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


 Edwina Caldwell
 1 years ago
 Views:
Transcription
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
Can Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? ChuShu L Department of Internatonal Busness, Asa Unversty, Tawan ShengChang
More informationAn Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
More informationMarginal Returns to Education For Teachers
The Onlne Journal of New Horzons n Educaton Volume 4, Issue 3 MargnalReturnstoEducatonForTeachers RamleeIsmal,MarnahAwang ABSTRACT FacultyofManagementand Economcs UnverstPenddkanSultan Idrs ramlee@fpe.ups.edu.my
More informationPRIVATE SCHOOL CHOICE: THE EFFECTS OF RELIGIOUS AFFILIATION AND PARTICIPATION
PRIVATE SCHOOL CHOICE: THE EFFECTS OF RELIIOUS AFFILIATION AND PARTICIPATION Danny CohenZada Department of Economcs, Benuron Unversty, BeerSheva 84105, Israel Wllam Sander Department of Economcs, DePaul
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationAnswer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 MultpleChoce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multplechoce questons. For each queston, only one of the answers s correct.
More informationHOUSEHOLDS DEBT BURDEN: AN ANALYSIS BASED ON MICROECONOMIC DATA*
HOUSEHOLDS DEBT BURDEN: AN ANALYSIS BASED ON MICROECONOMIC DATA* Luísa Farnha** 1. INTRODUCTION The rapd growth n Portuguese households ndebtedness n the past few years ncreased the concerns that debt
More informationInequality and The Accounting Period. Quentin Wodon and Shlomo Yitzhaki. World Bank and Hebrew University. September 2001.
Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.
More informationStaff Paper. Farm Savings Accounts: Examining Income Variability, Eligibility, and Benefits. Brent Gloy, Eddy LaDue, and Charles Cuykendall
SP 200502 August 2005 Staff Paper Department of Appled Economcs and Management Cornell Unversty, Ithaca, New York 148537801 USA Farm Savngs Accounts: Examnng Income Varablty, Elgblty, and Benefts Brent
More informationReturns to Experience in Mozambique: A Nonparametric Regression Approach
Returns to Experence n Mozambque: A Nonparametrc Regresson Approach Joel Muzma Conference Paper nº 27 Conferênca Inaugural do IESE Desafos para a nvestgação socal e económca em Moçambque 19 de Setembro
More informationThe Current Employment Statistics (CES) survey,
Busness Brths and Deaths Impact of busness brths and deaths n the payroll survey The CES probabltybased sample redesgn accounts for most busness brth employment through the mputaton of busness deaths,
More information! # %& ( ) +,../ 0 1 2 3 4 0 4 # 5##&.6 7% 8 # 0 4 2 #...
! # %& ( ) +,../ 0 1 2 3 4 0 4 # 5##&.6 7% 8 # 0 4 2 #... 9 Sheffeld Economc Research Paper Seres SERP Number: 2011010 ISSN 17498368 Sarah Brown, Aurora OrtzNúñez and Karl Taylor Educatonal loans and
More informationTHE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek
HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo
More informationData Mining from the Information Systems: Performance Indicators at Masaryk University in Brno
Data Mnng from the Informaton Systems: Performance Indcators at Masaryk Unversty n Brno Mkuláš Bek EUA Workshop Strasbourg, 12 December 2006 1 Locaton of Brno Brno EUA Workshop Strasbourg, 12 December
More informationCulture and the Family: An Application to Educational Choices in Italy
Culture and the Famly: An Applcaton to Educatonal Choces n Italy Saggo ad Invto per la Rvsta d Poltca Economca July 2009 Paola Gulano UCLA, NBER, and IZA Abstract In ths essay we revew the assocaton between
More informationHeterogeneous Paths Through College: Detailed Patterns and Relationships with Graduation and Earnings
Heterogeneous Paths Through College: Detaled Patterns and Relatonshps wth Graduaton and Earnngs Rodney J. Andrews The Unversty of Texas at Dallas and the Texas Schools Project Jng L The Unversty of Tulsa
More informationGender differences in revealed risk taking: evidence from mutual fund investors
Economcs Letters 76 (2002) 151 158 www.elsever.com/ locate/ econbase Gender dfferences n revealed rsk takng: evdence from mutual fund nvestors a b c, * Peggy D. Dwyer, James H. Glkeson, John A. Lst a Unversty
More informationSearching and Switching: Empirical estimates of consumer behaviour in regulated markets
Searchng and Swtchng: Emprcal estmates of consumer behavour n regulated markets Catherne Waddams Prce Centre for Competton Polcy, Unversty of East Angla Catherne Webster Centre for Competton Polcy, Unversty
More informationMilitary Conscription and University Enrolment: Evidence from Italy
DISCUSSION PAPER SERIES IZA DP No. 4212 Mltary Conscrpton and Unversty Enrolment: Evdence from Italy Gorgo D Petro June 2009 Forschungsnsttut zur Zukunft der Arbet Insttute for the Study of Labor Mltary
More informationDEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMISP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
More informationDoes Higher Education Enhance Migration?
