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 examines the evolution of productivity in U.S. manufacturing plants from 1963 to 1992. We define a vintage effect as the change in productivity of recent cohorts of new plants relative to earlier cohorts of new plants, and a survival effect as the change in productivity of a particular cohort of surviving plants as it ages. Both factors contribute to industry productivity growth, but play offsetting roles in determining a cohort's relative position in the productivity distribution. Recent cohorts enter with higher productivity than earlier entrants did, whereas surviving cohorts show productivity increases as they age. These two effects roughly offset each other, however, so there is a rough convergence in productivity across cohorts in 1992 and 1987.