Skip to main content
Top
Published in: International Journal of Health Economics and Management 1/2020

01-03-2020 | Shock | Research article

Health expenditure and gross domestic product: causality analysis by income level

Authors: Rezwanul Hasan Rana, Khorshed Alam, Jeff Gow

Published in: International Journal of Health Economics and Management | Issue 1/2020

Login to get access

Abstract

The empirical findings on the relationship between gross domestic product (GDP) and health expenditure are diverse. The influence of income levels on this causal relationship is unclear. This study examines if the direction of causality and income elasticity of health expenditure varies with income level. It uses the 1995–2014 panel data of 161 countries divided into four income groups. Unit root, cointegration and causality tests were employed to examine the relationship between GDP and health expenditure. Impulse-response functions and forecast-error variance decomposition tests were conducted to measure the responsiveness of health expenditure to changes in GDP. Finally, the common correlated effects mean group method was used to examine the income elasticity of health expenditure. Findings show that no long-term cointegration exists, and the growth in health expenditure and GDP across income levels has a different causal relationship when cross-sectional dependence in the panel is accounted for. About 43% of the variation in global health expenditure growth can be explained by economic growth. Income shocks affect health expenditure of high-income countries more than lower-income countries. Lastly, the income elasticity of health expenditure is less than one for all income levels. Therefore, healthcare is a necessity. In comparison with markets, governments have greater obligation to provide essential health care services. Such results have noticeable policy implications, especially for low-income countries where GDP growth does not cause increased health expenditure.
Appendix
Available only for authorised users
Literature
go back to reference Abrigo, M. R., & Love, I. (2016). Estimation of panel vector autoregression in Stata. Stata Journal,16, 778–804.CrossRef Abrigo, M. R., & Love, I. (2016). Estimation of panel vector autoregression in Stata. Stata Journal,16, 778–804.CrossRef
go back to reference Acemoglu, D., & Johnson, S. (2007). Disease and development: The effect of life expectancy on economic growth. Journal of Political Economy,115(6), 925–985.CrossRef Acemoglu, D., & Johnson, S. (2007). Disease and development: The effect of life expectancy on economic growth. Journal of Political Economy,115(6), 925–985.CrossRef
go back to reference Adriana, D. (2014). Revisiting the relationship between unemployment rates and shadow economy. A Toda–Yamamoto approach for the case of Romania. Procedia Economics and Finance,10, 227–236.CrossRef Adriana, D. (2014). Revisiting the relationship between unemployment rates and shadow economy. A Toda–Yamamoto approach for the case of Romania. Procedia Economics and Finance,10, 227–236.CrossRef
go back to reference Asteriou, D. (2009). Foreign aid and economic growth: New evidence from a panel data approach for five South Asian countries. Journal of Policy Modeling,31(1), 155–161.CrossRef Asteriou, D. (2009). Foreign aid and economic growth: New evidence from a panel data approach for five South Asian countries. Journal of Policy Modeling,31(1), 155–161.CrossRef
go back to reference Baltagi, B. H., Lagravinese, R., Moscone, F., & Tosetti, E. (2017). Health care expenditure and income: A global perspective. Health Economics,26(7), 863–874.PubMedCrossRef Baltagi, B. H., Lagravinese, R., Moscone, F., & Tosetti, E. (2017). Health care expenditure and income: A global perspective. Health Economics,26(7), 863–874.PubMedCrossRef
go back to reference Bloom, D. E., Canning, D., & Sevilla, J. (2004). The effect of health on economic growth: A production function approach. World Development,32(1), 1–13.CrossRef Bloom, D. E., Canning, D., & Sevilla, J. (2004). The effect of health on economic growth: A production function approach. World Development,32(1), 1–13.CrossRef
go back to reference Clarke, J. A., & Mirza, S. (2006). A comparison of some common methods for detecting Granger noncausality. Journal of Statistical Computation and Simulation,76(3), 207–231.CrossRef Clarke, J. A., & Mirza, S. (2006). A comparison of some common methods for detecting Granger noncausality. Journal of Statistical Computation and Simulation,76(3), 207–231.CrossRef
go back to reference Clemente, J., Marcuello, C., Montañés, A., & Pueyo, F. (2004). On the international stability of health care expenditure functions: Are government and private functions similar? Journal of Health Economics,23(3), 589–613.PubMedCrossRef Clemente, J., Marcuello, C., Montañés, A., & Pueyo, F. (2004). On the international stability of health care expenditure functions: Are government and private functions similar? Journal of Health Economics,23(3), 589–613.PubMedCrossRef
go back to reference Dolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews,15(4), 369–386.CrossRef Dolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews,15(4), 369–386.CrossRef
