15% universal loan fee for HECS/HELP

The Grattan Institute released a report calling for a universal 15% loan fee to be added when student incur a higher education HECS/HELP liability.  Reasoning behind a 15% loan fee is that it would go towards offsetting the interest-rate subsidy students receive as a result of their HECS/HELP liability being indexed at the rate of CPI (currently 1.3%).  That is, a real rate of interest that is zero. As opposed to the Commonwealth Government actual cost of funding which is closer to 2.75% (current 10 year bond yield).  In 2015/2016 this interest rate subsidy was around $550million for the year on total outstanding HECS/HELP liabilities of around $40billion. Bruce Chapman also wrote an article for The Conversation supporting the idea of a 15% loan fee.

Below are my reasons why a 15% universal loan fee is a far better idea than alternative proposals for reducing the funding burden of HECS/HELP. Not just the interest-rate subsidy that makes HECS fair for all types of students with many different backgrounds but also the implicit understanding that some students will fail to repay their HECS liability due to simple bad luck and the uncertainty of life.

The key purpose of HECS is to provide all students with an opportunity to participate in higher education.  In order to give as many students as possible this opportunity it is logical that the underlying risk of some HECS debt will never being repaid will rise. Given that individuals tend to under-invest in education due to risk aversion associated with complex choices (especially students from low socio-economic backgrounds), the economic upside of increasing the freedom of choices in quality education is greater than any downside of some HECS never being repaid.

However, since a student’s HECS liability is capped the cost of any downside from students being unable to repay their HECS liability rests with the government.  This raises the question as to whether the cost should be borne by the government and hence all taxpayers or by the taxpayers who benefit from accessing HECS to participate in higher education.  If it is the later, there are a number of options to recover the cost of non-payment of HECS: a) increase the rate of interest on outstanding HECS, b) lower the repayment threshold, c) increase the marginal tax rate contribution, d) recover outstanding HECS liability from deceased estates, or e) an upfront fee retained by the government (and not paid to the higher education provider).

Of the five options, two are particularly problematic.

Increasing the interest rate on HECS liability above CPI (i.e. any real interest rate greater than zero) leads to discriminatory impacts on individuals with differing life-histories. In particular, a key reason for having a zero real rate of interest on ICLs/HECS is to address the gender asymmetry in life history.  Simply, a real rate of interest greater than zero discriminates against women.  But a zero real rate of interest also helps those who experience bad luck or take longer to benefit from the returns of higher education such as disabled students or those from low socio-economic backgrounds lacking the social capital to fully exploit the benefits of their education.

Recovering outstanding HECS liability from deceased estates gives rise to two counter-productive impacts. Firstly, by recovering outstanding HECS liabilities from deceased estates the key idea of HECS protecting students from the downside of choices in higher education is removed. Choices once again become risky, leading to an under-investment in education due to risk aversion. An outcome that will particularly effect students from less wealthy or lower socio-economic backgrounds. Secondly, it will only take a salient few cases where a young family loses their home due to a mother or father dying from misfortune for students to think twice about incurring a HECS liability. Not all people with an outstanding HECS liability die old.

The remaining three options do not give to serious social equity impacts.  Although they are not perfect.

Lowering the repayment threshold means that some students maybe repaying their HECS liability before they receive any increase in earnings from their investments in education.  A lower repayment threshold also increases the perceived ‘upfront’ cost of education which may lead to choice inertia where students choose not to participate in higher education.

In Australia the marginal HECS tax rate contribution is applied to all income in much the same way as the Medicare levy.  Although the rate varies depending on income levels, a less regressive approach is to apply a higher marginal HECS rate only for income above the HECS threshold as is done in the UK and New Zealand.  However, the salience of a higher tax rate may lead to some students questioning the value of their investment in education.

Similarly, a 15% surcharge may also lead to some students reconsider their investment in higher education.  However, previous policy changes have shown that students do not modify their choice behaviour when student contribution amounts change.  Applying subsidies to student contributions for STEM subjects did not increase demand for these subjects nor did demand change when these subsidies were removed.  There is also a concern that by adding a surcharge students will take longer to pay off their HECS liability.  But if the real interest rate is zero (no higher than CPI rate) there is no additional penalty for students that take longer to pay-off their HECS liability.

In addition to the above, a 15% surcharge is simple and transparent.  It keeps government transaction costs low and from a behavioural economics perspective does not increase choice complexity and therefore is unlikely to impact higher education participation.

