3. A before and after approach is most appropriate when: a) there is simultaneous causality. b)...

3. A before and after approach is most appropriate when:

a) there is simultaneous causality.

b) there is measurement error in the explanatory or dependent variable.

c) there is an omitted variable that varies across entities, but not over time.

d) there is an omitted variable that varies over time, but not across entities.

Solutions

Expert Solution

The before and after approach considers the omitted variables that change based on the combinations but not with respect to time. The changes are based on the other variables to which it is compared to. With regression, the variables will not change with respect to time but the variation is based on the entity.

Answer:Option C

Rahul Sunny answered 2 years ago

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