Murthy, V.N.R. | Ketenci, N.
Article | 2017 | International Journal of Health Economics and Management17 ( 1 ) , pp.29 - 50
Using a longer span of available time series data and employing powerful unit root and cointegration tests that allow for multiple structural breaks, developed recently by Carrion-i-Silvestre et al. (Econ Theory 25:1754–1792, 2009), Perron and Yabu (J Bus Econ Stat 27:369–396, 2009), Kejriwal and Perron (J Econ 146(1):59–73, 2008; J Bus Econ Stat 28(4):503–522, 2010a; J Time Ser Anal 31:305–328, 2010b) and Maki (Econ Model 29:2011–2015, 2012), this paper empirically investigates, whether technology continues to be a major driver of real per capita health expenditure, along with some control variables such as per capita income and li . . .fe expectancy, in the United States, during the period 1960–2012. Specifically, the paper applies the most recent cointegration tests under multiple structural breaks and extends the work of Okunade (J Health Econ 21(1):147–159, 2002) with the possibility whether a linear cointegration model with multiple structural breaks would provide a better economic model to quantify the impact of some major determinants of US real per capita health expenditure. This paper presents evidence to show that per capita real income, technology as indicated by four proxy measures and life expectancy at birth are some major drivers of real per capita health expenditure in the United States. Contrary to the available evidence in the literature, the finding of this paper is that the point aggregate income elasticity of health expenditure estimate is less than one, indicating that health care has evolved to become a necessity in the United States. Policy implications of the empirical findings are discussed in the paper. © 2016, Springer Science+Business Media New York
Ketenci, N. | Murthy, V.N.R.
Article | 2018 | Journal of Economics and Finance42 ( 3 ) , pp.508 - 525
In the United States, health economists, experts in population studies, and policy makers seek to understand the important factors that augment life expectancy. This paper attempts to identify empirically effects of some major determinants on life expectancy in the United States during the period 1960–2012. Recently developed powerful methods of unit root testing and cointegration analysis, Carrion-i-Silvestre et al. Economet Theor, 25, 1754–1792, (2009), Perron and Yabu J Bus Econ Stat, 27, 369–96, (2009), Kejriwal and Perron J Econ, 146(1), 59–73, (2008), Kejriwal and Perron J Bus Econ Stat, 28(4), 503–522, (2010a), and Maki Econ . . .Model, 29(5), 2011–2015, (2012) that allow for the presence of structural shifts, are employed. The papers’ findings reveal that the level of real per capita income and the level of educational attainment are the factors that affect the level of life expectancy most. Other factors such as the level of real health expenditure per capita and any measure of income inequality, although important, were found to be highly collinear with real per capita income. The policy implications of the results of the paper are discussed. © 2017, Springer Science+Business Media New York