Professor Elizabeth Savage


Professor Elizabeth Savage is one of Australia’s leading researchers on health care funding, private health insurance and health service use. Much of her experience is at the interface between research and policy.

She has two recent ARC Discovery Projects, one analysing the impact of elective surgery waiting times in public hospitals on the demand for private insurance and private hospital care, and the other modelling the structure of health care subsidies in order to determine the extent of deviations between current subsidies and alternatives based on predicted patient health risk. She is also an Associate Investigator in the ARC Centre of Excellence on Population Ageing Research. Her research on private health insurance, risk selection and waiting times won the Australian Health Economics Society Research Prize in both 2009 and 2013.

She was lead member of the Review of the Extended Medicare Safety Net which resulted in policy changes introduced in the 2009-2010 Budget. She has been a member of a Health Economics Advisory Panel for the Australian Department of Health and Ageing and an invited member of the Resource Distribution Formula Technical Committee for the NSW Department of Health.

In 2008 she was invited to give evidence to the Senate Economics Subcommittee Inquiry into the Medicare Levy Surcharge Thresholds and, in 2009, she participated in workshops for the Productivity Commission Inquiry into ‘The Performance of Public and Private Hospital Systems’ in Australia. In 2008 she was a member of the Long Term National Health Strategy group at the Australia 2020 Summit.

She was President of the NSW Branch of the Economics Society of Australia from 2005-2007 and has been on the Finance Committee  and Scientific Committees of the International Health Economics Association.

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
+61 2 9514 7722

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.

Can supervise: Yes

Book Chapters

Harris, A., Johar, M., Jones, G., Savage, E.J. & Sharma, 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

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.
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. 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.


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.