The economics of education and training PDF
Preview The economics of education and training
Studies in Empirical Economics Studies in Empirical Economics Aman Ullah (Ed.) Arno Riedl, Georg Winckler Semiparametric and Nonparametric and Andreas Wörgötter (Eds.) Econometrics Macroeconomic Policy Games 1989. ISBN 978-3-7908-0418-8 1995. ISBN 978-3-7908-0857-5 Walter Krämer (Ed.) Thomas Url and Andreas Wörgötter (Eds.) Econometrics of Structural Change Econometrics of Short 1989. ISBN 978-3-7908-0432-4 and Unreliable Time Series 1995. ISBN 978-3-7908-0879-7 Wolfgang Franz (Ed.) Hysteresis Effects in Economic Models Steven Durlauf, John F. Helliwell 1990. ISBN 978-3-7908-0482-9 and Baldev Raj (Eds.) Long-Run Economic Growth John Piggott and John Whalley (Eds.) 1996. ISBN 978-3-7908-0959-6 Applied General Equilibrium 1991. ISBN 978-3-7908-0530-7 Daniel J. Slortje and Baldev Raj (Eds.) Income Inequality Poverty Baldev Raj and Badi H. Baltagi (Eds.) and Economic Welfare Panel Data Analysis 1998. ISBN 978-3-7908-1136-0 1992. ISBN 978-3-7908-0593-2 Robin Boadway and Baldev Raj (Eds.) Josef Christl Advances in Public Economics The Unemployment/Vacancy Curve 2000. ISBN 978-3-7908-1283-1 1992. ISBN 978-3-7908-0625-0 Bernd Fitzenberger, Roger Koenker Jürgen Kaehler and Peter Kugler (Eds.) and José A. E. Machado (Eds.) Econometric Analysis of Financial Markets Economic Applications 1994. ISBN 978-3-7908-0740-0 of Quantile Regression 2002. ISBN 978-3-7908-1448-4 Klaus F. Zimmermann (Ed.) Output and Employment Fluctuations James D. Hamilton and Baldev Raj (Eds.) 1994. ISBN 978-3-7908-0754-7 Advances in Markov-Switching Models 2002. ISBN 978-3-7908-1515-3 Jean-Marie Dufour and Baldev Raj (Eds.) New Developments Badi H. Baltagi (Ed.) In Time Series Econometrics Panel Data 1994. ISBN 978-3-7908-0766-0 2004. ISBN 978-3-7908-0142-2 John D. Hey (Ed.) L uc Bauwens, Winfried Pohlmeier Experimental Economics and David V eredas (Eds.) 1994. ISBN 978-3-7908-0810-0 High Frequency Financial Econometrics 2008. ISBN 978-3-7908-1991-5 . Christian Dustmann Bernd Fitzenberger Stephen Machin (Eds.) The Economics of Education and Training Physica-Verlag ASpringerCompany Editorial Board Heather M. Anderson Bernd Fitzenberger Australian National University University of Freiburg Canberra,Australia Germany Badi H. Baltagi Robert M. Kunst Texas A & M University Institute for Advanced Studies College Station Vienna, Austria Texas, USA Editors Prof. Christian Dustmann Prof. Stephen Machin University College London (UCL) University College London (UCL) Department of Economics Department of Economics Gower Street Gower Street London WC1E 6BT London WC1E 6BT United Kingdom United Kingdom [email protected] [email protected] Professor Dr. Bernd Fitzenberger Albert-Ludwigs-University Freiburg Department of Economics Platz der Alten Synagoge 1 79085 Freiburg Germany [email protected] 11 papers have been first published in “Empirical Economics” Vol. 32, No. 2-3, 2007 and 2 papers in Vol. 33, No. 2, 2007 ISBN 978-3-7908-2021-8 e-ISBN 978-3-7908-2022-5 Library of Congress Control Number: 2007942365 © Physica-Verlag Heidelberg 2008 This work is subject to copyright. 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Cover Design: WMXDesign GmbH, Heidelberg, Germany Printed on acid-free paper 9 8 7 6 5 4 3 2 1 springer.com Contents Editorial:theeconomicsofeducationandtraining ................... 1 ChristianDustmann,BerndFitzenberger,andStephenMachin Doesreducingstudentsupportaffectscholasticperformance? EvidencefromaDutchreform..................................... 7 MichèleBelot,ErikCanton,andDinnandWebbink Part-timework,schoolsuccessandschoolleaving.................... 23 ChristianDustmannandArthurvanSoest Timetolearn?Theorganizationalstructureofschools andstudentachievement .......................................... 47 OzkanErenandDanielL.Millimet Whoactuallygoestouniversity? ................................... 79 OscarMarcenaro-Gutierrez,FernandoGalindo-Rueda,andAnnaVignoles Doestheearlybirdcatchtheworm?Instrumentalvariableestimates ofearlyeducationaleffectsofageofschoolentryinGermany ......... 105 PatrickA.PuhaniandA ndreaM.Weber PeereffectsinAustrianschools .................................... 133 NicoleSchneeweisandRudolfWinter-Ebmer Fairrankingofteachers........................................... 157 HendrikJürgesandKerstinSchneider SchoolcompositioneffectsinDenmark:quantileregression evidencefromPISA2000.......................................... 179 BeatriceSchindlerRangvid Whataccountsforinternationaldifferencesinstudentperformance? Are-examinationusingPISAdata ................................. 