Consider the following regression model: y_i = ₀ + ₁x_i + u_i. If the first four Gauss-Markov assumptions hold true, and the error term contains heteroskedasticity, then _____. A)Var(u_i|x_i) = 0 B)Var(u_i|x_i) = 1 C)Var(u_i|x_i) = i² D)Var(u_i|x_i) =

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In the presence of heteroskedasticity, the conditional variance of the error term is not constant, and therefore, it cannot be equal to zero or one. To estimate the variance of the error term, we need to use Heteroskedasticity-consistent standard errors (HCSEs) or White's standard errors. In this case, since there is no information given about the form of heteroskedasticity, the best choice is C, which provides a general formula for the conditional variance of the error term that depends on the explanatory variables.

Consider the Following Regression Model: Yi = 0

Consider the Following Regression Model: Y_i = ₀