Which of the following assumptions are required to show the consistency, unbiasedness and efficiency of…

By the Gauss-Markov Theorem, to prove that the Ordinary Least Squares (OLS) estimators are unbiased, consistent, and efficient within the class of linear unbiased estimators (BLUE — Best Linear Unbiased Estimators), only the first three assumptions on the disturbance term ν_t are required (alongside exogenous/non-stochastic regressors): - I. Zero mean: E(ν_t) = 0 (required for unbiasedness). - II. Homoscedasticity (constant variance): Var(ν_t) = σ² (required for minimum variance / efficiency). - III. No autocorrelation: cov(ν_t, ν_{t-j}) = 0 for all j ≠ 0 (required for minimum variance / efficiency). The normality assumption IV (ν_t ~ N(0, σ²)) is not required for unbiasedness, consistency, or Gauss-Markov efficiency (BLUE); it is only needed for exact finite-sample t and F hypothesis tests (or to establish Cramér-Rao efficiency across non-linear estimators as well). Therefore, ('I, II and III only') is the standard econometric answer.