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The Implications of Graduate Labor Market Performance in Designing a Student Loan Scheme for Malaysia

  • Lim Hock-Eam
  • Russayani Ismail
  • Yusnidah Ibrahim
Part of the International Economic Association Series book series (IEA)

Abstract

This chapter examines graduate labor market performance and its implications in the design of a student loan scheme for higher education in Malaysia. The current mortgage-type loan scheme under the National Higher Education Fund Corporation (NHEFC) creates a major problem in terms of loan defaults which contribute to high implicit subsidies and concerns related to the sustainability of this scheme. With high unemployment among fresh graduates and where over-education is found to be prominent among employed graduates, it is likely that the current mortgage-type loan scheme creates a heavy burden on many graduates with relatively low incomes. The important concept relates to what is known as the ‘repayment burden’, the proportion of a debtor’s income that is required to meet repayment obligations. To understand the extent of repayment burdens, age-earnings profiles are estimated for Malaysia and it is found that the earning ability of graduates varies by level and field of study. The current mortgage-type student loans are shown to impose quite high repayment burdens, particularly for graduates in arts and social sciences, with the results helping us to understand the extent of loan defaults. Adjusting the data to include unemployed graduates, which results in a more informed repayment burden calculation, adds very considerably to our assessment of the average repayment difficulties. In assessing the efficacy of the current loan scheme, we compare the implicit subsidies under the current mortgage-type student loans with a proposed (hypothetical) income contingent loan (ICL).

Keywords

Student Loan Unemployment Duration Loan Amount Collection Cost Loan Repayment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Economics Association 2014

Authors and Affiliations

  • Lim Hock-Eam
    • 1
  • Russayani Ismail
    • 1
  • Yusnidah Ibrahim
    • 1
  1. 1.Universiti Utara MalaysiaMalaysia

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