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Category: Econometrics

Published June 3, 2013

A Rant on Estimation with Binary Dependent Variables (Technical)

Suppose you are trying to explain some outcome [math]y[/math], where [math]y[/math] is equal to 0 or 1 (e.g., whether someone is a nonsmoker or a smoker). You also have data on a vector of explanatory variables [math]x[/math] (e.g., someone’s age, their gender, their level of education, etc.) and on a treatment variable [math]D[/math], which we will also assume is binary, so that [math]D[/math] is equal to 0 or 1 (e.g., whether someone has attended an information session on the negative effects of smoking).

If you were interested in knowing what the effect of attending the information session on the likelihood that someone is a smoker, i.e., the impact of [math]D[/math] on [math]y[/math] The equation of interest in this case is

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Published January 14, 2013

Economics, History, and Why Social Scientists Don’t Know Much About Anything

Economics and history have not always got on. Edward Lazear’s advice that all social
scientists adopt economists’ toolkit evoked a certain skepticism, for mainstream
economics repeatedly misses major events, notably stock market crashes, and rhetoric can be mathematical as easily as verbal. Written by winners, biased by implicit assumptions, and innately subjective, history can also be debunked. Fortunately, each is learning to appreciate the other … Each field has infirmities, but also strengths. We propose that their strengths usefully complement each other in untangling the knotty problem of causation.

This complementarity is especially useful to economics, where establishing what causes what is often critical to falsifying a theory. Carl (sic) Popper argues that scientific theory advances by successive falsifications, and makes falsifiability the distinction between science and philosophy. Economics is not hard science, but nonetheless gains hugely from a now nearly universal reliance on empirical econometric tests to invalidate theory. Edward O. Wilson puts it more bluntly: “Everyone’s theory has validity and is interesting. Scientific theories, however, are fundamentally different. They are designed specifically to be blown apart if proved wrong; and if so destined, the sooner the better.” Demonstrably false theories are thus pared away, letting theoreticians focus on as yet unfalsified theories, which include a central paradigm the mainstream of the profession regards as tentatively true. The writ of empiricism is now so broad that younger economists can scarcely imagine a time when rhetorical skill, rather than empirical falsification, decided issues, and the simplest regression was a day’s work with pencil and paper.

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Published November 8, 2012

Medical Analogies in the Social Sciences

Andrew Gelman writes:

Social scientists who use medical analogies to explain causal inference are, I think, implicitly trying to borrow some of the scientific and cultural authority of that field for [their] own purposes.

Social scientists are often tempted to illustrate their ideas with examples from medical research. When it comes to medicine, though, we are, with rare exceptions, at best ignorant laypersons (in my case, not even reaching that level), and it is my impression that by reaching for medical analogies we are implicitly trying to borrow some of the scientific and cultural authority of that field for our own purposes. Evidence-based medicine is the subject of a large literature of its own.

Gelman’s post is a contender for the Post with the Longest Title 2012 award (the title of the post is indeed “Social scientists who use medical analogies to explain causal inference are, I think, implicitly trying to borrow some of the scientific and cultural authority of that field for our own purposes.”)

I wonder if he got his inspiration from the Red Sparowes, whose song titles are known for being long (“the great leap forward poured down upon us one day like a mighty storm, suddenly and furiously blinding our senses,” off of their album Every Red Heart Shines Toward the Red Sun.)