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ANALYSING THE RELATIONSHIP BETWEEN HEALTH CARE EXPENDITURE AND HEALTH OUTCOMES IN WEST AFRICA BY

ANALYSING THE RELATIONSHIP BETWEEN HEALTH CARE EXPENDITURE AND HEALTH OUTCOMES IN WEST AFRICA BY RAZAK M. GYASI 1, CHARLOTTE M. MENSAH 2 & ADAM M. ANOKYE 3 1&2 DEPARTMENT OF GEOGRAPHY & RURAL DEVELOPMENT, KNUST, KUMASI 3 SCHOOL OF BUSINESS, UNIVERSITY OF CAPE COAST, CAPE COAST

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ANALYSING THE RELATIONSHIP BETWEEN HEALTH CARE EXPENDITURE AND HEALTH OUTCOMES IN WEST AFRICA BY

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  1. ANALYSING THE RELATIONSHIP BETWEEN HEALTH CARE EXPENDITURE AND HEALTH OUTCOMES IN WEST AFRICA BY RAZAK M. GYASI1, CHARLOTTE M. MENSAH2&ADAM M. ANOKYE3 1&2DEPARTMENT OF GEOGRAPHY &RURAL DEVELOPMENT, KNUST, KUMASI3 SCHOOL OF BUSINESS, UNIVERSITY OF CAPE COAST, CAPE COAST GGA Annual Conference, August, 2012, KNUST, Kumasi, Ghana

  2. OUTLINE OF PRESENTATION • INTRODUCTION • THE PROBLEM • OBJECTIVES OF THE STUDY • DATA &METHODS • RESULTS &DISCUSSION • POLICY IMPLICATIONS • REFERENCES

  3. INTRODUCTION • Health is an indicator of development and the mechanism for achieving development (Buor, 2008). • Strong health systems are fundamental to improving health outcomes and accelerate progress towards health-related MDGs (Sen, 1999; WHO, 2009). • The enjoyment of the highest attainable standard of health is fundamental right of every human being (WHO/UN, 2000; Human Right Council, 2002).

  4. THE PROBLEM • Higher government expenditure on human health creates three-tier-benefit (Barro, 1996). • Increasing life expectancy at birth by 10% increases economic growth rate by 0.35% a year (Comm. Macroeconomics & Health, 2001). • Studies are conducted to argue this relationship.

  5. THE PROBLEM CONT’D • To see health expenditure-health status relationship, studies are not comprehensive, eg. Castro-Leal (2000), Anyanwu and Erhijakpor (2007), Buor (2008). • Is there any linkages between health care spending and health status in West Africa?

  6. OBJECTIVES OF THE STUDY • To estimate the long-run relationship between health care expenditure and health status. • To estimate the short-run relationship between health care expenditure and health status in West Africa.

  7. DATA &METHODS • Time series data of three variables from 1990 to 2010 were used: • Health status Index • Health expenditure • Literacy rate Health expenditure and literacy rate were extracted from World Bank WDI online Database, June 2012

  8. DATA &METHODS • Health status index was constructed from 10 health indicator measures using principal component Analysis(PCA) • Prevalence of HIV, total (% of population ages 15-49)-HIV • Births attended by skilled health staff (% of total)-BASK • Contraceptive prevalence (% of women ages 15-49)-CONT • Immunization, measles (% of children ages 12-23 months)-IMM • Improved sanitation facilities (% of population with access)-ISF • Improved water source (% of population with access) -IWS • Life expectancy at birth, total (years) -LEB • Malaria cases reported -MAL • Maternal mortality ratio (national estimate, per 100,000 live births)-MMR • Pregnant women receiving prenatal care (%) -PWPC

  9. DATA &METHOD CONT’D • Eigenvector with lager eigenvalue was used to construct the index. All components used explained above 60% of the variation in HSI.

  10. TIME SERIES PROPERTIES OF THE DATA • There are many different unit root test used in the literature, however we use two most commonly used test • Augmented Dickey Fuller test (ADF) • Phillips and Perron test (PP) • The results of both tests indicate that all the variables are of I(1). Under such circumstance Johansen Multivariate Cointegration approach is appropriate.

  11. The Multivariate Cointegration approach is base on error correction representation of the p order Vector Autoregressive model with Gaussian error • Where is the first difference operator, is coefficient matrix representing short-run dynamics is Rank and is nxnmatrix, is error term Two different likelihood ratio tests were developed by Johansen for testing the number of Cointegration vectors (r): the trace test and maximum eigene value test given respectively by and

  12. RESULTSLong Run Test & Relationship +*(-*) is positive (negative) and significant at 5% level, +(-) is positive (negative) and insignificant at 5% level B-Benin, BF-Burkina Faso, CD- Cote d’Ivoire, CV-Cape Verde, GA-The Gambia, GH-Ghana, GU-Guinea, GB-Guinea Bissau, LB-Liberia, M-Mali, N-Niger, NG-Nigeria, SG-Senegal, SL-Sierra Leone, TG-Togo

  13. POLICY IMPLICATIONS • Governments should be committed to increase health care spending in West Africa. • General health education and awareness should be prioritised in West Africa. • As closer look should be taken to see weather health care resources are channelled to areas meant for.

  14. REFERENCES • Barro, Robert J. (1996a), “Determinants of Economic Growth: A Cross-Country Empirical Study”, NBER Working Paper No. 5968 (Cambridge, Massachusetts: National Bureau of Economic Research). • Buor, D. (2008). Analysing the socio-spatial inequities in the access of health services in sub-Saharan Africa: Interrogating geographical imbalances in the uptake of health care. Professorial Inaugural Lecture. Great Hall, KNUST, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. October 9, 2008. • Sen, Amartya (1999), Development as Freedom. Oxford: Oxford University Press. • WHO (2004) Comprehensive Community- and Home-based Health Care Model. World Health Organization Regional Office for South-East Asia. New Delhi, India SEARO Regional Publication No. 40.

  15. THANK YOU FOR COMING

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