ECON 2220 A Winter 2024
Assignment 2: Due March 15
PLEASE BE SURE TO READ THE DOCUMENT ENTITLED “GENERAL ASSIGNMENT GUIDELINES” BEFORE YOU BEGIN THIS ASSIGNMENT. ALL REFERENCES ARE TO THE 7th EDITION OF STUDENMUND. UNLESS SPECIFIED OTHERWISE, USE A 5% SIGNIFICANCE LEVEL FOR ALL TESTS. ASSIGNMENTS SHOULD BE SUBMITTED THROUGH BRIGHTSPACE EITHER ON OR BEFORE THE DUE DATE.
IF IN DOUBT, PROVIDE MORE DETAIL IN YOUR ANSWERS, RATHER THAN LESS.
NOTE: If a statistical table does not give an entry for the appropriate number(s) of degrees of freedom, then use the closest number(s) of degrees of freedom available.
1. Consider Question 7 of Chapter 3 (pp. 87-89), together with the new A2Q1.dta dataset.
Answer the following questions:
i) Obtain basic summary statistics for the variables PRICE, NEW, SCRATCH, and BIDRS using the STATA “summarize” command, and then copy and paste the output into your assignment.
ii) Estimate the model using STATA, and then copy and paste the output into your assignment.
iii) Report your regression results in the standard format of equation (3.2) on p. 72. (Use two decimal places for the estimated coefficients, the standard errors, and the t-statistics.)
iv) Carefully explain the real-world meaning of the three estimated slope coefficients.
v) What signs would you have expected for each of the estimated slope coefficients? Carefully explain your reasoning in each case.
vi) Based on your answer to part v), use t-tests to test these expectations about the signs of the estimated slope coefficients. Be sure to write down the null and alternative hypotheses in each case, and to explain whether you should reject or not reject the null hypothesis in each case.
vii) Test the overall significance of the regression using the step-by-step procedure outlined in the example on p.145. Be sure to write down the appropriate null and alternative hypotheses, and to explain whether you should reject or not reject the null hypothesis.
viii) Repeat part vii), but this time using the (more) general F-test formula given in equation (5.10). Be sure to write down the appropriate null and alternative hypotheses, and to explain whether you should reject or not reject the null hypothesis.
ix) Using the standard formula in equation (5.9), construct 90% 2-sided confidence intervals for each of the estimated slope coefficients. Be sure to show your working, step-by-step.
x) Using an appropriate STATA command(s), check your answerstopart ix). Copy and paste the relevant STATA output into your assignment.
xi) Re-estimate the model using STATA, but this time omit the BIDRS variable, and then copy and paste the output into your assignment.
xii) Report the regression results from part xi) in the standard format of equation (3.2) on p. 72. (Use two decimal places for the estimated coefficients, the standard errors, and the t-statistics.)
xiii) Using the discussion of four important specification criteria on p. 166- 167, compare the original model with the more parsimonious model which excludes BIDRS. Which model do you think is better? Carefully use the four specification criteria to make your decision, being sure to state which criteria support your decision and why.
2. Consider the US dataset A2Q2.dta, where the variables are defined as follows:
WAGES = current hourly wages in $
SCHOOL = years of schooling
EXPER = years of out-of-schoolwork experience
ETHBLACK = 1 if African-American, 0 otherwise
ETHHISP = 1 if Hispanic, 0 otherwise
Note that there are three ethnic groups in total, namely, African-American, Hispanic, and Other. Respondents are associated with one and only one of these three groups.
i) Obtain basic summary statistics for the variables in the dataset using the STATA summarize command, and then copy and paste the output into your assignment.
ii) Estimate the following wages model and then copy and paste the output into your assignment.
WAGEsi = β0 + β1sCHOOLi + β2 EXPERi + β3 ETHBLACki + β4 ETHHIsPi + Ei i = 1, 2, … , 500
iii) Carefully interpret the real-world meaning of the five parameter estimates.
iv) Are all of the parameter estimates individually statistically significant? Explain.
v) Use an appropriate F-test to test whether ethnicity has an overall impact on current hourly wages and therefore whether the two ethnicity dummy variables should be included in the model. Be sure to follow the detailed steps outlined on pp. 142- 144, including the provision of a clear statement of the relevant null and alternative hypotheses, the use of the general F-statistic formula given in equation (5.10), and a clear explanation of whether you should reject or not reject the null hypothesis and why.
vi) Would using the AIC and BIC criteria, rather than an F-test, in part v) have led you to reach a different conclusion? Explain. And, be sure to include any relevant output from STATA.
vii) On the basis of the answers to parts v) and vi), can you conclude that there either is or is not ethnicity-based discrimination in the US labour market? Explain your answer.
3. Professor Jones looks at the answers to Question 2 and decides to specify a log-linear version of the original model but without the two ethnicity dummy variables
lnwAGESi = β0 + β1SCHOOLi + β2 EXPERi + E i i = 1, 2, … , 500
i) Using an appropriate set of STATA commands, estimate this model, and then copy and paste ALL of the output into your assignment.
ii) Carefully interpret the real-world meaning of the three parameter estimates.
iii) Use your estimation results to predict the current hourly wages for an individual with 18 years of schooling and 5 years of out-of-schoolwork experience.
iv) Without using the ovtest command, use a RESET test to check the specification of the model. Be sure to include a clear statement of the appropriate null and alternative hypotheses, the formula for the test statistic, and the necessary calculations for your test in your answer. What do you conclude? Explain. Be sure to copy and paste any additional STATA output that you may require into your assignment.