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Professor Elizabeth Savage


Elizabeth Savage is Professor and Head of Economics in the UTS Business School. Prior to 2011 she led the Quantitative Analysis of Health Policy program in the UTS Centre for Health Economics Research and Evaluation. She is on the editorial boards of The Economic Record and the Australian Journal of Labour Economics. She is a past President of the Economic Society of Australia (NSW) and she has been an invited member of the Scientific and Finance Committees for the International Health Economics Association.

Savage is an applied microeconomist who has had a major impact on behavioural modelling and policy evaluation in Australia in a range of areas – taxation and welfare reform, the labour market and health economics. Her research modelling the equity and efficiency effects of taxation led to an invitation to contribute the chapter on Taxation to the Cambridge Handbook of Social Sciences in Australia. This won the Australian Publishers’ Association Award for Best Scholarly Reference Book in 2004. Her 1989 Journal of Public Economics paper is cited in a survey of empirical welfare measurement in the Journal of Economic Literature. In 2004 her research initiated a methodological debate on welfare measurement in discrete choice, stated preference health settings, which changed the practice in the estimation of welfare impacts from discrete choice experiments.

She one of Australia’s leading researchers on health care funding, private health insurance, health service use, and public-private mix in health care delivery. Her 2003 Journal of Health Economics paper was the first to quantify the extent of moral hazard associated with private health insurance in Australian and one of the first internationally to jointly model insurance status and hospital use. Her research with Ellis modelled a suite of health policy reforms, showing that the 50% increase in private health insurance enrolment in 2000 was driven less by the premium reduction than by behavioural responses to the deadline and advertising. Her research with Doiron and Jones, was the first to find favourable health insurance selection in Australia and investigate the factors driving this. Her health research has twice been awarded the Australian Health Economics Society Research Prize (2009 and 2013). It also led to an invitation to contribute to the second OECD book on elective surgery waiting times. Her prominent role in health economics research is recognised by her election as a Board Member of the ARC-funded Economic Design Network and the invitation to establish the Health Economics subgroup of the Network.

As Chief or Principal Investigator she has been awarded $A9 million in peer-reviewed research funding: including $A6.826 million for an NHMRC program of research on welfare measurement and policy evaluation in the health sector; $A880,000 from the ARC for a project investigating the impacts of public hospital waiting times on the choice between private and public health care; and $A657,000 from the ARC for research on health expenditure and risk adjustment. She is also an Associate Investigator in the ARC Centre of Excellence on Population Ageing Research, awarded $A12.7 million in 2011.


Elizabeth Savage is a leading researcher on the health care sector and health policy. Throughout her career her experience is at the interface between academic research and policy.

In 1987 she advised the federal government Office of the Economic Planning and Advisory Council on taxation, labour supply, savings and risk-taking. In 1989 she wrote a commissioned paper on the distributional effects of the wage accord for Monash University’s Public Sector Management Institute. As a consultant to the World Bank, she prepared a report on behaviourally consistent analysis of policy reforms. Over a period in the early 1990s , she provided regular advice on the pricing of public services to the NSW Social Policy Directorate. She also represented the Directorate at Government Pricing Tribunal hearings on water pricing policy. In 1999 she was one of five economists invited by the Productivity Commission to prepare a paper on the future direction of microeconomic policy in Australia.

She has undertaken detailed analysis of health policy in a range of applied areas and for a range of clients (Australian Department of Health and Ageing, NSW Department of Health, Victorian Department of Treasury and Finance, NSW Treasury). In 2003 her research on bulk-billing and general practice led to an invitation to write a report for the Australian Department of Health and Ageing on reform proposals for general practice. From 2005 to 2011 she was a member of a health economics advisory panel for the Australian Department of Health and Ageing (DHA). From 2006 to 2010 she was an invited member of the Resource Distribution Formula Technical Committee for the NSW Department of Health, overseeing funding to public hospitals.

In 2008 she was invited to prepare a submission and give evidence to Senate Standing Committee on Economics Inquiry into the Tax Laws Amendment (Medicare Levy Surcharge Thresholds) Bill. In 2009 she was an invited participant at the Productivity Commission Inquiry into ‘The Performance of Public and Private Hospital Systems’.

