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Advances in Politics and Economics 
ISSN 2576-1382 (Print) ISSN 2576-1390 (Online) 

Vol. 3, No. 2, 2020 
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57 
 

Original Paper 

Do Political Factors affect Government Health Spending? 

Empirical Evidence from Sub-Sahara African Countries 

Dianda Issa1* 

1 Ministry of Environment, Green economics and Climate Change, Ouagadougou, Burkina Faso 
* Dianda Issa, Ministry of Environment, Green economics and Climate Change, Ouagadougou, Burkina 

Faso 

 

Received: April 28, 2020       Accepted: May 20, 2020      Online Published: May 25, 2020 

doi:10.22158/ape.v3n2p57         URL: http://dx.doi.org/10.22158/ape.v3n2p57 

 

Abstract 

In Sub-Saharan Africa (SSA), access to essential health care services remains problematic. The financing 

of health care is mainly provided by private sources, mainly out-of-pocket payments which represent 

respectively 53.12% and 36.73% of total health expenditure in 2016. As for public health expenditure, 

essential for ensuring universal health coverage, it represents only about 35% of health expenditure. 

Thus, the increase in public spending on health from domestically sources proves to be a major challenge 

for the countries of the region in the prospect of reaching the SDG relating to health by 2030. This paper 

aims to analyse the determinants of domestic government health spending in SSA by focusing on 

political factors. We use data from 39 SSA countries covering the period 2010-2016 and 

panel-corrected standard errors method for empirical investigation. The results show that democracy 

favours an increase in government health spending. Furthermore, a political competitive environment, 

the guarantee and the protection of civil liberties and political right, accountability, government 

effectiveness and political stability are decisive for increasing government health spending. The results 

also showed that political participation does not affect public health spending. These results indicate 

that improving political factors is essential to increase public spending in SSA. 

Keywords 

political factors, domestic government health spending, health, Sub-Sahara Africa 

 

1. Introduction 

Increased levels of public funding of health services from domestic sources are required for achieving 

the Sustainable Development Goals (SDGs) related to health, especially Universal Health Coverage 

(UHC). In this respect, Kutzin (2013) reported that historically any country has managed to make 



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significant advances in UHC without having increased the funding of its health system from public 

resources. Recently, researchers have estimated the annual amount of health expenditure required in 

low-and middle-income countries for achieving health-related SDG 3 at US $ 112 per capita (Stenberg 

et al., 2017). In the same vein, the estimates of McIntyre, Meheus and Røttingen (2017) reveal that for 

progressing towards UHC, government expenditure on health, funded from domestically mobilised 

resources, must be at least 5% of Gross Domestic Product (GDP) in low income countries. 

However, in Sub-Saharan Africa (SSA), the level of domestic public health spending is low compared 

to what is required to achieve the health-related SDG by 2030. Across Sub-Saharan Africa countries, 

the average domestic government health expenditure per capita was only US$ 69.19 in Parity 

Purchasing Power (PPP) a person in 2016. Compared to US$ 940.61 in PPP for the world average, 

there is a difference of more than 13 times (World Bank, 2020a). This amount represents 35.07% of 

total health expenditures and 1.82% of GDP. Domestic private expenditure and its Out-Of-Pocket 

(OOP) component represent respectively 53.12 % and 36.73 % of total health spending. The 

preponderance of OOP spending leads to financial difficulties and even the impoverishment of 

vulnerable groups. The World Bank (2019) reported that in 2015, around 16 million Sub-Saharan 

Africans (1.6% of population) has been falled into poverty due to high OOP payments. The external 

health expenditure accounts for 11.68 % of total health expenditure.  

Similarly, SSA is the only region where communicable diseases still account for the majority of death. 

