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Measuring value-added in higher education Possibilities and limitations in the use of administrative data,1.Introduction,Statistically distinguishing value-added estimates between individual institution,Higher education institutional performance is multidimensional objective function.,A system of multiple metrics capturing various dimensions of institutional performance,1.Introduction,2.Defining value in higher education,Colleges aim to produce a wide range of benefits for students.,3.Measuring value added in higher education,Standardized tests,Grade point average (GPA),Graduation and persistence,Wages/earnings,Institutional performance,Disciplines & courses,A long time lag,3.Measuring value added in higher education,The calculation model,Yis is an outcome for student i who attended school s Xi,PRE is a vector of observable pre-enrollment student characteristics s are coefficients of school and can change over time Es are a set of indicators for enrollment at various college s is are other indicators,4.Data and sample,The value-added model using rich administrative data from the state of Texas that tracks students from high school, through college, and into the labor force.,4.Data and sample,Summarizes the data, for both the sample of all enrollees and only enrollees with non-zero UI(Unemployment Insurance) earnings.,5.Results,Earnings differences of enrollees at Texas four-year public colleges.,5.Results,Column 1: A base case that can be compared with models that control for selection into colleges Column 2: Race and gender controls Column 3: High school fixed effects and indicators for courses taken during high school Column 4: SAT score and various student and family demographics Column 5: Application group fixed effects,Shrink the range of point estimates,Reduce significant differences,5.Results,The significant differences in earnings between college.,5.Results,Graduation and persistence differences of enrollees at Texas four-year public colleges,5.Results,Scatter plots of the coefficients on school fixed effects in the earnings, graduation, and persistence models.,5.Results,Correlations between the school coefficients (Panel A) and the rank-order of school coefficients (Panel B) from the earnings, graduation, and persistence models.,The correlation is strongly positive between all the measures and ranks, with the strongest association between the graduation and persistence models.,6.Conclusion and recommendation,
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