Temi di discussione. University dropout: The case of Italy. del Servizio Studi. by Federico Cingano and Piero Cipollone


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1 Tem d dscussone del Servzo Stud Unversty dropout: The case of Italy by Federco Cngano and Pero Cpollone Number Aprl 2007
2 The purpose of the Tem d dscussone seres s to promote the crculaton of workng papers prepared wthn the Bank of Italy or presented n Bank semnars by outsde economsts wth the am of stmulatng comments and suggestons. The vews expressed n the artcles are those of the authors and do not nvolve the responsblty of the Bank. Edtoral Board: DOMENICO J. MARCHETTI, MARCELLO BOFONDI, MICHELE CAIVANO, STEFANO IEZZI, ANDREA LAMORGESE, FRANCESCA LOTTI, MARCELLO PERICOLI, MASSIMO SBRACIA, ALESSANDRO SECCHI, PIETRO TOMMASINO. Edtoral Assstants: ROBERTO MARANO, ALESSANDRA PICCININI.
3 UNIVERSITY DROPOUT: THE CASE OF ITALY by Federco Cngano* and Pero Cpollone* Abstract We combne ndvdual and aggregatelevel data on educatonal attanment to study the determnants of unversty dropout n Italy, one of the worst performers among developed countres. Based on detaled nformaton on a representatve sample of secondary school graduates and on local unversty supply we frst show that famly and educatonal background are relevant determnants of contnuaton probablty. In partcular, our results show that accountng for enrollmentnduced sample selecton sgnfcantly enhances the estmated coeffcents wth respect to standard probt analyss. We then combne our estmates wth data on famly and educatonal backgrounds of secondary school graduates n comparable European countres and fnd that dfferences n endowments only explan a mnor fracton of the observed crosscountry gap n students attanments. JEL Classfcaton: I21, I22, J62, C35. Keywords: unversty dropout, school transtons, socal moblty, tobt estmaton. Contents 1. Introducton Determnants of Unversty dropout probablty Statstcal framework and emprcal ssues Data descrpton Determnants of dropout probablty: results Explanng crosscountry attanment dfferences Conclusons References Tables * Bank of Italy, Economc Research Department.
4 1. Introducton 1 Both economsts and socologsts have long been nterested n the relatonshps between educatonal attanments and ndvdual, famlar and envronmental backgrounds (Mare, 1980; Wlls and Rosen, 1979; Shavt and Blossfeld, 1993). Evdence suggestng strong dependence of educatonal outcomes from characterstcs as gender, race or famly condtons represents a relevant ndcator of nequalty n the opportuntes of socal moblty. In recent years polcymakers and observers n many developed countres have focussed n partcular on the low retenton rate of tertary educaton systems whch mght have ncreasngly negatve dstrbutonal consequences gven the wdenng college wage premum 2. Qute surprsngly, a recent strand of lterature focussng on the determnants dropout among unversty students n several countres found small or no role for ndvdual varables as famly or educatonal backgrounds (see Naylor and Smth, 2001; Johnes and McNabb, 2004 and Arulampalam et al 2001 for the UK; Montmarquette et al for Canada; Jackobsen and Rosholm, 2003 for Denmark). In ths paper we study unversty wthdrawal decsons n Italy, a country dsplayng one of the hghest drop out rates among OECD members (58% aganst an average of 30%). Unlke the above mentoned papers, focusng on contnuaton decsons of enrolled unversty students, we base our analyss on a representatve sample of Italan secondary school graduates. Ths allows controllng for selecton bases arsng when some determnants of the dropout decson affects realzaton at prevous transton (Cameron and Heckman, 1998; Keane and Wolpn, 1997). Our selectoncorrected estmates explot both functonal forms and nstrumental varables dentfcaton based on measures of antcpated costs of unversty attendance. Contrary to the exstng evdence, our results pont to a very relevant role of both famly and educatonal background characterstcs on contnuaton probabltes. For example, 1 A prevous verson of ths work was presented at the EALE 2003 meetng wth the ttle Determnants of Unversty dropout probablty n Italy. We thank semnar partcpants, Antono Cccone and Alfonso Rosola for ther useful comments. The vews expressed here are our own and do not necessarly reflect those of the Bank of Italy. Correspondng author: Federco Cngano, Bank of Italy  Research Department, va Nazonale 91, Rome, Italy. Emal: 2 In Europe, polcy concerns on the effcency of hgher educaton systems were frst rased and dscussed n the socalled Bologna Conventon of June See 3
