Institutional Determinants of Informal Payments for Health Services: An Exploratory Analysis across 117 Countries
Abstract
:1. Introduction
Tackling Informal Payments for Healthcare: What Role for Institutions?
2. Materials and Methods
3. Results
3.1. Data Description
3.2. Findings
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Variable | Description | Source |
---|---|---|
Informal payments | ||
Informal payments in health sector | Share of population responding ‘Yes’ when it comes to ‘Medical and health services’ to the following question: ‘In your contact or contacts with the institutions have your or anyone living in your household paid a bribe in any form in the past 12 months?’ | The Global Corruption Barometer, Transparency InternationalDownloaded from QoG Standard dataset [40] |
Formal institutions | ||
Quality of governance | The Quality of Governance Index (estimate). The index was rescaled to 0–5 (best) values. The six dimensions of the index were aggregated using a factorial analysis. | Worldwide Governance indicators database of World Bank [39] |
Health expenditures | Current Health Expenditure (CHE) as % Gross Domestic Product (GDP), Percentage | World Health Organization |
Out-of-pocket expenditure | Out-of-pocket (OOPS) as % of Current Health Expenditure (CHE), Percentage | World Health Organization |
Private health expenditure | Domestic Private Health Expenditure (PVT-D) as % Current Health Expenditure (CHE), Percentage | World Health Organization |
Doctor ratio | Medical doctors (per 10,000) | World Health Organization |
Informal institutions | ||
Feel personally obliged to report corruption | Share of people agreeing with the following statement: ‘Feel personally obliged to report corruption’. The values are from and around 2017, with a ± 3 years margin interval. | The Global Corruption Barometer, Transparency InternationalDownloaded from QoG Standard dataset [40] |
Trust | Share of people responding that ‘Most people can be trusted’ to the following question: ‘Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?’ The values are from and around 2017, with a ± 3 years margin interval. | World Values SurveyDownloaded from QoG Standard dataset [40] |
Other variables | ||
Age dependency | Age dependency ratio (% of working-age population) | World Bank |
Education | Educational attainment (population weighted education per capita, age 25+, mean years) | Institute for Health Metrics and Evaluation [71] |
Employment | Employment to population ratio, 15+, total (%) (modelled ILO estimate) | World Bank |
GDP per capita | Real GDP per capita, PPP | PWT version 9.1 [72] |
GDP per capita growth | Real GDP growth | |
Life expectancy | Life expectancy at birth, total (years) | World Bank |
Urban | Urban population (% of total population) | World Bank |
Variable | Obs. | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
Panel data | |||||
Informal Payments | |||||
Informal payments in health sector | 354 | 13.39 | 14.02 | 0.00 | 66.45 |
High income | 138 | 5.75 | 7.87 | 0.00 | 35.85 |
Upper-middle income | 102 | 12.92 | 13.24 | 0.36 | 64.91 |
Lower-middle income | 90 | 20.03 | 13.06 | 0.97 | 60.34 |
Low income | 30 | 31.72 | 15.70 | 1.75 | 66.45 |
Formal institutions | |||||
Quality of governance | 354 | 2.66 | 0.94 | 0.79 | 4.43 |
Health expenditures | 354 | 6.81 | 2.60 | 1.78 | 16.35 |
Out-of-pocket expenditure | 354 | 33.20 | 18.62 | 1.20 | 82.88 |
Private health expenditure | 354 | 41.19 | 19.00 | 1.20 | 84.60 |
Doctor ratio | 264 | 25.77 | 18.00 | 0.13 | 78.09 |
Other variables | |||||
Age dependency | 354 | 56.60 | 15.91 | 26.99 | 104.70 |
Education | 354 | 9.13 | 3.44 | 1.69 | 14.69 |
Employment | 354 | 56.95 | 11.12 | 31.64 | 87.02 |
GDP per capita | 346 | 21,318.13 | 18,789.94 | 746.30 | 91,533.16 |
GDP per capita growth | 346 | 4.48 | 7.34 | −27.87 | 36.08 |
