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Do diverse degree courses matter for university attractiveness?

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Abstract

The present paper focuses on an unexplored line of research in Higher Education Institutions’ (HEIs) studies: the role of programmatic diversity on university attractiveness. Specifically, it highlights the role of diversification and divergence of the degree courses as a lever to attract more freshers. Diversification measures the range of the offered degree courses, while divergence indicates how the mix differs from the national standard. The work addresses the following three research questions: (1) are diversification and divergence beneficial to universities in attracting more freshers? Do these effects change with (2) the internal characteristics and (3) the external characteristics of universities? To this aim, the paper explores a panel data set of 75 Italian universities between 2012–2019. Overall, the findings indicate that programmatic diversity is beneficial but with specific differences according to size, research quality and the location of the HEIs. Furthermore, the proximity to other competitors plays an important role.

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Notes

  1. See the following link: http://publications.europa.eu/resource/cellar/8d8026dc-d7d7-4d04-8896-e13ef636ae6b.0010.02/DOC_5.

  2. Nationally programmed access is regulated by Law 264 of 1999. Article 1 (a) identifies the types of nationally programmed courses, “degree courses in medicine and surgery, veterinary medicine, dentistry and dental prosthetic, and architecture,” as well as bachelor’s and master’s degree courses concerning primary education and the training of health personnel in 22 types of professions, such as nursing science.

  3. Authors’ elaboration for the group of universities under investigation in 2014, the last year available in the database; see the link: https://eter-project.com/.

  4. Funding for public universities was issued by Law 537 in 1993, while funding for private universities was issued by Law 243 in 1991.

  5. To date, there are 50 and 100 classes, respectively, for the undergraduate and master’s degree courses.

  6. Agricultural-Forestry and Veterinary Sciences; Architecture and Civil Engineering; Art and Design; Computer Science and ICT Technology; Economics; Industrial and Information Engineering; Law; Linguistics; Literature-Humanities; Medical-Health and Pharmaceutical Sciences; Motor and Sport Sciences; Natural Sciences, Physics and Mathematics; Political-Social Sciences and Communication; Psychology; Teaching.

  7. Link Campus University is a private institution that received accreditation in September 2011. However, it has been excluded from the sample because its data were not made available until 2013.

  8. The VQR2 classifies universities according to the number of students in the academic year 2012-2013.

  9. Figure 5 plots these values in absolute terms.

  10. In “Appendix”, values in Fig. 6a, b are expressed in absolute terms.

  11. In the “Appendix”, Fig. 7 is plotted using absolute values.

  12. See Sect. 4 for a description of the variables.

  13. In this first-difference specification, individual effects would imply the existence of individual trends in the level specification which could lead to over-fitting concerns.

  14. Since the Roma LUISS experiences important variations (see Table 13), also in terms of the sign, between 2012 and 2014, the econometric analysis is also run without this outlier but the main results are confirmed.

  15. The convergence coefficient is larger when controlling for the university fixed effects (Column (5) of Table 2). This outcome can be due to the Hurwicz-type bias (Hurwicz 1950), which substantially biases downwards the fixed-effects estimator for the coefficient of the lagged dependent variable in short panel data samples (Barro 2012).

  16. According to the ISTAT definition: Rome, Milan, Naples, Turin, Bari, Bologna, Florence, Venice, Genoa, Reggio Calabria.

  17. The long-run effects seem very large, but we should point out that a 10 per cent increase in the level of diversification and divergence represents, respectively, a change above the 90 and 75 percentile of the distribution of observed annual changes over the period analysed. In fact, 50% of the annual variations of the indicators of diversification and divergence are less than 2% and 4.7%, respectively.

