Subject Code : EC452
Assignment Task:

INTRODUCTORY ECONOMETRICS:(EC452)

You were provided with an individualized data set. If you have not obtained the data set, please contact Julie Oliver or Gordon Kemp as a matter of urgency. Your data set is unique to you. You must not use the data set of any other student for your econometrics exercise.

In this exercise, your task is to examine the determinants of hourly wages for a sample of employed married women. The variables in your data set are: wage = hourly wage (in U.S. dollar), hours = weekly hours worked, age = individual’s age in years, Educ = years of education, union = indicator which takes the value 1 if the individual is a union member (and 0 otherwise), kidlt6 = indicator which takes the value 1 if there are children aged less than 6 in the household.

Use your data set and Stata (or other econometrics packages) to answer the following questions. (EC452)

1.(a) For each of the variables wage, union, and hours, what is the average, the standard deviation, the minimum value, and the maximum value in your data set?
(b) What is the number of observations in your data set?

2.(a) Generate a new variable wage as the (natural) logarithm of wage. Label this variable.
(b) What percentage of individuals are union members? What is the average hourly wage for union members who are at least 40 and at most 49 years old?
(c) Generate a new variable, age group, which takes value 1 if the individual is younger than 25 years, value 2 for the age group 25-34, 3 for the age group 35-44, 4 for the age group 45-54, and 5 for ages 55 and above. Tabulate the new variable. How many women are there in the age group 35-44?

3.(a) Examine graphically the relationship between age and union membership, using a bar graph. In this graph, each bar should show the average union membership status for one of the age categories de?ned in question 2c. Interpret your result.
(b) Calculate the correlation coe?cient between hourly wage and years of education. Is there a strong relationship between these two variables?

4.(a) Run a regression of hourly wage on experience and education and report the regression results.
(b) If education changes from 8 to 11 years, what is the predicted e?ect on hours worked?
(c) If education changes from 12 to 15 years, what is the predicted e?ect on hours worked?

5.(a) Generate a new variable for potential labour market experience using the formula exper = age - Educ - 6. (In the following, we will refer to this variable as ‘experience’ or exper.)
(b) Run a regression of log hourly wages (wage) on years of schooling and experience, and report the regression results.
(c) If education changes from 12 to 13 years, what is the predicted e?ect on the hourly wage?
(d) If education changes from 8 to 9 years, what is the predicted e?ect on the hourly wage?

6.(a) Generate a new variable, expertise, which is equal to the square of exper and then run a regression of log hourly wages on years of schooling, exper, and exper2, and report the regression results.
(b) Test if the coe?cients on expert and experts are jointly signi?cant (at a signi?cance level of 1%).
(c) Do you prefer the regression in part(a) to the regression in question 5b? Explain.

7.(a) Run a regression of wage on the union, Educ, and exper, and report the regression results.
(b) Interpret the estimated coe?cient on the union, and then use your regression results from part (a) of this question to test if a union has a statistically signi?cant e?ect on log hourly wages (at a signi?cance level of 10%).
(c) How much does the R2 increase by including union membership, compared to the speci?cation in question 5b?
(d) Based on your regression results from part (a) of this question, what change in education would be needed to o?set a change from non-union to union in terms of log hourly wages?

8.(a) Run a regression of luggage on the union, exper, Educ, and an interaction term between union and experience (union ×exper). What does the coe?cient on the interaction term measure?
(b) Test if the e?ect of experience di?ers with union membership at the 5% signi?cance level.
(c) What is the predicted log hourly wage for a union member with 10 years experience, and 12 years of education?

9.(a) Generate a new variable, work, which equals 1 if hours is strictly less than 30 and equals 0 otherwise. Then extend the model in question 7a by additionally accounting for work. Write down the resulting model and estimate its coe?cients.
(b) Based on your regression results from part (a) of this question, what is the predicted e?ect on hourly wages of working less than 30 hours per week? Is the e?ect statistically signi?cant (at a 5% level of signi?cance)?
(c) A researcher claims that unions help individuals with low labour market attachment to achieve better labour market outcomes. In particular, the claim is that individuals who work part-time, i.e. less than 30 hours per week, bene?t more from union membership (in terms of log hourly wages) than individuals who work fulltime, i.e. at least 30 hours per week. Explain how you can investigate this claim in the data, and report your ?ndings. Explain your results.

10.(a) Prepare a table reporting the estimates (and corresponding standard errors) from the regressions in questions 5b, 6a, 7a, 8a and 9a. In this table, each column should report the estimates of one regression.
(b) After running all these regressions, summarize the main ?ndings you have obtained. Are there any further variables or models you would like to include in the analysis? If yes, then explain why and state the models.


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  • Posted on : February 21st, 2019

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