Which of the following is not a condition to estimate a model for causality? A) E[U_i] = E[U_iX₁_i] = ... E[U_iX_ki] = 0. B) The sample is a random sample from the target population. C) The error terms are distributed normally. D) The data generating process can be described by a determining function such as $Y _ { i }$ = ?₀ + ?₁X₁_i + ...+ ?_kX_ki + U_i.

Question

Quizplus · Accepted Answer

While normal distribution may be a common assumption in estimating causal models, it is not an absolute condition. Other methods, such as robust regression, can be used to handle non-normal errors. The other conditions (A, B, and D) are important for estimating the model for causality.

Which of the Following Is Not a Condition to Estimate YiY _ { i }Yi​

Which of the Following Is Not a Condition to Estimate $Y _ { i }$