References

  • Abel JR, Deitz R (2012) Do colleges and universities increase their region’s human capital? J Econ Geogr 12(3):667–691

    Article  Google Scholar 

  • Agasisti T, Dal Bianco A (2007) Cost structure of Italian public universities: an empirical analysis. High Educ Eur 32(2–3):261–275

    Article  Google Scholar 

  • Barro RJ (2012) Convergence and modernization revisited, NBER working paper 18295

  • Beine M, Delogu M, Ragot L (2020) The role of fees in foreign education: evidence from Italy. J Econ Geogr 20(2):571–600

    Google Scholar 

  • Birnbaum R (1983) Maintaining diversity in higher education. Jossey-Bass, San Francisco

    Google Scholar 

  • Camozzi A (2005) La riforma universitaria. In: Balloni A, Cipolla C, Di Nallo E, Donati P, Guidicini P, La Rosa M (eds) La riforma universitaria nella società globale. FrancoAngeli, Milano, pp 45–78

  • Caruso G, Mallus E, Marrocu E, Paci R (2020) Gli effetti del contesto territoriale sull’efficienza delle università in italia. EyesReg 10(6):258–265

    Google Scholar 

  • Cattaneo M, Horta H, Malighetti P, Meoli M, Paleari S (2019) The relationship between competition and programmatic diversification. Stud High Educ 44(7):1222–1240

    Article  Google Scholar 

  • Cattaneo M, Malighetti P, Meoli M, Paleari S (2017) University spatial competition for students: the Italian case. Reg Stud 51(5):750–764

    Article  Google Scholar 

  • Ciriaci D (2014) Does university quality influence the interregional mobility of students and graduates? The case of Italy. Reg Stud 48(10):1592–1608

    Article  Google Scholar 

  • Contini D, Cugnata F, Scagni A (2018) Social selection in higher education. Enrolment, dropout and timely degree attainment in Italy. High Educ 75(5):785–808

    Article  Google Scholar 

  • CRENoS (2021) Economia della Sardegna: \(28^{\circ }\) Rapporto. Arkadia Editore, Cagliari

  • Dotti NF, Fratesi U, Lenzi C, Percoco M (2013) Local labour markets and the interregional mobility of Italian university students. Spat Econ Anal 8(4):443–468

    Article  Google Scholar 

  • Drucker J, Goldstein H (2007) Assessing the regional economic development impacts of universities: a review of current approaches. Int Reg Sci Rev 30(1):20–46

    Article  Google Scholar 

  • EC (2017) Seventh report on economic, social and territorial cohesion. My region, my Europe, our future, European Commission, Brussels

  • EC (2020) Commission proposal for a Council Recommendation on a Bridge to Jobs—reinforcing the Youth Guarantee. European Commission, Brussels

  • Elevati C, Lanzoni F (2004) 3+2= La nuova università. Alpha Test, Milano

  • Faggian A, McCann P (2006) Human capital flows and regional knowledge assets: a simultaneous equation approach. Oxf Econ Pap 58(3):475–500

    Article  Google Scholar 

  • Faggian A, McCann P (2009) Human capital, graduate migration and innovation in British regions. Camb J Econ 33(2):317–333

    Article  Google Scholar 

  • Faggian A, McCann P, Sheppard S (2006) An analysis of ethnic differences in UK graduate migration behaviour. Ann Reg Sci 40(2):461–471

    Article  Google Scholar 

  • Faggian A, McCann P, Sheppard S (2007) Human capital, higher education and graduate migration: an analysis of Scottish and welsh students. Urban Stud 44(13):2511–2528

    Article  Google Scholar 

  • Farhan BY (2016) The structure of Ontario’s higher education market. Int J Econ Bus Res 12(2):154–168

    Article  Google Scholar 

  • Fratesi U, Percoco M (2014) Selective migration, regional growth and convergence: evidence from Italy. Reg Stud 48(10):1650–1668

    Article  Google Scholar 

  • Gottlieb PD, Joseph G (2006) College-to-work migration of technology graduates and holders of doctorates within the United States. J Reg Sci 46(4):627–659

    Article  Google Scholar 

  • Gowen J, Owen VL (1991) Enrollment management and strategic planning: resolving a classic tension in higher education. Nonprofit Manag Leadersh 2(2):143–158

