Differential Grading Standards and University Funding: Evidence from Italy
* Universidad Carlos III, e-mail: mfbagues{at}emp.uc3m.es
IMT Lucca Institute for Advanced Studies, e-mail: m.syloslabini{at}imtlucca.it
BETA at University of Strasbourg and FEDEA, e-mail: nzinovyeva{at}fedea.es
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Abstract |
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 Top Abstract 1 Introduction2 Background3 Data4 Empirical analysis5 ConclusionReferences |
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This article documents that grades vary significantly across Italian public universities and degrees. We provide evidence suggesting that these differences reflect the heterogeneity of grading standards. A straightforward implication of this result is that university funding schemes based on students' academic performance do not necessary favour universities that generate higher value added. We test this for the case of the Italian funds allocation system, which rewards universities according to the number of exams passed by their students. We find that university departments that rank higher according to this indicator actually tend to be significantly worse in terms of their graduates' performance in the labour market. (JEL codes: I2, J31, J64)
Key Words: Higher education • grading standards.
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1 Introduction |
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TopAbstract1 Introduction2 Background3 Data4 Empirical analysis5 ConclusionReferences |
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In a number of European countries—including Italy, Spain and France—university grading standards are presumed to be similar across institutions. This presumption justifies the legal value that is typically given to university titles and explains why public funding of universities is increasingly related to the number of diplomas or grade points assigned by universities.
This article empirically investigates the existence of differences in grades and grading standards across Italian universities. It exploits three editions of a survey run on a representative sample of Italian graduates. The survey contains information about graduates' academic and labour market performance, as well as a large set of individual characteristics, including high-school grade, province of origin and various measures of family background. Conditional on this extensive set of controls, we find that grades vary considerably across universities and disciplines. Evidence from graduates' labour market performance and post-university external professional qualification exams ("abilitazione professionale") suggests that these variations in grades do actually reflect differences in grading standards and not true changes in students' quality. Indeed, we find a significant negative correlation between departments' average grades and the labour market outcomes of their graduates, i.e. graduating from a high grading department leads to a higher unemployment probability and lower wages. As well, graduates from departments with high average grades do not have higher chances to get professional qualifications in external examinations.
A straightforward policy implication follows from the above results. Policy makers should be very cautious about using students' academic performance as a proxy for university value added. If, as shown in this article, grading standards vary significantly across departments and universities, rewarding universities with high graduating rates may lead to undesirable consequences.
We test the relevance of this hypothesis using the main output variable that the Italian government takes into account in order to finance universities: the number of full-time equivalent students (FTE), which measures the number of exams that students have passed in a given year. Consistently with our predictions, we find that graduates from universities with a relatively higher number of FTE perform significantly worse in the labour market and do not obtain better results in professional qualification exams. The evidence thus suggests that a financing scheme which is meant to reward those universities that produce higher value added is, instead, favouring those universities with lower standards.
The rest of the article is organized as follows. Section 2 presents the existent literature on grading standards. Section 3 describes the data and the main variables used in the empirical part. Section 4 presents the empirical analysis and discusses policy implications. Finally, Section 5 summarizes the main results and provides the conclusions.
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2 Background |
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The issue of educational standards has been widely discussed in the economics literature both from a theoretical and an empirical perspective. Grading standards may vary over time and across higher education institutions for a number of reasons. Standards may adjust to the quality of students (Strenta and Elliott 1987). As well, professors may inflate grades to escape negative evaluations by students, whose opinions matter for tenure and promotion decisions (Siegfried and Fels 1979; Nelson and Lynch 1984). Some departments may also increase their grades to fill poorly attended courses that might otherwise be canceled (Dickson 1984; Staples 1998). In addition, Freeman (1999) argues that given the institutional constraints that prevent, within each university, a system of flexible money pricing for those courses with different expected earnings, instructors and departments may act strategically to manage enrolment by adjusting the time and the effort cost of achieving a given grade. More generally, Costrell (1994) notes that if institutions choose grading standards in a decentralized way a free rider problem may arise, as high standards might not be fully appropriated by each institution. De Paola and Scoppa (2007) point out that, in a decentralized setting, educational standards might be also influenced by the existence of labour market distorsions.
