"Truth" is Stranger than Prediction, More Questionable than Causal Inference

Abstract

Robert Luskin's article in this issue provides a useful service by appropriately qualifying several points I made in my 1986 American Journal of Political Science article. Whereas I focused on how to avoid common mistakes in quantitative political science, Luskin clarifies ways to extract some useful information from usually problematic statistics: correlation coefficients, standardized coefficients, and especially RZ. Since these three statistics are very closely related (and indeed deterministic functions of one another in some cases), I focus in this discussion primarily on R2, the most widely used and abused. Luskin also widens the discussion to various kinds of specification tests, a general issue I also address. In fact, as Beck (1991) reports, a large number of formal specification tests are just functions of R2, with differences among them primarily due to how much each statistic penalizes one for including extra parameters and fewer observations.