Explanation
When the variance of the error term is an increasing function of the explanatory variable, this indicates heteroscedasticity rather than homoscedasticity.
Key Concepts:
- Homoscedasticity: Assumes constant variance of error terms across all values of explanatory variables
- Heteroscedasticity: Occurs when the variance of error terms changes with the explanatory variables
- Violation: The described scenario clearly shows heteroscedasticity, which violates the homoscedasticity assumption
Other Options Analysis:
- B. Multicollinearity: Refers to high correlation between explanatory variables, not variance patterns
- C. Model is linear: The linearity assumption relates to the functional form, not variance properties
- D. No autocorrelation: Concerns correlation between error terms over time, not variance patterns
Correct Answer: A - Homoscedasticity assumption is violated