    Article  Google Scholar 

  • Groen JA (2004) The effect of college location on migration of college-educated labor. J Econometr 121(1–2):125–142

    Article  Google Scholar 

  • Groen JA, White MJ (2004) In-state versus out-of-state students: the divergence of interest between public universities and state governments. J Public Econ 88(9–10):1793–1814

    Article  Google Scholar 

  • Gu J (2012) Spatial recruiting competition in Chinese higher education system. High Educ 63(2):165–185

    Article  Google Scholar 

  • Horta H (2009) Global and national prominent universities: internationalization, competitiveness and the role of the state. High Educ 58(3):387–405

    Article  Google Scholar 

  • Hsing Y, Mixon FG Jr (1996) A regional study of net migration rates of college students. Rev Reg Stud 26(2):197–209

    Google Scholar 

  • Hübner M (2012) Do tuition fees affect enrollment behavior? Evidence from a ‘natural experiment’ in Germany. Econ Educ Rev 31(6):949–960

    Article  Google Scholar 

  • Huggins R, Johnston A (2009) The economic and innovation contribution of universities: a regional perspective. Eviron Plann C Gov Policy 27(6):1088–1106

    Article  Google Scholar 

  • Huggins R, Kitagawa F (2009) Devolution and knowledge transfer from universities: perspectives from Scotland and Wales. University of Wales, Wales

    Google Scholar 

  • Hurwicz L (1950) Least-squares bias in time series. In: Koopmans TC (ed) Statistical inference in dynamic economic models. Wiley, New York, pp 365–383

    Google Scholar 

  • Kitagawa F, Marzocchi C, Sánchez-Barrioluengo M, Uyarra E (2022) Anchoring talent to regions: the role of universities in graduate retention through employment and entrepreneurship. Reg Stud 56(6):1001–1014

    Article  Google Scholar 

  • Lowry RC (2007) The political economy of public universities in the united states: a review essay. State Polit Policy Q 7(3):303–324

    Article  Google Scholar 

  • Marginson S (2004) Competition and markets in higher education: a ‘glonacal’ analysis. Policy Futures Educ 2(2):175–244

    Article  Google Scholar 

  • Marginson S (2006) Dynamics of national and global competition in higher education. High Educ 52(1):1–39

    Article  Google Scholar 

  • Mateos-González JL, Boliver V (2019) Performance-based university funding and the drive towards ‘institutional meritocracy’ in Italy. Br J Sociol Educ 40(2):145–158

    Article  Google Scholar 

  • Mause K (2009) Too much competition in higher education? Some conceptual remarks on the excessive-signaling hypothesis. Am J Econ Sociol 68(5):1107–1133

    Article  Google Scholar 

  • McMillen DP, Singell LD Jr, Waddell GR (2007) Spatial competition and the price of college. Econ Inq 45(4):817–833

    Article  Google Scholar 

  • Mitze T, Burgard C, Alecke B (2015) The tuition fee ‘shock’: analysing the response of first-year students to a spatially discontinuous policy change in Germany. Pap Reg Sci 94(2):385–419

    Article  Google Scholar 

  • Moretti E (2004) Estimating the social return to higher education: evidence from longitudinal and repeated cross-sectional data. J Econometr 121(1–2):175–212

    Article  Google Scholar 

  • Nifo A, Vecchione G (2014) Do institutions play a role in skilled migration? The case of Italy. Reg Stud 48(10):1628–1649

    Article  Google Scholar 

  • Nifo A, Vecchione G (2015) Measuring institutional quality in Italy. Rivista Economica del Mezzogiorno 1–2(2015):157–181

    Google Scholar 

  • Rossi F (2009) Increased competition and diversity in higher education: an empirical analysis of the Italian university system. High Educ Pol 22:389–413

    Article  Google Scholar 

  • Rossi F (2010) Massification, competition and organizational diversity in higher education: evidence from Italy. Stud High Educ 35(3):277–300

    Article  Google Scholar 

  • Rowse GL, Wing P (1982) Assessing competitive structures in higher education. J High Educ 53(6):656–686

