教育的价值(英文版)论文分析.pptx

Measuring value-added in higher educationPossibilities and limitations in the use of administrative dataReasonThe growing interest for both funding and incentivizing purposes in higher educationSolutionA general methodology for measuring the value added of institutions ofhigher education DataInformation from different administrative sources in the state of Texas1.Introduction Statistically distinguishing value-added estimates between individual institutionResultHigher education institutional performance is multidimensional objective function.A system of multiple metrics capturing various dimensions of institutional performance1.Introduction 2.Defining value in higher educationColleges aim to produce a wide range of benefits for students.Imparts knowledge and skillsEconomic productivityWages increase students individual utilityoffer greater choices in the type of workimprove ability to make decisions about marriage,health,and parentingincrease sense of general happinessfoster non-pecuniary benefits Knowledge voting and supportingfree speechimprove civic societyfoster positive externalities3.Measuring value added in higher educationStandardized testsGrade point average(GPA)Graduation and persistenceWages/earningsInstitutional performanceDisciplines&coursesA long time lag3.Measuring value added in higher educationThe calculation modelYis is an outcome for student i who attended school sXi,PRE is a vector of observable pre-enrollment student characteristicss are coefficients of school and can change over timeEs are a set of indicators for enrollment at various college sis are other indicators4.Data and sampleThe 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.1.It is a large and diverse state that closely mirrors the demographic and socio-economic make-up of the U.S.population.2.The vast majority of Texans attend college in state,this helps mitigate sample selection issues.Reason4.Data and sampleSummarizes the data,for both the sample of all enrollees and only enrollees with non-zero UI(Unemployment Insurance)earnings.5.ResultsEarnings differences of enrollees at Texas four-year public colleges.5.ResultsColumn 1:A base case that can be compared with models that control for selection into collegesColumn 2:Race and gender controlsColumn 3:High school fixed effects and indicators for courses taken during high schoolColumn 4:SAT score and various student and family demographics Column 5:Application group fixed effectsShrink the range of point estimates Reduce significant differences 5.ResultsThe significant differences in earnings between college.5.ResultsGraduation and persistence differences of enrollees at Texas four-year public colleges5.ResultsScatter plots of the coefficients on school fixed effects in the earnings,graduation,and persistence models.5.ResultsCorrelations 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 recommendationInformation about the pre-enrollment characteristics of studentsTrue institutional qualityFunding and incentivizingFunding is tied to conditional completion ratesInstitutions may lower grading standards