Volume 22, Issue 86 (11-2022)
refahj 2022, 22(86): 353-389 |
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Khodabakhshi A, Gholamian B. (2022). A Comparative Study of the Impact of Governance Sub-Indicators on Health Expenditures in Rich and Poor Countries. refahj. 22(86), : 10 doi:10.32598/refahj.22.86.2424.2
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Introduction: Health is one of the main indicators of development in any country that investing on this sector will have a direct impact on community welfare and economic growth. Given the importance of the health sector in society, government investment in this area is considered as one of the main tasks of the government. Therefore, examining the quality of governments on the health sector is of particular importance. This became even more important when the advancement of technology and the uncontrolled growth of the population on the one hand and the lifestyle changes caused by industrialization and the emergence of new diseases on the other hand, led to an increase in health costs. In the recent decades, the cost of health care has increased in all countries. A look at the trend and size of these increases reveals that while the size of these costs varies greatly between and among the countries, the trend of this increase has also been significantly different from countries. This dramatic increase has led most governments to seek sustainable financing of health care costs. In an environment where awareness of the cost-effective, in addition to policy applications, it has also received special attention from economic and health researchers. The purpose of this study is to investigate the effect of governance index on health expenditures for two groups of low-income and high-income countries and to study the relationship between governance indicators on health expenditures. Also, due to the significant impact of human development index on health and health costs, this study examines the effect of human development index on health expenditure.
Method: This research is an analytical-descriptive study that seeks to investigate the impact of governance index components on health expenditures using panel data for low and high income countries in the period of 2000-2015. To check the significance of the variables, the Dickey-Fuller and Phillips-Perron unit root tests are used. The data of this research are of composite data. In order to determine the appropriate model for conducting research, the necessity of the model must first be tested in terms of integration or panel and the effects of being fixed or random. For this purpose, the F-Leimer test is used to determine the combined or tabular nature of the data, and the Hausman test is used to determine the nature of the fixed or random effects of the data. In the following part, the model specification tests and estimation and analysis of estimates for low-income countries and then high-income countries are presented. In order to provide the required statistics and information in this research, the documented information of statistical databases such as WDI, FAO and WHO and the World Bank has been used. Eviews10 software has been used in calculating and analyzing research data.
Findings: Based on the results, the logarithm of the variables of the health expenditure index at the level of 95% are meaningful. The results of Levin, Lin, and Chou tests show that the mean and variance of the variables over the time and the covariance between different years have been constant and the use of these variables in the model does not cause false regression.
Table 1. F Limer Test for the both Income groups
The F-Limer test for the low-income group indicates the rejection of the null hypothesis and the existence of heterogeneity of sections at the five percent level. Also, the value of obtained F statistic indicates the appropriateness of the panel method for estimating the model in this group. The F-Limer test for the high-income group indicates the rejection of the null hypothesis and the existence of heterogeneity of sections at the five percent level. Also, the value of obtained F statistic indicates the appropriateness of the data panel method for estimating the model in this group. After the combined data method was found that panel method is suitable for estimation, Hausman test was used to determine the fixed and random effect.
Table 2. Hasman Test for both Income groups
The Hausman test for the low-income group indicates that at the five percent level, the null hypothesis is rejected and the fixed effect is appropriate for estimating the model. The Hausman test for the high-income group showed that at the five percent level, the null hypothesis was rejected and the fixed effect was appropriate for estimating the model. The coefficient of determination or correlation coefficient between variables in the low income group is 0.65. The coefficient of determination between the variables in the high income group is 0.76. All coefficients of variables in both income groups were significant at 90% level and based on F values at 90% level was significant.
Discussion: Based on the estimated results of the model in the group of low-income countries, the effect of the following governance indicators on health expenditures is negative and significant. The results obtained for the high-income group show a positive and significant effect of governance indicators on health expenditures. In the group of low-income countries, the results showed that the rule of law index (Rule) has a positive and significant effect on total health expenditures and this value is 0.26.
