For as long as there have been economists there have been debates over the proper methodology for economics. Econometricians have by contrast avoided such arguments, preferring to get on with the job. Generally, discussions of econometric methodology have merely reflected the controversy between "classical' and "Bayesian' statistics. In some ways this has been unfortunate as there are at least three important benefits which might result from the adoption of an explicit methodology. First, it could provide a set of principles to guide and improve applied research. Second, it could help codify and organise econometric knowledge, which would greatly facilitate teaching. Finally, it could encourage researchers to report their results in an informative and succinct style.
In the last few years interest in the methodology of econometrics has increased, and distinctive styles of doing econometrics have emerged. Four major ones might be distinguished. A Bayesian approach to econometrics has long been advocated by Arnold Zellner. Time-series approaches have been exemplified in the work of Christopher Sims. An "LSE' methodology can be found primarily in the work of Denis Sargan and David Hendry. Finally, Edward Leamer has set out a collection of methods that have been described as "vestigial Bayesianism'.
In Discussion Paper No. 39 Michael McAleer , Paul Volker and CEPR Research Fellow Adrian Pagan explore the effectiveness of Leamer's methodology as a guide for applied research and as a reporting style. They argue that Leamer's methodology performs very poorly in these roles. To substantiate their claim they examine one of the techniques used by advocates of this methodology: Extreme Bounds Analysis (EBA).
Suppose one is interested in measuring the effect of interest rates on the demand for money. Extreme Bounds Analysis would begin with a fairly general model of money demand which included interest rates, as well as other variables. This general model can be "simplified' in various ways, for example by excluding one or more explanatory variables. Extreme Bounds Analysis is concerned with the largest and smallest values of the estimates of the interest rate coefficient when various simplified models are estimated.
Suppose the estimated coefficient varies greatly over the range of simplified models. Inference concerning the coefficient is then said to be be "fragile' or "unreliable', since the coefficient estimate obtained appears to be sensitive to the precise specification of the model used. McAleer, Pagan and Volker demonstrate that such analysis based on extreme bounds is directly related to traditional tests of hypotheses that particular simplifications of the model are compatible with the data. The extreme bounds methodology, according to the authors, merely presents in a different format the same information as does conventional regression analysis. Pagan and his coauthors argue that the most disturbing feature of the extreme bounds technique is that it also provides much less information about other aspects of the model's adequacy. They argue that this "vestigial Bayesianism' is therefore inadequate both as a research guide and as a reporting style.
The Discussion Paper concludes by examining the best known application of the EBA technique - a demand for money study by Thomas Cooley and Steven Le Roy. Cooley and Le Roy found that the impact of interest rates on money demand is "ill-determined'. Pagan, McAleer and Volker argue that Cooley and Le Roy arrived at such a conclusion only as a result of their adoption of this inadequate methodology, and that the misgivings expressed about the theory of vestigial Bayesianism also apply in its practice.

What Will Take the Con Out of Econometrics?
Michael McAleer, Adrian R Pagan and Paul A Volker

Discussion Paper No. 39, January 1985 (ATE)