DISCUSSION PAPER SERIES IZA DP No. 7754 Does Hgher Educaton Enhance Mgraton? Mka Haapanen Petr Böckerman November 2013 Forschungsnsttut zur Zukunft der Arbet Insttute for the Study of Labor Does Hgher
More informationMarginal Benefit Incidence Analysis Using a Single Crosssection of Data. Mohamed Ihsan Ajwad and Quentin Wodon 1. World Bank.
Margnal Beneft Incdence Analyss Usng a Sngle Crosssecton of Data Mohamed Ihsan Ajwad and uentn Wodon World Bank August 200 Abstract In a recent paper, Lanjouw and Ravallon proposed an attractve and smple
More informationManagement Quality, Financial and Investment Policies, and. Asymmetric Information
Management Qualty, Fnancal and Investment Polces, and Asymmetrc Informaton Thomas J. Chemmanur * Imants Paegls ** and Karen Smonyan *** Current verson: December 2007 * Professor of Fnance, Carroll School
More informationAnalysis of Premium Liabilities for Australian Lines of Business
Summary of Analyss of Premum Labltes for Australan Lnes of Busness Emly Tao Honours Research Paper, The Unversty of Melbourne Emly Tao Acknowledgements I am grateful to the Australan Prudental Regulaton
More informationADVERSE SELECTION IN INSURANCE MARKETS: POLICYHOLDER EVIDENCE FROM THE U.K. ANNUITY MARKET *
ADVERSE SELECTION IN INSURANCE MARKETS: POLICYHOLDER EVIDENCE FROM THE U.K. ANNUITY MARKET * Amy Fnkelsten Harvard Unversty and NBER James Poterba MIT and NBER * We are grateful to Jeffrey Brown, PerreAndre
More informationThe Effects of Tax Rate Changes on Tax Bases and the Marginal Cost of Public Funds for Canadian Provincial Governments
The Effects of Tax Rate Changes on Tax Bases and the Margnal Cost of Publc Funds for Canadan Provncal Governments Bev Dahlby a and Ergete Ferede b a Department of Economcs, Unversty of Alberta, Edmonton,
More informationCalculation of Sampling Weights
Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a twostage stratfed cluster desgn. 1 The frst stage conssted of a sample
More informationStructural Estimation of Variety Gains from Trade Integration in a Heterogeneous Firms Framework
Journal of Economcs and Econometrcs Vol. 55, No.2, 202 pp. 7893 SSN 20329652 ESSN 20329660 Structural Estmaton of Varety Gans from Trade ntegraton n a Heterogeneous Frms Framework VCTOR RVAS ABSTRACT
More informationKiel Institute for World Economics Duesternbrooker Weg 120 24105 Kiel (Germany) Kiel Working Paper No. 1120
Kel Insttute for World Economcs Duesternbrooker Weg 45 Kel (Germany) Kel Workng Paper No. Path Dependences n enture Captal Markets by Andrea Schertler July The responsblty for the contents of the workng
More informationSection 5.4 Annuities, Present Value, and Amortization
Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today
More informationThe program for the Bachelor degrees shall extend over three years of fulltime study or the parttime equivalent.
