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Determinants of healthcare expenditures in Australia: Testing the revised Newhouse conjecture on technological change effects
Albert A. Okunade (aokunade@memphis.edu) and Xiaohui You (xyou@memphis.edu)
Department of Economics, 450BB (The FCBE)
University of Memphis, Memphis, TN 38152 (USA)
Paper proposed for presentation at the 5th Biennial Conference of the American Society of Health Economists (ASHEcon).
Abstract
The income and technology change effects on health care expenditure growths have long been a central interest in health care economics and policy studies. Conceptual measures of medical technologies remain complex. Health care expenditure (HCE) researchers have used use the residual components approach or explicit technological proxies. Since Newhouse (1977, 1992), researchers model the determinants of HCE as dependent on major drivers, such as, income, insurance, age, etc. Our current study of HCE in Australia is based on unit root and cointegration tests (rules our spurious regression estimates) uses 1971-2011 macroeconomic data series and applies both the residual components method and the technology proxies approach to quantify the effects of technological changes and income on aggregate HCE. Our study is novel in that we investigate several alternative technology change proxies (input and output measures), including economy-wide R&D expenditures (capturing spillover effects), hospital sector R&D, physicians, mortality rate, and a technology index based on medical devices. Our results suggest that health care in Australia is a normal good and a technical necessity with the income elasticity, in the 0.19 - 0.85 depending on the model. The estimated technology effects of HCE, particularly those using alternative technology proxy measures and the Johansen-Juselius co-integration procedure, are in the 0.30 – 0.35 range (different from the 0.50 – 0.75 range for the US in the seminal paper by Newhouse) is close to the 0.24 – 0.48 range in the revised Newhouse (2013) study based on the US health care expenditure data. Implications of these findings are given in the context of medical technologies as a global sector.