Suppose you want to estimate the model Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄.However,you cannot measure X₄,so you estimate Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ instead.This is an example of regression result that will be subject to: A)autocorrelation. B)heteroscedasticity. C)multicollinearity. D)specification bias.

Question

Quizplus · Accepted Answer

This is an example of specification bias, which occurs when the model being estimated is not correctly specified or is missing relevant variables. In this case, the model is missing the variable X₄, which may be an important predictor of Y. Therefore, the estimated coefficients for the other variables may be biased and unreliable.

Suppose You Want to Estimate the Model Y = β0

Suppose You Want to Estimate the Model Y = β₀