5 we fnd that a ten years ncrease n father s schoolng (correspondng to movng from compulsory educaton to unversty degree) s assocated to a reducton n dropout probablty by 14 percentage ponts, aganst an average predcted probablty of 22 percent. The estmated effects obtaned not accountng selecton are sgnfcantly smaller, nearly 5 percent, and n lne wth the above mentoned works. We use these fndngs to check whether the dsproportonately hgh unversty dropout rate n Italy can be explaned n terms of the level and qualty of schoolng of the adult populaton. We combne ndvdual data on parental backgrounds and educatonal currcula of secondary school graduates n four large European countres wth our estmates and compute the fracton of the gap n observed dropout rates attrbutable to dfferences n these varables. Despte the sometmes large crosscountry gap n background varables, we fnd that assgnng Italan parents the same average levels of educaton observed n comparable developed countres would n the best case scenaro reduce wthdrawal by just 6 percentage ponts. Changng the composton of secondary school graduates by type of school attended would not explan much of the gap ether. 3 Whle rasng concerns on the effectveness of the exstng system of educaton n equalzng opportuntes and promotng socal moblty, our analyss thus suggests that changes n (observable) ntal condtons are unlkely to yeld sgnfcant reductons average wthdrawal rates. The rest of the paper s organzed as follows. Secton 2 llustrates the statstcal framework we used n the analyss and dscuss selecton and endogenety problems n the estmaton; we subsequently descrbe the data set and present the results. Secton 3 computes the crosscountry comparatve exercse. Secton 4 brefly concludes. 3 Clearly, ths exercse s partal snce we can not take nto account the potental effects of crosscountry dfferences n endowments on contnuaton probabltes. 4
6 2. Determnants of Unversty dropout probablty 2.1. Statstcal framework and emprcal ssues To llustrate the man selecton ssues nvolved n estmatng the determnants of ndvdual schoolng attanment consder a smple statstcal model assumng that the unobserved dsutlty assocated to school attendance by ndvdual ( * y ), s determned accordng to: * ' ' (1) y = FBβ 1 + EBβ 2 + LCβ 3 + X γ + ε In equaton (1) EB and FB descrbe student educatonal and famly background, respectvely, LC captures relevant local condtons, X s a vector of ndvdual characterstcs and ε s a dsturbance term capturng resdual unobserved heterogenety. Students wll dropout f * y s hgher than a gven threshold, normalzed to zero. Let D be the dropout ndcator, then wthdrawal ( D = 1) s observed f y * > 0. Dropout probablty can therefore be wrtten as: ' ' (2) P D = 1) = P( ε > FB β EB β LC β X γ ). ( When ε dstrbutes as a normal standard the above model can be estmated n a standard unvarate Probt regresson framework. Ths s the approach taken by recent studes on the determnants of unversty wthdrawal (Naylor and Smth, 2001; Montmarquette et al. 2001). However, the smple occurrence that some varable affectng the choce to dropout also determned outcomes at prevous transtons mples sample selecton bas would lkely affect the estmated margnal probabltes. To llustrate the nature of the dstorton consder unversty enrollment decson and assume that famlar background (as parents educaton or ncome) s the only determnant of college enrollment (E*) and drop out (D*): D E = * FB = * FB β + η α + ε 5
7 wth α >0 and β<0, respectvely. Suppose that ndvdual enrolls f E * > 0 and drops out f D * > 0 and assume for smplcty that FB can be ether 0 or 1. The average effect of FB on wthdrawal E( D * E * * * * * > 0, FB = 1) E( D E > 0, FB = 0) = β + E( η E > 0, FB = 1) E( η E > 0, FB = 0) could be obtaned estmatng β n the frst equaton only f: E( η E * * > 0, FB = 1) E( η E > 0, FB = 0) = 0 Snce accordng to the selecton equaton the lowfb enrolled would necessarly have hgher average unobservables than the hghfb enrolled, the condton above would not hold f corr(ε,η) 0. For example, snce hgher draws from the dstrbuton of ε are requred for students wth bad as opposed to good famly backgrounds to enroll, f corr(ε,η)<0 they would also have lower chances to dropout on average. If not accounted for, such selecton mechansm would bas the estmated margnal effect of famly background upwards n a sngleprobt regresson of dropout probablty. Smlar reasonng could apply to educatonal background and other relevant controls. Enrollmentnduced selecton can be accounted for specfyng a modfed verson of Tobt type 2 model (Amemya 1985) * ' (3) D = X D β + η * ' (4) E = X E α + ε where D* and E* are two latent varables representng, respectvely, the propensty of each ndvdual to enroll and subsequently wthdraw and X D and X E are dfferent group of explanatory varables. In ths framework, we only observe the sgn of E* (E*>0 ndcatng enrollment) and, when ths s postve, the sgn of D* (D * 0 ndcatng the student has not wthdrawn). The followng table summarzes the avalable nformaton for ths model: D * 0 D * > 0 E * 0 e =0 d =unobserved e =0, d =unobserved E * > 0 e =1 d =0 e =1, d =1 where the couple {e, d } represent the observed sample for ndvdual, e s an ndcator for college enrolment and d s an ndcator for drop out. 6