go back to reference Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling,29(4), 1450–1460.CrossRef Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling,29(4), 1450–1460.CrossRef
go back to reference Everaert, G., & De Groote, T. (2016). Common correlated effects estimation of dynamic panels with cross-sectional dependence. Econometric Reviews,35(3), 428–463.CrossRef Everaert, G., & De Groote, T. (2016). Common correlated effects estimation of dynamic panels with cross-sectional dependence. Econometric Reviews,35(3), 428–463.CrossRef
go back to reference Farag, M., Nandakumar, A., Wallack, S., Hodgkin, D., Gaumer, G., & Erbil, C. (2013). Health expenditures, health outcomes and the role of good governance. International Journal of Health Care Finance and Economics,13(1), 33–52.PubMedCrossRef Farag, M., Nandakumar, A., Wallack, S., Hodgkin, D., Gaumer, G., & Erbil, C. (2013). Health expenditures, health outcomes and the role of good governance. International Journal of Health Care Finance and Economics,13(1), 33–52.PubMedCrossRef
go back to reference Gengenbach, C., Palm, F. C., & Urbain, J. P. (2006). Cointegration testing in panels with common factors. Oxford Bulletin of Economics and Statistics,68(1), 683–719.CrossRef Gengenbach, C., Palm, F. C., & Urbain, J. P. (2006). Cointegration testing in panels with common factors. Oxford Bulletin of Economics and Statistics,68(1), 683–719.CrossRef
go back to reference Glied, S., & Smith, P. C. (2011). The Oxford handbook of health economics. Oxford: Oxford University Press.CrossRef Glied, S., & Smith, P. C. (2011). The Oxford handbook of health economics. Oxford: Oxford University Press.CrossRef
go back to reference Granados, J. A. T. (2012). Economic growth and health progress in England and Wales: 160 years of a changing relation. Social Science and Medicine,74(5), 688–695.CrossRef Granados, J. A. T. (2012). Economic growth and health progress in England and Wales: 160 years of a changing relation. Social Science and Medicine,74(5), 688–695.CrossRef
go back to reference Hall, S. G., & Jones, C. I. (2007). The value of life and the rise in health spending. The Quarterly Journal of Economics,122(2007), 39–72.CrossRef Hall, S. G., & Jones, C. I. (2007). The value of life and the rise in health spending. The Quarterly Journal of Economics,122(2007), 39–72.CrossRef
go back to reference Hansen, P., & King, A. (1996). The determinants of health care expenditure: A cointegration approach. Journal of Health Economics,15, 127–137.PubMedCrossRef Hansen, P., & King, A. (1996). The determinants of health care expenditure: A cointegration approach. Journal of Health Economics,15, 127–137.PubMedCrossRef
go back to reference Harris, R. D., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics,91(2), 201–226.CrossRef Harris, R. D., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics,91(2), 201–226.CrossRef
go back to reference Hartwig, J. (2008). What drives health care expenditure? Baumol’s model of ‘Unbalanced growth’ revisited. Journal of Health Economics,27, 603–623.PubMedCrossRef Hartwig, J. (2008). What drives health care expenditure? Baumol’s model of ‘Unbalanced growth’ revisited. Journal of Health Economics,27, 603–623.PubMedCrossRef
go back to reference Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics,115(1), 53–74.CrossRef Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics,115(1), 53–74.CrossRef
go back to reference Kapetanios, G., Pesaran, M. H., & Yamagata, T. (2011). Panels with non-stationary multifactor error structures. Journal of Econometrics,160(2), 326–348.CrossRef Kapetanios, G., Pesaran, M. H., & Yamagata, T. (2011). Panels with non-stationary multifactor error structures. Journal of Econometrics,160(2), 326–348.CrossRef
go back to reference Ke, X., Saksena, P., & Holly, A. (2011). The determinants of health expenditure: A country-level panel data analysis. Working paper of the Results for Development Institute (R4D). Geneva: World Health Organization. www.resultsfordevelopment.org. Accessed on August 11th, 2017. Ke, X., Saksena, P., & Holly, A. (2011). The determinants of health expenditure: A country-level panel data analysis. Working paper of the Results for Development Institute (R4D). Geneva: World Health Organization. www.​resultsfordevelo​pment.​org. Accessed on August 11th, 2017.
go back to reference Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics,74(1), 119–147.CrossRef Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics,74(1), 119–147.CrossRef
go back to reference Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics,108(1), 1–24.CrossRef Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics,108(1), 1–24.CrossRef
go back to reference Liddle, B., & Messinis, G. (2015). Which comes first-urbanization or economic growth? Evidence from heterogeneous panel causality tests. Applied Economics Letters,22(5), 349–355.CrossRef Liddle, B., & Messinis, G. (2015). Which comes first-urbanization or economic growth? Evidence from heterogeneous panel causality tests. Applied Economics Letters,22(5), 349–355.CrossRef