In 2009 she was lead member of the ‘Review of the Extended Medicare Safety Net’ for DHA. The review resulted in a number of policy changes introduced in the 2009-2010 Federal Budget. In 2011 she led the team commissioned by DHA to review the 2009-10 policy changes (‘Extended Medicare Safety Net: Review Capping Arrangements Report’). The second review found that, while the capping arrangements reduced the government’s financial exposure to increases in provider fees for capped items, it had a number of unintended consequences (increased volume, expanded eligibility and increased fees for uncapped items) again resulting in policy change.

Recognition of her research achievements is demonstrated by her invitation to the Long Term National Health Strategy stream at the Australia 2020 Summit, the only academic economist invited to the group.
Image of Elizabeth Savage
Head of Economics Discipline Group, Economics Discipline Group
Core Member, Centre for the Study of Choice
BSc (Arch) Hons 1 (Syd), MSc (Econ) (LSE)
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+61 2 9514 3202

Research Interests

Private health insurance and health sector use; risk and risk selection; health system performance; behavioural modelling, welfare measurement and policy evaluation; payment mechanisms for health care providers; screening programs and access to health; obesity.

Book Chapters

Johar, M., Jones, G., Savage, E.J., Sharma, A. & Harris, A. 2013, 'Australia' in Luigi Siciliani, Michael Borowitz and Valerie Moran (eds), Waiting times policies in the health sector: What works?, OECD, US, pp. 71-97.
Hall, J.P. & Savage, E.J. 2005, 'The role of the private sector in the Australian healthcare system' in Maynard, A (eds), The Public-Private Mix for Health, Radcliffe Publishing, Abingdon, UK, pp. 247-278.
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Apps, P., Jones, G. & Savage, E.J. 2003, 'Taxation' in McAllister, I; Dowrick, S; Hassan, R (eds), The Cambridge Handbook of Social Sciences in Australia, Cambridge University Press, Cambridge, pp. 138-152.
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Conference Papers

Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2010, 'Expected waiting times and the decision to buy private health insurance', 1st Australasian Workshop on Econometrics and Health Economics, Melbourne, March 2010.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2010, 'The demand for private health insurance: Do waiting lists or waiting times matter?', American Society of Health Economists Conference, Cornell University, USA, June 2010.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2010, 'The demand for private health insurance: Do waiting lists or waiting times matter?', European Conference of Health Economics, Helsinki, Finland, July 2010.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2009, 'The influence of waiting times on the decision to purchase private health insurance', Labour Econometrics Workshop, Brisbane, August 2009.

