Results from school choice interviews – Switching schools

Switching school type – primary to secondary school

Of the 22 parents interviewed, nine families (41%) changed the type of school their children attended between primary and secondary school.  Most of these changes, five families, were from public schools to independent schools.  Two families enrolled their children in selective public schools and two families made the decision to change from a Catholic primary school to a public secondary schools. The change from Catholic public primary schools to public secondary schools was largely motivated by strong preferences for a co-education school environment.  Catholic secondary tend to be predominantly single sex schools.

Switching School - ChildSwitching schools – parents’ and children’s secondary school attended

In general choices followed the academic background of the parents.  Choices where changed either when parent schooling experience was negative or a salience characteristic of the parent school experience was missing.  For example, negative experiences from attending a regional public school leading to a preference independent school education or the absence of co-educational choice at Catholic schools leading to a change to public or independent schools.

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School choice: a qualitative exploration of behavioural decision rules involved in parental investment in education

I will be presenting this seminar/paper at Monash University, Melbourne, Thu 4 Sep 2014

School choice: a qualitative exploration of behavioural decision rules involved in parental investment in education

ABSTRACT: This seminar explores the decision architecture used by parents in choosing secondary schools for their children. I describe the preferences, concerns and constraints faced by 22 parents from across public, independent and Catholic school segments in Victoria, Australia, based on face-to-face interviews.  In particular I will focus on the complexity of the decision process faced by parents in choosing a school for their children, the potential for conflict, uncertainty over long time frames, and the diversity of factors influencing and constraining choice.  Latent semantic analysis is used to identify linguistically revealed preferences from the way parents describe their decision processes in the interviews.  Specific economic behaviour observed in the field will be discussed focusing on inter-generational discounting, decision heuristics, joint decision making, signalling and responses to ambiguity risk. The implications of behavioural decision rules and heterogeneous types of economic decision strategies on education policy will be discussed.

Education as a hedonic good

Parental investment choices concerning a child’s education are unique.  These choices involve decision behaviour more commonly associated with hedonic goods while simultaneously leading to utilitarian outcomes with objective trade-offs.  The utilitarian outcomes are clear and well documented.  For an individual, increased investment in a child’s education leads to higher future earnings, better health and increased life expectancy. Hedonic goods on the other hand are characterized by choices strongly influenced by emotional conditioning, social positioning and the context of personal expectations (Rayo & Becker 2007).   Hedonic choices are usually infrequent making it difficult to maximize utility through repetitive refinement, Arrow’s (1962) ‘learning by doing’.

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How student peers influence university attendence

Status Quo/Default option:  Once the majority of students in a peer group aspire to university (herding behaviour and information cascades) the more likely the remaining students will treat going to university as the default option, being the status quo (default option: Johnson & Goldstein 2003, status quo: Samuelson & Zeckhauser 1988).

Incomplete information & pooling benefits: All students face varying degrees of uncertainty in their decision making about university. Individually, each will possess varying levels and types of information about the benefits and constraints of attending.  The peer-effect on a student’s preference to attend university arises from the benefit of pooling information to reduce uncertainty.  As more students aspire to and explore the opportunities of university, more information becomes available to the pool of students overall.  As uncertainty decreases the more risk-adverse students will be inclined to attend university.

Socially Desirable: As more students within a peer-group aspire to university, the more salient the preference becomes. At a certain point, social desirability leads to an increased positive correlation of the preferences to attend university across the peer-group. Continue reading

Using linguistic analysis to understand how parents choose schools for their children

In economics, there is limited use of linguistic analysis to understand decision making processes and the contextual relationship between preferences.  Over the last 6 months I have undertaken field research to understand how parents choose a school for their children and the decision architecture associated with this choice.  The objective was not simply to collect information about stated preferences per se, but to understand the complexity of the decision process.   I collected 22 exploratory interviews from Melbourne and regional Victorian parents – with a reasonable level of diversity in family demographics – looking at how they approach the problem of choosing a school for their children.

The purpose of these interviews was to principally explore for interesting economic ideas and questions arising from field observations.  The intent was not to achieve a statistically robust collection of interviews of limited scope but instead to explore for opportunities that would warrant targeted econometric, experimental or theoretical research in the later part of my PhD.   The presentation I gave at the 2014 ‘Cooperation and conflict in the family’ conference on an intergenerational discount heuristic is one of the ideas that arose from these field observations/interviews.

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Demographics of parents interviewed about choice of secondary school

The table below provides some detail as to the level diversity of the interviewed parents.  It is important to note that the focus of the study was to explore and understand the decision architecture of how parents choose a school for their children.  Consequently, a degree of priority was given to finding parents who had switched schools from public to private (independent/Catholic) or from private to public in the transition from primary to secondary schooling.

demographics

Non-Catholic private schools in Australia are called ‘independent schools’ because these schools (particularly the elite schools) govern, manage, resource and finance themselves independently of any broader religious or philanthropic affiliation.

