Consider the simple regression model: y = beta_0 beta_1 x u. This model satisfies the Gauss-Markov assumptions (SLR.1 - SLR.5). Given a sample of n observations, a researcher decides to estimate beta_1 using the estimator: beta_hat_1 = (sum of xi * yi) / (sum of x^2) which is not the regular OLS estimator. Without deriving this estimator's properties, what can we say about this estimator in comparison to the OLS estimator? (think about the Gauss-Markov Theorem). a) beta_hat_1 has larger variance. b. beta_hat_1 is biased and has larger variance. c. beta_hat_1 is biased and/or has larger variance. d) beta_hat_1 is biased