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Generalized cointegration: a new concept with an application to health expenditure and health outcomes

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  • Stephen Hall
  • P. Swamy
  • George Tavlas

Abstract

We propose a new generalization of the concept of cointegration that allows for the possibility that a set of variables are involved in an unknown nonlinear relationship. Although these variables may be unit-root non-stationary, there exists a nonlinear combination of them that takes account of such non-stationarity. We then introduce an estimation technique that allows us to test for the presence of this generalized cointegration in the absence of knowledge as to the true nonlinear functional form and the full set of regressors. We outline the basic stages of the technique and discuss how the issue of unit-root non-stationarity and cointegration affects each stage of the estimation procedure. We then apply this technique to the relationship between health expenditure and health outcomes, which is an important but controversial issue. A number of studies have found very little or no relationship between the level of health expenditure and outcomes. In econometric terms, if there is such a relationship then there should exist a cointegrating relationship between these two variables and possibly many others. The problem that arises is that we may be either unable to measure these other variables or that we do not know about them, in which case we may incorrectly find no relationship between health expenditures and outcomes. We then apply the concept of generalized cointegration; we obtain a highly significant relationship between health expenditure and health outcomes.
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  • Stephen Hall & P. Swamy & George Tavlas, 2012. "Generalized cointegration: a new concept with an application to health expenditure and health outcomes," Empirical Economics, Springer, vol. 42(2), pages 603-618, April.
    • Handle: RePEc:spr:empeco:v:42:y:2012:i:2:p:603-618
    DOI: 10.1007/s00181-011-0483-y
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    14. P. Swamy & I-Lok Chang & Jatinder Mehta & George Tavlas, 2003. "Correcting for Omitted-Variable and Measurement-Error Bias in Autoregressive Model Estimation with Panel Data," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 225-253, October.
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    16. I-Lok Chang & P.A.V.B. Swamy & Charles Hallahan & George S. Tavlas, 2000. "A Computational Approach to Finding Causal Economic Laws," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 105-136, October.
    17. Alan M. Garber & Jonathan Skinner, 2008. "Is American Health Care Uniquely Inefficient?," NBER Working Papers 14257, National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:

    1. Stephen G. Hall & Heather D. Gibson & G. S. Tavlas & Mike G. Tsionas, 2020. "A Monte Carlo Study of Time Varying Coefficient (TVC) Estimation," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 115-130, June.
    2. Stephen G. Hall & P. A. V. B. Swamy & George S. Tavlas, 2012. "Milton Friedman, the demand for money, and the ECB’s monetary policy strategy," Review, Federal Reserve Bank of St. Louis, vol. 94(May), pages 153-186.
    3. Hall Stephen G. & Kenjegaliev Amangeldi & Swamy P. A. V. B. & Tavlas George S., 2013. "The forward rate premium puzzle: a case of misspecification?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 265-279, May.
    4. Hall, Stephen G. & Hondroyiannis, George & Kenjegaliev, Amangeldi & Swamy, P.A.V.B. & Tavlas, George S., 2013. "Is the relationship between prices and exchange rates homogeneous?," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 411-438.
    5. Rezwanul Hasan Rana & Khorshed Alam & Jeff Gow, 2020. "Health expenditure and gross domestic product: causality analysis by income level," International Journal of Health Economics and Management, Springer, vol. 20(1), pages 55-77, March.
    6. P.A.V.B. Swamy & George S. Tavlas & Stephen G. Hall, 2015. "On the Interpretation of Instrumental Variables in the Presence of Specification Errors," Econometrics, MDPI, vol. 3(1), pages 1-10, January.
    7. Omotor, Douglason G., 2019. "A Thrifty North and An Impecunious South: Nigeria's External Debt and the Tyranny of Political Economy," MPRA Paper 115292, University Library of Munich, Germany, revised 12 Oct 2019.
    8. Gallet, Craig A. & Doucouliagos, Hristos, 2017. "The impact of healthcare spending on health outcomes: A meta-regression analysis," Social Science & Medicine, Elsevier, vol. 179(C), pages 9-17.
    9. Paleologos, John M. & Polemis, Michael L., 2013. "What drives investment in the telecommunications sector? Some lessons from the OECD countries," Economic Modelling, Elsevier, vol. 31(C), pages 49-57.

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    More about this item

    Keywords

    Generalized cointegration; Non-stationarity; Time-varying coefficient model; Coefficient driver; C130; C190; C220;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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