In contrast, Catholic schools are managed, financed and resourced centrally in a manner broadly similar to government run public schools but with higher levels of community involvement and direct fee payment associated with the choice of school. While there has been a trend for Independent secondary schools to move from single sex to co-educational, Catholic secondary schools in the metropolitan cities by and large are single sex schools.

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Factors influencing academic outcomes

Recently Gary Becker in the Becker-Posner blog opined that “I believe much of the blame rests with the fact that many children from minority families are raised with a single and not very educated parent, and that the quality of the schools attended by minority children is deficient.”  This is quite a pessimistic statement considering it has been 50 years since the publishing of Becker’s seminal work on the economics of human capital ‘Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education’ (1964).

Below is a high level summary of the factors effecting academic outcomes associated with school choice.

Factors influencing academic outcomes

Factors affecting academic outcomes and generational mobility are complex and highly endogenous. I will add a number of posts on this specific topic over time as I try to tease out all the factors and try to draw logical and consistent connections between these factors.

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Becker, G. S. (1964). Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education.

Social discount rate & very long term investment horizons

My interest in how discount rates are applied to investment decisions comes from my corporate background building and evaluating many business cases for large, long term projects where parameters, including the discount rate, are prone too often to gaming behaviour.  Particularly for government and semi-government organisations which don’t have the advantage of a straight forward Weighted Average Cost of Capital (WACC) calculation.

The recent paper by Gowdy et al. (2013) ‘The evolution of hyperbolic discounting: Implications for truly social valuation of the future’ made me think more about the vexed question of how the social discount rate should be calculated.  With exponential discounting, which is typically used in corporate finance, the present value of returns in future years approach zero fairly quickly.  This is problematic for social issues such as climate change, as indicated in ‘The economics of climate change’ (Stern 2007), the motivation for incurring remediation costs now is the expected positive social returns far out into the future.

Gowdy et al.’s view is that hyperbolic discounting should be used because it at least leaves a positive residual present value for long dated social returns in the future.  A hyperbolic discount rate approaches a value over time which is materially greater than zero compared to the conventional exponential discount rate that approaches zero. However, hyperbolic discounting is a behavioural heuristic which varies greatly across sections of the community.  Research conducted by Harrison et al. (2002)  ‘Estimating individual discount rates in Denmark: A field experiment’  indicated that hyperbolic discount rate between socio-economic groups can differ by around 10%, 32.9% for the poor verse 22.5% for the rich.

My view was why not just have a zero discount rate?

Interestingly in the paper ‘Are we consuming too much’, (Arrow et al 2004) the authors noted that Ramsey (1928) and Solow (1974) were of the view the social discount rate should be zero. A zero discount rate was rejected because it implies a savings rate of around 67% which economists including Arrow thought was not realistic. However, if you assume the cost of bringing up kids forms part of the investment/savings requirement, this would account for 50% outright of the 67% (leaving 17%) savings expected when the discount rate is zero. ‘Cost of raising a child in Australia’ summary data : 50% of income ~ 3 kids, middle income, after tax of 30%.

Treating the cost of raising children as ‘savings’ then makes applying a zero social discount rate to long term, inter-generational, decisions reasonable.  The difference between an optimal social consumption discount rate and zero being the ‘positive externality (outside the marketplace) from the welfare of future generations’ (Arrow et al. 2004).

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Arrow K, et al. 2004 ‘Are we consuming too much?’ The Journal of Economic Perspectives, 18(3), 147-172.

Gowdy, J., Rosser, J. B., & Roy, L. (2012). The evolution of hyperbolic discounting: Implications for truly social valuation of the future. Journal of Economic Behavior & Organization.

Harrison, G. W., Lau, M. I., & Williams, M. B. (2002). Estimating individual discount rates in Denmark: A field experiment. The American Economic Review, 92(5), 1606-1617.

Ramsey FP, 1928 ‘A mathematical theory of saving’, The Economic Journal, 38(152), 543-559.

Solow RM 1974 ‘The economics of resources or the resources of economics’, The American Economic Review, 64(2), 1-14.

Stern, N. (2008). The economics of climate change. The American Economic Review, 98(2), 1-37.

School choice and Equity: OECD Literature Review

Pauline Musset’s OECD Education Working Paper ‘School choice and equity, current policies in OECD countries and literature review’ is a great review of research exploring motivations and educational outcomes of school choice policies, with a particular focus on evidence based research.  This working paper is one of the most lucid and succinct reviews of the very contentious area of education policy and its ability to effect educational outcomes.