In 2016, more than half (56.36%) of deaths in SSA were caused by communicable diseases, maternal 

causes, conditions arising during pregnancy and childbirth, and nutritional deficiencies against 33.69% 

for non-communicable diseases (World Bank, 2020a). In the meantime, in other regions of the world, 

communicable and related diseases caused between 5.23% in North America and 26.95% of deaths in 

South Asia, the world average being 20.18%. In addition, SSA is the only region in the world where 

half of the health services deemed essential to achieve UHC are not accessible to the population. Only 

43.89 % of these essential services are satisfied compared to 65.69% as the world average in 2017. 

The importance of health spending, particularly public spending, in improving the health of populations 

has led some researchers to empirically identify their determinants in order to achieve better 

implementation of health policies (Tandon, Fleisher, Li, & Yap, 2014; Braendle & Colombier, 2016). 

Early authors focused on socio-economic and demographic determinants (Newhouse, 1977; Gbesemete 

& Gerdtham, 1992). However, increasingly, some researchers recognize the role of political factors in 

the financing and delivering of social services to citizens, including health services. As Gregorio and 

Gregorio (2013) pointed out, the financing and delivery of health services, by their natures, are political. 

In this sense, Kumar (2015) argued that as long as healthcare does not become a political demand and 

an electoral issue, the situation of a low level of public health care funding will not change.  

Unfortunately, only a few studies had been conducted on panel of SSA countries (Fosu, 2008) and case 

studies from Nigeria (Imoughele & Ismaila, 2013; Olawunmi, 2014) and Leshoto (Ramashamole & 

Thamae, 2015) and have focused only on accountability and political (in)stability with divergent results. 



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Accordingly, this paper seeks to address this gap in our understanding of healthcare issues investigating 

the effect of a set of political factors on government health expenditures. Understanding what political 

factors matters for public health spending can provide insight about the levers on which it is necessary 

to act to increase public spending on health with regard to its role for the path towards universal health 

coverage. 

The remainder of the paper is organized as follows. The section 2 presents literature review. The 

section 3 relates to the methodology approach. Section 4 presents and discusses the empirical results. 

The last section concludes and gives some policy implications. 

 

2. Literature Review 

This section presents the literature review on the political determinants of public health spending. We 

are interested in the political regime, in political competition, in political rights and civil liberties, in 

government functioning, in political participation, in accountability and in political stability. It is 

important to note that even if they are distinct, some political factors are linked. For example, 

according to Besley and Kudamatsu (2006), accountability and government effectiveness are more 

common in democratic system. Likewise, political rights and civil liberties, political participation and 

competition are closely linked to democratic regime rather than autocracy. 

2.2 Political Regime and Public Health Spending 

The first political factor taken into account is regime type. Theoretically, democracies are more likely 

to spend more resources on health than autocracies due to social and redistributive policies (Besley & 

Kudamatsu, 2006). According to Acemoglu and Robinson (2006), democracy is a regime more 

beneficial to the majority of the population and will result in policies that are relatively more 

favourable to it. Conversely, nondemocracy is a regime for the elite and the privileged. In this regime, 

the leaders are more likely to look after theirs interests. The majority of populace in the developing 

world is poor and have a preference for social policies, particularly in terms of education, health and 

social protection programs. These programs benefit the poor relatively more than the rich (Baqir, 2002). 

The extension of suffrage to individuals from the poorest strata, inadequately served by health care, 

water and sanitation, education or family planning, induced by democratization, promotes 

redistribution policies (Meltzer & Richard, 1981; McGuire, 2013). Median voter hypothesis explains 

this propensity of democratic countries to be more distributive by allocating more resources to the 

health and education sectors, compared to autocratic countries. Democratic leaders from an electoral 

perspective are attentive to the preferences of the median voter who, generally in these countries, is 

from middle or poor class. Being of this class, he has a preference for social health, education and 

social protection programs in relation to defence services (Habibi, 1994). Thereby, politicians should 

try to improve the quality, quantity and accessibility of such services (McGuire, 2013).  

