Maja Mihaljević Kosor University of Split, Faculty of Economics, CROATIA Examining the Determinants of Student Non-completion in.

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Maja Mihaljević Kosor University of Split, Faculty of Economics, CROATIA Examining the Determinants of Student Non-completion in Higher Education: An Application to Croatia

Main problems in HE (in Aghion et al., 2008; van der Ploeg and Veugelers, 2008a) :  Duration of studies  Small number of students earning a degree  Large number of students dropping out 1. Main motives…

Defining and measuring non-completion Contributions from authors in the UK and US Tinto’s Student Integration Model (1971):  Student persistence (non-completion) depends on SOCIAL and ACADEMIC integration at the HEI Main variables influencing non-completion:  Ability, gender, age, …  Socio-economic background  Current schooling characteristics  Peer effects (non-linearities)  Effort (usually not included) 2. Previous Empirical Work…

3. Developing a Model of Student Non- completion for the First Year of Studies… NC_1= f(X, F, S, P, E, C) X = personal characteristics F = family characteristics S = previous schooling characteristics P = peer effects E = effort C = current schooling characteristics

Data: Faculty-level data from one large Croatian HEI Time period: N=3310 students Model (1) and Model (2) 4. Preliminary Results…

Limitations… Missing data Focusing on first year non-completion

VARIABLE Model (1) N=1153 Model (2) N=2287 Coeff.(z-stat.)Coeff.(z-stat.) Constant Personal characteristics (X) Age 0.166*** ***5.31 Urban Married Previous schooling characteristics (S) Gymnasium-technical-1.299*** ***-4.43 Studied related subject-0.577** ***-2.73 Sec. school grades-0.007*** ***-9.17 Admission exam Family characteristics (F) F_Uni. Or non-university college degree-0.501*** ***-3.72 F_Basic or no school completed M_Uni. Or non-university college degree-0.374* **2.38 M_Basic or no school completed Table 1: Regression results for logit estimation of non-completion of the first level of studies, Model (1) and Model (2)

Current schooling characteristics (C ) Fee status 0.474* Full-time student ***-4.32 Current GPA ***-3.42 Peer effects (P) Peers_ Peers_1sq Effort (E) Exam attempts Year dummies (T) Enrolled in ***-6.15 Enrolled in ***-3.60 Enrolled in *** ***-3.17 Enrolled in *** Enrolled in *** Enrolled in **-2.41 Enrolled in **-2.06 Notes: Significant at ***1%, **5% and *10%.

Table 2: Predicted probabilities Types of students Probability of first year non- completion Model (1) Model (2) Type 1 Mature, married, enrolled part time, paying a tuition fee, parents completed sec. school Type 2 Young, single, full-time student, enrolled tuition-free, highly educated parents Type 3 An “average” student

Table 3: Regression results for Model (2) with MI(20), N=3310 VARIABLECoeff.(z-stat.) Constant Personal characteristics (X) Age 0.091***6.60 Urban Married Previous schooling characteristics (S) Gymnasium-technical-0.453***-3.40 Studied related subject-0.522***-3.72 Sec. school grades-0.007***-9.60 Admission exam-0.003**-2.55 Family characteristics (F) F_Uni. or non-university college degree-0.340***-3.24 F_Basic or no school completed M_Uni. or non-university college degree-0.293***-2.57 M_Basic or no school completed

Current schooling characteristics (C ) Fee status **2.52 Full-time student-1.053***-4.13 Peer effects (P) Peers_ Peers_1sq 3.44e Year dummies (T) Enrolled in *** Enrolled in ***-8.46 Enrolled in ***-8.33 Enrolled in ***-6.24 Enrolled in ***-6.09 Enrolled in ***-2.64 Enrolled in ***-4.82 Notes: Significant at ***1%, **5% and *10%.