Journal Articles

Shmueli, A. & Savage, E.J. 2014, 'Private and public patients in public hospitals in Australia', Health Policy, vol. 115, no. 2-3, pp. 189-195.
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Johar, M., Jones, G. & Savage, E.J. 2014, 'What explains the quality and price of GP services? An investigation using linked survey and administrative data', Health Economics, vol. 23, no. 9, pp. 1115-1133.
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Johar, M., Jones, G. & Savage, E.J. 2013, 'Emergency admissions and elective surgery waiting times', Health Economics, vol. 22, no. 6, pp. 749-756.
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An average patient waits between 2 and 3 months for an elective procedure in Australian public hospitals. Approximately 60% of all admissions occur through an emergency department, and bed competition from emergency admission provides one path by which waiting times for elective procedures may be lengthened. In this article, we investigated the extent to which public hospital waiting times are affected by the volume of emergency admissions and whether there is a differential impact by elective patient payment status. The latter has equity implications if the potential health cost associated with delayed treatment falls on public patients with lower ability to pay. Using annual data from public hospitals in the state of New South Wales, we found that, for a given available bed capacity, a one standard deviation increase in a hospital's emergency admissions lengthens waiting times by 19 days on average. However, paying (private) patients experience no delay overall. In fact, for some procedures, higher levels of emergency admissions are associated with lower private patient waiting times.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2013, 'Discrimination in a universal health system: Explaining socioeconomic waiting times gaps', Journal Of Health Economics, vol. 32, no. 1, pp. 181-194.
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One of the core goals of a universal health care system is to eliminate discrimination on the basis of socioeconomic status. We test for discrimination using patient waiting times for non-emergency treatment in public hospitals. Waiting time should reflect patients+ clinical need with priority given to more urgent cases. Using data from Australia, we find evidence of prioritisation of the most socioeconomically advantaged patients at all quantiles of the waiting time distribution. These patients also benefit from variation in supply endowments. These results challenge the universal health system+s core principle of equitable treatment.
Johar, M., Jones, G. & Savage, E.J. 2013, 'The effect of lifestyle choices on emergency department use in Australia', Health Policy, vol. 110, no. 2-3, pp. 280-290.
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Background: Much attention has been paid to patient access to emergency services, focusing on hospital reforms, yet very little is known about the characteristics of those presenting to emergency departments. Objectives: By exploiting linkage of emergency records and a representative survey of the 45 and older population in Australia, we provide unique insights into the role of lifestyle in predicting emergency presentations. Methods: A generalized linear regression model is used to estimate the impact of lifestyles on emergency presentations one year ahead. We control for extensive individual characteristics and area fixed-effects. Results: Not smoking, having healthy body weight, taking vitamins, and exercising vigorously and regularly can reduce emergency presentations and also prevent subsequent admissions from emergency. There is no evidence that heavy drinking leads to more frequent emergency visits, but we find a high tendency for heavy drinkers to smoke and be in poor health, which are both major predictors of emergency visits. Conclusions: Targeted public health interventions on smoking, body mass and exercise may reduce emergency visits. Effective public health interventions which target body mass, exercise, current smoking and smoking initiation, may have the effect of reducing ED usage and subsequent admission.
Ellis, R., Fiebig, D.G., Johar, M., Jones, G. & Savage, E.J. 2013, 'Explaining health care expenditure variation: Large-sample evidence using linked survey and health administrative data', Health Economics, vol. 22, no. 9, pp. 1093-1110.
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Explaining individual, regional, and provider variation in health care spending is of enormous value to policymakers but is often hampered by the lack of individual level detail in universal public health systems because budgeted spending is often not attributable to specific individuals. Even rarer is self-reported survey information that helps explain this variation in large samples. In this paper, we link a cross-sectional survey of 267?188 Australians age 45 and over to a panel dataset of annual healthcare costs calculated from several years of hospital, medical and pharmaceutical records. We use this data to distinguish between cost variations due to health shocks and those that are intrinsic (fixed) to an individual over three years. We find that high fixed expenditures are positively associated with age, especially older males, poor health, obesity, smoking, cancer, stroke and heart conditions. Being foreign born, speaking a foreign language at home and low income are more strongly associated with higher time-varying expenditures, suggesting greater exposure to adverse health shocks
Buchmueller, T.P., Fiebig, D.G., Jones, G. & Savage, E.J. 2013, 'Preference heterogeneity and selection in private health insurance: The case of Australia', Journal Of Health Economics, vol. 32, no. 5, pp. 757-767.
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A basic prediction of theoretical models of insurance is that if consumers have private information abouttheir risk of suffering a loss there will be a positive correlation between risk and the level of insurancecoverage. We test this prediction in the context of the market for private health insurance in Australia.Despite a universal public system that provides comprehensive coverage for inpatient and outpatient care,roughly half of the adult population also carries private health insurance, the main benefit of which is moretimely access to elective hospital treatment. Like several studies on different types of insurance in othercountries, we find no support for the positive correlation hypothesis. Because strict underwriting regu-lations create strong information asymmetries, this result suggests the importance of multi-dimensionalprivate information. Additional analyses suggest that the advantageous selection observed in this marketis driven by the effect of risk aversion, the ability to make complex financial decisions and income.
