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ECON 2100: Assignment 1 (due on Oct 8)

Please submit your solutions in a PDF document. To show any work done in R,

also include the R script file. Please submit BOTH (PDF & R) files on LMS. Each

question is for 10 points.

1. Draw two labor supply curves, with hours of work on the x-axis and wage rate on the y- axis, where

(a) the income effect dominates the substitution effect

(b) the substitution effect dominates the income effect

2. Theoretically, both (a) and (b) from question 1 are possible. Based on your

understanding of the labor market in general, which one makes more sense? Explain.

3. Download “labor_supply.xlsx” (posted on LMS). This partial dataset comes from the

2018 Current Population Survey (CPS) and includes the following information provided

by the survey participants: hours worked last week, hourly wage, age, gender, race, and

educational attainment. Note that educational attainment has three levels: no high

school degree, high school degree but no college degree, college degree or above.

Run a simple linear regression with Y = hours worked last week and X = hourly wage.

Is there a significant relationship between work hours and wage? If so, at which

significance level?

Provide an interpretation of the coefficient estimate on wage.

4. Run a multiple linear regression including age, age-squared, gender, race, and

educational attainment as “additional” independent variables. Before running the

regression, make sure to create dummy variables for gender, race, and educational

attainment. Hint: two dummy variables are necessary for educational attainment.

What happens to the magnitude of the coefficient estimate on wage, when compared

to question 3? What does this tell us about the role of the other independent variables

in explaining the relationship between work hours and wage?

Is each independent variable statistically significant? Is the overall model significant?

Provide an interpretation of the coefficient estimate on each independent variable.

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5. Based on your estimated model from question 4, sketch by hand a labor supply curve. Is

this labor supply curve consistent with your answer to question 2? Explain.

6. Add the following two independent variables (in addition to all the other independent

variables from previous questions) and run a multiple linear regression:

(i) an interaction between wage and gender

(ii) an interaction between wage and race

Provide interpretations of the coefficient estimates on wage and interactions (i) and (ii).

7. Add wage-squared as an independent variable (in addition to all the other independent

variables from previous questions, EXCEPT the interactions from question 6) and run a

multiple linear regression. Based on your estimated model, sketch by hand a labor

supply curve. What does this labor supply curve tell us about the relative size of the

income effect vs. the substitution effect?

Are these two effects ever equal to each other? If so, at what wage rate?

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