Bachel of Commerce Bachel of Commerce (Accountng) Bachel of Commerce (Cpate Fnance) Bachel of Commerce (Internatonal Busness) Bachel of Commerce (Management) Bachel of Commerce (Marketng) These Program
More informationManagement Quality and Equity Issue Characteristics: A Comparison of SEOs and IPOs
Management Qualty and Equty Issue Characterstcs: A Comparson of SEOs and IPOs Thomas J. Chemmanur * Imants Paegls ** and Karen Smonyan *** Current verson: November 2009 (Accepted, Fnancal Management, February
More informationScale Dependence of Overconfidence in Stock Market Volatility Forecasts
Scale Dependence of Overconfdence n Stoc Maret Volatlty Forecasts Marus Glaser, Thomas Langer, Jens Reynders, Martn Weber* June 7, 007 Abstract In ths study, we analyze whether volatlty forecasts (judgmental
More informationCriminal Justice System on Crime *
On the Impact of the NSW Crmnal Justce System on Crme * Dr Vasls Sarafds, Dscplne of Operatons Management and Econometrcs Unversty of Sydney * Ths presentaton s based on jont work wth Rchard Kelaher 1
More informationThe Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk
The Cross Secton of Foregn Currency Rsk Prema and Consumpton Growth Rsk By HANNO LUSTIG AND ADRIEN VERDELHAN* Aggregate consumpton growth rsk explans why low nterest rate currences do not apprecate as
More informationTuition Fee Loan application notes
Tuton Fee Loan applcaton notes for new parttme EU students 2012/13 About these notes These notes should be read along wth your Tuton Fee Loan applcaton form. The notes are splt nto three parts: Part 1
More informationWage inequality and returns to schooling in Europe: a semiparametric approach using EUSILC data
MPRA Munch Personal RePEc Archve Wage nequalty and returns to schoolng n Europe: a semparametrc approach usng EUSILC data Marco Bagett and Sergo Sccchtano Unversty La Sapenza Rome, Mnstry of Economc
More informationBank Credit Conditions and their Influence on Productivity Growth: Companylevel Evidence
Bank Credt Condtons and ther Influence on Productvty Growth: Companylevel Evdence Rebecca Rley*, Chara Rosazza Bondbene* and Garry Young** *Natonal Insttute of Economc and Socal Research & Centre For
More informationA Multistage Model of Loans and the Role of Relationships
A Multstage Model of Loans and the Role of Relatonshps Sugato Chakravarty, Purdue Unversty, and Tansel Ylmazer, Purdue Unversty Abstract The goal of ths paper s to further our understandng of how relatonshps
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract  Stock market s one of the most complcated systems
More informationDo Banks Use Private Information from Consumer Accounts? Evidence of Relationship Lending in Credit Card Interest Rate Heterogeneity
Do Banks Use Prvate Informaton from Consumer Accounts? Evdence of Relatonshp Lendng n Credt Card Interest Rate Heterogenety Sougata Kerr, Stephen Cosslett, Luca Dunn December, 2004 Author nformaton: Kerr,
More informationGeneral or Vocational? Evidence on School Choice, Returns, and Sheep Skin Effects from Egypt 1998
Twentyffth Annual Meetng of The Mddle East Economc Assocaton (MEEA) Alled Socal Scence Assocatons Phladelpha, Pennsylvana January 79, 2005 General or Vocatonal? Evdence on School Choce, Returns, and
More informationEducation and Family Income
Prelmnary: Comments Welcome Educaton and Famly Income Jo Blanden*, Paul Gregg** and Stephen Machn* May 2002 * Department of Economcs, Unversty College London and Centre for Economc Performance, London
More informationLIFETIME INCOME OPTIONS
LIFETIME INCOME OPTIONS May 2011 by: Marca S. Wagner, Esq. The Wagner Law Group A Professonal Corporaton 99 Summer Street, 13 th Floor Boston, MA 02110 Tel: (617) 3575200 Fax: (617) 3575250 www.ersalawyers.com
More informationThe covariance is the two variable analog to the variance. The formula for the covariance between two variables is
Regresson Lectures So far we have talked only about statstcs that descrbe one varable. What we are gong to be dscussng for much of the remander of the course s relatonshps between two or more varables.