Johar, M. & Savage, E.J. 2013, 'Discovering unhealthiness: Evidence from cluster analysis', Annals of Epidemiology, vol. 23, no. 10, pp. 614-619.
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Purpose This study examines information on an array of health limitations, chronic conditions, treatments, and drug consumptions to reveal the prevalence and severity of unhealthiness that are not directly observed. Methods Cluster analysis is applied to 265,468 individuals who participated in the 45 and Up Study in Australia. Results Among the study participants, 8% of those age 45-54 years, 10% of those age 55-64, 13% of those age 65-74, and 17% of those age 75 and older were classified as unhealthy. For the youngest individuals, unhealthiness is characterized by moderate-to-high mental distress, a poor physical health score equivalent to the score associated with having four major limitations in physical functioning, teeth health less than good, and having been diagnosed with at least two chronic conditions. The oldest individuals also suffer from these limitations, as well as dependence on at least three different drug groups and two medical treatments, but they are in better mental health state. Conclusions Understanding unhealthiness across population groups will result in more effective allocation of health resources. Older populations require more resources to be devoted to the management of physical health and chronic illnesses.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2012, 'Geographic differences in hospital waiting times', Economic Record, vol. 88, no. 281, pp. 165-181.
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Access to elective surgery in Australian public hospitals is rationed using waiting lists. In this article, we undertake a DiNardo-Fortin-Lemieux reweighting approach to attribute variation in waiting time to clinical need or to discrimination. Using data from NSW public patients in 2004-2005, we find the discrimination effect dominates clinical need especially in the upper tail of the waiting time distribution. We find evidence of favourable treatment of patients who reside in remote areas and discrimination in favour of patients residing in particular Area Health Services. These findings have policy implications for the design of equitable quality targets for public hospitals.
King, M., Viney, R.C., Smith, D.P., Hossain, I., Street, D., Savage, E.J., Fowler, S., Berry, M.P., Stockler, M.R., Cozzi, P., Stricker, P.D., Ward, J. & Armstrong, B. 2012, 'Survival gains needed to offset persistent adverse treatment effects in localised prostate cancer', British Journal Of Cancer, vol. 106, no. 4, pp. 638-645.
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Men diagnosed with localised prostate cancer (LPC) face difficult choices between treatment options that can cause persistent problems with sexual, urinary and bowel function. Controlled trial evidence about the survival benefits of the full range of treatment alternatives is limited, and patients' views on the survival gains that might justify these problems have not been quantified. A discrete choice experiment (DCE) was administered in a random subsample (n = 357, stratified by treatment) of a population-based sample (n = 1381) of men, recurrence-free 3 years after diagnosis of LPC, and 65 age-matched controls (without prostate cancer). Survival gains needed to justify persistent problems were estimated by substituting side effect and survival parameters from the DCE into an equation for compensating variation (adapted from welfare economics). Median (2.5, 97.5 centiles) survival benefits needed to justify severe erectile dysfunction and severe loss of libido were 4.0 (3.4, 4.6) and 5.0 (4.9, 5.2) months. These problems were common, particularly after androgen deprivation therapy (ADT): 40 and 41% overall (n = 1381) and 88 and 78% in the ADT group (n = 33). Urinary leakage (most prevalent after radical prostatectomy (n - 839, mild 41%, severe 18%)) needed 4.2 (4.1, 4.3) and 27.7 (26.9, 28.5) months survival benefit, respectively. Mild bowel problems (most prevalent (30%) after external beam radiotherapy (n = 106)) needed 6.2 (6.1, 6.4) months survival benefit.
Johar, M. & Savage, E.J. 2012, 'Sources of advantageous selection: Evidence using actual health expenditure risk', Economics Letters, vol. 116, no. 3, pp. 579-582.
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In a market where insurers are not allowed to risk rate, we find evidence of advantageous selection using observed health expenditure risk. Selection is driven by income and optimism about the future. This may explain insurers' profitability, despite community rating.
Johar, M., Jones, G. & Savage, E.J. 2012, 'Healthcare expenditure profile of older Australians: Evidence from linked survey and health administrative data', Economic Papers, vol. 31, no. 4, pp. 451-463.
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This article provides a comprehensive profile of individual healthcare expenditure using the 45 and Up Study of over 267,000 NSW residents linked to administrative medical service records. Individuals aged 45 and over consume two-thirds of healthcare expenditure in Australia. We compute annual total healthcare expenditure comprising hospital admissions, emergency presentations, out-of-hospital medical consultations and diagnostic tests and subsidised drugs. The average annual expenditure in the sample is $4334 in 2009 dollars. Less than 3 per cent have zero expenditure. Health service mix varies with age, with the share of hospital expenditure increasing with age. The age trends of total expenditure and its components are then examined by key demographic, socioeconomic and health characteristics, providing important insights into future healthcare demand and a foundation for future research into the drivers of healthcare expenditures and the distribution of health subsidies.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2011, 'Waiting times for elective surgery and the decision to buy private health insurance', Health Economics, vol. 20, no. S1, pp. 68-86.
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More than 45% of Australians buy health insurance for private treatment in hospital. This is despite having access to universal and free public hospital treatment. Anecdotal evidence suggests that avoidance of long waits for public treatment is one possible explanation for the high rate of insurance coverage. In this study, we investigate the effect of waiting on individual decisions to buy private health insurance. Individuals are assumed to form an expectation of their own waiting time as a function of their demographics and health status. We model waiting times using administrative data on the population hospitalised for elective procedures in public hospitals and use the parameter estimates to impute the expected waiting time and the probability of a long wait for a representative sample of the population. We find that expected waiting time does not increase the probability of buying insurance but a high probability of experiencing a long wait does. On average, waiting time has no significant impact on insurance. In addition, we find that favourable selection into private insurance, measured by self-assessed health, is no longer significant once waiting time variables are included. This result suggests that a source of favourable selection may be aversion to waiting among healthier people.