8 We also assume that {ε, η } are..d. drawn from a bvarate dstrbuton wth zero mean, varances σ 2 1 and σ 2 2 and covarance σ 12. The assocate lkelhood functon for ndvdual would be: e [ ] * 1 e * 1 d * d * (5) L = [ P ( E 0) ] * ( P ( D 0 ) e = 1) ( P ( D > 0 e = 1) ) ( P ( E > 0) ) The frst part of the expresson accounts for ndvduals who dd not enroll, whle the second takes care of unversty students that ether dropped out (frst term) or are stll enrolled at the tme of ntervew (second term). In order to estmate the above lkelhood we assumed that the {ε, η } are jontly normal. Ths way our statstcal framework represents a modfed verson of the Heckman selecton model studed by Van de Ven and Van Praag (1981). There are a varety of reasons why unobserved propensty to enroll and to contnue tertary studes mght be postvely correlated, mplyng that corr(ε,η )<0. One that has receved consderable attenton n the lterature s ablty. When not observed, dfferences n the cost each ndvdual faces when acqurng educaton, ether due to ntellectual sklls or motvaton etc., are lkely to nduce severe bases. For example, our data show that nearly all (90%) chldren to academc father attend unversty, more than twce the share of students whose father only acheved compulsory educaton (see Table1). If ablty s a relevant dmenson for selecton nto Unversty, enrolled students comng from more dsadvantaged famles would on average be more talented than ther colleagues comng from rcher famles, attenuatng the estmated mpact of parents educaton (.e. upwardbas). When X D = X E parameter dentfcaton n (5) smply rely on functonal form assumptons. When the costs of attendance are an mportant component of enrollment decsons, however, one may explot the dentfcaton power nduced by ndvduallevel varaton n those costs. Indcators of the local supply of unversty courses, capturng the fact that students grown up n an area wthout college face hgher costs of educaton, and/or the number of kds n the famly, a proxy of the resources avalable per capta gven household characterstcs are two nstruments used n the lterature (Card, 1995; Cappellar, 2003). Relyng on such sources of varaton mples assumng that all effects of drect costs, affectng the expected prvate rate of returns to unversty educaton, are antcpated and ncluded n the enrollment decson. Therefore mplct assumptons here would be that, condtonal on socoeconomc characterstcs (accountng for example for locaton choces) and early school. 7
9 performances, dropout decsons are determned by ndvdual shocks (such as an update of ther ablty, motvaton, tastes, etc.) that are unrelated to the local avalablty of Unversty courses (and/or to famlysze). Gven our sample of secondary school graduates s lkely to be nonrandom, the model above wll not allow us to recover populatonparameters. Hence, our estmates would fal to predct the consequences of polces targeted at unversty dropouts f such polces n turn affected the estmated coeffcents through compostoneffects on the sample of hghschool graduates Data descrpton Our data orgnate from a survey realzed n 2001 by the Italan Natonal Statstcal Insttute (ISTAT) on nearly ndvduals. The sample, consstng of approxmately 5% of the populaton, s representatve of students who got ther secondary school degree n 1998, and contans very detaled nformaton on ther actvty up to 2001, ther educatonal background and both famly and ndvdual characterstcs 4. The data allows n partcular trackng the whole educatonal hstory of each ndvdual, and provde a full descrpton of academc or labor market performance durng the three years after graduaton at secondary schools. Furthermore t dstngushes between students currently enrolled at Unversty, those who dropped out and those who entered the labor market. More specfcally, n our emprcal analyss we wll explot the followng nformaton contaned n the survey. Indvdual characterstcs nclude sex, age, marrage, number of sblngs and the place of resdence ths data s avalable at a very detaled (.e. muncpalty) geographcal level. Indcators of past educatonal choces and performance are the degree obtaned at the end of compulsory school (lower secondary school), the type of upper secondary school attended, the number of years taken to completon and the degree obtaned. As to famly background, whle we do not have nformaton on ncome, the data report both parents educaton (measured by years of formal educaton obtaned when the student was 14), and parents professon (wth a breakdown nto entrepreneur, professonal, hgh sklled 4 For a complete descrpton of the samplng procedure see ISTAT (2002) Percors d studo e d lavoro de dplomat. Indagne Manuale utente e traccato record avalable at 8