Life expectancy | 354 | 72.40 | 7.93 | 48.47 | 83.33 |
Urban | 354 | 61.57 | 21.22 | 10.92 | 100.00 |
Cross-sectional data | |||||
Informal payments | |||||
Informal payments in health sector | 113 | 15.00 | 13.68 | 0.50 | 66.45 |
High income | 40 | 6.70 | 8.01 | 0.50 | 33.07 |
Upper-middle income | 32 | 13.84 | 11.85 | 1.83 | 50.95 |
Lower-middle income | 27 | 20.43 | 11.17 | 3.46 | 44.56 |
Low income | 14 | 30.86 | 17.00 | 2.95 | 66.45 |
Formal institutions | |||||
Quality of governance | 113 | 2.55 | 0.93 | 0.86 | 4.39 |
Health expenditures | 113 | 6.76 | 2.60 | 2.06 | 16.28 |
Private health expenditure | 113 | 40.18 | 18.41 | 1.64 | 79.07 |
Informal institutions | |||||
Feel personally obliged to report corruption | 64 | 56.17 | 20.69 | 10.00 | 92.00 |
Trust | 42 | 19.71 | 15.12 | 2.14 | 63.98 |
Other variables | |||||
Age dependency | 113 | 57.64 | 17.35 | 27.46 | 103.19 |
Education | 113 | 8.88 | 3.60 | 1.73 | 14.46 |
Employment | 113 | 57.61 | 12.18 | 33.49 | 86.46 |
Life expectancy | 113 | 72.08 | 7.98 | 50.17 | 82.96 |
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Two-Way Fixed Effects | Tobit | Fractional Probit | |||||||
---|---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
Log of Education | −2.235 | −2.518 | −2.915 | −2.636 | −2.540 | 4.992 | −7.302 | −0.0183 | −0.0542 |
(4.709) | (4.822) | (4.875) | (4.975) | (4.528) | (5.431) | (4.653) | (0.0337) | (0.142) | |
Log of Age dependency | −1.282 | −1.543 | −1.596 | −1.511 | −1.569 | −2.169 | −2.402 | −0.0604 | −0.417 * |
(1.964) | (1.911) | (1.912) | (1.951) | (2.177) | (1.980) | (1.905) | (0.0581) | (0.249) | |
Log of Employment | 2.546 ** | 3.001 ** | 2.977 ** | 3.006 ** | 3.059 ** | 3.280 *** | 2.814 ** | −0.0231 | −0.256 |
(1.280) | (1.225) | (1.214) | (1.229) | (1.171) | (1.240) | (1.138) | (0.0484) | (0.216) | |
Life expectancy | 0.142 * | 0.142 ** | 0.147 * | 0.144 * | 0.142 * | 0.192 * | 0.142 ** | −0.00522 ** | −0.0299 *** |
(0.0762) | (0.0687) | (0.0757) | (0.0764) | (0.0755) | (0.0991) | (0.0716) | (0.00233) | (0.0112) | |
Log of Health expenditures | −0.255 | −0.180 | −0.203 | −0.0756 | −0.0730 | 1.134 * | −0.245 | 0.0279 | 0.127 |
(0.418) | (0.404) | (0.424) | (0.494) | (0.514) | (0.627) | (0.416) | (0.0252) | (0.105) | |
Log of Out-of-pocket expenditure | −0.660 ** | −0.704 ** | |||||||
(0.287) | (0.272) | ||||||||
Quality of governance | −0.978 * | −1.010 * | −1.024 * | −1.036 * | −0.499 | −0.947 * | −0.0608 *** | −0.324 *** | |
(0.550) | (0.554) | (0.563) | (0.535) | (0.631) | (0.529) | (0.0182) | (0.0839) | ||
Log of Private health expenditure | −0.643 ** | −0.696 ** | −0.685 ** | −1.126 ** | −0.574 * | −0.0153 | −0.0425 | ||
(0.297) | (0.314) | (0.298) | (0.445) | (0.295) | (0.0178) | (0.0651) | |||
GDP per capita growth | −0.00353 | ||||||||
(0.00613) | |||||||||
Log of GDP per capita | −0.0595 | ||||||||
(0.699) | |||||||||
Log of Doctors ratio | −0.257 | ||||||||
(0.228) | |||||||||
Urban | 0.118 * | ||||||||
(0.0652) | |||||||||
Obs./Countries | 353/117 | 353/117 | 353/117 | 345/113 | 345/113 | 263/97 | 353/117 | 354/117 | 354/117 |
R-squared | 0.223 | 0.233 | 0.230 | 0.231 | 0.230 | 0.306 | 0.240 | - | - |
BIC | 525.3 | 526.4 | 528.1 | 529.3 | 529.6 | 366.5 | 529.2 | −663.7 | - |
OLS | Tobit | Fractional Probit | |||||||
---|---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
Log of Education | 0.540 * | 0.563 | 0.478 | 0.833 | 0.901 * | 0.831 | 0.991 | 0.184 *** | 1.040 *** |
(0.290) | (0.652) | (0.515) | (0.604) | (0.449) | (0.749) | (0.690) | (0.0608) | (0.306) | |
Log of age dependency | −0.955 ** | 0.217 | −0.886 | 0.0143 | −0.334 | −0.0428 | 0.174 | −0.0315 | 0.191 |
(0.474) | (0.962) | (0.770) | (0.975) | (0.710) | (1.241) | (1.209) | (0.0979) | (0.503) | |
Log of employment | −1.666 *** | −1.481 * | −2.353 *** | −1.513 * | −1.891 *** | −1.997 * | −1.830 | −0.280 ** | −1.554 *** |