Johar, M. & Savage, E.J. 2010, 'Do private patients have shorter waiting times for elective surgery? Evidence from New South Wales public hospitals', Economic Papers, vol. 29, no. 2, pp. 128-142.
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The Productivity Commission (2008) identified waiting times for elective surgery as a measure of governments+ success in providing accessible health care. At the 2007 COAG meeting, the Prime Minister identified reduction of elective surgery waiting times in public hospitals as a major policy priority. To date, the analysis of waiting time data has been limited to summary statistics by medical procedure, doctor specialty and state. In this paper, we look behind the summary statistics and analyse the extent to which private patients are prioritised over comparable public patients in public hospitals. Our empirical evidence is based on waiting list and admission data from public hospitals in NSW for 2004+2005. We find that private patients have substantially shorter waiting times, and tend to be admitted ahead of their listing rank, especially for procedures that have low urgency levels. We also explore the benefits and costs of this preferential treatment on waiting times.
Van Gool, K., Savage, E.J., Viney, R.C., Haas, M.R. & Anderson, R. 2009, 'Who's getting caught? An analysis of the Australian Medicare Safety Net', The Australian Economic Review, vol. 42, no. 2, pp. 143-154.
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The Medicare Safety Net (MSN) was introduced in March 2004 to provide financial relief for those who incur high out-of-pocket costs from medical services. The policy has the potential to improve equity. This study examines: (i) how the health and income profiles of small areas influence MSN expenditure; and (ii) the distribution of expenditure by medical service type. The results indicate that MSN expenditure is positively related to income and that patients who use private obstetricians and assisted reproductive services are the greatest beneficiaries. The MSN has possibly created greater inequities in Australia's health-care financing arrangements.
Van Doorslaer, E., Clarke, P., Savage, E.J. & Hall, J.P. 2008, 'Horizontal inequities in Australia's mixed public/private health care system', Health Policy, vol. 86, no. 1, pp. 97-108.
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Recent comparative evidence from OECD countries suggests that Australia's mixed public+private health system does a good job in ensuring high and fairly equal access to doctor, hospital and dental care services. This paper provides some further analysis of the same data from the Australian National Health Survey for 2001 to examine whether the general finding of horizontal equity remains when the full potential of the data is realized. We extend the common core cross-country comparative analysis by expanding the set of indicators used in the procedure of standardizing for health care need differences, by providing a separate analysis for the use for general practitioner and specialist care and by differentiating between admissions as public and private patients. Overall, our analysis confirms that in 2001 Medicare largely did seem to be attaining an equitable distribution of health care access: Australians in need of care did get to see a doctor and to be admitted to a hospital. However, they were not equally likely to see the same doctor and to end up in the same hospital bed. As in other OECD countries, higher income Australians are more likely to consult a specialist, all else equal, while lower income patients are more likely to consult a general practitioner. The unequal distribution of private health insurance coverage by income contributes to the phenomenon that the better-off and the less well-off do not receive the same mix of services. There is a risk that + as in some other OECD countries + the principle of equal access for equal need may be further compromised by the future expansion of the private sector in secondary care services. To the extent that such inequalities in use may translate in inequalities in health outcomes, there may be some reason for concern.
Doiron, D., Jones, G. & Savage, E.J. 2008, 'Healthy, wealthy and insured? The role of self-assessed health in the demand for private health insurance', Health Economics, vol. 17, no. 3, pp. 317-334.
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Both adverse selection and moral hazard models predict a positive relationship between risk and insurance; yet the most common finding in empirical studies of insurance is that of a negative correlation. In this paper, we investigate the relationship between ex ante risk and private health insurance using Australian data. The institutional features of the Australian system make the effects of asymmetric information more readily identifiable than in most other countries. We find a strong positive association between self-assessed health and private health cover. By applying the Lokshin and Ravallion (J. Econ. Behav. Organ 2005; 56:141++172) technique we identify the factors responsible for this result and recover the conventional negative relationship predicted by adverse selection when using more objective indicators of health. Our results also provide support for the hypothesis that self-assessed health captures individual traits not necessarily related to risk of health expenditures, in particular, attitudes towards risk. Specifically, we find that those persons who engage in risk-taking behaviours are simultaneously less likely to be in good health and less likely to buy insurance.
Jones, G., Savage, E.J. & Van Gool, K. 2008, 'The distribution of household health expenditures in Australia', The Economic Record, vol. 84, no. Special, pp. 99-114.