10 and low sklled whte collar, blue collar, no qualfcaton). We also know whether at least one of the grandparents had acheved hgher educaton. We wll combne such nformaton wth ndcators of local condtons capturng spatal dfferences n the socoeconomc envronment that mght be mportant determnants of educatonal outcomes. In partcular we ncluded the local unemployment rate n the place of resdence and a measure of the degree of urbanzaton, captured by the populaton sze of the muncpalty, both recovered from the Natonal Populaton Census (ISTAT, 2001). Table 3 presents students dstrbutons accordng to secondary school attendance, and shows that the (weghted) sample provdes a very good representaton of the populaton along these two dmensons. Accordng to our data more than 40% of students ntervewed n 2001 had obtaned a techncal school degree n 1998, and almost a thrd of the sample attended General schools ( Lce ). These numbers are very closed to the populaton dstrbuton. Fgures n Table 3 ndcate that the rate of response to the survey, conducted as a Computer Added Telephone Intervew, has not sgnfcantly affected the samplng desgn as devsed by the Natonal Statstcal Offce. However graduates partcpatng to the ntervews mght have tended to msreport ther actual choces, n partcular regardng Unversty enrollment and dropout. As regards enrollment decsons, avalable admnstratve data allows comparsons wth the populaton n terms of the rato of students enterng any tertary educaton course n the same year they obtan the degree (see Tab.4). Accordng to the Mnstry of Educaton n 1998 ths share (45.5%) was only slghtly hgher than the rato provded by our sample (44.2%). Dscussng the sample representatveness n terms of dropout rates s slghtly more complcated. Out of the 7483 students who entered tertary educaton n 1998, 1048 declared to have gven up studyng wthn the threeyear perod covered by our survey. Unfortunately, there s no drectly comparable admnstratve data reportng the dropout rate by cohort of graduates enrolled. One avalable proxy for the dropout rate s the share of students no longer enrolled n the same Unversty course by year of enrollment. (Note that ths measure, used as offcal dropout fgure by the admnstraton s lkely to overestmate the abandonment rate snce t ncludes students swtchng to a dfferent course). In the academc year 2001/02 we fnd that, relatve to students enrolled n 1998, such share amounted to 28% (Table 4). In our sample the share of 1998 graduates who left or changed unversty by summer of
11 amounts to 23%, suggestng that our wthdrawal rate s slghtly underestmated 5. There are several reasons why the dropout rate turns out to be too low n the sample. Frst, dropouts could tend to msreport. Some of them could not even declare to have ever been enrolled, explanng the slghtly lower share mentoned above. Others, though declarng to have enrolled, mght not report the abandonment. We can attempt to control for such students by analyzng consstency of answers throughout the survey. For example one mght thnk that students enrolled but havng passed no exam wthn three years from enrollment are actual (or potental) dropouts. Includng such students, the share of dropouts after three years form graduaton n the sample rses to 25%. Also, graduate students who declared to have never been enrolled after graduaton but reportng to have rejected some job offer or to have left a job to better concentrate on ther studes could plausbly be mputed to the dropout populaton, as well those male who, after three year from graduaton, have not yet joned the (compulsory) mltary servce. In ths case the share of dropouts rses to nearly 28%, n lne wth avalable admnstratve data. 6 As far as famly background s consdered, Table 5 show the sample dstrbuton by degree completed by each parent, at the tme students ntervewed were 14 years old. In nearly 50% of cases both parents had at most completed compulsory educaton (8 years of formal schoolng). Fathers are on average slghtly more educated than mothers and assortatve matng (.e. famles n whch both parents tend to have the same amount of educaton) tend to preval at low educatonal levels. Our data also ndcate that the majorty of secondary school graduates fathers were ether blue collar or employed n the retal sector, whle less than 20% were sklled or hgh sklled whte collars (ntellectual and scentfc professons, qualfed techncans, etc.). 