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Flashcards in 13 Experiments Deck (6)
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1
Q

differences estimator

A

E(β1) = E[Yi | Xi = 1] − E[Yi | Xi = 0]

2
Q

Conditional Mean Independence

A

Conditional Mean Independence:
E[ui | Xi , Wi] = E[ui | Wi] != 0

This is unproblematic as long as we are only interested in the causal effect of Xi and not in the causal effect of Wi:

Under Conditional Mean Independence, OLS will give an unbiased estimate of the causal effect of Xi

3
Q

Threats to internal validity during ideal randomized experiments

A
Failure to randomize
Failure to follow the treatment protocol
Attrition
Hawthorne effect
Small samples
4
Q

The treatment might not be assigned randomly but instead is based on characteristics or preferences of the subjects

If this is due to the fact that the experimenter assigned the treatment randomly conditional on observed characteristics…
• .

A

The treatment might not be assigned randomly but instead is based on characteristics or preferences of the subjects

If this is due to the fact that the experimenter assigned the treatment randomly conditional on observed characteristics…

…we can estimate the causal effect by including these observed characteristics in the regression (conditional mean independence)

5
Q

If the treatment is randomly assigned conditional on unobserved characteristics or preferences…

A

If the treatment is randomly assigned conditional on unobserved characteristics or preferences…

…the estimated treatment “effect” will reflect both the effect of the treatment and the effect of these unobserved characteristics.

6
Q

Double-blind experiment

A

Subjects and experimenters know that they are in an experiment, but neither know which subjects are in the treatment group and which in the control group.