Spurious correlation in estimation of the health production function: A note
AbstractIn this paper, we address the issue of spurious correlation in the production of health in a systematic way. Spurious correlation entails the risk of linking health status to medical (and nonmedical) inputs when no links exist. This note first presents the bounds testing procedure as a method to detect and avoid spurious correlation. It then applies it to a recent contribution by Lichtenberg (2004), which relates longevity in the United States to pharmaceutical innovation and public health care expenditure. The results of the bounds testing procedure show longevity to be linearly related to these two factors. Therefore, the estimates reported by Lichtenberg (2004) cannot be said to be result of spurious correlation, to the contrary, they very likely reflect an effective relationship, at least for the United States.
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Bibliographic InfoPaper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 09-227.
Length: 15 pages
Date of creation: May 2009
Date of revision:
Health; Life expectancy; Innovation; Pharmaceuticals; Health care expenditure; Cointegration;
Other versions of this item:
- Sule Akkoyunlu & Frank R. Lichtenberg & Boriss Siliverstovs & Peter Zweifel, 2010. "Spurious correlation in estimation of the health production function: A note," Economics Bulletin, AccessEcon, vol. 30(3), pages 2505-2514.
- Sule Akkoyunlu & Frank R. Lichtenberg & Boriss Siliverstovs & Peter Zweifel, 2009. "Spurious correlation in estimation of the health production function: A note," SOI - Working Papers 0903, Socioeconomic Institute - University of Zurich.
- H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
- I12 - Health, Education, and Welfare - - Health - - - Health Production
- J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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