Olena joined the School in July 2007 after completing her Ph.D. at the University of Iowa.
Her research interests include Bayesian Econometrics, Health Economics and Labour Economics.
Olena's current research projects address (i) econometric modelling of health care expenditure;
(ii) the impact of public hospital waiting times on patient utilization of public and private health care services in a mixed public-private health care system;
(iii) econometric modelling of the demand for private health insurance in USA and Australia.
Labor Economics, Applied Econometrics, Bayesian Econometrics
Kettlewell, N., Stavrunova, O. & Yerokhin, O. 2018, 'Premium subsidies and demand for private health insurance: results from a regression discontinuity design', Applied Economics Letters, vol. 25, no. 2, pp. 96-101.View/Download from: Publisher's site
© 2017 Informa UK Limited, trading as Taylor & Francis Group. This article investigates the impact of a private health insurance (PHI) subsidy on the demand for PHI in the context of the Australian health care system. In particular, we focus on the subpopulation of elderly Australians and exploit discontinuous increases to the universal 'PHI rebate' that occur when people turn 65 and 70 years. Using a regression discontinuity design, we find the policy has little effect on take-up of PHI and is best interpreted as a wealth transfer to elderly Australians who already have insurance.
Stavrunova, O. & Keane, M. 2016, 'Adverse Selection, Moral Hazard and the Demand for Medigap Insurance', Journal of Econometrics, vol. 190, no. 1, pp. 62-78.View/Download from: UTS OPUS or Publisher's site
In this paper we study the adverse selection and moral hazard effects of Medicare supplemental insurance (Medigap). While both have been studied separately, this is the first paper to analyze them in a unified econometric framework. We find that adverse selection into Medigap is weak, but the moral hazard effect is substantial. On average, Medigap coverage increases health care spending by 24%, with especially large effects for relatively healthy individuals. These results have important policy implications. For instance, they imply that conventional remedies for inefficiencies created by adverse selection (e.g., mandatory enrollment) may lead to substantial health care cost increases
Stavrunova, O., Thorp, S. & Spicer, A. 2016, 'How Portfolios Evolve After Retirement: Evidence from Australia', The Economic Record, vol. 92, pp. 241-67.View/Download from: UTS OPUS or Publisher's site
Households in many countries reach retirement with lump sumsof nancial wealth accumulated in dened contribution retirementplans. Retired households need to manage risks and generateincome from their savings. We stud y the dynamics of retirementwealth and portfolio allocation using the three wealth waves of theHousehold, Income and Labour Dynamics in Australia panelsurvey. The average retired household maintained or accumulatedwealth in 2002– 2006 and decumulated in 2006– 2010 consistentwith trends in nancial asset prices. At older ages, householdsprefer portfolios with less risk and more liquidity, while maintain-ing ownership of the family home. The probability of householdsexhausting nancial assets increased over the sample, but house-holds who depleted nancial wealth did not liquidate their housingwealth at higher rates than othe r households. In contrast to theUSA, the overall effect of health shocks on the wealth of retiredAustralian households is minimal, but nancial shocks have largeeffects.
We analyze the effect of an individual insurance mandate (Medicare Levy Surcharge) on the demand for private health insurance (PHI) in Australia. With administrative income tax return data, we show that the mandate has several distinct effects on taxpayers' behavior. First, despite the large tax penalty for not having PHI coverage relative to the cost of the cheapest eligible insurance policy, compliance with mandate is relatively low: the proportion of the population with PHI coverage increases by 6.5 percentage points (15.6%) at the income threshold where the tax penalty starts to apply. This effect is most pronounced for young taxpayers, while the middle aged seem to be least responsive to this specific tax incentive. Second, the discontinuous increase in the average tax rate at the income threshold created by the policy generates a strong incentive for tax avoidance which manifests itself through bunching in the taxable income distribution below the threshold. Finally, after imposing some plausible assumptions, we extrapolate the effect of the policy to other income levels and show that this policy has not had a significant impact on the overall demand for private health insurance in Australia.
