Modeling Income Dynamics for Public Policy Design: An Application to Income Contingent Student Loans

36 Pages Posted: 31 Aug 2013

See all articles by Tim Higgins

Tim Higgins

Australian National University (ANU) - College of Business and Economics

Mathias Sinning

Australian National University (ANU) - Crawford School of Public Policy

Abstract

This paper studies the importance of dynamic earnings modeling for the design of income contingent student loans (ICLs). ICLs have been shown to be theoretically optimal in terms of efficiency in the presence of risk aversion, adverse selection and moral hazard, and have attractive equity properties. Recognition of their benefits has led to their adoption for tertiary education tuition fees in countries including Australia, New Zealand, and the UK. Since the design of ICLs relies on the prediction of the underlying costs, we explore the extent to which the complexity of earnings modeling affects the estimation of loan subsidies. The use of Australian data allows us to compare our simulated debt repayments to actual repayments under the Australian Higher Education Contribution Scheme (HECS). Our findings reveal that the complexity of earnings modeling has considerable implications for the calculation of loan subsidies.

Keywords: educational finance, dynamic stochastic modeling, panel data, income contingent loans

JEL Classification: H81, I22, C15

Suggested Citation

Higgins, Tim and Sinning, Mathias, Modeling Income Dynamics for Public Policy Design: An Application to Income Contingent Student Loans. IZA Discussion Paper No. 7556, Available at SSRN: https://ssrn.com/abstract=2318737 or http://dx.doi.org/10.2139/ssrn.2318737

Tim Higgins (Contact Author)

Australian National University (ANU) - College of Business and Economics ( email )

Canberra
Australia

Mathias Sinning

Australian National University (ANU) - Crawford School of Public Policy ( email )

ANU College of Asia and the Pacific
J.G. Crawford Building, #132, Lennox Crossing
Canberra, Australian Capital Territory 0200
Australia

HOME PAGE: http://www.mathiassinning.com

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