1999
DOI: 10.1002/(sici)1099-1050(199908)8:5<459::aid-hec454>3.3.co;2-l
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Sensitivity of elasticity estimates for OECD health care spending: analysis of a dynamic heterogeneous data field
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Cited by 37 publications
(30 citation statements)
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“…Real per capita GDP was employed as a proxy for income or economic growth, while life expectancy (LE) was used as a proxy for population health status or outcome. The relative price (RELP) is the ratio of the price index for health to the GDP deflator (Hansen and King 1996;Roberts 1999). This study covered the annual sample from 1970 to 2010.…”
Section: Data and Resultssupporting
confidence: 85%
“…Real per capita GDP was employed as a proxy for income or economic growth, while life expectancy (LE) was used as a proxy for population health status or outcome. The relative price (RELP) is the ratio of the price index for health to the GDP deflator (Hansen and King 1996;Roberts 1999). This study covered the annual sample from 1970 to 2010.…”
Section: Data and Resultssupporting
confidence: 85%
“…Regarding the long-run, they all confirm GDP as a significant driver and both PAT and LL as non-significant variables. Also, the income elasticities are all greater than one, contradicting the results obtained with the grouped FMOLS and DOLS, but in line with previous results using ARDL models (Roberts, 1999;. In the short-run, the three estimations match on showing that PHY and LL do not affect the adjustment to the long-run equilibrium relationship.…”
Section: Long and Short-run Estimationcontrasting
confidence: 43%
“…To illustrate the robustness of our results, Column (1) uses only the ‘adjusted Baumol variable’, real GDP growth and year dummies as explanatory variables. We use real GDP growth as the key control variable because in the literature, GDP is the most important variable in determining HCE (Roberts, ). Column (2) adds the ratio of fiscal expenditures to fiscal revenue, the ratio of people older than 65 years to the total population and pollution variables to the set of explanatory variables.…”
Section: Resultsmentioning
confidence: 99%