5 Another common measure of the dropout rate s the complement to one of the success rates, obtaned by comparng the number of Unversty degrees obtaned n a partcular year wth the number of students who enrolled some (n Italy, 7) years before. Estmated ths way the drop out rate was 58.5% n A smlar fgure can be obtaned n our sample groupng those who left any tertary course wth students stll enrolled n 2001 who passed less than three exams per year. 6 Changng the outcome measure along these lnes dd not affect the results. Our preferred measure ncludes enrolled students who reported abandonment or declared to be employed fulltme at the tme of ntervew. On the other hand, ncludng among dropouts students who declared to be enrolled n a dfferent course, as n the admnstratve defnton, tends to attenuate the estmated effects. 10
12 2.3. Determnants of dropout probablty: results In ths secton we dscuss the man results from our Unversty dropout probablty model wth selecton, and compare them wth unvarate probt results. Followng the lterature on educatonal outcomes, we focus on a specfcaton ncludng ndcators of famly background, (both n terms of parents years of schoolng, grandparents educaton and father s professon), of past educatonal background and performance (the type of secondary school attended and the degrees obtaned at the end of lowerprmary, mandatory schools), and a set of ndvdual varables (sex, age, marrage status). Controls for local condtons nclude local unemployment rate and degree of urbanzaton of the muncpalty the secondary school s located n. Summary statstcs of the man varables used n the emprcal part are presented n Table 6. Column 1 n Table 7 reports the margnal effects on dropout probablty of the man varables as estmated accountng for selecton nto unversty. To ease comparson wth standard probt estmates (reported n column 3) we evaluate such effects settng all observable characterstcs at the mean of the subsample of Unversty enrolled. Results from our Tobt estmates ndcate that both famly background and educatonal background varables sgnfcantly affect wthdrawal decsons. In partcular, the dropout probablty s decreasng n father s years of formal educaton: the estmated coeffcent mples that a ten years ncrease n father s schoolng (correspondng to movng from compulsory educaton to Unversty degree) reduces the dropout probablty by 14 percentage ponts. Gven the predcted probablty at sample mean s 21%, the mpled fall of wthdrawal rsk we estmate s consderable. As our dscusson n secton 2.1 suggested the effect obtaned estmatng a standard probt regresson s substantally lower (5%). Smlar conclusons can be drawn comparng the estmated coeffcents on mother educaton. How one should nterpret the dfferences n educatonal responses by famly background s a matter of debate n the recent lterature on educatonal attanments (Card, 1999, 2001; Kane, 2001; Cameron and Heckman, 1998; Carnero and Heckman, 2002). The man concurrng explanatons are shortterm credt constrants and longterm factors fosterng cogntve and noncogntve abltes through a better learnng envronment or a hgher qualty of educaton. To dscrmnate between the two channels Cameron and Heckman (1998) 11
13 propose to estmate famlyeffects controllng for measures of early educatonal outcomes, whch should absorb longterm factors. Our estmates of szeable famlyeffects are obtaned condtonng on the degree obtaned at prmary school: f nterpreted n ths framework, then, they would pont to the exstence of shortterm credt constrants n educaton. Our results pont to a role for educatonal backgrounds, n that wthdrawal probabltes decrease movng from Vocatonal to General schools. Agan, accountng for selecton magnfes the effect that would have been nferred wthout correcton for the schooltype effect on enrollment decsons, as a consequence of the fact that the same varables have exactly the opposte effect on enrollment than they have on wthdrawal. Interpretng these coeffcents s complcated by the fact that past educatonal choces mght have nduced sortng of students (for example, by learnng abltes) nto school types. 7 To the extent that sortng based on learnng abltes s accounted for by early educatonal outcomes, our results ndcate that, for example, the predcted dropout probablty for the average Vocatonal student would reduce by more than 50% f, other thngs equal, she had obtaned a degree from a General school. Fnally, we fnd that female students have a lower dropout probablty than ther male colleagues. All other varables accountng for famlar background (grandparents educaton and father professon, not shown for brevty) and local condtons (as captured by the degrees of urbanzaton and rate of actvty n the muncpalty) do not play any sgnfcant role. As far as Unversty enrolment s concerned we fnd that, other thngs equal, enrollment probablty ncreases substantally n the educatonal attanment of both parents, wth almost dentcal coeffcents. 