Revisiting Tobin's 1950 Study of Food Expenditure.

This re-analysis of Tobin's (l950)study makes three points: (1) graphs are a powerful device for discovery and for communication, and can reveal much of the information in the data; (2) squeezing out the more subtle multivariate messages requires some solution to the usual overparameterization problem. Data-mining is still the treatment of choice for this crippling disease, but it is more akin to leeches than to anti-biotics. A Bayesian sensitivity analysis is an alternative, but it isn't a perfect cure either; and (3) clear identification of the issues can help keep the enterprise from wandering off in technically amusing but largely irrelevant directions.