In the Context of a Controlled Experiment, Consider the Simple $\hat \beta _ { 1 }$

question 13

Multiple Choice

In the context of a controlled experiment, consider the simple linear regression formulation Y_i = ?₀ + ?₁X_i + u_i. Let the Y_i be the outcome, X_i the treatment level when the treatment is binary, and u_i contain all the additional determinants of the outcome. Then calling $\hat \beta _ { 1 }$ a differences estimator

• A)makes sense since it is the difference between the sample average outcome of the treatment group and the sample average outcome of the control group.
• B)and \(\hat \beta _ { 0 }\) the level estimator is standard terminology in randomized controlled experiments.
• C)does not make sense, since neither Y nor X are in differences.
• D)is not quite accurate since it is actually the derivative of Y on X.

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