Journal of Mathematical Sciences: Advances and ApplicationsAuthor's: DENNIS K. MURIITHI, GLADYS G. NJOROGE, MARK O. OKONGO and ELIZABETH W. NJOROGE
Pages: [1] - [17]
Received Date: June 7, 2013
Submitted by:
This paper looks into the allocations made by the Higher Education Loans Board (HELB) relative to the economic status of the student. In this paper, we modelled HELB loan application data from three public universities to determine whether the loan was allocated based on the needs of the respective applicants. The data was classified to consider the amounts awarded by the HELB. This was possible since we observed that HELB loans were awarded in distinct categories (Kshs 35,000, Kshs 40,000, Kshs 45,000, Kshs 50,000, Kshs 55,000, and Kshs 60,000). In this paper, we used multinomial logistic regression in classifying the applicants into the identified categories. The models were generated that included all predictor variables that were useful in predicting the response variable. The study revealed that the loans were not awarded based on the need of respective applicants. This has led to mis-classification when allocating loan. This study revealed that wealth, house worth, and amount of fees paid for siblings were other factors that could be considered to identify needy students. This results show that multinomial regression model gives accurate estimates that can enable HELB make a viable awarding decision thus minimizing the number of mis-classifications when awarding HELB loan, if any, although further studies may be commissioned to confirm or disapprove our findings.
regression, logistic, multinomial, higher education, loan.