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Out-of-pocket health expenditures in Australia are high in international comparisons and have been growing at a faster rate than most other health costs in recent years. This raises concerns about the extent to which out-of-pocket costs have constrained access to health services for low income households. Using data from the ABS Household Expenditure Survey 2003-2004, we model the relationships between health expenditure shares and equivalised total expenditure for categories of out-of-pocket health expenditures and analyse the extent of protection given by concession cards. To allow for flexibility in the relationship we adopt Yatchew's semi-parametric estimation technique. This is the first detailed distributional analysis of household health expenditures in Australia. We find mixed evidence for the protection health concession cards give against high out-of-pocket health expenditures. Despite higher levels of subsidy, households with concession cards do not have lower out-of-pocket expenditures than non-cardholder households except for the highest expenditure quintile. Cards provide most protection for GP out-of-pocket expenditures
Ellis, R. & Savage, E.J. 2008, 'Run for cover now or later? The impact of premiums, threats and deadlines on private health insurance in Australia', International Journal of Health Care Finance and Economics, vol. 8, no. 4, pp. 257-277.
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Between 1997 and 2000 the Australian government introduced three policy reforms that aimed to increase private health insurance coverage and reduce public hospital demand. The first provided income-based tax incentives; the second gave an across-the-board 30% premium subsidy; and the third introduced selective age-based premium increases for those enrolling after a deadline. Together the reforms increased enrolment by 50% and reduced the average age of enrollees. The deadline appeared to induce consumers to enroll now rather than delay. We estimate a model of individual insurance decisions and examine the effects of the reforms on the age and income distribution of those with private cover. We interpret the major driver of the increased enrollment as a response to a deadline and an advertising blitz, rather than a pure price response.
Birch, S., Haas, M.R., Savage, E.J. & Van Gool, K. 2007, 'Targeting services to reduce social inequalities in utilisation: An analysis of breast cancer screening in New South Wales', Australia and New Zealand Health Policy, vol. 4:12, pp. 1-9.
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Many jurisdictions have used public funding of health care to reduce or remove price at the point of delivery of services. Whilst this reduces an important barrier to accessing care, it does nothing to discriminate between groups considered to have greater or fewer needs. In this paper, we consider whether active targeted recruitment, in addition to offering a 'free' service, is associated with a reduction in social inequalities in self-reported utilization of the breast screening services in NSW, Australia.
Viney, R.C., Savage, E.J. & Louviere, J.J. 2005, 'Empirical investigation of experimental design properties of discrete choice experiments in health care', Health Economics, vol. 14, no. 4, pp. 349-362.
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Experimental design is critical to valid inference from the results of discrete choice experiments (DCEs). In health economics, DCEs have placed limited emphasis on experimental design, typically employing relatively small fractional factorial designs, w
Lancsar, E. & Savage, E.J. 2004, 'Deriving welfare measures from discrete choice experiments: inconsistency between current methods and random utility and welfare theory.', Health Economics, vol. 13, no. 9, pp. 901-907.
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Savage, E.J. & Jones, G. 2004, 'An analysis of the general practice access scheme on GP incomes, bulk billing and consumer copayments', The Australian Economic Review, vol. 37, no. 1, pp. 31-40.
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Jones, G., Savage, E.J. & Hall, J.P. 2004, 'Pricing of general practice in Australia: some recent proposals to reform Medicare', Journal of Health Services Research and Policy, vol. 9, no. 2, pp. 63-68.
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Savage, E.J. & Wright, D.J. 2003, 'Moral hazard and adverse selection in Australian private hospitals: 1989-1990', Journal Of Health Economics, vol. 22, no. 3, pp. 331-359.
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Savage, E.J. 2003, 'Equity, payment incentives and cost control in Medicare: an assessement of the government's proposals', Health Sociology Review, vol. 12, no. 1, pp. 5-16.
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Jones, G. & Savage, E.J. 1996, 'An Evaluation Of Income Splitting With Variable Female Labor Supply', Economic Record, vol. 72, no. 218, pp. 224-235.
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Debate on the tax unit in Australia often involves claims that a system with allows spouses to split their incomes for the purposes of taxation is superior to an individual based system. In this paper we estimate a female labour supply model on data for
Savage, E.J. & Hart, A. 1995, 'Environmental policy and the theory of second best', Economic Papers, vol. 14, no. 4, pp. 1-15.
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Over the past two decades there has been growing interest in environmental policy. Lobbying by conservationists and growing community concern over pollution and the degradation of the natural environment have stimulated governments to address problems of externalities more seriously. In this policy debate the views of economists are becoming increasingly prominent. There is little doubt that economics has an important contribution to make in environmental policy, however the dominant economists' view represents quite a restricted subset of the relevant economic theory.
Apps, P. & Savage, E.J. 1989, 'Labour supply, welfare rankings and the measurement of inequality', Journal Of Public Economics, vol. 39, no. 3, pp. 335-364.
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This paper presents an analysis of inequality using utility-based measures of welfare derived from different approaches to modelling household labour supplies. The almost Ideal Demand System specification of preferences is selected for the estimation of a neoclassical household model and of individual decision models which incorporate different assumptions concerning the intra-household distribution of income using the Rosen (1976) tax perception methodology. The study also explores the implications of a model which does not constrain time at home to leisure. Welfare rankings and inequality measures defined on equivalent income are compared for each type of model. The analysis uses Australian unit record data on 3,352 households drawn from the Australian Bureau of Statistics 1981-82 Income and Housing Sample Survey file. The results indicate the sensitivity of welfare orderings and inequality measures to the choice of decision model and to the specification of lump-sum transfers between family members. A comparative study of equivalent incomes and selected money income variables also illustrates the limitations of observed household and individual incomes as welfare indicators for the analysis of inequality and for policy design