More informationAn Empirical Study of Search Engine Advertising Effectiveness
An Emprcal Study of Search Engne Advertsng Effectveness Sanjog Msra, Smon School of Busness Unversty of Rochester Edeal Pnker, Smon School of Busness Unversty of Rochester Alan RmmKaufman, RmmKaufman
More informationFixed income risk attribution
5 Fxed ncome rsk attrbuton Chthra Krshnamurth RskMetrcs Group chthra.krshnamurth@rskmetrcs.com We compare the rsk of the actve portfolo wth that of the benchmark and segment the dfference between the two
More informationCausal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes causeandeffect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
More informationMultiplePeriod Attribution: Residuals and Compounding
MultplePerod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens
More informationCambodian Child s Wage Rate, Human Capital and Hours Worked Tradeoff: Simple Theoretical and Empirical Evidence for Policy Implications
GSIS Workng Paper Seres ambodan hld s Wage Rate, Human aptal and Hours Worked Tradeoff: Smple Theoretcal and Emprcal Evdence for Polcy Implcatons Han PHOUMIN Sech FUKUI No. 6 August 2006 Graduate School
More informationWORKING PAPER. C.D. Howe Institute. The Effects of Tax Rate Changes on Tax Bases and the Marginal Cost of Public Funds for Provincial Governments
MARCH 211 C.D. Howe Insttute WORKING PAPER FISCAL AND TAX COMPETITIVENESS The Effects of Tax Rate Changes on Tax Bases and the Margnal Cost of Publc Funds for Provncal Governments Bev Dahlby Ergete Ferede
More informationIntrayear Cash Flow Patterns: A Simple Solution for an Unnecessary Appraisal Error
Intrayear Cash Flow Patterns: A Smple Soluton for an Unnecessary Apprasal Error By C. Donald Wggns (Professor of Accountng and Fnance, the Unversty of North Florda), B. Perry Woodsde (Assocate Professor
More informationWhy Do Cities Matter? Local Growth and Aggregate Growth
Why Do Ctes Matter? Local Growth and Aggregate Growth ChangTa Hseh Unversty of Chcago Enrco Morett Unversty of Calforna, Berkeley Aprl 2015 Abstract. We study how growth of ctes determnes the growth of
More informationTraditional versus Online Courses, Efforts, and Learning Performance
Tradtonal versus Onlne Courses, Efforts, and Learnng Performance KuangCheng Tseng, Department of Internatonal Trade, ChungYuan Chrstan Unversty, Tawan ShanYng Chu, Department of Internatonal Trade,
More informationThe impact of hard discount control mechanism on the discount volatility of UK closedend funds
Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 Ahmed F. Salhn (Egypt) The mpact of hard dscount control mechansm on the dscount volatlty of UK closedend funds Abstract The mpact
More informationMacro Factors and Volatility of Treasury Bond Returns
Macro Factors and Volatlty of Treasury Bond Returns Jngzh Huang Department of Fnance Smeal Colleage of Busness Pennsylvana State Unversty Unversty Park, PA 16802, U.S.A. Le Lu School of Fnance Shangha
More informationProceedings of the Annual Meeting of the American Statistical Association, August 59, 2001
Proceedngs of the Annual Meetng of the Amercan Statstcal Assocaton, August 59, 2001 LISTASSISTED SAMPLING: THE EFFECT OF TELEPHONE SYSTEM CHANGES ON DESIGN 1 Clyde Tucker, Bureau of Labor Statstcs James
More informationANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 6105194390,
More informationUsing Series to Analyze Financial Situations: Present Value
2.8 Usng Seres to Analyze Fnancal Stuatons: Present Value In the prevous secton, you learned how to calculate the amount, or future value, of an ordnary smple annuty. The amount s the sum of the accumulated
More informationSolution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt.
