Consider a multiple regression model examining the impact of various independent variables on the dependent variable Y . The model specified is as follows: $$ Y = \beta_0 + \beta_1X_1 + \beta_2X_2 + \beta_3X_3 + \epsilon $$ Where: Y is the dependent variable. X_1, X_2, X_3 are independent variables. ε is the error term. In the context of this model, which of the following statements is true regarding the assumptions necessary for ordinary least squares (OLS) regression to yield reliable estimates?

Exam

CFA Level 2

Section

Difficulty

Quantitative Methods

Model Assumptions in OLS Regression

Very Hard Multiple Regression Analysis Model Assumptions

Consider a multiple regression model examining the impact of various independent variables on the dependent variable Y. The model specified is as follows:

$$ Y = \beta_0 + \beta_1X_1 + \beta_2X_2 + \beta_3X_3 + \epsilon $$

Where:

Y is the dependent variable.
X_1, X_2, X_3 are independent variables.
ε is the error term.

In the context of this model, which of the following statements is true regarding the assumptions necessary for ordinary least squares (OLS) regression to yield reliable estimates?

The error term ε must be normally distributed regardless of the distribution of the independent variables.

The variance of the error term ε must be constant; this is known as homoscedasticity.

The independent variables X_1, X_2, X_3 must have no correlation with each other.

Hint

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