(0.418) | (0.783) | (0.534) | (0.759) | (0.521) | (1.127) | (1.160) | (0.108) | (0.489) | |
Life expectancy | −0.0510 *** | −0.0857 | −0.0442 | −0.0619 | 0.0140 | 0.0110 | 0.0208 | −0.00300 | 0.0238 |
(0.0184) | (0.0660) | (0.0288) | (0.0604) | (0.0318) | (0.105) | (0.102) | (0.00856) | (0.0469) | |
Log of Health expenditure | −0.0272 | −0.0786 | −0.0530 | −0.0594 | −0.0390 | −0.0348 | −0.0379 | −0.00811 | −0.0886 * |
(0.0399) | (0.0688) | (0.0715) | (0.0633) | (0.0613) | (0.108) | (0.108) | (0.00653) | (0.0474) | |
Log of Private health expenditure | −0.00742 | 0.0139 | −0.609 | −0.0243 | −0.491 | −0.886 | −0.807 | −0.0673 | −0.293 |
(0.151) | (0.291) | (0.385) | (0.291) | (0.392) | (0.532) | (0.487) | (0.0404) | (0.192) | |
Quality of governance | −0.646 *** | −0.842 *** | −0.950 *** | −0.805 | −0.0647 * | −0.404 ** | |||
(0.186) | (0.298) | (0.337) | (0.500) | (0.0359) | (0.172) | ||||
Feel personally obliged to report corruption | −0.0161 ** | −0.0108 | −0.0219 * | −0.0166 | −0.000390 | −0.00486 | |||
(0.00775) | (0.00838) | (0.0118) | (0.0144) | (0.00121) | (0.00545) | ||||
Trust | −0.0140 | −0.0103 | −0.0378 ** | −0.0324 * | −0.000807 | −0.00511 | |||
(0.0131) | (0.0114) | (0.0168) | (0.0176) | (0.00124) | (0.00770) | ||||
Observations | 113 | 63 | 42 | 63 | 42 | 28 | 28 | 29 | 29 |
BIC | 296.6 | 178.0 | 118.9 | 173.5 | 114.2 | 85.46 | 85.45 | −37.88 | 57.91 |
R-squared | 0.584 | 0.539 | 0.583 | 0.598 | 0.659 | 0.649 | 0.689 | - | - |
Hypothesis | Result | ||
---|---|---|---|
Formal Institutions | H1. Quality of Governance: Informal payments in health are more likely to occur with ill-functioning formal institutions. | Confirmed | Significant negative impact of quality of governance on informal payments. |
H2. Resource allocation: Higher shares of financial resources/private financing reduce informal payments in health. | Partially confirmed | ||
H2a. The higher the share of health resources, the lower the prevalence of informal payments in health. | Not confirmed | Unsignificant impact of the share of health expenditures on informal payments in health. | |
H2b. The higher the share of private financing, the lower the prevalence of informal payments in health. | Confirmed | Significant negative impact of out-of-pocket and domestic private health expenditure on informal payments in health. | |
H3. Healthcare accessibility: higher accessibility rates reduce informal payments in health. | Not confirmed | Unsignificant impact of the ratio of physicians (per 10,000 inhabitants) on informal payments in health. | |
Informal Institutions | H4. Patient’s norms and values: Informal payments in health are more likely to occur with ‘bad’ informal institutions. | Confirmed | Significant negative impact of trust, and feel personally obliged to report corruption on informal payments in health. |
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Incaltarau, C.; Horodnic, A.V.; Williams, C.C.; Oprea, L. Institutional Determinants of Informal Payments for Health Services: An Exploratory Analysis across 117 Countries. Int. J. Environ. Res. Public Health 2021, 18, 12421. https://doi.org/10.3390/ijerph182312421
Incaltarau C, Horodnic AV, Williams CC, Oprea L. Institutional Determinants of Informal Payments for Health Services: An Exploratory Analysis across 117 Countries. International Journal of Environmental Research and Public Health. 2021; 18(23):12421. https://doi.org/10.3390/ijerph182312421
Chicago/Turabian StyleIncaltarau, Cristian, Adrian V. Horodnic, Colin C. Williams, and Liviu Oprea. 2021. "Institutional Determinants of Informal Payments for Health Services: An Exploratory Analysis across 117 Countries" International Journal of Environmental Research and Public Health 18, no. 23: 12421. https://doi.org/10.3390/ijerph182312421