An extensive empirical literature has documented the existence of variations in grades over time across American universities and colleges. In particular, there has been, at least since the 1960s, an increase in the grades issued by American universities, coupled with the perception of a deterioration in academic standards (Kolevzon 1981; Sabot and Wakeman-Linn 1991; Anglin and Meng 2000). As well, there exists a line of studies, which provide evidence on divergence in grades across different disciplines (Dickson 1984; Sabot and Wakeman-Linn 1991; Freeman 1999). For instance, Sabot and Wakeman-Linn (1991) report average grades received by students in several disciplines in eight American colleges and universities, finding a clear division of colleges into high and low grading departments.
Differences in grades are also observed in Europe. A report on the development of exam grades in Germany finds that the average grades vary widely across universities (Wissenschaftsrat 2004). Several authors also observe that in the UK degree results vary according to institution. For example, Chapman (1997) studies the degree results from 1973 to 1993 for eight disciplines and finds a clear tendency for certain universities to award consistently higher percentages of top degrees in all disciplines with respect to the corresponding national average. As far as Italy is concerned, Boero et al. (2001) report that grades tend to vary significantly across degrees and regions.
Unfortunately, in most of these studies it is difficult to disentangle whether the observed differences in grades reflect different qualifications and performance or, conversely, differences in teaching and assessment practices. As Boero et al. (2001) put it, whether the observed differences "indicate use of differential standards across the different institutions or genuine institutional differences in value-added cannot be identified from the data" (Boero et al. 2001, p. 27). However, assessing whether the observed heterogeneity in grades stems form different grading standards or from differences in graduates' true performance might be important for a number of reasons. Both in Europe and in the US, variations in grading standards might be problematic in the presence of informational asymmetries about the quality of graduates and/or institutions. Most importantly, in many European countries the institutional design of higher education typically requires the homogeneity of grading standards across institutions. This assumption explains why titles have a legal value and are legally required for many occupations and, as well, why several countries, such as Italy and Denmark, have adopted output funding schemes based on the number of diplomas or grade points each higher education institutions delivers.
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3 Data |
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We investigate the potential existence of differences in grading standards across Italian universities and fields of studies using a very detailed dataset concerning Italian university graduates, which allows to observe their socioeconomic background, high-school grades, university performance and, finally, their outcomes in the labour market and in professional qualification exams.
More specifically, our main data are drawn from three distinct but almost identical surveys named Indagine Inserimento Professionale Laureati (Survey on University-to-Work Transition) run in 1998, 2001 and 2004 on individuals that graduated in 1995, 1998 and 2001, respectively.1
The target samples consist of 25,716 individuals in 1998, 36,373 individuals in 2001 and 38,470 individuals in 2004. They represent respectively the 25, 28.1 and 24.7 percent of the total population of university graduates in Italian universities. The response rates were of 64.7, 53.3, and 67.6 percent for a total of 17,326, 20,844 and 26,006 respondents. In all 3 years, the sample is stratified according to sex, university and obtained degree and in the analysis below all estimations are performed using stratification weights. We exclude from the sample graduates from physical education studies and from the so-called "laurea primo livello", since they were surveyed only in the 2001 edition (501 and 475 observations, respectively).
As other European continental countries, Italy has a system of open admission into public universities: most departments are obliged to admit every applicant, without being allowed to set up any entry restrictions. This system is common to all public universities and all disciplines except medicine, veterinary and architecture. For a number of reasons, grading standards are likely to be different in those universities and fields of study that can select their students; thus, we further restrict our sample to those departments that cannot select students. This reduces the total size of the sample to 61,844 observations.