209 ThomasFuchsandLudgerWößmann vi Contents PISA:Whatmakesthedifference?Explainingthegapintest scoresbetweenFinlandandGermany .............................. 241 AndreasAmmermuller Theimpactofunionizationontheincidenceofandsources ofpaymentfortraininginCanada ................................. 267 DavidA.GreenandThomasLemieux Evaluatingmulti-treatmentprograms:theoryandevidence fromtheU.S.JobTrainingPartnershipActexperiment............... 293 MianaPlescaandJeffreySmith Employmenteffectsoftheprovisionofspecificprofessionalskills andtechniquesinGermany ....................................... 331 BerndFitzenbergerandStefanSpeckesser ChristianDustmann·BerndFitzenberger·StephenMachin Editorial: the economics of education and training In recent years, there has been a big resurgence of interest in the economics of education and training. This has come from many quarters, including academic research,inpolicycirclesandingeneralmediadebate.Thiscollectionofpaperson various aspects of the economics of education and training reflects this increased interest. Education and training are keys to explain the current competitive strengths of national economies, and to secure future competitiveness. In an increasingly globalisedworldeconomy,nationaleconomiescompeteintheproductionoftrade- ablegoodsand,facilitatedthroughmoderntechnologies,awiderangeofservices. There are the first signs of specialisation on national level, for instance, Germany showing continued strength in manufacturing, while the UK is increasingly with- drawingfromthissectorandspecialisinginfinancialandothertradableservices.In thepast(andinmanyContinentalEuropeancountriespossiblyuntilthefirstPISA study), educational and training institutions were often seen as providers of nec- essaryskillsfornationaleconomies, butthisviewhaschangeddramatically, with educationandtrainingnowbeingseenasakeyingredientforinternationalcompet- itiveness,andwithinsti tutionsthatprovideeducationbeingamainingredientthat helpsecurecompetitivepositions. Over the last ten to fifteen years, there have been a number of major changes in the way we deal with our educational institutions. First, there is now a strong tendency to steer educational institutions into directions that provide cutting-edge knowledgeandabilitytonewgenerationsofworkers,withthemainobjectivenow beingtoimprovingthepositionofthenationaleconomy,ratherthanensuringequal- ity. This is particularly so in Continental European countries, where past reforms weredrivenbyconsiderationsofequalityinopportunity,andwheretheideaofpro- visionofeducationaccordingtoindividualabilityisgainingstrength.Second,there hasbeenanewopennesstoreformagendas,whichlooksacrossnationalboundaries toimprovingnationalcurriculabyincorporatingcomponentsthatprovedsuccessful inothercountries.Thisgoesalongsideeffortsto‘normalise’nationalcurriculaby introducingcomparabledegrees.TheBolognaagreementforhighereducationisan example.Third,educationisincreasinglyseenasagoodthatcanbemoreefficiently provided in a quasi-market setting. Competition between schools is no novelty in 2 C.Dustmannetal. theAnglo-SaxonworldandseemslikelytoincreaseinContinentalEuropeancoun- tries(forexample,withtherebeingincreasingpressurestomakeachievementtables publicly available).At the high end of education, competition for funds and well- payingstudentsisanimportantingredientforsecuringfinancingofuniversitiesand highereducationinstitutionsintheUS,Australia,Canada,andtheUK.Introduction ofcomparabledegreesinEuropewillsoonaddEuropeancountriestothatlist.And fourth, vocational training systems and government–sponsored training programs are being reformed in similar ways in many European countries that traditionally haveseentheseasaveryimportantpartofskillformation.Germanyhasrecently introduced quasi-market mechanisms (vouchers, performance standards) into the provisionofpublic-sector–sponsoredtraining. Thepapersinthisspecialissuecomethereforeatatimeofheightenedinterest inthetopic.Theycoveralargerangeofissuesatthecoreofcontemporarydebate. Theseincludefinancingofeducation,transitionfromschooltowork,organisation ofeducation,schoolqualityandissuesthatrelatetoit,suchasqualityofpeersand teachers.Theyalsoaddressissuesthatrelatetomorevocationaltrainingactivities, and how these are influenced by purpose-made programmes, or other institutions. The remainder of this editorial summarises the contributions to the special issue. We start with the papers on specific aspects of the educational systems in single countries. The first eight papers cover issues like impact of student support, time