8 For example, the enrollment probablty of chldren born to unversty graduates s 24% hgher than t s for offsprng of lower hgh school graduates. Condtonal on parents educaton, enrollment s also strongly affected by the type of secondary school attended. The avalablty of detaled ndvdual nformaton allowed us to test robustness of these fndngs to the use of nstruments measurng tertary educaton partcpaton costs. In our exercse dentfcaton requres the antcpated costs of attendance determne the demand for educaton but do not drectly affect outcomes once observable characterstcs are taken 7 Ths would be the case f, for example, general schools attract all good students whle all bad students choose other schools and yeld upward bas estmates of schooltype coeffcents. 8 The reported margnal effects are evaluated at the secondary graduates (not just the enrolled) mean values of the observable characterstcs. 12
14 nto account. Usng data from the Statstcal Offce of the Mnstry of Unversty and Research we constructed several measures of Unversty courses avalablty at the local level. For every muncpalty n Italy we measured the dstance from the nearest Unversty and a dstanceweghted ndex of unversty and degree subjects avalable n the entre terrtory. Although n Italy Unversty tuton costs are generally low, large dstances from Unverstes mply hgher costs for households (n terms of transportaton, rents etc.). As an addtonal measure of the actual avalablty of Unversty courses we ncluded the provnceshare of unversty enrolled n 1998 over the populaton aged Second, we consdered the number of sblngs n the household. The larger the sze of the famly, the hgher the probablty that the observed student competes wthn the famly (ether due to scarce resources, or to the fact that each household attaches decreasng utlty to one extra chld enrolled, etc) and ths lowers her enrollment probablty, wthout affectng unversty outcomes. The results obtaned usng the nstrumental varables descrbed above are reported n Table 8. In columns 1 and 2 we consdered changes n the cost of enrollment nduced by geographc varaton n the avalablty of tertary educaton courses, whle n columns 3 and 4 we also accounted for the effect of dfferent famly szes. The estmated coeffcents confrm the relevance of accountng for enrollment decsons n studes on the effects of socoeconomcs status and educatonal background Explanng crosscountry attanment dfferences All commonly used ndcators of educatonal attanment pont to the exstence of large dfferences n completon rates between Italy and comparable European countres. Accordng to the OECD, for example, noncompleton rates n Europe ranged from about 20 per cent n the Unted Kngdom and Ireland to 40 per cent n Austra and France, and reached nearly 60 per cent n Italy (OECD, 2003). Whle these fgures mght represent countryspecfc 9 Approprate measurement of the dropout ndcator seems to be also mportant for the results. When ncludng among dropouts students who changed unversty course wthn the perod consdered, a defnton that s closer to the admnstratve data on wthdrawal, both estmates of famly and educatonal background coeffcents became consderably weaker. Ths suggests that the use of data assembled by sngle unverstes wth no possblty to control for spurous wthdrawals (as n Montmarquette et al. 2000) could further bas the nference aganst the exstence of famly and educatonal background effects. 13
15 equlbrum outcomes f the populaton of unversty enrolled dffered n unobservable ndvdual characterstcs as motvaton, dscount rates etc. (see Ecksten and Wolpn, 1999), our results allow us to evaluate the relevance of an alternatve explanaton based on dfferences n observables. The frst column n Table 9 reports the average years of formal educaton accumulated by parents of secondary school graduates n several European countres, computed from the 1998 ssue of the European Communty Households Panel (ECHP). Fgures for Italy are very close to those we obtaned n our sample and are lower than those of other countres. The second column reports the exstng dfferences n the secondary school graduates as to the type of school ( program orentaton ) attended accordng to OECD statstcs: Italan graduates from general schools, assocated to hgher survvor probablty than vocatonal schools, are fewer than n comparable European countres. In