The surveys provide information on (i) individual characteristics that are pre-determined with respect to college choices and outcomes, (ii) college-related individual indicators and (iii) labour market outcomes. The first set of variables includes information on the individual sociodemographic background such as gender, nationality, number of siblings, province of residence before college enrolment, parents' education and employment when respondent was around 14-years old, the situation of military service obligations before attending university and self-reported high-school curricula–high-school grade and type of school attended. The second includes university-related indicators: the type of degree and university attended, educational outcomes—i.e. final grade obtained and the number of years spent for the completion of the degree2—and additional information such as occupational status during studies, changes in the degree followed, attainment of an other degree and whether the respondent originated from a town or province other than the one where her university was located. Official grades range from 66 points to a maximum of 110 e lode. Third, the survey collects self-reported information about a number of occupational outcomes 3 years after graduation. Among others, it is possible to observe whether the graduate is employed, whether the job requires a university degree, her wage and several indexes of job satisfaction. Table 1 depicts descriptive statistics for the key individual variables.3
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In addition to the individual information, we use data on several college characteristics. Fields of study are aggregated in 12 different disciplines.4 Table 2 displays descriptive statistics at the department level on the share of full-time equivalent (FTE) Students—the main measure used by the Ministry for distribution of ordinary financial funds across universities—and ordinary financial funds themselves.5 Finally, we also consider a number of demographic and economic indicators at the provincial level such as gross domestic product (GDP), total population and unemployment.
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4 Empirical analysis |
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TopAbstract1 Introduction2 Background3 Data4 Empirical analysis5 ConclusionReferences |
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To begin with, we investigate whether grades vary significantly across disciplines and universities. Then, we analyse whether the potential existence of differences in grades across institutions stems from differences in grading standards or, rather, it reflects genuine differences in institutional value added. Finally, we analyse how the existence of differential grading standards affects the funding of Italian universities.
4.1 Grades
The grades obtained by a university graduate are likely to be related to a number of personal characteristics including parental background and pre-university ability. We estimate the following model:
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| (1) |
controls general changes across time. Finally, the error term 
itfu captures any remaining factor affecting academic performance. Column 1 of Table 3 shows the results of an ordinary least square (OLS) estimation of Equation (1) where the dependent variable is the final aggregate grade obtained by the individual during her studies. In addition to individual pre-determined characteristics, the regression also controls for the number of extra years taken to graduate.6 The effect of individual characteristics is largely consistent with those obtained by previous studies.7 We also observe that grades are positively correlated with unemployment rates. This is consistent with the work of Dornbusch et al. (2000) and Di Pietro (2006), who point out that local labour market conditions may influence students' decisions. Lower unemployment rate may encourage a number of students to devote less effort to studying in university, in order to take advantage of the improved labor market conditions.
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Moreover, grades tend to vary to a large extent both across universities and across faculties.8 Figure 1 shows the set of estimated university dummy coefficients, i.e. the component of an individual's; grade that is statistically explained by her attendance to a given institution, conditional on her observable characteristics, discipline, geographical origin and the time she took to graduate. Universities are ordered from left to right according to their official university code, lower codes corresponding in general to northern locations and bigger codes' to southern ones. The positive slope suggests that, as one moves across universities from the north to the south of Italy, grades—conditional on individual's; observable characteristics—tend to increase. Similarly, Figure 2 shows how grades vary across disciplines. This figure suggests that there are notable differences in the size of discipline fixed-effects on grades with Engineering, Economics and Statistics, Chemistry and Pharmacy, and Law being among the lowest grading and Agriculture, Literature, Pedagogy and Architecture among the highest grading disciplines.
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The second column of Table 3 displays the results of the above model when we use as dependent variable the number of extra years taken to graduate. The previous findings are largely confirmed. Results concerning the variation of university and discipline dummy coefficients in this case are qualitatively very similar to the ones of Figures 1 and 2 and are available upon request.
Two important caveats apply to the above estimations. First, note that the estimation builds on the information provided by individuals with similar characteristics, including geographic origin, but who decide to attend different departments. This strategy provides consistent estimates as long as these individuals do not differ significantly in their unobservable characteristics. Second, another important concern regards the endogeneity of the sample. In fact, we observe only graduates, but not drop-outs.9
4.2 Differences in quality or differences in grading standards?
The above results show that grades, conditional on graduates' predetermined characteristics, tend to vary greatly across universities and fields. In principle, these differences could be due either to the value added by universities or to their grading standards. To investigate these alternative explanations, we use two additional proxies of quality. First, we exploit the indicators detecting graduates' labour market performance. If higher grades reflect higher value added, graduates from high grading departments should perform better in the labour market. Second, we use the outcomes of external professional qualifying exams. In Italy, they are compulsory for a number of professional occupations. If higher grades reflect higher quality, graduates from high grading institutions should display higher passing rates.