    Article  Google Scholar 

  • Sá C, Florax RJ, Rietveld P (2004) Determinants of the regional demand for higher education in the Netherlands: a gravity model approach. Reg Stud 38(4):375–392

    Article  Google Scholar 

  • Sá C, Florax RJ, Rietveld P (2006) Does accessibility to higher education matter? Choice behaviour of high school graduates in the Netherlands. Spat Econ Anal 1(2):155–174

    Article  Google Scholar 

  • Shapiro JM (2006) Smart cities: quality of life, productivity, and the growth effects of human capital. Rev Econ Stat 88(2):324–335

    Article  Google Scholar 

  • Spiess CK, Wrohlich K (2010) Does distance determine who attends a university in germany? Econ Educ Rev 29(3):470–479

    Article  Google Scholar 

  • Teixeira PN, Rocha V, Biscaia R, Cardoso MF (2012) Competition and diversity in higher education: an empirical approach to specialization patterns of Portuguese institutions. High Educ 63(3):337–352

    Article  Google Scholar 

  • Teixeira P, Rocha V, Biscaia R, Cardoso MF (2014) Policy changes, marketisation trends and spatial dispersion in European higher education: comparing public and private sectors. Camb J Reg Econ Soc 7(2):271–288

    Article  Google Scholar 

  • Valero A, Van Reenen J (2019) The economic impact of univerities: evidence from the globe. Econ Educ Rev 68:53–67

    Article  Google Scholar 

  • Van Vught F (2008) Mission diversity and reputation in higher education. High Educ Pol 21(2):151–174

    Article  Google Scholar 

  • Veugelers R, Del Rey E (2015) The contribution of universities to innovation, (regional) growth and employment. Technical report, EENEE analytical report

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Aknowledgements

This research was funded by the Sardinian Government, CUP F76C18001100002. LR 7, 2007, ‘University, Innovation and Economic Growth. A macro and micro analysis’. We thank the institution for the financial support given to this project. We are very grateful to our friend and colleague Gianfranco Atzeni for incisive suggestions. Claudio Detotto is also grateful to the Gran Sasso Science Institute for providing kind hospitality and necessary arrangements for his stay at GSSI, L’Aquila (Italy), where a part of this work was done. The Ministry of University and Research (MUR) is also acknowledged for data accessibility.

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Authors and Affiliations

  1. Department of Economics and Business, University of Sassari, Sassari, Italy

    Bianca Biagi & Manuela Pulina

  2. Gran Sasso Science Institute, L’Aquila, Italy

    Bianca Biagi & Laura Ciucci

  3. CRENoS, Sassari, Italy

    Bianca Biagi, Laura Ciucci, Claudio Detotto & Manuela Pulina

  4. LISA UMR CNRS 6240, University of Corsica, Corte, France

    Claudio Detotto

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  1. Bianca Biagi
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  2. Laura Ciucci
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Correspondence to Laura Ciucci.

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Appendix

Appendix

See Tables 9, 10, 11, 12, 13, 14 and Figs. 5, 6, 7.

Table 9 Average national portfolio (percentages)
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Table 10 Summary statistics
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Table 11 Correlation matrix
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Table 12 Full estimates: overall diversification and divergence
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Table 13 Top 10 of variations in Diversification index
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Table 14 Top 10 of variations in Divergence index
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Fig. 5
figure 5

Freshers enrollment in Italy by university size and location. Years: 2012–2019

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Fig. 6
figure 6

Diversification index in Italy: overall, by university size and location. Years: 2011–2018 (bachelor’s degree)

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Fig. 7
figure 7

Divergence index in Italy: overall, by university size and location. Years: 2011–2018 (bachelor’s degree)

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Biagi, B., Ciucci, L., Detotto, C. et al. Do diverse degree courses matter for university attractiveness?. Ann Reg Sci 72, 1189–1229 (2024). https://doi.org/10.1007/s00168-023-01240-3

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