Table 10 we report the changes n the OECD fgures for dropout rate (defned as the share of unversty enrolled havng abandoned before the ffth year) and survvor rates (the rato of survvors at the ffth year relatve to the populaton n the relevant age cohort), computed combnng these data wth our estmates. Specfcally, column 1 shows the dropout rate obtaned attrbutng Italan secondary school graduates foregn famly backgrounds as reported n table The estmated reducton n wthdrawal ranges from 2 to 9.3 percent, leavng the average observed gap above 20 percentage ponts. In column 2 we apply a smlar procedure to calculate the effect of a change n the rato of secondary school graduates from general schools to populaton (correspondngly lowerng the shares n other schools) to other countres level. The mpled reducton n wthdrawal rate ranges from 0.5 to less than 5 percentage ponts. Combnng both exercses would nduce reductons of the dropout rates rangng from about 3 to 10.3%. The dfference n wthdrawal rate would n the best case scenaro (France) stll be as large as 19%. The mpact on the survvor rate s computed smlarly but account for the effects of changes n the observable varables on enrollment rates. Results showed n columns 5 to 7 ndcate the rato of ffthyear enrolled students to populaton could n the best case 10 Gven our estmates refer to the contnuaton probablty at the thrd year, whle OECD drop out and survvor rates are computed at the ffth year the estmated effect had to be extrapolated. Detals are reported n the note to the table. 14
16 (UK, both exercses combned) ncrease by 9 percentage ponts. It would be stll more than 30 ponts below the actual survvor rate n the Unted Kngdom, however. 11 We are unfortunately unable to assess to what extent changes n the sample composton as to famly and educatonal backgrounds could affect the smulated attanments rates through changes n the estmated coeffcents. However, the magntude of the unexplaned dfferental n attanments suggests the role played by countryspecfc characterstcs n explanng productvty dfferences should be extremely relevant. 12 One such characterstc, one that motvated recent reforms of the unversty system, s the lmted supply of tertary TypeB (.e. three year) courses wth respect to other countres. 13 Alternatvely, the populaton of Italan students mght dffer as to unobservable characterstcs affectng the opportunty cost of attendance, as motvaton, dscount rates or outsde opportuntes. In ths case a hgher fracton of the enrolled would be wllng to wthdraw as they receve offers from the labor market. Fnally, Italan students mght be relatvely more. 4. Conclusons We explot a survey conducted on a representatve sample of Italan hgh school graduates to study the determnants of unversty dropout accountng for enrollmentnduced selecton. Contrary to recent emprcal work focusng on samples of unversty enrolled, our results ndcate dfferences n background ndvdual characterstcs, and n partcular n famly characterstcs, play a determnant role n explanng wthdrawal. Comparng our results wth those obtaned wth standard unvarate analyss allowed us to determne the bas 11 Snce n our estmatons survvor rates are obtaned relatve to the populaton of secondary school graduates, as opposed to the entre populaton cohort used by OECD, here we need to assume that the rato of Secondary School graduates to the relevant populaton cohort s constant, that s t does not change wth famly background. An alternatve would be to report the smulated ratos of Survvors to Secondary School graduates, but ths s not a commonly used OECD fgure. 12 Interestngly, recent estmates of the returns to nvestng n tertary educaton by Cccone et al. (2004) suggest that dfferences n the expected economc gans from unversty attendance should not play a major role ether. In year 2000 the prvate returns to unversty educaton, calculated as the dscount rate that equates the present value of the addtonal costs of attendance to the present value of the stream of netoftax earnngs generated by an ncrease n educaton, n Italy was above 10%, broadly n lne wth returns n Germany, France and Span (and much larger than the returns to alternatve nvestment). 13 Note, however, that the dropout rate n Italy s not much lower n short than longterm courses (49 as opposed to 58 per cent accordng to OECD data). Smple calculatons obtaned redstrbutng students across ISCED type A and B courses as n reference countres show the drop out rate would reduce by at most 3.4%. 15