Labour market outcomes
Graduates' labour market performance Li is likely to be affected by a number of socioeconomic characteristics Xi, by their field of study Df and by the university attended Du. Equation (2) analyses this relationship:
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| (2) |
Table 3 presents the estimation results of this model when labour market performance is measured, 3 years after graduation, by the employment status (column 3), the wage (column 4) and the probability of finding a job, which requires a university degree (column 4) of those individuals who are in the labour force.10 If, on the one hand, female perform better in terms of grades, on the other, they exhibit a worse performance in the labour market. Similarly, foreign graduates are not able to transform their higher academic performance into better labour market outcomes.
In addition to personal characteristics, the institution attended is a key predictor of future labour market performance. Figure 3 depicts the estimates of universities' fixed effects on wages conditional on the individuals' observable characteristics, their geographical origin and discipline. Again, universities are ordered from left to right according to their official ISTAT code number, which increases as we move from the north to the south of Italy. Thus, the negative slope observed in Figure 3 suggests that northern universities' graduates tend to earn higher wages than southern universities' ones. A similar pattern is observed if we restrict our analysis to graduates who finished their studies on time. Including the region of actual residence does not affect the pattern observed in the histogram. Thus, our results are not driven by unobserved labour market conditions. The picture is similar if we use as dependent variable graduates' employment status: given two students with similar socioeconomic backgrounds and geographical origins, those who graduate from a northern university are more likely to be successful in the labour market than those who graduates from a southern university, even if they end up working in the same region. This result is consistent with previous studies that also find a premium for graduating in the north (Brunello and Cappellari 2005; Pozzoli 2006; Makovec 2007). Moreover, we observe significant differences across disciplines in terms of wages. In particular, conditional on graduating in the same university, high-school grades, individual background and province of origin, graduates in Engineering, Economics and Statistics, Chemistry and Pharmacy and Medicine are likely to have higher wage with respect to graduates in Veterinary, Literature, Law and Pedagogy (Figure 4).
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As shown in Figures 1 and 3, while grades tend to be higher in southern universities, labour market outcomes tend to be better for those that graduate in the North. With the exception of Law departments,11 the same pattern generally holds at the discipline level: high grading disciplines tend to provide lower labour market opportunities for their student. This descriptive evidence suggests that there exists a negative correlation between departments' grades and their graduates' labour market outcomes, both across universities and across fields of study. Bellow, we formally test this statistical relationship.
First, we estimate an equation, in which—as in Equation (1)—we analyse the determinants of grades, but we substitute the discipline and university dummies with a set of dummies specific to each university department separately for 1995, 1998 and 2001 Dtd:
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| (3) |
Second, using the department dummies coefficients 
, we decompose individuals' grades into two components: (1) 
reflecting the (conditional) average grade obtained by individuals that graduated within the same cohort and department and (2) the relative grade obtained by the individual, calculated as a difference between the actual grade and the estimated grade conditional on personal characteristics 
. Third, we study how these components affect labour market performance measures:
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Table 4 presents the estimation results of Equation (4) using three different measures of graduates' labour market performance: the probability of being employed (columns 1 and 2), the probability of finding a job that requires a university degree (columns 3 and 4) and the expected wage (columns 5 and 6). Conditional on their observable personal characteristics, the number of years spent in university and the discipline chosen, students that obtain higher grades relative to their classmates are more likely to be employed 3 years after graduation and, if employed, tend to earn a significantly higher wage. However, the department's; average grade has the opposite effect. Students that graduated from universities where average grades were higher are significantly less likely to be employed (column 1) and, if employed, they are not more likely to have a job that requires a degree (column 3) and do not tend to earn more (column 5). Results remain essentially the same if we include among the controls graduates' class size or the region of graduates' residence when being interviewed. In columns 2, 4 and 6, we compare individuals who graduated in the same university but who had enrolled into different fields. We find that those individuals who obtained their degree in departments with relatively higher average grades are significantly less likely to find a job which requires being a graduate (column 4) and actually tend to earn significantly less (column 6). As in the previous analysis, controlling for the region of current residence does not have a significant effect on the estimates.
