Over at the Legal Professions Blog, my good friend Jeff Lipshaw, equipped with an excel spreadsheet, a map, and a ruler, has taken on the perennial claim that the Lawyer/Judge input variable in U.S. News contains a "coastal bias." His analysis says no, but Jeff has asked for some help.
Using a simple OLS model, my dependent variable is 2006 Lawyer/Judge Reputation. My independent variables include Academic Reputation, 75th percentile LSAT (which is good proxy for total rank), a west coast dummy (Arizona, California, Oregon, and Washington; 27 schools = 1) and an east coast dummy (Delaware, Maine, Maryland, Massachusetts, New York, New Hampshire, New Jersey, Pennsylvania, Rhode Island, Vermont, and Virginia; 54 schools = 1) . Here is a summary of the results, which corroborate Jeff's theory:
Obviously, the signs for both coasts are negative (i.e., no systematic boost for either coast), and the p-value for East Coast implies a statistically significant penalty for being an east coast school. Perhaps schools far away from the major east coast legal markets are destine to seem better than the nearby law schools that firms know well but tend to run down. The adjusted R-squared for the model is 75.7%.
We might be able to specify a better regression model, or recode with a better definition of "coastal", or correct for some minor heteroscedasticity. But anyone who thinks they can salvage the bias theory is probably kidding themselves.
Jeff, you should plan on spending the summer in Ann Arbor at the ICPSR statistics boot camp. You clearly show promise.