Debt-free path to innovation

Leaver, S. Potts, J. 2016, ‘Debt-free path to innovation’, Institute of Public Affairs Review: A Quarterly Review of Politics and Public Affairs, 68-2


Not-for-Debt (NfD) companies: A new exemption class for innovation start-ups.

There are already a number of different regulatory types of firms available, such as sole-trader, partnerships, private companies and public companies. However, a unique characteristic of start-ups firms is that they are more likely to fail than succeed. There is no company type available within the current regulatory framework that implicitly recognises this risk profile of start-up firms.

Malcolm Turnbull wants to reform corporate regulation – particularly to soften Australia’s rather punitive bankruptcy provisions – to create new start-up friendly business laws. The National Science and Innovation Agenda Report proposes to reduce bankruptcy from three years to one year, allow directors to trade while insolvent, and stop counterparties from terminating dealings with insolvent companies.

Corporate regulation was never designed or intended to promote new business growth, but rather to control existing and particularly large, mature businesses. For the most part, it does this successfully. However, Turnbull’s proposals fail to make a fundamental distinction between two very different types of firm failure. For start-up firms, particularly in the technology sector, a high failure rate is not only normal, it is often desirable. It’s a sign of experimental undertakings and rapid learning.

Changing the bankruptcy period from three years to one isn’t much of an incentive and won’t change reputational risk associated with the stigma of bankruptcy. Bankruptcy appears on credit reports for five years and remains on a public National Personal Insolvency Index for life. Although directors of insolvent firms are protected from liability for a company’s debt, the risk of significant penalties remain. Individuals can be barred for five years from directorships if they have been a director of more than two insolvent companies within seven years. Being a director of a company that trades while insolvent can lead to criminal penalties and potentially being liable for debts incurred while insolvent.

Applying the current bankruptcy and insolvency framework to innovation firm start-ups – where failure is treated as an exception – makes no sense. Continue reading

Six keys to making high school choices

An article on my research in the Sun Herald, Sydney, 7 Aug 2016

Understanding the behavioural economics behind choosing a school can save parents a lot of time, writes JAMES MELOUNE

Education is the bedrock of a prosperous society. However the responsibility for getting education “right” and wealth of school choices can be bewildering for some parents.

The behavioural economics behind decisions parents make has prompted Sean Leaver, a former banker, to survey parents. Leaver, a PhD candidate at Melbourne’s RMIT University, has surveyed more than 800 families. His thesis, Behavioural Economics and the Complexity of School Choice, has found there are six keys to high school choice.


Leaver’s study found that parents fall into one of five groups, based on what they feel is most important for their child’s development. Continue reading

Applying big-data techniques to small-data: Latent Semantic Analysis of interviews investigating reasons for parents’ choice of school

A paper I’m working on at the moment.

Applying big-data techniques to small-data: Latent Semantic Analysis of interviews investigating reasons for parents’ choice of school

ABSTRACT    In economics, preferences are revealed from the measurable attributes of actual choices. However, choices in education are complex. Many factors underlie the decision processes associated with how parents choose a school for their children. In-depth interviews investigating how and why parents choose a particular school for their children suggest that there are a wide variety of attributes playing an important role in this process.  For economic analysis these attributes are not easily identified and measured within a traditional revealed preference framework. In this study I apply latent semantic analysis to a set of 22 open-ended interviews exploring how and why parents choose a particular school for their children to extract latent choice attributes in a measurable form.  Latent semantic analysis is used to elicit key words from these interviews to reveal those attributes  associated with a parent’s actual choice of school. These words, such as ‘encourage’ and ‘support’, represent particular choice mindsets that frame a wide range of possible choice attributes into a smaller bundle of evaluated attributes that can be mapped to a parent’s actual choice.  Latent semantic analysis is used to first calculate the semantic distance between individual interviews and a set of target words.  Semantic distances are then statistically analysed for clustering subject to school-type (such a public, independent, Catholic and government selective). These semantically revealed words can then be analysed in a more traditional economic framework as trade-offs between particular preference attributes. Importantly, this analysis indicates that there exist distinct groups of parents who are motivated by different choice mindsets but ultimately choose the same type of school. Some of the advantages and disadvantages of applying big-data techniques to small-data sets of relatively large open-ended text responses are discussed.

Some readings (& podcast) putting Randomized Control Trials (RCT)s into perspective

Like incentivised laboratory experiments Randomized Control Trials (RCTs) are all the rage in economics.  RCTs are commonplace in the health sector starting with Pasteur’s first controlled trials 200 years ago. While application of RCTs to social sciences is relatively recent.

