A TTEMPTS to ascertain the productivity of university resources have typically relied on simple regression techniques; some measure of output is regressed on variables reflecting university services with controls for student characteristics. The results of these studies can generally be described as inconclusive with respect to the questions of whether or not university inputs matter. For example, Astin (1968) failed to find any strong relationship between university resources and educational value-added, as measured by student performance on the Graduate Record Examination field test, controlling for scores on the National Merit Scholarship Qualifying Test upon entering college. However, Perl (1971) found a strong, statistically significant relationship between university expenditures per pupil and the proportion of graduates attending graduate and professional schools. Such differences in conclusions can be attributed to many factors. Various authors employ different measures for attainment, university services and the control variables. Also, differences in the levels of aggregation (e.g., university versus departmental observations) are important in rationalizing varying results. Beyond these specific differences, a deficiency common to each study is that they all treat university service flows as exogenous. Failure to account for at least student choices as to courses, major fields of study, and college or university of attendance implies that existing models are misspecified.1 Prior research has generally assumed that university resources (R) and student characteristics (X) combine to produce learning (Q):

This paper derives an after tax version of the Capital Asset Pricing Model. The model accounts for a progressive tax scheme and for wealth and income related constraints on borrowing. The equilibrium relationship indicates that before-tax expected rates of return are linearly related to systematic risk and to dividend yield. The sample estimates of the variances of observed betas are used to arrive at maximum likelihood estimators of the coefficients. The results indicate that, unlike prior studies, there is a strong positive relationship between dividend yield and expected return for NYSE stocks. Evidence is also presented for a clientele effect.