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Recently I came across this brilliant example of avoiding reducing selection bias when extracting quasi-experimental data from the world towards the beginning of the book "Good Economics for Hard Times" by Banerjee and Duflo.
The authors were interested in understanding the impact of migration on income. However, most data on migration contains plenty of selection bias. For example, people who choose to migrate are usually audacious risk-takers or have the physical strength, know-how, funds and connections to facilitate their undertaking,
To reduce these selection biases, the authors looked at people forced to relocate due to rare natural disasters, such as volcano eruptions.
That does help reduce the selection bias; I don't see why that would eliminate it?
I was more focused on chance of death not financials. The chance of said little old granny dying before being settled, either on the way or at the time of the initial event, is likely higher than the chance of the 25y old healthy male.
5Alexander
Oh, it wouldn't eliminate all selection bias, but it certainly would reduce it. I said "avoid selection bias," but I changed it to "reduce selection bias" in my original post. Thanks for pointing this out.
It's tough to extract completely unbiased quasi-experimental data from the world. A frail elder dying from a heart attack during the volcanic eruption certainly contributes to selection bias.
It's tough to extract completely unbiased quasi-experimental data from the world.
Understatement.
I can't go into more details here unfortunately, and some of the details are changed for various reasons, but one of the best examples I've seen of selection bias was roughly the following:
Chips occasionally failed. When chips failed, they were sent to FA[1] where they were decapped[2] and (destructively) examined[3] to see what went wrong. This is a fairly finicky process[4], and about half the chips that went through FA were destroyed in t... (read more)