allocation,accesstohighereducation,theimpactofschoolentryage,peereffectsand ranking of teachers.The next two papers involve cross-country studies of student achievement based on the PISA data. The remaining three papers are concerned with training the workforce. One paper studies the effects of unions on training. Twopaperscontributetotheliteratureontheevaluationoftrainingprograms. The study by Michele Belot, Erik Canton, and Dinand Webbink investigates the impact of student support on performance and time allocation of students in Dutchhighereducation.In1996,themaximumdurationofgrantswasreducedby one year, and thereby limited to the nominal duration of the study program. This reformcouldhavehadsubstantialfinancialconsequencesforstudents.Theauthors evaluate the effects of the reform using a difference-in-differences approach.The mainfindingsarethatafterthereform,studentsearlyintheirstudy(1)switchlessto otherprograms,(2)obtainhighergrades,and(3)donotspendmoretimestudying orworking.Inaddition,forstudentsnotolderthan20yearswhentheystartedtheir study,largereffectsarefoundforallperformancevariables(switching,percentage ofcompletedcourses,graduationinthefirstyearandgrade-pointaverages).These findingsareconsistentwithrecentevidenceonheterogeneoustreatmenteffectsfor higherabilitystudents. Turning to a different aspect of time allocation and education, Christian Dustmann andArthur van Soest analyse part-time employment of teenagers who arestillinfull-timeeducation,theiracademicperformanceandtheirschool-leaving decisions.Theestimationstrategyinthepapertakesaccountofthepossibleinter- dependencies of these events and distinguishes between two alternative states to full-timeeducation:enteringthelabourforcefull-timeandgoingontofurthertrain- ing.Theauthorsmodelthisdecisioninaflexibleway.Theanalysisisbasedondata fromtheUKNationalChildDevelopmentStudy,whichhasanunusuallyrichsetof variables on school and parental characteristics.The main finding is that working part-timewhileinfull-timeeducationhasonlysmalladverseeffectsonexamper- formanceforfemales,andnoeffectsformales.Theeffectofpart-timeworkonthe Editorial: theeconomicsofeducationandtraining 3 decisiontostayonatschoolisalsonegative,butsmall,andmarginallysignificant formales,butnotforfemales.Otherimportantdeterminantsofexamsuccessaswell asthecontinuationdecisionareparentalambitionsaboutthechild’sfutureacademic career. Utilizing parametric and nonparametric techniques, Daniel L. Millimet and OzkanErenalsoassesstheimpactofaheretoforerelativelyunexplored‘input’inthe educationalprocess,timeallocation,onthedistributionofacademicachievement. Theresultsindicatethatschoolyearlengthandthenumberandaveragedurationof classesaffectstudentachievement.However,theeffectsarenothomogeneous–in termsofbothdirectionandmagnitude–acrossthedistribution.Itisfoundthattest scoresintheuppertailofthedistributionbenefitfromashorterschoolyear,while alongerschoolyearincreasestestscoresinthelowertail.Furthermore,testscores inthelowerquantilesincreasewhenstudentshaveatleasteightclasseslasting46– 50minonaverage,whiletestscoresintheupperquantilesincreasewhenstudents havesevenclasseslasting45minorlessor51minormore. ThestudybyFernandoGalindo-Rueda,OscarMarcenaro-Gutierrez,andAnna Vignoles is concerned with access to higher education (HE), a major policy issue in England andWales.There is concern that children from lower socio-economic backgrounds are far less likely to get a degree. The authors analyse the changing association between socio-economic background and the likelihood of going to university,usingdatafromtheYouthCohortStudy,spanningtheperiod1994–2000. The study finds evidence of substantial social class inequality in HE participation butconcludesthatthisislargelyduetoeducationinequalitiesthatemergeearlierin theeducationsystem.ConditionalonGCSEandA-levelperformance,noadditional roleisfoundforsocio-economicbackgroundorparentaleducationindetermining pupils’likelihoodofgoingtouniversity. PatrickA. Puhani andAndrea M. Weber estimate the effect of age of school entryoneducationaloutcomesusingtwodifferentdatasetsforGermany,sampling pupilsattheendofprimaryschoolandinthemiddleofsecondaryschool.Results are obtained based on instrumental variable estimation exploiting the exogenous variationinmonthofbirth.Thestudyfindsrobustandsignificantpositiveeffectson educationaloutcomesforpupilswhoenterschoolatseveninsteadofsixyearsofage: Testscoresattheendofprimaryschoolincreasebyabout0.40standarddeviations and the probability to attend the highest secondary schooling track (Gymnasium) increasesbyabout12%points. The study by RudolfWinter-Ebmer