) 2. (15 points) Obtain summary statistics and histograms for the variables wage and educ and scatter diagram of those two variables. For the diagrams, give informative titles and variable names instead of just using the default titles and variable names. For example, you could use Years of Education in place of educ. Discuss the data characteristics. 3. (9 points) Estimate the linear regression wage; = 1 + [seduc; + u;, where u; is the error and 8; and 3 are the unknown population coefficients. Assuming that Eluleduc] = 0, interpret the estimated coefficient on educ (3 points) and test whether or not the population coefficient is zero at the 1 % significance level (3 points). What is the predicted wage of a person with eight years of education (3 points) 4. (8 points) Estimate the linear regression In(wage;) = 51 + Boeduc; + u;, where u; is the error and 3; and (3 are the unknown population coefficients. Assuming that Elu|educ] = 0, and using the estimates, what is the predicted change of wage for every additional year of education (3 points)? Then, interpret the R? (2 point). This numeric value of R? here can be similar to that of the regression in Question 3. However, they are conceptually different. Explain the difference (3 points). 5. (6 points) You suspect that the hourly wage could depend on experience (years of potential experience). Discuss under what condition(s) the estimated coefficients in the previous questions would be biased due to the omission of the experience (2 points). Give a reasonable and intuitive story on why omission of experience would cause omitted variable bias in the regression with only educ like in the previous question (2 points). Under your story, explain whether the estimated coefficient on educ in Question 4 would be overestimated or underestimated (2 points). 6. (4 points) The variable exper is years of potential experience. Regress In(wage) on educ and exper. Discuss the estimation results. In particular, explain statistical significance and the difference between the estimated coefficient on educ in this regression and that in Question 5. 7. (6 points) tenure is years with current employer. Since tenure captures the productivity of the individual at a particular job, we may consider it as a determinant of hourly earnings. Regress In(wage) on educ, exper, and tenure (3 points). Using the estimates, compute the estimated effect on wage when an individual stays at the same firm for another year (3 points). Note that when tenure increases by one year, exper must also increase by one year. 8. (8 points) TIs your predicted effect in Question 7 statistically significantly different from zero at the seven percent of level? Clearly write down the null hypothesis (3 points). Test your hypothesis using R by loading relevant packages (2 point). Explain your decision whether to reject the hypothesis (3 points)