The gender pay gap and discrimination Spending a couple of hours going through a JEL survey of modern research on the gender wage gap, yours truly was struck almost immediately by how little that research really has accomplished in terms of explaining gender wage discrimination. With all the heavy regression and econometric alchemy used, wage discrimination is somehow more or less conjured away … Trying to reduce the risk of having established only ‘spurious relations’ when dealing with observational data, statisticians and econometricians standardly add control variables. The hope is that one thereby will be able to make more reliable causal inferences. But if you do not manage to get hold of all potential confounding factors, the model risks
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Lars Pålsson Syll considers the following as important: Economics
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The gender pay gap and discrimination
where occupation (OCC) is a mediator variable and unobserved ability (A) is a variable that affects both occupational choice and wages. The usual way to find out the effect of discrimination on wages is to perform a regression ‘controlling’ for OCC to get what one considers a ‘meaningful’ estimate of real gender wage discrimination:
W = a + bD + cOCC
The problem with this procedure is that conditioning on OCC not only closes the mediation path (2) but — since OCC is a ‘collider’ — opens up the backdoor path (3) and creates a spurious and biased estimate. Forgetting that may even result in the gender discrimination effect being positively related to wages! So if we want to go down the standard path (controlling for OCC) we certainly also have to control for A if we want to have a chance of identifying the causal effect of gender discrimination on wages. And that may, of course, be tough going, since A often (as here) is unobserved and perhaps even unobservable …