Truth versus Precision in Economics.

• Author: Neuberg, Leland G.

This book is a thoughtful critical contribution to economic methodology. Mayer distinguishes two types of mainstream economic theorizing--formalist and empirical science. Formalist theorizing relies heavily on axiomatic mathematical models. Examples include general equilibrium theory in microeconomics, new classical theory in macroeconomics, and structural parameter analysis in econometrics. Empirical theorizing is the sort of endeavor engaged in by the applied econometrician in constructing equations and formulating hypotheses.

Mayer argues that formalist theorizing has come to dominate the economics profession. The best graduate schools stress the formalist orientation and downgrade all aspects of understanding an economy through data analysis. A "principle of the strongest link" characterizes the argument of a typical professional journal article. The paper focuses on the formal link of the argument's chain, and neglects the other links and assumptions. Getting the formal link right gives the argument precision, but truth suffers because of the neglected links.

Mayer offers a sensible economic explanation of how formalism has come to dominate economics. He illustrates the damage done by the formalist mindset with a series of examples from new classical macro-economics. He cites surveys of economic graduate students to show that they are unhappy about formalist dominance. He deftly marshals philosophers of science to bolster his argument. Unusual among economic methodologists, Mayer understands and respects Karl Popper and Thomas Kuhn, but also sees where each could lead economists astray.

His chapter on how econometricians often abuse Neyman-Pearson hypothesis-testing theory surpasses in clarity anything I've read on the subject. Yet the same chapter implicitly raises a question. It calls for sensitivity analysis of empirical results to omitted variables, variation in lags, alternative functional forms, alternative data sets, and different sample periods. Since sensitivity analysis is inherently incomplete, e.g., there is always another omitted variable to look at, how good is the economic understanding that empirical analysis alone provides?

Hypothesis testing is problematic in many economic situations. For example, to make an economic policy decision often requires knowledge of whether one variable is the cause of another. One can test the hypothesis that the two variables are correlated. With nonexperimental data, though, their...