Table 3. Estimation results for the low income group
This means, if a unit's rule of law index improves, health expenditure will increase by 26 percent. Also, the quality index of laws and regulations (Regulatory) index of control of corruption (Control) and index of efficiency and effectiveness (Government), index of political stability and non-violence (political) and index of right to comment and accountability (Voice) have a negative and significant effect on total health expenditure and these values are -0.43, -0.30, -0.22, -0.11, -0.40,
Table 4. Estimation results for the high income group
Also for high-income countries, Regulatory Quality Index, Rule Index, Government Efficiency and Effectiveness Index, Political Stability and Nonviolence, Voice Response Index. And Corruption control has a positive and significant effect on total health expenditure and these values are 0.11, 0.43, 0.51, 0.02, 0.19, 0.14, respectively. Arguing the results of the research, the governing system of low-income countries, which also have poor governance, is advised to try to reduce political instability and cumbersome laws. In addition, in these countries, in order to remove barriers to trade and create a competitive environment, it is necessary to enact relevant laws and regulations. In this group of countries, governments must play a regulatory role in improving market activity and resolving its problems.
Classification (JEL): I18, E60, O57
Keywords: Health costs, Governance, Panel data
Ethical Considerations
Authors’ contributions
All authors contributed in producing of the research.
Funding
In the present study, all expenses were borne by the authors, and they did not have any sponsors.
Conflicts of interest
The authors of the article undertake that there is no conflict of interest in this article.
Acknowledgments
In this article, all rights relating to references are cited and resources are carefully listed.
Method: This research is an analytical-descriptive study that seeks to investigate the impact of governance index components on health expenditures using panel data for low and high income countries in the period of 2000-2015. To check the significance of the variables, the Dickey-Fuller and Phillips-Perron unit root tests are used. The data of this research are of composite data. In order to determine the appropriate model for conducting research, the necessity of the model must first be tested in terms of integration or panel and the effects of being fixed or random. For this purpose, the F-Leimer test is used to determine the combined or tabular nature of the data, and the Hausman test is used to determine the nature of the fixed or random effects of the data. In the following part, the model specification tests and estimation and analysis of estimates for low-income countries and then high-income countries are presented. In order to provide the required statistics and information in this research, the documented information of statistical databases such as WDI, FAO and WHO and the World Bank has been used. Eviews10 software has been used in calculating and analyzing research data.
Findings: Based on the results, the logarithm of the variables of the health expenditure index at the level of 95% are meaningful. The results of Levin, Lin, and Chou tests show that the mean and variance of the variables over the time and the covariance between different years have been constant and the use of these variables in the model does not cause false regression.
Table 1. F Limer Test for the both Income groups
| Low Income Group | |||
| Prob | Statistics | Statistics | |
| 0.0000 | 82.353437 | Cross- section F | |
| 0.0000 | 290.556603 | Cross- section chi square | |
| High Income Group | |||
| Prob | Statistics | Statistics | |
| 0.0000 | 67.393803 | Cross- section F | |
| 0.0000 | 264.157645 | Cross- section chi square | |
The F-Limer test for the low-income group indicates the rejection of the null hypothesis and the existence of heterogeneity of sections at the five percent level. Also, the value of obtained F statistic indicates the appropriateness of the panel method for estimating the model in this group. The F-Limer test for the high-income group indicates the rejection of the null hypothesis and the existence of heterogeneity of sections at the five percent level. Also, the value of obtained F statistic indicates the appropriateness of the data panel method for estimating the model in this group. After the combined data method was found that panel method is suitable for estimation, Hausman test was used to determine the fixed and random effect.
Table 2. Hasman Test for both Income groups
| Low Income Group | |
| 12.629959 | Chi-sq. Statistics |
| 0.0493 | Prob |
| High Income Group | |
| 14.470178 | Chi-sq. Statistics |
| 0.0248 | |
| Prob |
The Hausman test for the low-income group indicates that at the five percent level, the null hypothesis is rejected and the fixed effect is appropriate for estimating the model. The Hausman test for the high-income group showed that at the five percent level, the null hypothesis was rejected and the fixed effect was appropriate for estimating the model. The coefficient of determination or correlation coefficient between variables in the low income group is 0.65. The coefficient of determination between the variables in the high income group is 0.76. All coefficients of variables in both income groups were significant at 90% level and based on F values at 90% level was significant.
