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Posts Tagged ‘Causation’

Go away and think

Wise counsel on understanding the history and context of any fact or assumed causation.  When solving problems, we often want to start with a clean slate, unencumbered by history.  Even where that is possible, it is not always wise.  Only when we understand the nature of the status quo do we begin to be in a position to intelligently change it.  From G.K. Chesterton in The Thing (1929), Ch. IV : The Drift From Domesticity.

In the matter of reforming things, as distinct from deforming them, there is one plain and simple principle; a principle which will probably be called a paradox. There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, “I don’t see the use of this; let us clear it away.” To which the more intelligent type of reformer will do well to answer: “If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.”

This paradox rests on the most elementary common sense. The gate or fence did not grow there. It was not set up by somnambulists who built it in their sleep. It is highly improbable that it was put there by escaped lunatics who were for some reason loose in the street. Some person had some reason for thinking it would be a good thing for somebody. And until we know what the reason was, we really cannot judge whether the reason was reasonable.  It is extremely probable that we have overlooked some whole aspect of the question, if something set up by human beings like ourselves seems to be entirely meaningless and mysterious. There are reformers who get over this difficulty by assuming that all their fathers were fools; but if that be so, we can only say that folly appears to be a hereditary disease. But the truth is that nobody has any business to destroy a social institution until he has really seen it as an historical institution. If he knows how it arose, and what purposes it was supposed to serve, he may really be able to say that they were bad purposes, that they have since become bad purposes, or that they are purposes which are no longer served. But if he simply stares at the thing as a senseless monstrosity that has somehow sprung up in his path, it is he and not the traditionalist who is suffering from an illusion.

There is a correct answer to that question, but it’s unlikely we’ll ever know what it was.

From Why Do Education and Health Care Cost So Much? by Megan McArdle.  A great example of the challenges related to causal density.  We may accurately identify all the causes of an outcome but still not be able, because of poor understanding of the relationships between root causes, to predict outcomes.  Absent accurate prediction, we don’t really understand the nature of a problem at all.

So how do we explain health care and college cost inflation? Well, health care economist David Cutler once offered me the following observation: In health care, as in education, the output is very important, and impossible to measure accurately. Two 65-year-olds check into two hospitals with pneumonia; one lives, one dies. Was the difference in the medical care, or their constitutions, or the bacteria that infected them? There is a correct answer to that question, but it’s unlikely we’ll ever know what it was.

Similarly, two students go to different colleges; one flunks out, while the other gets a Rhodes Scholarship. Is one school better, or is one student? You can’t even answer these questions by aggregating data; better schools may attract better students. Even when you control for income and parental education, you’re left with what researchers call “omitted variable bias” — a better school may attract more motivated and education-oriented parents to enroll their kids there.

So on the one hand, we have two inelastic goods with a high perceived need; and on the other hand, you have no way to measure quality of output. The result is that we keep increasing the inputs: the expensive professors and doctors and research and facilities.

I would quibble with McArdle.  There are actually two problems.  It is true that it is hard to measure education and health outcomes and that is a challenge.  But even if we were able to measure with great precision and accuracy, that is still not the same as forecasting.  Measuring is a predicate to forecasting.

If we precisely and accurately measure our initiating action X, we want to know with some level of accuracy and certainty that X will lead to Y, the outcome we desire.  If we cannot predict the outcome, it means we don’t understand the relationship between and among the various causes.

Solution to low public transportation utilization

From Mobility for the Poor: Car-Sharing, Car Loans, and the Limits of Public Transit by Jeff Khau.  An example of the importance of establishing the difference between correlation and causation; of the importance of directionality of causation; of context; of root cause analysis; and goal definition.

Theoretically, one can look at this graph and legitimately make the argument that in order to increase public utilization of public transportation, one ought to increase the average commute time.  It is a good exercise in critical thinking to spot the fallacy of such an interpretation.

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