Chapter 9 Revew problems 9.1 Interest rate measurement Example 9.1. Fund A accumulates at a smple nterest rate of 10%. Fund B accumulates at a smple dscount rate of 5%. Fnd the pont n tme at whch the forces
More informationLecture 3: Force of Interest, Real Interest Rate, Annuity
Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annutymmedate, and ts present value Study annutydue, and
More informationAn Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services
An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsnyng Wu b a Professor (Management Scence), Natonal Chao
More informationWhen Talk is Free : The Effect of Tariff Structure on Usage under Two and ThreePart Tariffs
0 When Talk s Free : The Effect of Tarff Structure on Usage under Two and ThreePart Tarffs Eva Ascarza Ana Lambrecht Naufel Vlcassm July 2012 (Forthcomng at Journal of Marketng Research) Eva Ascarza
More informationUNIVERSITA CATTOLICA DEL SACRO CUORE  Milano  QUADERNI DELL ISTITUTO DI ECONOMIA DELL IMPRESA E DEL LAVORO
UNIVERSITA CATTOLICA DEL SACRO CUORE  Mlano  QUADERNI DELL ISTITUTO DI ECONOMIA DELL IMPRESA E DEL LAVORO The Wage Effect of Workng n the Publc Sector When Educaton and Sector Choces Are Endogenous:
More informationTo manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.
Corporate Polces & Procedures Human Resources  Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:
More informationADVERSE SELECTION IN INSURANCE MARKETS: POLICYHOLDER EVIDENCE FROM THE U.K. ANNUITY MARKET
ADVERSE SELECTION IN INSURANCE MARKETS: POLICYHOLDER EVIDENCE FROM THE U.K. ANNUITY MARKET Amy Fnkelsten Harvard Unversty and NBER James Poterba MIT and NBER Revsed May 2003 ABSTRACT In ths paper, we nvestgate
More information17 Capital tax competition
17 Captal tax competton 17.1 Introducton Governments would lke to tax a varety of transactons that ncreasngly appear to be moble across jursdctonal boundares. Ths creates one obvous problem: tax base flght.
More informationThe Application of Fractional Brownian Motion in Option Pricing
Vol. 0, No. (05), pp. 738 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qngxn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com
More informationProblem Set 3. a) We are asked how people will react, if the interest rate i on bonds is negative.
Queston roblem Set 3 a) We are asked how people wll react, f the nterest rate on bonds s negatve. When
More informationBeating the Odds: Arbitrage and Wining Strategies in the Football Betting Market
Beatng the Odds: Arbtrage and Wnng Strateges n the Football Bettng Market NIKOLAOS VLASTAKIS, GEORGE DOTSIS and RAPHAEL N. MARKELLOS* ABSTRACT We examne the potental for generatng postve returns from wagerng
More informationChapter 11 Practice Problems Answers
Chapter 11 Practce Problems Answers 1. Would you be more wllng to lend to a frend f she put all of her lfe savngs nto her busness than you would f she had not done so? Why? Ths problem s ntended to make
More informationTHE DETERMINANTS OF THE TUNISIAN BANKING INDUSTRY PROFITABILITY: PANEL EVIDENCE
THE DETERMINANTS OF THE TUNISIAN BANKING INDUSTRY PROFITABILITY: PANEL EVIDENCE Samy Ben Naceur ERF Research Fellow Department of Fnance Unversté Lbre de Tuns Avenue Khéreddne Pacha, 002 Tuns Emal : sbennaceur@eudoramal.com
More informationDO LOSS FIRMS MANAGE EARNINGS AROUND SEASONED EQUITY OFFERINGS?
