Can I get an indulgence for bad control?

We get a lot of questions about bad control.  Here’s an interesting one from Colin Vance:

I'd like to estimate the effect of fuel price (which I assume is exogenous) 
on distance driven. As a control, I would like to include the fuel
efficiency of the driver's car. Although efficiency is likely to be
endogenous, leaving it out of the specification runs the risk of
imparting omitted bias on my fuel price estimate. But since it is
*just* a control, I'm inclined to leave efficiency as is in the model
and not worry about whether it is endogenous. Wise move?
Any insights would be appreciated!

Before tackling the metrics, think about a likely motivation for the research question.  Suppose the government is considering a rise in the gas tax.  Policy-makers would like to know how this will affect driving habits and fuel consumption.  The government is unlikely to forbid people from buying a new more fuel efficient car in response to the tax, in fact they probably would like to encourage that.  So who needs to know what the causal effect of a price rise is conditional on being locked in to my current vehicle?  I think this observation neatly answers Colin’s  question.  Prices will go up, driving behavior will change for a number of reasons.  There is no scenario where only one response is all that’s allowed (driving in the same car). Then there is the econometric problem that conditioning on fuel efficiency will not actually answer the question of how driving behavior changes for those who don’t buy a more fuel efficient car.  That’s the bad control problem described in MHE – but that’s just metrics.

JA

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