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Health expenditure, longevity, and child mortality: dynamic panel data approach with global data

Author

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  • Devdatta Ray

    (University of Eastern Finland (UEF Kuopio Campus))

  • Mikael Linden

    (University of Eastern Finland (UEF Kuopio Campus))

Abstract

In this study, effects of public and private health expenditures on life expectancy at birth and infant mortality are analysed on a global scale with 195 countries in the years 1995–2014. The global data set is divided into country categories according to growth in life expectancy, decrease in infant mortality rate, and level of gross national income per capita. Some new dynamic panel model estimators, argued to be more efficient with high persistence series and predetermination compared to popular but complex GMM estimators, show that public health expenditures are generally more health-promoting than private expenditures. However, the health effects are not as great as primary education effects. Although the new estimators provide some new and valuable information on health expenditure effects on life expectancy and infant mortality on a global scale, they do not show desired robustness.

Suggested Citation

  • Devdatta Ray & Mikael Linden, 2020. "Health expenditure, longevity, and child mortality: dynamic panel data approach with global data," International Journal of Health Economics and Management, Springer, vol. 20(1), pages 99-119, March.
  • Handle: RePEc:kap:ijhcfe:v:20:y:2020:i:1:d:10.1007_s10754-019-09272-z
    DOI: 10.1007/s10754-019-09272-z
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    1. John Nixon & Philippe Ulmann, 2006. "The relationship between health care expenditure and health outcomes," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 7(1), pages 7-18, March.
    2. Jacob Novignon & Solomon Olakojo & Justice Nonvignon, 2012. "The effects of public and private health care expenditure on health status in sub-Saharan Africa: new evidence from panel data analysis," Health Economics Review, Springer, vol. 2(1), pages 1-8, December.
    3. Gerdtham, Ulf-G. & Jonsson, Bengt, 2000. "International comparisons of health expenditure: Theory, data and econometric analysis," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 1, pages 11-53, Elsevier.
    4. Pesaran, M. Hashem, 2015. "Time Series and Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780198759980.
    5. Bun, Maurice J.G. & Carree, Martin A., 2005. "Bias-Corrected Estimation in Dynamic Panel Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 200-210, April.
    6. Daron Acemoglu & Amy Finkelstein, 2008. "Input and Technology Choices in Regulated Industries: Evidence from the Health Care Sector," Journal of Political Economy, University of Chicago Press, vol. 116(5), pages 837-880, October.
    7. Huang, Rongbing & Ritter, Jay R., 2009. "Testing Theories of Capital Structure and Estimating the Speed of Adjustment," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(2), pages 237-271, April.
    8. So, Beong Soo & Shin, Dong Wan, 1999. "Recursive mean adjustment in time-series inferences," Statistics & Probability Letters, Elsevier, vol. 43(1), pages 65-73, May.
    9. Maurice J. G. Bun, 2003. "Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 29-58, February.
    10. Gouriéroux, Christian & Phillips, Peter C.B. & Yu, Jun, 2010. "Indirect inference for dynamic panel models," Journal of Econometrics, Elsevier, vol. 157(1), pages 68-77, July.
    11. Pierre‐Yves Crémieux & Marie‐Claude Meilleur & Pierre Ouellette & Patrick Petit & Martin Zelder & Ken Potvin, 2005. "Public and private pharmaceutical spending as determinants of health outcomes in Canada," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 107-116, February.
    12. Sudhir Anand & Martin Ravallion, 1993. "Human Development in Poor Countries: On the Role of Private Incomes and Public Services," Journal of Economic Perspectives, American Economic Association, vol. 7(1), pages 133-150, Winter.
    13. Phillips, Peter C.B. & Sul, Donggyu, 2007. "Bias in dynamic panel estimation with fixed effects, incidental trends and cross section dependence," Journal of Econometrics, Elsevier, vol. 137(1), pages 162-188, March.
    14. Bidani, Benu & Ravallion, Martin, 1997. "Decomposing social indicators using distributional data," Journal of Econometrics, Elsevier, vol. 77(1), pages 125-139, March.
    15. Hayakawa, Kazuhiko & Pesaran, M. Hashem, 2015. "Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 188(1), pages 111-134.
    16. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    17. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 26-29, January.
    18. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    19. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, June.
    20. Bun, Maurice J. G. & Kiviet, Jan F., 2003. "On the diminishing returns of higher-order terms in asymptotic expansions of bias," Economics Letters, Elsevier, vol. 79(2), pages 145-152, May.
    21. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    22. João Medeiros & Christoph Schwierz, 2013. "Estimating the drivers and projecting long-term public health expenditure in the European Union: Baumol's "cost disease" revisited," European Economy - Economic Papers 2008 - 2015 507, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    23. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    24. Michael Keane & Timothy Neal, 2016. "The Keane and Runkle estimator for panel-data models with serial correlation and instruments that are not strictly exogenous," Stata Journal, StataCorp LP, vol. 16(3), pages 523-549, September.