17 nduced by sample selecton s substantal. Despte beng large, however, background condtons do not seem to be able to explan why the dropout rate n Italy s so hgher than n comparable countres. In terms of polcy, our analyss confrms the strong concerns regardng the ablty of the Italan educatonal system to promote socal coheson va equal educatonal opportuntes. It suggests the role of famlar background manly reflects shortterm fnancal constrants rather than long term effect shapng offsprng ablty at early ages. Fnally, t ndcates that large dfferences n unversty completon rates mght persst wth respect to other countres even f educatonal attanments n the populaton converged. We are unfortunately unable to assess the relevance of alternatve explanatons ncludng dfferences n ndvdual unobservables determnng students attachment, whch would requre ncreasng selectvty (rasng tutons, selecton at entry, etc.), or hgher exposure to adverse unantcpated shocks due to lower access to (ether publc or prvate) credt. 16
18 References Amemya T. (1985), Advanced Econometrcs, Harvard Unversty Press, Cambrdge, Massachusetts. Arulampalam, W., R. A. Naylor and J. Smth (2001), A Hazard Model of the Probablty of Medcal School Dropout n the Unted Kngdom, IZA Dscusson Papers 333, Insttute for the Study of Labor (IZA) Cameron, S. and J. Heckman (1998) Lfe Cycle Schoolng and Dynamc Selecton Bas: Models and Evdence for Fve Cohorts of Amercan Males. JPE, vol. 106, no. 2 Cappellar, L. (2003) The effects of hgh school choces on academc performance and early labour market outcomes, Quadern dell Isttuto d economa dell mpresa e del lavoro, Unverstà cattolca, Mlano. Card D. (1995) Usng Geographc varaton n College Proxmty to Estmate the Returns to Schoolng, n Aspect of Labor Market Behavor: essays n Honor of John Vanderkamp, ed. by Chrstofdes, L., Grant, E. and R. Swdnsky. Toronto: Unversty of Toronto Press. Card, D. (1999) The causal effect of educaton on earnngs, n (O. Ashenfelter, and D. Card, eds.), Handbook of Labor Economcs, Vol 3A. Amsterdam: Elsever Scence, North Holland, pp Card, D. (2001) Estmatng the return to schoolng: progress on some persstent econometrc problems, Econometrca, vol. 69(5), pp Carnero, P. and J. Heckman (2002) The Evdence on Credt Constrants n Postsecondary Schoolng. Economc Journal 112, no.482: Cccone A., F. Cngano and P. Cpollone (2004) The prvate and socal returns to schoolng n Italy, Gornale degl Economst, vol.63  n.3/4 Ecksten Z. and K. Wolpn (1999) Why Youth Dropout of Hgh school. The mpact of preferences, opportuntes and abltes, Econometrca Vol. 67, no.6 ISTAT (2002) Percors d studo e d lavoro de dplomat. Indagne 2001, avalable at ISTAT (2001) 14 Censmento della popolazone e delle abtazon (2001),, avalable at Jackobsen V. and M. Rosholm (2003), Droppng out of school? A competng rsk Analyss of Young Immgrants Progress n the Educatonal System, IZA Dscusson paper No
19 Johnes G. and R. McNabb (2004) Never Gve up on the Good Tmes: Student Attrton n the UK Oxford Bulletn of Economcs and Statstcs, Volume 66, Number 1, pp (25) Kane, T. (2001). Collegegong and nequalty: a lterature revew, workng paper, Russell Sage Foundaton. Keane, M. and K. Wolpn 1997 The Career Decsons of Young Men, Journal of Poltcal Economy, Unversty of Chcago Press, vol. 105(3), pages , June. Mare, R. D. (1980), Socal Background and School Contnuaton Decsons. Journal of The Amercan Statstcal Assocaton 75: Montmarquette C., S. Mahseredjan and R. Houle (2001): The determnants of Unversty Dropouts: a bvarate probablty model wth sample selecton, Economcs of Educaton Revew, Elsever, vol. 20(5), pages , October. OECD (2003), Educaton at glance. OECD Indcators 2002, Pars, France Naylor R. and J. Smth (2001): Droppng out of unversty: a statstcal analyss of the probablty to wthdrawal for UK unversty students, Journal of Royal Statstcal Socety.164 (part 2), pp Van de Ven W. and B. Van Praag (1981) The Demand for Deductbles n Prvate Health Insurance, Journal of Econometrcs, 17, pp Wlls, R. and S. Rosen (1979). Educaton and selfselecton, Journal of Poltcal Economy, vol. 87(5), pp. S7 36. Shavt Y. and H. Blossfeld (1993) Persstng barrers. A comparatve study of educatonal unequalty n thrteen countres, Westvew Press, Boulder (CO). 18
20 Enrollment rates by father schoolng (percentage ponts) Table 1 No degree Prmary school (5 years) Father schoolng Junor hgh school (8 years) Professonal dploma (10 years) Hgh school (13 years) College (18 years) All Not enrolled Enrolled Total Source: Istat (2002) Percors d studo e d lavoro de dplomat. Indagne Populatonweghted percentages Enrollment rates by type of secondary school (percentage ponts) Table 2 Type of school Enrolled Not Enrolled TOTAL Vocatonal schools Techncal schools Other schools Lce TOTAL Source: Istat (2002) Percors d studo e d lavoro de dplomat. Indagne Populatonweghted percentages 19
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