go back to reference Lütkepohl, H., & Krätzig, M. (2004). Applied time series econometrics. Cambridge: Cambridge University Press.CrossRef Lütkepohl, H., & Krätzig, M. (2004). Applied time series econometrics. Cambridge: Cambridge University Press.CrossRef
go back to reference McCoskey, S. K., & Selden, T. M. (1998). Health care expenditures and GDP: Panel data unit root test results. Journal of Health Economics,17, 369–376.PubMedCrossRef McCoskey, S. K., & Selden, T. M. (1998). Health care expenditures and GDP: Panel data unit root test results. Journal of Health Economics,17, 369–376.PubMedCrossRef
go back to reference Menard, A.-R., & Weill, L. (2016). Understanding the link between aid and corruption: A causality analysis. Economic Systems,40(2), 260–272.CrossRef Menard, A.-R., & Weill, L. (2016). Understanding the link between aid and corruption: A causality analysis. Economic Systems,40(2), 260–272.CrossRef
go back to reference Persyn, D., & Westerlund, J. (2008). Error-correction-based cointegration tests for panel data. Stata Journal,8(2), 232–241.CrossRef Persyn, D., & Westerlund, J. (2008). Error-correction-based cointegration tests for panel data. Stata Journal,8(2), 232–241.CrossRef
go back to reference Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica,74(4), 967–1012.CrossRef Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica,74(4), 967–1012.CrossRef
go back to reference Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics,22(2), 265–312.CrossRef Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics,22(2), 265–312.CrossRef
go back to reference Pesaran, M. H., & Tosetti, E. (2011). Large panels with common factors and spatial correlation. Journal of Econometrics,161(2), 182–202.CrossRef Pesaran, M. H., & Tosetti, E. (2011). Large panels with common factors and spatial correlation. Journal of Econometrics,161(2), 182–202.CrossRef
go back to reference Rafiq, S., Salim, R., & Bloch, H. (2009). Impact of crude oil price volatility on economic activities: An empirical investigation in the Thai economy. Resources Policy,34(3), 121–132.CrossRef Rafiq, S., Salim, R., & Bloch, H. (2009). Impact of crude oil price volatility on economic activities: An empirical investigation in the Thai economy. Resources Policy,34(3), 121–132.CrossRef
go back to reference Shahbaz, M. (2012). Does trade openness affect long run growth? Cointegration, causality and forecast error variance decomposition tests for Pakistan. Economic Modelling,29(6), 2325–2339.CrossRef Shahbaz, M. (2012). Does trade openness affect long run growth? Cointegration, causality and forecast error variance decomposition tests for Pakistan. Economic Modelling,29(6), 2325–2339.CrossRef
go back to reference Shaw, J. W., Horrace, W. C., & Voge, R. J. (2005). The determinants of life expectancy: An analysis of the OECD health data. Southern Economic Journal,71(4), 768–783.CrossRef Shaw, J. W., Horrace, W. C., & Voge, R. J. (2005). The determinants of life expectancy: An analysis of the OECD health data. Southern Economic Journal,71(4), 768–783.CrossRef
go back to reference Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 48(1), 1–48.CrossRef Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 48(1), 1–48.CrossRef
go back to reference Swanson, N. R., & Granger, C. W. (1997). Impulse response functions based on a causal approach to residual orthogonalization in vector autoregressions. Journal of the American Statistical Association,92(437), 357–367.CrossRef Swanson, N. R., & Granger, C. W. (1997). Impulse response functions based on a causal approach to residual orthogonalization in vector autoregressions. Journal of the American Statistical Association,92(437), 357–367.CrossRef
go back to reference Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics,66(1), 225–250.CrossRef Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics,66(1), 225–250.CrossRef
go back to reference Villaverde, J., Maza, A., & Hierro, M. (2014). Health care expenditure disparities in the European Union and underlying factors: A distribution dynamics approach. International Journal of Health Care Finance and Economics,14(3), 251–268.PubMedCrossRef Villaverde, J., Maza, A., & Hierro, M. (2014). Health care expenditure disparities in the European Union and underlying factors: A distribution dynamics approach. International Journal of Health Care Finance and Economics,14(3), 251–268.PubMedCrossRef
go back to reference Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics,69(6), 709–748.CrossRef Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics,69(6), 709–748.CrossRef
go back to reference Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge: MA: MIT Press. Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge: MA: MIT Press.
Metadata
Title
Health expenditure and gross domestic product: causality analysis by income level
Authors
Rezwanul Hasan Rana
Khorshed Alam
Jeff Gow
Publication date
01-03-2020
Publisher
Springer US
Keywords
Shock
Shock
Published in
International Journal of Health Economics and Management / Issue 1/2020
Print ISSN: 2199-9023
Electronic ISSN: 2199-9031
DOI
https://doi.org/10.1007/s10754-019-09270-1

Other articles of this Issue 1/2020

International Journal of Health Economics and Management 1/2020 Go to the issue