    25. Richard Heijink & Xander Koolman & Gert Westert, 2013. "Spending more money, saving more lives? The relationship between avoidable mortality and healthcare spending in 14 countries," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(3), pages 527-538, June.
    26. Filmer, Deon & Pritchett, Lant, 1999. "The impact of public spending on health: does money matter?," Social Science & Medicine, Elsevier, vol. 49(10), pages 1309-1323, November.
    27. Everaert, Gerdie & Pozzi, Lorenzo, 2007. "Bootstrap-based bias correction for dynamic panels," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1160-1184, April.
    28. Filmer, Deon & Pritchett, Lant, 1997. "Child mortality and public spending on health : how much does money matter?," Policy Research Working Paper Series 1864, The World Bank.
    29. Han, Chirok & Phillips, Peter C. B. & Sul, Donggyu, 2014. "X-Differencing And Dynamic Panel Model Estimation," Econometric Theory, Cambridge University Press, vol. 30(1), pages 201-251, February.
    30. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    31. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09ij4j0h0h1 is not listed on IDEAS
    32. Hahn, Jinyong & Moon, Hyungsik Roger, 2006. "Reducing Bias Of Mle In A Dynamic Panel Model," Econometric Theory, Cambridge University Press, vol. 22(3), pages 499-512, June.
    33. John Anyanwu & Andrew E. O. Erhijakpor, 2007. "Working Paper 91 - Health Expenditures and Health Outcomes in Africa," Working Paper Series 226, African Development Bank.
    34. Li-Lin Liang & Andrew J Mirelman, 2014. "Why Do Some Countries Spend More for Health? An Assessment of Sociopolitical Determinants and International Aid for Government Health Expenditures," Health, Nutrition and Population (HNP) Discussion Paper Series 88182, The World Bank.
    35. Jan Kiviet & Milan Pleus & Rutger Poldermans, 2017. "Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models," Econometrics, MDPI, vol. 5(1), pages 1-54, March.
    36. Barthold, D. & Nandi, A. & Mendoza Rodríguez, J.M. & Heymann, J., 2014. "Analyzing whether countries are equally efficient at improving longevity for men and women," American Journal of Public Health, American Public Health Association, vol. 104(11), pages 2163-2169.
    37. Liang, Li-Lin & Mirelman, Andrew J., 2014. "Why do some countries spend more for health? An assessment of sociopolitical determinants and international aid for government health expenditures," Social Science & Medicine, Elsevier, vol. 114(C), pages 161-168.
    38. Bun, Maurice J.G. & Carree, Martin A., 2006. "Bias-corrected estimation in dynamic panel data models with heteroscedasticity," Economics Letters, Elsevier, vol. 92(2), pages 220-227, August.
    39. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 1-9, January.
    40. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    41. Han, Chirok & Phillips, Peter C.B., 2013. "First difference maximum likelihood and dynamic panel estimation," Journal of Econometrics, Elsevier, vol. 175(1), pages 35-45.
    42. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2015. "In search of robust methods for dynamic panel data models in empirical corporate finance," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 84-98.
    43. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    44. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    45. International Monetary Fund, 2002. "Moreon the Effectiveness of Public Spendingon Health Care and Education: A Covariance Structure Model," IMF Working Papers 2002/090, International Monetary Fund.
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    2. Beatrice Patricia Oberkner & Marius Cristian Milos, 2022. "Analysis of the Linkage Between Health Public Expenditures and Health Outcomes at the European Union Level," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 943-947, September.
    3. Zeynep Ceylan & Abdulkadir Atalan, 2021. "Estimation of healthcare expenditure per capita of Turkey using artificial intelligence techniques with genetic algorithm‐based feature selection," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 279-290, March.
    4. Sanmarchi Francesco & Esposito Francesco & Bucci Andrea & Toscano Fabrizio & Golinelli Davide, 2021. "Association between Economic Growth, Mortality, and Healthcare Spending in 31 High-Income Countries," Forum for Health Economics & Policy, De Gruyter, vol. 24(2), pages 101-118, December.
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    6. Ronald Miranda‐Lescano & Leonel Muinelo‐Gallo & Oriol Roca‐Sagalés, 2023. "Human development and decentralization: The importance of public health expenditure," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(1), pages 191-219, March.
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    More about this item

    Keywords

    Health expenditures; Low and high incomes; Life expectancy; Dynamic panel methods;
    All these keywords.

    JEL classification:

    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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