However, by their very nature social sciences involve researching social groups and networks where information is distributed and co-ordinated with relative ease and frequency.

This creates a unique problem for RCTs in social research because it is very difficult to construct experiments that are able to completely seal information within evaluated units.  Importantly, the closer the social networks of individuals the more likely there will be information contamination and that individuals in the ‘control’ condition will act on this information.

Individuals in the ‘control’ group on learning about the conditions of the ‘intervention’ group may seek their own alternative solutions or act adversely due to the perception of being excluded. Heckman’s discussion of how social networks in groups make RCTs difficult in social sciences is particularly relevant to policy interventions in the education space.  Education by its very nature is a learning space within which social groups actively share information.

‘The Problem With Evidence-Based Policies’
A good review of RCT in economics and policy interventions.

‘James Heckman on Facts, Evidence, and the State of Econometrics’
Heckman raises the problem of trying to do RCTs in a social environment when social networks of groups are closely linked (as in schools & social groups).  He discusses this impact on HIV RCT clinical trials and education/work based interventions.

‘Experimental Conversations: Nobel Winner Angus Deaton’
Deaton is in the longitudinal study camp.

For those interested the problem of endogeneity in economic behaviour due to social interactions and beliefs:

‘Striving for balance in economics: towards a theory of the social determination of behaviour’.
Karla Hoff & Joseph Stiglitz


An Incentive Compatible Model for Higher Education deregulation

Given the level of opportunism occurring in the Australian Vocational Education & Training higher education sector since deregulation (uncapping places & fees), recent articles:

I think it is worth reblogging my Senate submission (Feb 2015) suggesting a new incentive compatible model for a deregulated higher education market where education providers have ‘skin in the game’.  This Senate submission provided a solution to what I saw as a fundamental misunderstanding of the risks associated with deregulating higher education within the current policy framework, published as an opinion piece in The Australian (Oct 2014):

This was followed up by an article calling for universities to have more ‘skin in the game’ (Mar 2015):

I presented this model at the ANU Forum on Higher Education Financing, Friday 13th August 2015, on the topic ‘Should universities have skin in the game?’.

This model can be applied to any type of higher education provider where students have access to government administered income-contingent loans. Whether providers be universities, vocational, professional bodies or dedicated postgraduate institutions.  This model can even be applied to specific types of courses which are regulated separately, such as proposed Australian university flagship courses.

Continue reading

What drives increases in University fees? Bennett hypothesis vs Baumol’s cost disease

Over the last 15 years, increases in higher education fees have accelerated and are now rising faster than any other part of the economy.  Outstripping even the rising cost of medicine and health care.  And yet we see no meaningful improvements in productivity or GDP growth over the same time period.  Since 1978, the cost of higher education has increased in the US by 1,120% – more than 11 times.  This graph from Bloomberg clearly illustrates the anomaly of higher education fee inflation.

 Bloomberg tuition (s)Source: Bloomberg, Data: Bloomberg Labor Department

 What’s driving higher education fees higher? 

What we see in the wider economy does not justify an explanation that fees are increasing in line with improved earnings expectations.  There is some improvement in earnings overall but productivity and GDP are not rising anywhere near as fast to justify this optimism.  If we had a matching 1,120% increase in productivity or GDP over the last 30 years the world economy would be a lot more rosier place than it is at the Continue reading

Breaking down the myth that we need competition to make education policy work

An article published in The Australian today Push for universities to share students‘ discussed some of my views regarding the lessons we have learnt from deregulating the schools sector and the consequential impact on the ‘market’ dynamics of educational institutions (i.e. how universities behave).  One of the myths put forward as a reason for deregulating fees within the higher education sector in Australia is the (misguided) belief that competition in student fees will lead to institutional diversity.  However, when it comes to experience goods in education, student (parent) risk aversion leads to a strong preference for universities (schools) to offer the largest range of subjects possible given available funds.  This leads to the crowding of efficiencies from specialization and potentially sacrifices educational quality if the competition is intense.

