Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Until recently, estimates of demand functions for public goods were obtained (either with aggregate or micro survey data) using single equation estimation techniques. However, demand estimates may be biased when in dividuals' choices of communities are dependent upon the quantity and quality of public good provided. This paper spells out the nature of this bias (called Tiebout bias) and suggests an improved maximum-likelihood estimation technique. The technique is applied to a data set involving local public education in Michigan. Copyright 1987 by MIT Press.