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Lorenzo's
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Econometric Modeling as Junk Science
(Ted Goertzel, The Skeptical Inquirer, Jan/Feb 2002)
Do you believe that every time a prisoner is executed in the United States, eight future murders are deterred? Do you believe that a 1% increase in the number of citizens licensed to carry concealed weapons causes a 3.3% decrease in the state's murder rate? Do you believe that 10 to 20% of the decline in crime in the 1990s was caused by an increase in abortions in the 1970s? Or that the murder rate would have increased by 250% since 1974 if the United States had not built so many new prisons? . . . If you were misled by any of these studies, you may have fallen for a pernicious form of junk science: the use of mathematical models with no demonstrated predictive capability to draw policy conclusions. . . . Although economists are the leading practitioners of this arcane art, sociologists, criminologists and other social scientists have versions of it as well. It is known by various names, including "econometric modeling," "structural equation modeling," and "path analysis." . . . If one had perfect measures of all the causal variables, this would work. But the data are never good enough. Repeated efforts to use multiple regression to achieve definitive answers to public policy questions have failed. . . . But many social scientists are reluctant to admit failure. They have devoted years to learning and teaching regression modeling, and they continue to use regression to make causal arguments that are not justified by their data. I call these arguments the myths of multiple regression, and I would like to use four studies of murder rates as examples. . . . Myth One: More Guns, Less Crime. . . . Myth Two: Imprisoning More People Cuts Crime . . . Myth Three: Executing People Cuts Crime . . . Myth Four: Legalized Abortion Caused the Crime Drop in the 1990s.

[COMMENT: For the author's detailed discussion of each of the above myths, click the link above and read the full text of this essay.]

posted by LoZo 4:50 PM