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The above results may help to rationalize the puzzling correlation that arises when we compare the academic performance of Italian graduates with their performance in the labour market. A simple descriptive analysis of the data provided by the ISTAT surveys on year 1995, 1998 and 2001 graduates reveals that those individuals that had obtained higher grades in university do not obtain higher wages later on (see Table 5, columns 1, 2 and 3).12 In the last edition of the survey, it turns out that grades are negatively correlated with earnings: graduates who obtained lower grades tend to earn relatively more. Of course, as our above results suggested, this negative relationship is driven by the different grading standards that departments apply. As expected, once we take into account the university and the department from which an individual has graduated the expected positive relationship between grades and salary is re-established (though, significant only at 11 percent).
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Professional qualification exams
An additional way to test whether higher grades reflect higher quality or simply different standards is to exploit the outcomes of post-university professional qualification exams ("abilitazione professionale"). These exams are granted by official professional organizations and are meant to certify that a given graduate holds a minimal set of competencies for a given profession. They are not compulsory but are required in order to perform legally a number of professions. The set of professions for which an exam is required includes Architects, Chemists, Accountants, Physicians, Psychologists or Engineers.13
The ISTAT survey allows to observe whether a given graduate has passed the corresponding external qualification exam within 3 years of her graduation. A potential source of bias of this measure might arise from the fact that we only observe whether individuals succeeded in the professional qualification exam, but not whether they took it and failed. This problem is likely to be bigger in those disciplines where graduates have other professional possibilities that do not require an official qualification.
As it is shown in Table 1, about half of respondents have passed an external qualification exam after graduation. However, the distribution of this percentage across fields is not homogenous14: the probability that a graduate pass the qualification exam ranges from 0 to 40 percent in 66 percent of courses, from 40 to 60 in 4 percent of courses and from 60 to 100 percent in 30 percent of courses. In other words, there exist a big group of courses in which more than 60 percent of graduates do not ever pass the exam, another group of courses in which more than 60 percent of graduates pass the exam and very few courses that could not be attributed either to the first or to the second group. In order to minimize the problem of self-selection described above, we restrict the analysis to those occupations where graduates have a very limited scope for professional possibilities unless they pass the external qualification exam. In what follows only the latter group of courses, namely, the one in which more than 60 percent of graduates passed the exam (mainly Engineering and Chemistry courses), is considered.
Column 6 of Table 3 shows the relationship between individual characteristics and the probability of success in qualification exams. As expected, success in this exam is closely related to graduates' quality, as measured by high-school grades and other socioeconomic characteristics.
In Table 6, we analyse the relationship between university grades and performance in external qualification exams. We find that conditional on the department and university attended, those graduates that obtained relatively better grades than their classmates in university are significantly more likely to pass the qualification exams. Then, we investigate whether the (conditional) average grade of all individuals that graduated within the same cohort and department 
, as defined in the previous subsection, has a similar positive effect on graduates' performance in professional qualification exams Ai, estimating the following regression:
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As shown in column 2 of Table 6, while we still find that within each department better students are more likely to succeed in professional qualification exams, in general graduates from departments with higher average grades tend to be less successful in professional qualification exams. Given that in these fields the lack of success in external exams is associated with significantly lower employment rates and with significantly lower probabilities of finding a job, which requires a degree, our results suggest that the variations in the department-average component of grades are not likely to reflect better quality.15
4.3 Differential grading standards and the funding of italian universities
Before 1993, the Italian national ministry of education was in charge of fixing the total amount of funds, their shares across public universities and their allocation across disciplines. Its decisions were largely made on historical bases and were sometimes affected by distinct deals with single institutions and faculties within institutions. In 1993, a reform was approved allowing each university to become an autonomous entity with its own budget to be allocated across distinct disciplines (law n.537/1993). Moreover, discretion was replaced by a complex set of rules, which in the short run left about 90 percent of the big bulk of public funding to be assigned on historical basis and the rest to be allocated via an equalization component (EC). The latter is supposed to progressively substitute the former. The EC objective is 2-fold: first, to reduce public funding disparities across universities and across disciplines and, second, to incentivate quality. On the incentives side, the EC seeks to reward the quality of teaching linking funding to the number of exams passed by enrolled students. Technically, the funds depend positively on the share of FTE students, which is defined as the ratio between the number of exams that students passed and the number of exams that students should have taken. See Perotti (2002) for details.