Discussion: Based on the estimated results of the model in the group of low-income countries, the effect of the following governance indicators on health expenditures is negative and significant. The results obtained for the high-income group show a positive and significant effect of governance indicators on health expenditures. In the group of low-income countries, the results showed that the rule of law index (Rule) has a positive and significant effect on total health expenditures and this value is 0.26.
Table 3. Estimation results for the low income group
| Independent variable | Coefficient | Std. Error | t-statistic | Prob | ||||
| Control | -0.303244 | 0.122057 | -2.484436 | 0.0141 | ||||
| Government | -0.220015 | 0.110395 | -1.992986 | 0.0482 | ||||
| Political | -0.116383 | 0.042483 | -2.739490 | 0.0069 | ||||
| Regulatory | 0.432677- | 0.098034 | -4.413560 | 0.0000 | ||||
| Rule | 0.268787 | 0.143578 | 1.872066 | 0.0632 | ||||
| Voice | 0.405991- | 0.103718 | -3.914371 | 0.0001 | ||||
| Effects Specification | ||||||||
| 91.61940 | F_statistic | 0.651565 | R-squared | |||||
| 0.00000 | Prob(F_statistic) | 0.645277 | Adjusted R_squared | |||||
| 1.831633 | Durbin-Watson stat | 8.905990 | Sum squared resid | |||||
This means, if a unit's rule of law index improves, health expenditure will increase by 26 percent. Also, the quality index of laws and regulations (Regulatory) index of control of corruption (Control) and index of efficiency and effectiveness (Government), index of political stability and non-violence (political) and index of right to comment and accountability (Voice) have a negative and significant effect on total health expenditure and these values are -0.43, -0.30, -0.22, -0.11, -0.40,
Table 4. Estimation results for the high income group
| Independent variable | Coefficient | Std. Error | t-statistic | Prob | ||
| Control | 0.149692 | 0.028660 | 5.223100 | 0.0000 | ||
| Government | 0.518193 | 0.035425 | 14.62795 | 0.0000 | ||
| Political | 0.021634 | 0.018943 | 1.142079 | 0.2553 | ||
| Regulatory | 0.117237 | 0.039060 | 3.001477 | 0.0032 | ||
| Rule | 0.434714 | 0.053523 | 8.122065 | 0.0000 | ||
| Voice | 0.193994 | 0.042596 | 4.554322 | 0.0000 | ||
| Effects Specification | ||||||
| 1156.813 | F_statistic | 0.761770 | R-squared | |||
| 0.00000 | Prob(F_statistic) | 0.750912 | Adjusted R_squared | |||
| 1.683187 | Durbin-Watson stat | 136.9929 | Sum squared resided | |||
Also for high-income countries, Regulatory Quality Index, Rule Index, Government Efficiency and Effectiveness Index, Political Stability and Nonviolence, Voice Response Index. And Corruption control has a positive and significant effect on total health expenditure and these values are 0.11, 0.43, 0.51, 0.02, 0.19, 0.14, respectively. Arguing the results of the research, the governing system of low-income countries, which also have poor governance, is advised to try to reduce political instability and cumbersome laws. In addition, in these countries, in order to remove barriers to trade and create a competitive environment, it is necessary to enact relevant laws and regulations. In this group of countries, governments must play a regulatory role in improving market activity and resolving its problems.
Classification (JEL): I18, E60, O57
Keywords: Health costs, Governance, Panel data
Ethical Considerations
Authors’ contributions
All authors contributed in producing of the research.
Funding
In the present study, all expenses were borne by the authors, and they did not have any sponsors.
Conflicts of interest
The authors of the article undertake that there is no conflict of interest in this article.
Acknowledgments
In this article, all rights relating to references are cited and resources are carefully listed.
Type of Study: orginal |
Received: 2021/06/21 | Accepted: 2022/04/24 | Published: 2022/11/13
Received: 2021/06/21 | Accepted: 2022/04/24 | Published: 2022/11/13
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