Question

Using data from 50 workers, a researcher estimates Wage = β₀ + β₁Education + β₂Experience + β₃Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table.

	Coefficients	Standard Error	t Stat	p-Value
Intercept	7.17	4.26	1.68	0.0991
Education	1.81	0.35	5.17	0.0000
Experience	0.45	0.10	4.50	0.0000
Age	−0.01	0.06	−0.17	0.8684

a-1. Interpret the point estimate for β₁.

• As Education increases by 1 year, Wage is predicted to increase by 1.81/hour.

• As Education increases by 1 year, Wage is predicted to increase by 0.45/hour.

• As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant.

• As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant.

a-2. Interpret the point estimate for β₂.

• As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour.

• As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour.

• As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Education constant.

• As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Education constant.

b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

c. Predict the hourly wage rate for a 22-year-old worker with 3 years of higher education and 4 years of experience. (Do not round intermediate calculations. Round your answer to 2 decimal places.)

Answer 1

Coefficients	Standard Error	t Stat	p-Value
Intercept	7.17	4.26	1.68	0.0991
Education	1.81	0.35	5.17	0.0000
Experience	0.45	0.10	4.50	0.0000
Age	−0.01	0.06	−0.17	0.8684

a-1)

• As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant.

a-2)

• As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Education constant.

b)

Wage = 7.17 + 1.81 * Education + 0.45 * Experience - 0.01 * Age

c)

Wage = 7.17 + 1.81 * 3 + 0.45 * 4 - 0.01 * 22

Wage = 14.18