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.View/Download from: UTS OPUS or Publisher's site
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 systems core principle of equitable treatment.
Stavrunova, O. & Yerokhin, O. 2012, 'Two-part fractional regression model for the demand for risky assets', Applied Economics, vol. 44, no. 1, pp. 21-26.View/Download from: UTS OPUS or Publisher's site
Empirical studies of household portfolio choices are often interested in quantifying the effects of various covariates on the fraction of a households wealth invested in risky assets such as common stocks. The preferred econometric specification in these studies is the two-limit Tobit model, which can accommodate the fractional nature of the dependent variable. However, it is restrictive, because it assumes that the same data generating process determines both whether households participate in the stock market and the fraction of wealth invested in stocks. This article demonstrates that, in this setting, a two-part version of the fractional response model of Papke and Wooldridge (1996) constitutes an attractive alternative to Tobit by comparing the performance of the two models using data on portfolio choices of Australian households. We find that (1) the Tobit model is rejected by our data in favour of a two-part specification; and (2) marginal effects of covariates on the share of risky assets conditional on participation estimated from Tobit are confounded by the effects of these covariates on the participation decision.
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.View/Download from: UTS OPUS or Publisher's site
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.
This paper develops a smooth mixture of Tobits (SMTobit) model for healthcare expenditure. The model is a generalization of the smoothly mixing regressions framework of Geweke and Keane (J Econometrics 2007; 138: 257290) to the case of a Tobit-type limited dependent variable. A Markov chain Monte Carlo algorithm with data augmentation is developed to obtain the posterior distribution of model parameters. The model is applied to the US Medicare Current Beneficiary Survey data on total medical expenditure. The results suggest that the model can capture the overall shape of the expenditure distribution very well, and also provide a good fit to a number of characteristics of the conditional (on covariates) distribution of expenditure, such as the conditional mean, variance and probability of extreme outcomes, as well as the 50th, 90th, and 95th, percentiles. We find that healthier individuals face an expenditure distribution with lower mean, variance and probability of extreme outcomes, compared with their counterparts in a worse state of health. Males have an expenditure distribution with higher mean, variance and probability of an extreme outcome, compared with their female counterparts. The results also suggest that heart and cardiovascular diseases affect the expenditure of males more than that of females.
Stavrunova, O. & Yerokhin, O. 2011, 'An Equilibrium Model of Waiting Times for Elective Surgery in NSW Public Hospitals', Economic Record, vol. 87, no. 278, pp. 384-398.View/Download from: UTS OPUS or Publisher's site
This article studies the effects of waiting times on the demand and supply of elective surgery in NSW public hospitals. The demand and supply equations are estimated at the level of postal code areas using data on public hospital elective surgery admissions in 2004 2005, postal code area characteristics and area-level provisions of public and private hospital capacities. Empirical results imply that demand for elective surgery is affected negatively, and supply positively, by waiting time. The estimated elasticity of demand with respect to waiting time is higher in NSW than estimates reported in studies based on data from the UK National Health Service.
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.View/Download from: UTS OPUS or Publisher's site
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.
Stavrunova, O., Johar, M. & Popovski, D. 2016, 'Weather Disasters and Mental Health: The Case of Damage to Housing', European Conference on Health Economics [ECHE], Hamburg.
Stavrunova, O., Johar, M. & Popovski, D. 2017, 'Weather Disasters and Mental Health: The Case of Damage to Housing', 8th Workshop on Economics of Health and Wellbeing, Melbourne.
Stavrunova, O., Thorp, S. & Spicer, A. 2015, 'How Portfolios Evolve After Retirement: Evidence from Australia.', 11th World Congress in Health Economics (iHEA), Milan.
Stavrunova, O. 2010, 'Adverse selection, moral hazard and the demand for medigap insurance', 13th Australian Labour Econometrics Workshop, Melbourne, Australia.
Stavrunova, O. 2010, 'Adverse selection, moral hazard and the demand for medigap insurance', 19th European Workshop on Econometrics and Health Economics, Lausanne, Switzerland.