Other research activity

Cronin, P.A., Haas, M.R., Savage, E.J. & Vu, A.M. 2009, 'Misperceptions of body mass: Analysis of NSW Health Survey 2003. CHERE Working Paper 2009/7'.
Fiebig, D.G., Savage, E.J. & Viney, R.C. 2003, 'Economic analysis of inter-relationships between private health insurance & health expenditures', ARC Discovery Grant.


Van Gool, K., Savage, E.J., Johar, M., Knox, S.A., Jones, G. & Viney, R.C. 2011, 'Extended Medicare Safety Net: Review of Capping Arrangements Report 2011: a report by the Centre for Health Economics Research and Evaluation', Commonwealth of Australia, Canberra, pp. 1-130.
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The Extended Medicare Safety Net (EMSN) was introduced by the Australian Government in 2004 to provide financial relief for families and singles who incur high health-related out of pocket (OOP) costs. For those who qualify, the EMSN provides benefits in addition to the standard Medicare rebate for Medicare services provided out of hospital. Families and singles qualify for EMSN benefits once they have accumulated a given threshold in OOP costs for out of hospital services during the calendar year. After the threshold is reached, the EMSN pays 80 per cent of all OOP costs for out of hospital Medicare-related services for the remainder of the calendar year. An independent review of the EMSN, published in 2009 (the 2009 Review), found that the EMSN accounted for three per cent of total Medicare spending, but that EMSN expenditure was growing at more than twice the rate of total Medicare spending. It also found that the EMSN led to a significant increase in average provider fees, particularly in some medical speciality areas. The fee increases resulted in considerable leakage of government benefits. Over 50 per cent of all EMSN benefits contributed to the funding of obstetrics and assisted reproductive technology (ART) services. While the EMSN did make services more affordable for some (e.g. people using ART services and patients with complex conditions such as cancer), it had little impact on affordability of services for those living in more remote or in lower socioeconomic areas.
Apps, P., Ray, R. & Savage, E.J. 2004, 'The economics of a two tier health system: A fairer Medicare? Discussion Paper 478', Centre for Economic Policy Research, Australian National University, Canberra, Australia, pp. 1-24.
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This paper analyses a recent proposal of the Australian Government to reform the existing Medicare system. It develops models of the physician+s behaviour and of a household+s demand for medical insurance under the proposed system, and then proceeds to characterise the equilibrium under the new proposals. It argues that those most likely to be made worse off are low income households with children, though a full evaluation of the effects of the proposal requires it to be analysed in a public finance framework.