JNU SIS 2021 Question 5: Goodness of fit and model selection
Consider the following two regression models:
Model 1: yi=α0+α1x1i+ui
Model 2: yi=β0+β1x1i+β2x2i+ui
Which of the following statements are true?
A. Model 2 must have an R2 at least as high as that of model 1
B. Model 2 must have an adjusted R2 at least as high as that of model 1
C. Models 1 and 2 would have identical values of R2 if the estimated coefficient on β2 is zero
D. Models 1 and 2 would have identical values of adjusted R2 if the estimated coefficient on β2 is zero
Choose the correct answer from the options given below:
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Answer and worked solution
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Plain-text version
Consider the following two regression models: Model 1: yᵢ = α₀ + α₁ x₁ᵢ + uᵢ Model 2: yᵢ = β₀ + β₁ x₁ᵢ + β₂ x₂ᵢ + uᵢ Which of the following statements are true? A. Model 2 must have an R² at least as high as that of model 1 B. Model 2 must have an adjusted R² at least as high as that of model 1 C. Models 1 and 2 would have identical values of R² if the estimated coefficient on β₂ is zero D. Models 1 and 2 would have identical values of adjusted R² if the estimated coefficient on β₂ is zero Choose the correct answer from the options given below: (A) A, B, C and D (B) A, B and C only (C) A and C only (D) B and D only
Also written as: Consider the following two regression models: Model 1: y_i = alpha_0 + alpha_1 x_(1i) + u_i Model 2: y_i = beta_0 + beta_1 x_(1i) + beta_2 x_(2i) + u_i Which of the following statements are true? A. Model 2 must have an R^2 at least as high as that of model 1 B. Model 2 must have an adjusted R^2 at least as high as that of model 1 C. Models 1 and 2 would have identical values of R^2 if the estimated coefficient on beta_2 is zero D. Models 1 and 2 would have identical values of adjusted R^2 if the estimated coefficient on beta_2 is zero Choose the correct answer from the options given below:
Goodness of fit and model selection has come up 27 times in 6 exams since 2009.
What this question tests
This question is on Adjusted R-squared and model comparison, part of Goodness of fit and model selection in Econometrics.
Penalising extra regressors and when R-squared can be compared across models.
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