位置2的问题 If a proposed instrumental variable unexpectedly fails to meet the exclusion restriction, our estimate of the treatment effect using two-stage least squares will include the effect of the treatment along with all other paths from the instrument to the outcome.TrueFalseDon't Know清除选择Single choice
A
True
B
False
C
Don't Know

Question

位置2的问题 If a proposed instrumental variable unexpectedly fails to meet the exclusion restriction, our estimate of the treatment effect using two-stage least squares will include the effect of the treatment along with all other paths from the instrument to the outcome.TrueFalseDon't Know清除选择Single choice

A

True

B

False

C

Don't Know

BlackTom AI · Accepted Answer

Let's break down the question and assess each option in turn.
Option 1: True. The statement claims that if an instrumental variable (IV) fails to satisfy the exclusion restriction, the two-stage least squares (2SLS) estimate will capture the treatment effect plus all other causal paths from the instrument to the outcome. In IV terminology, violation of the exclusion restriction means the instrument affects the outcome not only through the treatment but also via other channels. Consequently, the 2SLS estimator becomes inconsistent for the causal effect of the treatment, because part of the instrument’s influence on the outcome is not mediated by the treatment. Therefore, this option correctly describes a key pitfall of a misspecified IV.
Option 2: False. Saying the 2SLS estimate would still cleanly identify only the treatment effect ignores the core requirement of the exclusion restriction. If the exclusion restriction is violated, the instrument can affect the outcome through pathways other than the treatment, contaminating the estimate. This makes the statement in Option 2 incorrect.
Option 3: Don't Know. If a student does not know about the exclusion restriction and its role in IV estimation, they might be uncertain. However, the scenario described directly ties to a standard result: violation of the exclusion restriction leads to biased, inconsistent estimates that reflect both the treatment and other instrumented pathways to the outcome. Without this understanding, choosing Don't Know would be unsafe, but the underlying concept points toward a specific conclusion.
In summary, each option hinges on understanding how the exclusion restriction affects the validity of 2SLS estimates. The true appraisal is that a failure of the exclusion restriction contaminates the instrument's pathway to the outcome, violating the clean identification of the treatment effect.

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