The main driver of student (parent) risk aversion is the high switching costs associated with changing misinformed choices.  This happens a lot with experience goods where there is little opportunity to repeatedly test choices.  Choices in education are completely different to consumer purchases of milk or bread for example.  Where a bad choice is low cost and easily rectified. Continue reading

ANU Forum on Higher Education Financing

I will be presenting at the ANU Forum on Higher Education Financing, Friday 13th August 2015, on the topic ‘Should universities have skin in the game?’ based on my Senate submission ‘An Incentive Compatible Model for Higher Education deregulation’

Details on the conference: Continue reading

Behavioural Education Economics

My academic paper on the ‘Behavioural Education Economics’ is now up on the web.  This will be a chapter in a forthcoming handbook on Behavioural Economics, due out Sep 2016..

ABSTRACT    The purpose of ‘Behavioural education economics’ is to understand the psychological factors influencing student performance and educational choices. One of the key insights of behavioural education economics is that educational decision making is characterised by choices which are usually not repeated and rely heavily on heuristics to solve complex choices in the absence of prior learning. At the heart of behavioural education economics is an understanding that academic outcomes are malleable. That investment decisions associated with education are primarily driven by non-cognitive behaviours and cognitive biases that affect participation in education and subsequently motivations to commit resources to these investments and maintain these choices over time. The focus of this paper will be on three key non-cognitive behaviours associated with choices in education that impact the quality of investments in education: self-control, self-efficacy and identity.

The paper can be accessed via this link:

Problem of rational adaptive behaviour in at-risk youth

Heller, S. B., Shah, A. K., Guryan, J., Ludwig, J., Mullainathan, S., & Pollack, H. A. (2015). Thinking, Fast and Slow? Some Field Experiments to Reduce Crime and Dropout in Chicago (No. w21178). National Bureau of Economic Research.

ABSTRACT This paper describes how automatic behavior can drive disparities in youth outcomes like delinquency and dropout. We suggest that people often respond to situations without conscious deliberation. While generally adaptive, these automatic responses are sometimes deployed in situations where they are ill-suited. Although this is equally true for all youths, disadvantaged youths face greater situational variability. This increases the likelihood that automaticity will lead to negative outcomes. This hypothesis suggests that interventions that reduce automaticity can lead to positive outcomes for disadvantaged youths. We test this hypothesis by presenting the results of three large-scale randomized controlled trials (RCTs) of interventions carried out on the south and west sides of Chicago that seek to improve the outcomes of low-income youth by teaching them to be less automatic. Two of our RCTs test a program called Becoming a Man (BAM) developed by Chicago-area non-profit Youth Guidance; the first, carried out in 2009-10, shows participation improved schooling outcomes and reduced violent-crime arrests by 44%, while the second RCT in 2013-14 showed participation reduced overall arrests by 31%. The third RCT was carried out in the Cook County Juvenile Temporary Detention Center (JTDC) in 2009- 11 and shows reductions in return rates of 21%. We also present results from various survey measures suggesting the results do not appear to be due to changes in mechanisms like emotional intelligence or self-control. On the other hand results from some decision-making exercises we carried out seem to support reduced automaticity as a key mechanism. Continue reading

Behavioural economics and the complexity of school choice

This is the abstract for a seminar I presented to the Victorian Dept. of Education and Training on the 13th April 2015 on behavioural economics and the complexity of school choice.

ABSTRACT  The purpose of this seminar is to present research investigating the decision architecture of how parents choose a school for their children through the lens of behavioural economics. The research focuses on providing insights into the following key questions : To what extent does active choice exist and is there choice inertia? What are the decision rules parents use to overcome complexity and limited opportunities for learning? What are the choice attributes that motivate a parent’s choice of school?  Do parent behave differently when making educational choices for their children compared to other economic decisions? And is there a relationship between the behavioural components of the decision making and the type of school chosen?  The talk will also focus on how behavioural economics can inform research design. Using exploratory interviews of parents to observe economic decision making in the field. Relating these observations back to economic theory to generate possible explanations for choice behaviour. And then subsequently testing these hypotheses by going back into the field and collecting quantitative evidence.  Both the implications of my results and the general application of behavioural economics to education policy will be discussed.

Call for unis to carry HECS loans risk

I was interviewed yesterday on my submission to the Australian Senate inquiry into higher education deregulation.

“Vice chancellors are being disingenuous at the moment. They are freeloading and are comfortable with the government taking all the risk. They need to get out of the sandpit and into the real world,”

The attached pdf is a copy of the resulting article in The Australian today.

Call for unis to carry HECS loans risk

An Incentive Compatible Model for Higher Education deregulation

On Friday I made a submission to the Senate Inquiry into “The principles of the Higher Education and Research Reform Bill 2014, and related matters”.  The submission was accepted and now available for public release (attached).

