Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The authors consider the relative bias of the OLS-based estimate s(squared) of the disturbance variance in the linear regression model when disturbances are stationary AR(1). They improve upon previous bounds for the bias and show that E(s[squared]/["sigma" squared]) tends to zero as autocorrelation increases whenever there is an intercept in the regression. Copyright 1992 by MIT Press.