Some of the topics covered are:

  • self-segregation based on ability, ethnicity or socioeconomic background
  • diversity of schooling
  • performance differences across school types and countries
  • the use of vouchers and the effectiveness of different types of voucher systems
  • how school choice can exacerbate social inequity

I found Pauline Musset’s classifications of the ideological motivations for increasing school choice opportunities for parents particularly useful.  She classifies these motivations into 3 groups:

  • introduction of market mechanisms in education to remedy inefficiencies;
  • individualist-libertarian claims of a parental right for choice in education;
  • school choice as a way of making education systems more equitable.

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Musset, P. (2012), “School Choice and Equity: Current Policies in OECD Countries and a Literature Review”, OECD Education Working Papers, No. 66, OECD Publishing.

Why do Australian parents pay $5.4billion more for education than they need to?

Why are Australian parents spending an extra $5.4billion per year in school fees when socio-economic sorting across public schools would lead to the same academic outcomes?

In Australia nearly a 1/3 of children attend non-government schools, however, analysis by the Australian Council for Educational Research shows that the type of school a child attends has little impact on academic outcomes.  School academic outcomes are primarily driven by the socio-economic factors of the parents and the student peer group of the school.  ACER’s analysis of the 2009 PISA results (Thomson et al. 2010) shows that the majority, greater than 90%, of a student’s academic results are the result of either their family background or student peer effects at a particular school. These results are consistent with the recent Grattan report ‘The myth of markets in school education’ that the choice of school type had little to no influence on academic outcomes, other than the student peer effects associated with the socio-economic composition of the school student body.

If we apply the classic community optimization problem  (Tiebout 1956), in a solely public school system, families in their attempt to optimize both wealth and academic outcomes will sort themselves spatially & demographically in a way that leads to optimal choice outcomes.  In this way the benefits of a child’s socio-economic background will be matched with a student peer group of a similar socio-economic background in order achieve optimal academic outcomes for families.  Below is a conceptual diagram of the sorting.

Tiebout like sorting

While the educational outcome maybe optimal sorting, there is no net gain for the economy as what is gained at the top is given back at the bottom.  This is consistent with econometric studies in the USA (Ladd 2002). What is optimised is the wealth vs. education trade-offs for individual families.

We know that this type of Tiebout-like sorting occurs naturally within an economy from econometric studies showing a correlation between residential house prices and school quality (Black 1999).  In Canberra, Australia, a study done by Davidoff & Leigh (2008) indicated that for every 5% increase in school average academic achievement prices of houses nearby increased by 3.5%.

Tiebout like sorting - private schools

Approximately 20% of school students attend Catholic schools in Australia and another 14% attend Independent schools.  If academic outcomes are principally a function of socio-economic factors and not school type, why are Australian parents paying an extra $5.4billion per year (2009 figures) to choose a non-government school?

Is this because school choice is driven primarily by signalling of student peer group socio-economic ‘quality’ and private schools provide better signalling of this ‘quality’?  Or is school choice is driven primarily by ‘consumption’ of non-academic preferences such as teacher leadership, culture, & personal development?

I hope to answer these questions by conducting an online discrete choice experiment into school choice as part of my PhD research.

The basis for my $5.4billion calculation is:

From waterfall Graph 5 of the Gonski report, in 2009 student school attendance by type for Australia was: Gov’t 2.3million, Catholic 0.7million, Independent 0.5million. Private/parental costs per student per type are: Gov’t $0.4k, Catholic $2.6k, Independent $8.2k Deducting the Gov’t baseline parent cost of $0.4k, $5.4billion = (700k catholic students x $2.2k) + (500k Independent students x $7.8k). Note also that these school cost figures are recurrent costs/income and for both primary & secondary schools. Capital grants are excluded, mainly because capital costs have a number of sources other than parents.

It is interesting to note that the total recurrent cost of teaching a gov’t school student is $11.1k per year (2009) and that Catholic schools have a lower cost of delivery at $10k per student for what you could say is a better quality outcome.

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Black, S 1999 ‘Do better schools matter? Parental valuation of elementary education’, Quarterly Journal of Economics 114 (2), 577–599.

Davidoff, IAN & Leigh, A 2008, ‘How Much do Public Schools Really Cost? Estimating the Relationship between House Prices and School Quality’, Economic Record 84(265): 193-206.

Ladd, HF 2002, ‘School Vouchers: A Critical View’, Journal of Economic Perspectives 16(4): 3-24.

Thomson, S, De Bortoli, L, Nicholas, M, Hillman, K & Buckley, S 2010 ‘Highlights from the full Australian Report: challenges for Australian education: results from PISA 2009’, Australian Council for Educational Research.

Tiebout, CM 1956, ‘A pure theory of local expenditures’, The journal of political economy, 64(5), 416-424.

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