The determinants of health care expenditure: an empirical evidence from Asean countries

• Main Author: Nor Faizah, Ahmad @ Mohammed Razikin
• Format: Thesis
• Language: English; English
• Published: 2017
• Subjects: RA410.55 Hospital Care.
• Online Access: http://etd.uum.edu.my/7164/
• Institution: Universiti Utara Malaysia

The main motivation of this research project is to investigate the determinants of Health Care Expenditure (HCE): an empirical evidence from ASEAN countries. There are 200 total observations that involved annual data from 1995 to 2014 in Brunei Darussalam, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam. Data collection for this study is based on secondary data that obtained from the Central of International Data, World Development Indicator (World Bank Database, 2016), World Health Organization (WHO, 2016), ASEAN Up Database and also from the central bank of each country. The data used in this study is to prove the significant relationship between dependent and independent variables for the four models. The first model, Panel A analyses the relationship between HCE with the Gross Domestic Product (GDP), Population, Life Insurance Coverage (LIC), Household Final Consumption Expenditure (HFCE) and Consumer Price Index (CPI). For the second model, Panel B examines the significant influence of HCE, Population, LIC, HFCE and CPI on the economic growth. Based on the variables of these both models, then Panel C and Panel D were generated by using natural logarithm (ln). Pooled Ordinary Least Square (POLS) of Regression Model revealed that Panel A found the GDP, Population, LIC and CPI are positively correlated to the HCE that have the statistical significant at 0.01 level. However, there is a negative relationship between HFCE and HCE at the statistical significant of 0.01 level. Next, Panel B indicated the HCE, LIC and HFCE have positive correlation with GDP at the statistical significant of 0.01 level except for LIC at 0.05 level. While, there is a negative relationship between Population and CPI with the GDP at statistical significant of 0.01 and 0.10 level respectively. Panel C represented the lnGDP, lnLIC, lnHFCE and lnCPI are positively correlated to the lnHCE that have the statistical significant at 0.01 level. However, there is a negative relationship between lnPop and lnHCE at the statistical significant of 0.01. Last but not least, Panel D showed the lnHCE, lnPop and lnLIC have positive correlation with lnGDP at the statistical significant of 0.01 level except for lnLIC that has no statistical influence. While, there is a negative relationship between lnHFCE and lnCPI with lnGDP at the statistical significant of 0.01 level. Regarding to these findings, this study was supported the previous empirical works as well as presents the several policy implications and recommendations for research improvement in the future.