Trying to understand this problem:
Suppose you had access to a dataset that follows individuals from adolescence throughout adulthood. Each year, you observe earnings, educational attainment, health, and marital status. Suppose you were interested in seeing how marriage causally affects the earnings of men. Using the described data, how would you examine this question? What would be your identifying assumption? How could you assess the plausibility of this assumption?
First I'm trying to understand, what is an identifying assumption? I think it's the assumption you test that tells you whether there was a causal relationship or not. Is that right?
And my first thoughts on answering the homework problem are these:
I would have to determine that income and marriage aren't simultaneously determined, reverse causal, or both influenced by the same variable. So creating a counterfactual group (unmarried men) and matching with married men could set up a good difference in differences.
But how to assess the plausibility of this assumption? I usually just plug numbers into the computer and don't care about plausibility. What makes an assumption more plausible in econometrics?