In summary: “The purpose of this submission is to suggest a model which combines the social equity benefits of Income-contingent Loans with a market design that is ‘incentive compatible’ through an appropriate price discovery mechanism.”

The model seeks to ensure ‘incentive compatibility’ between the social objectives of Income-Contingent Loans and market objectives of returns to investments in education being optimised. Continue reading

Research Plan – papers to be written based on Survey Results

Papers I’m preparing based on results from the School Choice survey

1.  Six rules parent’s use to solve the problem of complexity and uncertainty in school choice

2. Extent to which children participate in school choice

3. Complexity of school choice, joint decision making and the potential for conflict

4. Quantity and Quality of Children: Why parent education trumps wealth

5. Intergenerational stickiness of school choice: An Australian perspective

6. The Alchian-Allen effect in school choice: School travel time and a child’s ability

7. To what extent does active school choice exist in Australia?

8. Determinants of school choice: What motivates parents to choose a particular school?

9. Big-5 personality traits and a parent’s choice of school

10. The value of Field Economics: An exploration of school choice in Australia

11. Hardest decision parents will make: School Choice

12. Social Preferences of Australian Parents & School Choice

Plus I need to submit the following paper soon:

1.  Behavioural education economics

Why research reputation trumps teaching reputation in universities

Submitted to the Journal for Brief Ideas

Why research reputation trumps teaching reputation in universities

In humans we see lekking behaviour in the general rule that people like being around successful people. This is why social A-lists exist. More generally as animal behaviour, a lek is a gathering of individuals for the purposes of competitive display – competitive signalling. For universities, A-list researchers attract other high quality researchers and also crucially high quality teachers. Why is this important for attracting high quality teachers? Academics themselves are generally seen to be sensitive to reputational influences of their peer group. High quality teachers will be hesitant to join to a university who’s reputation is ambiguous (uncertainty as to rank). The solution is to have an unambiguous reputational signal. However, the signal needs to overcome the problems of asymmetric information associated with the observation (‘measurement’) of quality. It is for this reason that research reputation trumps teaching reputation. Research reputation is a less ambiguous signal as a result of the strength of external validation – active peer review in both academic and public domains (media). Teaching reputation is harder to validate outside the university in which it occurs, leading to the problem of asymmetric information.

Leaver S 2015 ‘Why research reputation trumps teaching reputation in universities’ Journal for Brief Ideas, Zenodo,10.5281/zenodo.15414

Survey demographics – School Choice

The surveys generated a representative spread of parent backgrounds, including age, education level and household income.

parent demographics2

The survey also generated a good spread of secondary school types attended by children. A situation where children in one family attend more than one school type (Mixed) is likely to occur because of 1) individual children gaining selective entry or Continue reading

‘Determinants of Parent School Choice’ Online Survey – the Results

This post will provide updated links to results as I post them. Posts will initially focus on straight forward results associated with specific questions, before proceeding onto more complex statistically analysis of relationships between questions. Continue reading

‘Determinants of Parent School Choice’ Online Survey

I’m a PhD student at RMIT investigating the underlying motivations of parent school choice from an economics perspective.  The objective of this research is to understand the behavioural decision rules used by parents in choosing schools for their children.  This survey is anonymous and may take up to 30 mins to complete. A brief bio about myself can be found here.

——————————————– The survey is now closed —————————–

The key focus of this survey is the idea that education is an investment in a child’s future. Consequently, investments in a child’s education (such as school choice) are generally considered to be governed by the same general economic principles that we see in similarly complex decision making. However, parents usually make these decisions with limited time and resources.  This survey seeks to test this assumption by understanding the relationship between school choices and economic behaviour linked to risk and social preferences.  We draw on insights from behavioural economics to test whether decision behaviour is consistent across different types of choices and different contexts in which choices are made. This survey follows on from my qualitative research into school choice (Victoria, Australia).  It also draws on some interesting observations coming out of the linguistic analysis of these qualitative interviews which indicated the potential existence of distinct economic decision types influenced by economic risk and social preferences.  The survey also draws inspiration from Jonathon’s Haidt’s research on how ‘Liberals and conservatives rely on different sets of moral foundations’. The other investigators for this research project are my PhD supervisors Professor Jason Potts, Dr Foula Kopanidis from RMIT’s School of Economics, Finance & Marketing and the research has been approved by RMIT’s Human Research Ethics committee (No.18945).

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