DO LOSS FIRMS MANAGE EARNINGS AROUND SEASONED EQUITY OFFERINGS? Fernando Comran, Unversty of San Francsco, School of Management, 2130 Fulton Street, CA 94117, Unted States, fcomran@usfca.edu Tatana Fedyk,
More informationCHAPTER 14 MORE ABOUT REGRESSION
CHAPTER 14 MORE ABOUT REGRESSION We learned n Chapter 5 that often a straght lne descrbes the pattern of a relatonshp between two quanttatve varables. For nstance, n Example 5.1 we explored the relatonshp
More informationMERGERS AND ACQUISITIONS IN THE SPANISH BANKING INDUSTRY: SOME EMPIRICAL EVIDENCE
MERGERS AN ACQUISITIONS IN THE SPANISH BANKING INUSTRY: SOME EMPIRICA EVIENCE Ignaco Fuentes and Teresa Sastre Banco de España Banco de España Servco de Estudos ocumento de Trabajo n.º 9924 MERGERS AN
More informationUsing an Ordered Probit Regression Model to Assess the Performance of Real Estate Brokers
Usng an Ordered Probt Regresson Model to Assess the Performance of Real Estate Brokers ChunChang Lee, Department of Real Estate Management, Natonal Pngtung Insttute of Commerce, Tawan ShuMan You, Department
More informationFinancial Instability and Life Insurance Demand + Mahito Okura *
Fnancal Instablty and Lfe Insurance Demand + Mahto Okura * Norhro Kasuga ** Abstract Ths paper estmates prvate lfe nsurance and Kampo demand functons usng householdlevel data provded by the Postal Servces
More informationwww.gov.uk/studentfinance 2016/17
www.gov.uk/studentfnance SECTION 1 WHAT SUPPORT CAN YOU GET? FEES, LOANS, GRANTS & MORE *Fgures shown n ths secton are based on the 2015/16 student fnance polcy and may change SECTION 1 TUITION FEES AND
More informationKiel Institute for World Economics Duesternbrooker Weg 120 24105 Kiel (Germany) Kiel Working Paper No. 1119
Kel Insttute for World Economcs Duesternbrooker Weg 120 24105 Kel (Germany) Kel Workng Paper No. 1119 Under What Condtons Do Venture Captal Markets Emerge? by Andrea Schertler July 2002 The responsblty
More informationStatistical Methods to Develop Rating Models
Statstcal Methods to Develop Ratng Models [Evelyn Hayden and Danel Porath, Österrechsche Natonalbank and Unversty of Appled Scences at Manz] Source: The Basel II Rsk Parameters Estmaton, Valdaton, and
More informationInstitute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
More informationCahiers de la Chaire Santé
Cahers de la Chare Santé The nfluence of supplementary health nsurance on swtchng behavour: evdence from Swss data Auteurs : Brgtte Dormont, PerreYves Geoffard, Karne Lamraud N 4  Janver 2010 1 The nfluence
More informationClassification errors and permanent disability benefits in Spain
1 Classfcaton errors and permanent dsablty benefts n Span Serg JménezMartín José M. Labeaga Crstna Vlaplana Preto 1. Introducton There s a controverted debate about the effects of permanent dsablty benefts
More informationThe OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
More informationTransition Matrix Models of Consumer Credit Ratings
Transton Matrx Models of Consumer Credt Ratngs Abstract Although the corporate credt rsk lterature has many studes modellng the change n the credt rsk of corporate bonds over tme, there s far less analyss
More informationWORKING PAPER SERIES TAKING STOCK: MONETARY POLICY TRANSMISSION TO EQUITY MARKETS NO. 354 / MAY 2004. by Michael Ehrmann and Marcel Fratzscher
WORKING PAPER SERIES NO. 354 / MAY 2004 TAKING STOCK: MONETARY POLICY TRANSMISSION TO EQUITY MARKETS by Mchael Ehrmann and Marcel Fratzscher WORKING PAPER SERIES NO. 354 / MAY 2004 TAKING STOCK: MONETARY
More informationThe Analysis of Outliers in Statistical Data
THALES Project No. xxxx The Analyss of Outlers n Statstcal Data Research Team Chrysses Caron, Assocate Professor (P.I.) Vaslk Karot, Doctoral canddate Polychrons Economou, Chrstna Perrakou, Postgraduate
More informationStart me up: The Effectiveness of a SelfEmployment Programme for Needy Unemployed People in Germany*
Start me up: The Effectveness of a SelfEmployment Programme for Needy Unemployed People n Germany* Joachm Wolff Anton Nvorozhkn Date: 22/10/2008 Abstract In recent years actvaton of meanstested unemployment
More informationHealth Insurance and Household Savings
Health Insurance and Household Savngs Mnchung Hsu Job Market Paper Last Updated: November, 2006 Abstract Recent emprcal studes have documented a puzzlng pattern of household savngs n the U.S.: households
More informationThe Development of Web Log Mining Based on ImproveKMeans Clustering Analysis
The Development of Web Log Mnng Based on ImproveKMeans Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationIs the home bias in equities and bonds declining in Europe?