Stavrunova, O. 2010, 'Adverse selection, moral hazard and the demand for medigap insurance', Australian Health Economics Society Conference, Sydney, Australia.
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.
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.
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.
Stavrunova, O. 2009, 'Equilibrium model of waiting times for non-emergency procedures in the NSW public hospitals', 31st Australian Conference for Health Economists, Hobart, Australia.
Stavrunova, O. 2009, 'Equilibrium model of waiting times for non-emergency procedures in the NSW public hospitals', III World Conference of Spatial Econometrics, Barcelona, Spain.
Stavrunova, O. & Yerokhin, O. 2008, 'Bayesian Analysis of a Two-Part Model with Fractional Response: AnApplication to Household Portfolio Choice', Econometric Society Australasian Meeting, Wellington.
Keane, M.P. & Stavrunova, O. 2014, 'Adverse Selection, Moral Hazard and the Demand for Medigap Insurance'.
The size of adverse selection and moral hazard e ects in health insurance markets
has important policy implications. For example, if adverse selection e ects are small
while moral hazard e ects are large, conventional remedies for ine ciencies created
by adverse selection (e.g., mandatory insurance enrolment) may lead to substantial
increases in health care spending. Unfortunately, there is no consensus on the mag-
nitudes of adverse selection vs. moral hazard. This paper sheds new light on this
important topic by studying the US Medigap (supplemental) health insurance market.
While both adverse selection and moral hazard e ects of Medigap have been studied
separately, this is the rst paper to estimate both in a uni ed econometric framework.
Our results suggest there is adverse selection into Medigap, but the e ect is small.
A one standard deviation increase in expenditure risk raises the probability of insur-
ance purchase by 0.055. In contrast, our estimate of the moral hazard e ect is much
larger. On average, Medigap coverage increases health care expenditure by 24%.
Besley, Hall and Preston (JPubEc, 1999) investigate how waiting for medical treatment in
public hospitals influences the decision to buy private health insurance, which covers faster private
treatment. They find sizable positive impacts which have subsequently been influential on waiting lists
management policies. This paper re-examines this result, in particular the sensitivity to the use of
waiting lists as a proxy for waiting times. It is found that waiting lists do not predict private
health insurance demand, and that the impact of waiting time in motivating the purchase of insurance
has been overstated.
Spicer, A., Stavrunova, O. & Thorp, S. 2013, 'How Portfolios Evolve After Retirement: Evidence From Australia'.
Households in many developed economies now reach retirement with lump sums of financial wealth accumulated through defined contribution retirement plans. Managing wealth from individual accumulations and public provision is
critical to retirement welfare. We study the dynamics of retirement wealth and asset allocation using the three wealth waves of the Household Income and Labour Dynamics in Australia (HILDA) panel survey. We find significant influences
of ageing on asset holdings with older households preferring less risk and more liquidity, while maintaining ownership of the family home. In terms of absolute changes in wealth the average retired household accumulated in 2002-06 and
decumulated 2006-10 in line with financial market trends. More diversified households did better. The probability of retired households depleting non-housing wealth to less than one month's Age Pension payment increased over the
sample. Finally, in contrast to the US, the overall effect of health shocks on the wealth of retired Australian households is minimal.
One of the core goals of a universal health care system is to eliminate discrimi-
nation on the basis of socioeconomic status. We test for discrimination using patient
waiting times for non-emergency treatment in public hospitals. Waiting time should
ect patients' clinical need with priority given to more urgent cases. Using data from
Australia, we nd evidence of prioritisation of the most socioeconomically advantaged
patients at all quantiles of the waiting time distribution. These patients also bene t
from variation in supply endowments. These results challenge the universal health
system's core principle of equitable treatment.
Johar, M., Jones, G., Keane, M., Savage, E.J. & Stavrunova, O. 2010, 'Differences in waiting times for elective admissions in NSW public hospitals: A decomposition analysis by non-clinical factors. CHERE Working Paper 2010/7'.