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