Questions -

Q1. Why it is desirable to remove insignificant variables from a regression?

Q2. We may consider an example taken from Studenmund (2001: 193-5). The restricted equation for a demand for chicken function is:

Y^{^} = 32.9 - 0.70 PC_t + 0.27 YD_t

= (-8.33) (45.91)

SSR_R = 185.66 N = 44

Where Y^{^} is the estimated demand for chicken;

PC is the price of chicken;

t is the time subscript;

YD is disposable income.

The unrestricted equation is estimated as:

Y^{^} = 23.80 - 0.59PC_t + 0.36YD_t + 0.02Y^{^}_t² - 0.007Y^{^}_t³ + 0.000055Y^{^}_t⁴

= (-0.34) (0.50) (0.29) (-0.68) (1.02)

SSR_U = 138.41 N = 44

In this case the unrestricted functional form (specification) is to the fourth power. Calculate RESET test statistic to find that estimated linear form is the correct specification of the model.

Q3. Consider the following simultaneous equations system.

y_1t = α₀ + α₁y_2t + α₂y_3t + α₃X_1t + α₄X_2t + u_1t (1)

y_2t = β₀ + β₁y_3t + β₂X_1t + β₃X_3t + u_2t (2)

y_3t = γ₀ + γ₁y_1t + γ₂X_2t + γ₃X_3t + u_3t (3)

a. What do you understand by the term 'identification'? Describe a rule for determining whether a system of equations is identified. Apply this rule to equation (1)-(3).

b. Which would you consider the more serious misspecification: treating exogenous variables as endogenous, or treating endogenous variables as exogenous? Explain your answer.