This interest results from the fact that health expenditures are important issues in electoral debates. In 

the case of Organisation for Economic Co-operation and Development countries for example, Potrafke 



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(2010) and Bellido, Olmos, and Román (2019) report that politicians act opportunistically by 

increasing public health expenditures in election years. The parties, which promise to spend more in 

health, have more chances to win the presidential elections and parliamentary seats (Karyani, Rad, 

Pourreza, & Shaahmadi, 2015). In order to stay in power, democratic leaders must win the support of a 

larger share of the population; they have therefore an incentive to provide welfare-promoting resources 

to a larger proportion of the population (Wigley & Akkoyunlu-Wigley, 2017). Along these lines, Grépin 

and Dionne (2013) argue that universal health coverage is a “visible” good that a politician could use as 

a campaign promise (or instrument while in power) to generate broad electoral support. As a result, 

leaders are encouraged to devote more resources to funding and providing these public services, 

thereby aligning society’s needs with priorities in terms of allocating public spending.  

In contrast, under a nondemocratic regime, with power concentrated in the hands of the ruling elite, 

they will prefer targeted transfers to politically influential groups. Moreover, autocracies generally rely 

on the rich, who care less about public spending on education and health than the poor or middle 

classes (Klomp & Haan, 2013). As a substantial part of the electorate benefiting from redistribution 

programs is excluded from the decision-making process, the expenditure devoted to these programs is 

low (Habibi, 1994). 

2.2 Political Competition, Political Right, Civil Liberties and Public Health Spending 

Electoral competition is another major political factor determining the provision of health services by 

the public authorities and therefore the resources devoted to heath sector. Health spending is an 

electoral issue, notably in the developing countries. In order to win the elections or stay in power, 

politicians must gain the support of a large majority of the population and are thus, more likely to offer 

public service that benefit the majority, including health (Lake & Baum, 2001; Buracom, 2016). In a 

context where elections are free and fair, the electoral competition puts pressure on political parties to 

pursue universal, rather than more targeted health policies (Grépin & Dionne, 2013). The more 

politicians operate in an environment where competition is high and elections are free and fair, the 

more they are encouraged to succeed in health policies in order to have the support necessary for their 

re-election, due to the absence of the possibility to secure the loyalty of majority voters through 

cronyism and corruption. By making the political market more contestable, political competition 

constrains the politicians to improve the living standards (Lake & Baum, 2001).  

The increase of health and education spending is partly related to the fact that high political 

competition minimizes political rent while low level of political competition reduces welfare due to 

excessive rent seeking (Polo, 1998). It should be noted however that when political competition is such 

that the re-election of government in power is sufficiently unlikely, it can focus on maximizing political 

rent seeking during their mandate with the aim of enjoying it in the event of non-re-election (Bardhan 

& Yang, 2004).  

The guarantee of political liberty defined as the rights to run for office and vote, is another factor likely 

to influence public health spending. More political liberty facilitates greater citizen voice, namely those 



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from disadvantaged classes and hence enables them to have more political influence on budgetary 

allocation (Habibi, 1994). For these groups, the most important and priority government spendings are 

those related to health, education and social protection programs. Therefore, in a context where this 

social class is the majority, the rise of their political influence will compel the government to increase 

social expenditures. Therefore, societies in which political freedoms are more guaranteed allocate more 

resources to health (Tandon et al., 2014).  

Additionally, civil liberties including freedom of association, assembly and speech and freedom of 

press (Profeta, Puglisi, & Scabrosetti, 2013), affect government health spending. The freedoms of 

association, assembly and speech enable citizens and journalists to call attention to problems in the 

society. Under these conditions, they can denounce the poor quality of health services and press the 

authorities to improve it (McGuire, 2010; McGuire, 2013; Profeta, Puglisi, & Scabrosetti, 2013). On 

this subject, Avelino, Brown, and Hunter (2005) reported that important pressure groups involving 

social security lobbies and health care professionals have been able to influence governmental policy 

across different regime types. 