Drk Schoenmaker (Netherlands), Thjs Bosch (Netherlands) Is the home bas n equtes and bonds declnng n Europe? Abstract Fnance theory suggests that nvestors should hold an nternatonally dversfed portfolo.
More informationHigh Correlation between Net Promoter Score and the Development of Consumers' Willingness to Pay (Empirical Evidence from European Mobile Markets)
Hgh Correlaton between et Promoter Score and the Development of Consumers' Wllngness to Pay (Emprcal Evdence from European Moble Marets Ths paper shows that the correlaton between the et Promoter Score
More informationCourse outline. Financial Time Series Analysis. Overview. Data analysis. Predictive signal. Trading strategy
Fnancal Tme Seres Analyss Patrck McSharry patrck@mcsharry.net www.mcsharry.net Trnty Term 2014 Mathematcal Insttute Unversty of Oxford Course outlne 1. Data analyss, probablty, correlatons, vsualsaton
More informationHARVARD John M. Olin Center for Law, Economics, and Business
HARVARD John M. Oln Center for Law, Economcs, and Busness ISSN 10456333 ASYMMETRIC INFORMATION AND LEARNING IN THE AUTOMOBILE INSURANCE MARKET Alma Cohen Dscusson Paper No. 371 6/2002 Harvard Law School
More informationCovariatebased pricing of automobile insurance
Insurance Markets and Companes: Analyses and Actuaral Computatons, Volume 1, Issue 2, 2010 José Antono Ordaz (Span), María del Carmen Melgar (Span) Covaratebased prcng of automoble nsurance Abstract Ths
More informationHot and easy in Florida: The case of economics professors
Research n Hgher Educaton Journal Abstract Hot and easy n Florda: The case of economcs professors Olver Schnusenberg The Unversty of North Florda Cheryl Froehlch The Unversty of North Florda We nvestgate
More informationCONSUMER LINES OF CREDIT: THE CHOICE BETWEEN CREDIT CARDS AND HELOCS. In the U.S. today consumers have a choice of two major types of lines of credit
CONSUMER LINES OF CREDIT: THE CHOICE BETWEEN CREDIT CARDS AND HELOCS OSU Economcs Workng Paper WP0404 I. INTRODUCTION In the U.S. today consumers have a choce of two major types of lnes of credt credt
More informationNumber of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000
Problem Set 5 Solutons 1 MIT s consderng buldng a new car park near Kendall Square. o unversty funds are avalable (overhead rates are under pressure and the new faclty would have to pay for tself from
More informationLocation Factors for NonFerrous Exploration Investments
Locaton Factors for NonFerrous Exploraton Investments Irna Khndanova Unversty of Denver Ths paper analyzes the relatve mportance of geologcal potental and nvestment clmate for nonferrous mnerals exploraton
More informationThe influence of supplementary health insurance on switching behaviour: evidence on Swiss data
Workng Paper n 0702 The nfluence of supplementary health nsurance on swtchng behavour: evdence on Swss data Brgtte Dormont, Perre Yves Geoffard, Karne Lamraud The nfluence of supplementary health nsurance
More information