In principle, the measure of quality based on the share of FTE students might be subject to at least two problems. First, it fails to take into account the initial quality of students. Universities that attract students of better quality will tend to perform relatively better even if they fail to provide better education. Second, in the absence of quality assurance mechanisms, the FTE might capture both the students true quality and the easiness (or grading standards) of a given institution.16 In fact, the evidence provided in the previous section suggests that the relationship between the average grades issued by different universities and the performance of their graduates in the labour market or in qualification exams is, if any, negative. A straightforward implication of this result is that financing universities based on their self-evaluated academic performance does not necessary reward those universities that generate a higher value.
Table 7 shows the relationship between graduates' labour market outcomes and the share FTE students in the department where they graduated, conditional on graduates' socioeconomic background and pre-university measures of quality. While the number of FTE students is meant to proxy the quality of a department, we find a strong and significant negative relationship between this measure and graduates' labour market outcomes, as measured by occupation rates (column 1) and obtaining a job which requires a university degree (column 2). We also find no significant relationship whatsoever between the share of FTE students and graduates' wages (column 3) or their performance in professional qualification exams and (column 4).
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To sum up, FTE fails to capture quality of institutions, at least as measured by graduates' performance in the labour market and in professional qualification exams.
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5 Conclusion |
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In recent years, a number of European countries, including Italy, have adopted output funding schemes based on the number of diplomas or grade points each institution delivers. One of the pre-conditions for such systems to be effective in providing quality enhancing incentives is ensuring homogeneity of educational quality and grading standards across institutions. Otherwise, as noted by Jacobs and Van der Ploeg (2006), this practice might undermine incentives to improve educational quality, as in most cases the quantity rather than the quality of output is rewarded due to the difficulties in measuring the later.
In this article, we analyse grading standards across Italian universities and disciplines. More specifically, we study the performance of several cohorts of Italian graduates in the labour market and in external qualification exams and analyse how it relates to their performance in university. We find that, conditional on a large set of individuals' observable characteristics that includes geographical origin, high-school grade and socioeconomic background, graduates from high-grading departments tend to perform significantly worse in the labour market. Moreover, graduates from high-grading universities are less likely to succeed in external qualifying exams that are required for many professional activities. These results suggest that the significant variations in grades that can be observed in Italy across disciplines and universities reflect to a large extent differences in grading standards.
In line with this evidence, we also find that the output measure of university quality that has been adopted by the Italian Ministry of Education to allocate funds across universities—i.e. the number of FTE students defined as the ratio between the number of exams that students passed and the total number of exams that they should have taken—is negatively correlated with graduates' labour market outcomes.
This finding rises concerns on the effectiveness of such funding mechanisms. In light of this evidence, the implementation of quality ensuring mechanisms–such as a system of external examiners as in the UK—should be seriously considered as a necessary complement to any output funding scheme. Additionally, given that obtaining objective evaluations of external examiners might be itself problematic and costly, a more radical policy option may involve fostering reputation effects in the market for higher education. This goal may be approached in different ways, for instance, by allowing universities to select their students and, simultaneously, promoting student mobility, by letting universities set tuition fees and introducing efficient student loan systems.17
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Acknowledgments |
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We would like to thank Stijn Kelchtermans, Reinhilde Veugelers and participants at seminars at the Université Louis Pasteur, Sant' Anna School of Advance Studies, 2nd EIASM workshop on Process of Reform of University Systems, XXII Jornadas de Economia Industrial, University of Alicante, the V Brucchi Luchino workshop and the CESifo Workshop on Innovation and Higher Education for their comments on an earlier draft of this article. The empirical analysis of this article would not have been possible without the data and the help provided by ISTAT (the Italian Statistical Office). The econometric analysis was carried out at the ADELE Laboratory in Rome.
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Footnotes |
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1 Differences may stem from the different interviewing technologies used in the surveys: in 1998 ISTAT mailed paper-based questionnaires, while in 2001 and 2004 graduates were first contacted by mail and then questions were asked following the so-called CATI. (Computer-assisted telephone interview) technique.