and Nicole Schneeweis deals with educa- tionalproductioninAustriaandisfocusedontheimpactofschoolmatesonstudents’ academic outcomes. The authors use PISA 2000 and 2003 data to estimate peer effectsfor15-and16-year-oldstudents.Schoolfixedeffectsareemployedtoaddress thepotentialself-selectionofstudentsintoschoolsandpeergroups.Theestimations showsignificantpositiveeffectsofthepeergrouponstudents’readingachievement, andlesssoformathematics.Thepeereffectinreadingislargerforstudentsfrom less-favourablesocialbackgrounds.Furthermore,quantileregressionssuggestpeer effectsinreadingtobeasymmetricinfavouroflow-abilitystudents,meaningthat studentswithlowerskillsbenefitmorefrombeingexposedtocleverpeers,whereas thosewithhigherskillsdonotseemtobeaffectedmuch. Kerstin Schneider and Hendrik Jürges are concerned with a different aspect of educational production, namely rankings of teacher quality. Economic theory suggeststhatitisoptimaltorewardteachers,dependingontherelativeperformance 4 C.Dustmannetal. oftheirstudents.Theauthorsdevelopaneconometricapproach,basedonstochastic frontier analysis, to construct a fair ranking that accounts for the socio-economic backgroundofstudentsandschoolsandfortheimprecisioninherentinachievement data. Using German PIRLS (IGLU) data, the hierarchical structure of the data is exploitedtoestimatetheefficiencyofeachteacher.Aparsimonioussetofvariables sufficestogetanestimateoftheunobservedteacherquality.AHausman–Taylortype estimatoristhepreferredestimatorbecauseteacherefficiencyandsomeexogenous variablesarecorrelated. InastudyforDenmark,BeatriceSchindlerRangvidcombinesdatafromthefirst waveofthePISAstudywithregisterdatatoestimatetheeffectofthesocio-economic mixofschoolsonstudentstestscores.Theadministrativedataallowustoaddfamily backgrounddataforallsame-agedschoolmatesofthePISAstudents.Tocompensate forendogeneityintheschoolcompositionvariable,theresultsareconditionedon a rich set of family and school variables from the PISAdata. Quantile regression resultssuggestdifferentialschoolcompositioneffectsacrosstheconditionalreading score distribution, with students in the lower quantiles achieving the largest test scoregains.Mathematicsresultssuggestthathigh-andlow-abilitystudentsbenefit equally from attending schools with a better student intake, and most results for scienceareonlymarginallysignificant.Theseresultsimplythatmixingstudentsof differenthomebackgroundscouldimproveequityofachievementforbothreading andmathematics;however,theaverageskilllevelwouldimproveonlyforreading literacy.Inmathematics,mixingstudentswouldnotraiseaverageoutcomes,because thedetrimentaleffectonstudentsinthehigherquantileswouldoffsetpositiveeffects onthoseinthelowerquantiles. So far, we have discussed studies for single countries. Ludger Wößmann and ThomasFuchsusethePISAstudent-levelachievementdatabasetoestimateinterna- tionaleducationproductionfunctions.Studentcharacteristics,familybackgrounds, homeinputs,resources,teachersandinstitutionsareallsignificantlyassociatedwith math,scienceandreadingachievement.Theirmodelsaccountformorethan85% ofthebetween-countryperformancevariation,withroughly25%accruingtoinsti- tutional variation. Student performance is higher with external exams and budget formulation, and also with school autonomy in textbook choice, hiring teachers andwithin-schoolbudgetallocations.Autonomyismorepositivelyassociatedwith performance in systems that have external exit exams. Students perform better in privatelyoperatedschools,butprivatefundingisnotdecisive. Inasecondcross-countrystudy,AndreasAmmermülleranalyzesthelargedif- ference in the level and variance of student performance in the 2000 PISAstudy between Finland and Germany. To explain the better performance of Finnish stu- dents,thestudyestimateseducationalproductionfunctionsforbothcountries,using auniquemicro-leveldatasetwithimputeddataandaddedschooltypeinformation. The difference in reading proficiency scores is assigned to different effects, using Blinder–Oaxaca and Juhn–Murphy–Pierce decomposition methods. The analysis showsthatGermanstudentsandschoolshaveonaveragemorefavourablecharac- teristics except for the lowest deciles, but experience much lower returns to these characteristics in terms of test scores than Finnish students. The role of school types remains ambiguous. Overall, the observable characteristics explain more of thevariationintestscoresinGermanythaninFinland. Turningtothestudiesinthisspecialissueontheeconomicsoftraining,thestudy by Thomas Lemieux and DavidA. Green uses theAdult Education and Training
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