ISSN: 2056-3736 (Online Version) | 2056-3728 (Print Version)

Determinants of public health spending in WAEMU area: An empirical investigation

Tito Nestor TIEHI and Foungnigué Noé COULIBALY

Correspondence: Tito Nestor TIEHI, titotiehi@gmail.com

Department of Economics and Management Sciences, University of Cocody-Abidjan, Côte d’Ivoire

pdf (1016.03 Kb) | doi: https://doi.org/10.47260/bae/914

Abstract

The aim of this article is to analyze the determinants of government spending on health in the West African Economic and Monetary Union (WAEMU) area. To do this, we have collected panel data on which an autoregressive Distributed Lag model (ARDL) approach is applied at the end of econometric tests (Stationarity and Co-integration). As main results, population growth, use of mosquito nets, hospital beds, number of doctors, nurses - midwives, corruption scores and political stability are responsible for government spending. To be short, we can note that these determinants are both supply and demand factors. Thus, government action is not only political (ensuring political stability, good governance), but also medical (ensuring the professionalism of healthcare staff and raising awareness among the population about the use of Treated Mosquito nets with limited duration of action).

Keywords:

  Public health spending and health, Autoregressive Distributed Lag, WAEMU


References

Acemoglu D., Johnson R. et Robinson J.A. (2004), « J. (2005). “Institutions as the Fundamental Cause of Long-Run Growth” », Handbook of Economic Growth, North-Holland, Amsterdam.

Akinci, Fevzi, Hamidi, Samer, Suvankulov, Farrukh, et al. Examining the impact of health care expenditures on health outcomes in the Middle East and N. Africa. Journal of Health Care Finance, 2014, vol. 41, n°1, pp. 2-22

Coulibaly F. N. 2021. Analysis of the main components of health spending in the WAEMU area: the role of government spending. International Journal of Social Science and Economic Research, 2021, Vol. 06, n°7, pp.2128-2136. https://doi.org/10.46609/IJSSER.2021.v06i07.007         

Engel, Nora, Wachter, Keri, Pai, Madhukar, et al. Addressing the challenges of diagnostics demand and supply: insights from an online global health discussion platform. BMJ Global Health, 2016, vol. 1, no 4, p. e000132.

Fisher, R. A. 1936. The use of multiple measurements in taxonomic problems. Annals of Eugenics 7: 179–188.

Goldstein, Neal D., Palumbo, Aimee J., Bellamy, Scarlett L., et al. State and local government expenditures and infant mortality in the United States. Pediatrics, 2020, vol. 146, n°5. https://doi.org/10.1007/s10198-018-1010-2

Jean Brignon Camal Gallouj, (2011). Précis de santé publique et d’économie de la santé, 2ème Edition Lamare

Johansen. (1965), Publics Economics, Amsterdam, North-Holland.

Kaufmann D., Kraay A. et Mastruzzi M. (2005), Governance matters IV: governance indicators for 1996-2004, The World Bank.

Kaufmann D., Kraay A. et Mastruzzi M. (2007), « Growth and governance : A reply », The Journal of Politics, vol. 69, n°2, pp. 555–562.

Ke, X. U., Saksena, P., & Holly, A. (2011). The determinants of health expenditure: a country-level panel data analysis. Geneva : World Health Organization, vol. 26, pp. 1-28.

Lillrank, Paul, GROOP, P. Johan, et Malmström, Tomi J. Demand and supply–based operating modes—a framework for analyzing health care service production. The Milbank Quarterly, 2010, vol. 88, n°4, pp. 595-615.

Mauro P. (1997), Why Worry about Corruption? International Monetary Fund, 24 p.

Mauro P. (1998), « La corruption: causes, conséquences et voies à explorer », Finances & Développement, vol. 35, n°1, pp. 11–14.

McLaren, L., & Dutton, D. J. (2020). The social determinants of pandemic impact : an opportunity to rethink what we mean by “public health spending”. Canadian Journal of Public Health, vol. 111, n°4, pp. 451-453.

Mtiraoui A.B.A. (2015), « Action du pouvoir public et développement économique : Application au secteur de la santé dans la région MENA », 3rd International Conference on Business, Economics, Marketing & Management - BEMM \ 2015.

Pearson, K. (1901). Principal components analysis. The London, Edinburgh and Dublin Philosophical Magazine and Journal, vol. 6, n°2, p 566.

Pesaran M.H., Shin Y. et Smith R.J. (2001), « Bounds testing approaches to the analysis of level relationships », Journal of Applied Econometrics, vol. 16, n°3, pp. 289‑326.

Pesaran M.H., Shin Y. et Smith R.J. (2001), « Bounds testing approaches to the analysis of level relationships », Journal of Applied Econometrics, vol. 16, n°3, pp. 289‑326.

Phillips, P. C. B., and P. Perron. 1988. Testing for a unit root in time series regression. Biometrika 75 : pp. 335–346.

Schmidt, P. and R. Sickles., (1984). "Production frontiers and panel data", Journal of Business and Economic Statistics, 2, 367-374.

Tiehi T.N. (2013), HIV/AIDS spread in West African countries: Does public corruption matter? International Journal of Developing Societies, vol 2, n°2, pp. 61-67

WHO (2020) Statistical Information System (WHOSIS).

Wooldridge, J. M. 2010. Econometric Analysis of Cross Section and Panel Data. 2nd ed. Cambridge, MA: MIT Press.

World Bank, (2020). Worldwide Governance Indicators 2020.

Yan, Huang-Ting et Lin, Yu-Chun. How time horizons of autocrats’ impact health expenditure: mixed methods research. BMC public health, 2020, vol. 20, pp. 1-9.