2 In Italy, the final grade is calculated as the sum of the grades obtained by the graduate during her courses plus the grade received for the so-called degree dissertation (tesi di laurea). Any student whose final grade is higher than 110 obtains what is known as "110 e lode". For simplicity, in the empirical analysis reported bellow the potential existence of grades above 110 has been disregarded. The results obtained using a tobit regression, available upon request, are very similar to the ones reported here. Also, note that in the Italian education system in the analysed period students were not constrained either in time or in the number of trials taken for passing exams.
3 The unemployment rate for graduates in our sample is 14.7 percent. It is consistent with the OECD 2003 data suggesting that 13.6 percent of Italian graduates aged 25–29 not being in education are unemployed. Italian graduates experience disadvantage in terms of early performance in the labour market as the overall unemployment rate among individuals aged 25–29 is 10.4 percent (OECD, Education at a Glance 2005).
4 The aggregated disciplines are Agriculture, Architecture, Chemistry and Pharmacy, Economics and Statistics, Engineering, Law, Literature, Medicine and Surgery, Pedagogy, Political and Sociological Studies, Sciences, Veterinary. In what follows the term department stands for the corresponding disciplinary unit within a particular university.
5 Information on the number of FTEs comes from the Osservatorio per la valutazione del sistema universitario (1998). See Perotti (2002) for detailed information on how the number of FTEs affects universities' funding.
6 The difficulty of each particular program could be described in two ways: as the time that is necessary in order to complete a program and obtain a certain grade or as the final grade that an individual will obtain if she takes a given period time to graduate.
7 See, for instance, Boero et al. (2001) who studies the determinants of academic success using the ISTAT survey corresponding to year 1998.
8 The inclusion in equation (1) of university and discipline fixed affects significantly the explanatory of the model. Including university dummies increases the R-square from 21.68 percent to 28.54 percent. The subsequent inclusion of the discipline fixed effects raises R-square to 39.82 percent.
9 This shortcoming generates two problems. First, the factors that afect the grades obtained by those students that do not manage to graduate could differ from the factors affecting the grades obtained by graduates. A key assumption is, therefore, that the grades obtained by graduates consistently reflect, conditional on observables, the grades obtained by those students that dropped out before graduation. Second, a more subtle problem is related to the fact that the very same unobservable characteristics—i.e. talent or grading standards—that affect grades do also affect selection into the sample, this is, graduation. This makes the usual selection based on observables assumption likely to fail. Still, the nature of the problem allows us to make some predictions about the direction of the bias, at least among the cohort of students that graduate on time. Any factor that generates an increase in grades would presumably increase the size of this cohort. The new sample would include individuals which are, conditional on observables, relatively worse in unobservables. This suggests that the effect of factors that generate an increase in grades will tend to be underestimated or, in other words, that the estimated coefficients will tend to be a lower bound of their true value.
10 Results are essentially unchanged, if we consider instead the whole population of graduates, including also those graduates that do not look for a job.
11 Law is a quite particular case. Note that in Italy, graduates in Law must spend at least 2 years as interns before taking professional qualification exams and becoming lawyers.
12 Boero et al. (2001) already point out that the grades of 1998 graduates show no correlation with their wages.
13 For a complete list of Italian professional organizations and details of respective exams see http://it.wikipedia.org/wiki/Albo_professionale.
14 Degree course defines graduates' specialization within a certain discipline. Each disciplinary field on average offers around 10 different degree courses.
15 Those graduates who passed the professional exam have a probability of finding a job that matches the knowledge acquired in university, which is 11 percentage points higher than the rest of individuals in the sample. Note also that if individuals' unobserved ability in university performance was positively correlated to individuals' unobserved ability in professional qualification exams, the estimated coeffcient must be considered as an upper bound of its true value.
16 In 1996 and 1999, two distinct kinds of evaluating committees were established to preserve quality: a National Committee (Comitato Nazionale per la Valutazione del Sistema Universitario) and several Internal Committees (Nuclei di Valutazione Interna). However, as convincingly argued by Perotti (2002), their objectives are too vague and they turned out to be to be largely ineffective.
17 See Mas-Colell (2003–2004) for a thorough discussion on reforms that might foster competition and reputation effects in the European higher education space.
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