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Spurious regression problems in the determinants of health care expenditure: a comment on Hitiris (1997)

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  • Jennifer Roberts

Abstract

In a recent article in this journal Hitiris used panel data for ten EC countries to analyse the determinants of aggregate health care expenditure. This comment shows that the model was plagued by a spurious regression problem. The data are reexamined using standard unit root and cointegration testing procedures, as well as new tests for unit roots in panels and for long-run relationships when the orders of integration of the underlying regressors are not known. There is overwhelming evidence for non-stationarity of the variables, and no conclusive evidence regarding the existence of equilibrium relationships. The apparent significance of the dependency rate and the rate of inflation in the Hitiris model were simply due to the influence of common stochastic trends. New results confirm the overriding importance of income in determining aggregate health care spending, but suggest a shortrun income elasticity significantly less than one. The results also uncover a number of problems in modelling the determinants of health care expenditure and warn against drawing firm conclusions from aggregate level models in an area where theory provides little guidance.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

Volume (Year): 7 (2000)
Issue (Month): 5 ()
Pages: 279-283

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Handle: RePEc:taf:apeclt:v:7:y:2000:i:5:p:279-283

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Cited by:
  1. Joan Costa-Font & Marin Gemmill & Gloria Rubert, 2008. "Re-visiting the Health Care Luxury Good Hypothesis: Aggregation, Precision, and Publication Biases?," Working Papers in Economics 197, Universitat de Barcelona. Espai de Recerca en Economia.
  2. Clemente, Jesus & Marcuello, Carmen & Montanes, Antonio & Pueyo, Fernando, 2004. "On the international stability of health care expenditure functions: are government and private functions similar?," Journal of Health Economics, Elsevier, vol. 23(3), pages 589-613, May.
  3. McCoskey, Suzanne K. & Selden, Thomas M., 1998. "Health care expenditures and GDP: panel data unit root test results," Journal of Health Economics, Elsevier, vol. 17(3), pages 369-376, June.
  4. Roel van Elk & Esther Mot & P.H. Franses, 2009. "Modelling health care expenditures; overview of the literature and evidence from a panel time series model," CPB Discussion Paper 121, CPB Netherlands Bureau for Economic Policy Analysis.
  5. Silvia Fedeli, 2012. "The impact of GDP on health care expenditure: the case of Italy (1982-2009)," Working Papers 153, University of Rome La Sapienza, Department of Public Economics.
  6. Jochen Hartwig & Jan-Egbert Sturm, 2012. "An outlier-robust extreme bounds analysis of the determinants of health-care expenditure growth," KOF Working papers 12-307, KOF Swiss Economic Institute, ETH Zurich.
  7. Esther Stroe-Kunold & Joachim Werner, 2009. "A drunk and her dog: a spurious relation? Cointegration tests as instruments to detect spurious correlations between integrated time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(6), pages 913-940, November.
  8. Paresh Kumar Narayan, 2010. "Modelling health and output at business cycle horizons for the USA," Health Economics, John Wiley & Sons, Ltd., vol. 19(7), pages 872-880.
  9. Amiri, Arshia & Ventelou, Bruno, 2012. "Granger causality between total expenditure on health and GDP in OECD: Evidence from the Toda–Yamamoto approach," Economics Letters, Elsevier, vol. 116(3), pages 541-544.

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