scholarly journals Factors associated with federal student loan default among borrowers in a statewide system of community and technical colleges.

2017 ◽  
Author(s):  
Brittany Inge
Keyword(s):  
Technical Colleges ◽  
Student Loan ◽  
Loan Default ◽  
Factors Associated ◽  
Community And Technical Colleges ◽  
Student Loan Default

Factors Associated with Student Loan Default among Different Racial and Ethnic Groups

1998 ◽  
Vol 69 (2) ◽  
pp. 206-237 ◽  
Author(s):  
J. Fredericks Volkwein ◽  
Bruce P. Szelest ◽  
Alberto F. Cabrera ◽  
Michelle R. Napierski-Prancl
Keyword(s):  
Ethnic Groups ◽  
Student Loan ◽  
Loan Default ◽  
Factors Associated ◽  
Student Loan Default

Factors Associated with Student Loan Default among Different Racial and Ethnic Groups

1998 ◽  
Vol 69 (2) ◽  
pp. 206 ◽  
Author(s):  
J. Fredericks Volkwein ◽  
Bruce P. Szelest ◽  
Alberto F. Cabrera ◽  
Michelle R. Napierski-Prancl
Keyword(s):  
Ethnic Groups ◽  
Student Loan ◽  
Loan Default ◽  
Factors Associated ◽  
Student Loan Default

Individual and campus characteristics associated with student loan default

1995 ◽  
Vol 36 (1) ◽  
pp. 41-72 ◽  
Author(s):  
J. Fredericks Volkwein ◽  
Bruce P. Szelest
Keyword(s):  
Student Loan ◽  
Loan Default ◽  
Student Loan Default

An Economic Analysis of Student Loan Default

1989 ◽  
Vol 11 (1) ◽  
pp. 61-68 ◽  
Author(s):  
Laura L. Greene
Keyword(s):  
North Carolina ◽  
Economic Analysis ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Student Loan ◽  
Loan Default ◽  
Student Loan Default ◽  
Direct Student ◽  
The University

An existing model of student loan default uses discriminant function analysis to identify the characteristics of borrowers who repay their loans and those who default. This paper uses data on National Direct Student Loan borrowers at the University of North Carolina at Greensboro to confirm the results of a previous paper’s discriminant function analysis and to present an alternative method of analysis, the Tobit technique. An advantage of Tobit is that it uses information not only from the categorical default/no default decision but also from the magnitude of the default.

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