Analogously, the existence of a modicum of press freedom allows the publication of reports of acute 

health crises or unfavourable social statistics, thus highlighting shortcomings in the provision of social 

services (McGuire, 2010). The increase of freedom in press led to an availability of newspapers and 

internet web-sites to people. In press materials, citizens can express their opinions, comment and 

criticise public policies (Karyani et al., 2015). The press, interface between the rulers and ruled 

publishes the latter’s needs. This puts politicians face to face with their historic responsibilities. Since 

health is an important issue for population, rulers are more inclined to spend more on health. If they act 

otherwise, they will be punished by voters at the polling time. 

2.3 Government Functioning, Political Participation and Public Health Spending 

The selection of politicians is another mechanism through which political factor can influence the level 

of public health spending. Indeed, as Besley and Kudamatsu (2006) pointed out, democracies, due to 

electoral competition and the stronger mechanisms of selection, are more likely to bring to the head of 

states, more honest and competent governments than autocracies. Even if some autocratic leaders may 

also intend to improve population health, health intervention policies in democracies are supported and 

implemented by more knowledgeable, impartial and incorruptible officials (Besley & Kudamatsu, 2006; 

Wang, Mechkova, & Andersson, 2019). In such an environment, the search for rent is minimized and 

the decisions taken by the authorities are more likely to be in line with the priorities of the populations, 

thus favouring the general interest (Hooda, 2016). With this in mind, in a context where the provision 

of better-quality health services is a good desired by a large part of the population, as is the case in 

developing countries, governments will be more inclined to prioritize the health sector in budgetary 

arbitrations. Hence, the effectiveness of the government can determine cross-country differences in 

public health spending (Klomp & Haan, 2013; Laiprakobsup, 2019).  

From a theoretical standpoint, political participation-the right of citizens to participate in the selection 



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of rulers and the extent to which they exercise it-may lead to increased social spending, among which 

health. The more this participation is increased, the more the governments are sensitive to the concerns 

of the majority. Therefore, budget allocation is more likely to be in line with the priorities of the 

population. In this vein, Joshi and Yu (2014) argue that pressure on the state from organized lower-class 

groups can strongly influence the incentives of political leaders to provide them social services and 

benefits. So, the participation of the poor in the political system leads to outcomes which benefit them, 

with one such outcome being the amount of public resources devoted to the provision of education and 

health services (Baqir, 2002). Detraz and Peksen (2018) note that women tend to be heavily represented 

among these marginalized segments of society, and have long been portrayed as one of the major 

beneficiaries of welfare services. When they have access to political positions, they tend to strongly 

advocate for social spending.  

2.4 Accountability, Political Stability and Public Health Spending 

Accountability has been evidenced as a political factor by which to increase government health 

spending. Specifically, accountability drives the elected government to spend more on healthcare. In an 

environment where a broad set of citizens demands accountability at a regular interval to politicians, as 

it is the case of elections, the politicians are more encouraged to allocate public resources in accordance 

with people’s priorities (Datta, 2020). In this case, increasing government accountability may be more 

effective strategies to ensuring that health is given the priority it deserves (Tandon et al., 2014). Failure 

to increase the access to health services and improve health status of population may results in 

politician being removed from office at the next elections. According to Huber, Mustillo and Stephens 

(2008) and Gibson (2018), democracy is associated with increases in public health spending because 

democratic government is more accountable to the demands of the citizenry. In contrast, Kumah and 

Brazys (2016) posited that it is the related and distinct concept of accountability that yields positive 

public spending outcomes rather than democracy considering as a unitary whole. The unaccountability 

of political leaders may on the contrary, give rise to opportunities for public agents to support rent 

generating sectors to the detriment of social sector (Cockx & Francken, 2014). 

The stability of the political environment is a critical dimension of political institutions that can 

determine le level of resources devoted to health. In a context where the political environment is stable 

and certain, the governments are more willing to invest in health (Klomp & Haan, 2013). As well, the 

governments which are able to retain office and undertake declared programs tend to spend more on 

health (Liang & Mirelman, 2014). For these latter authors, there is an intrinsic difference in objectives 

of stable and unstable governments. The former is able to place more emphasis on long-term social 

programs, such as health. Many public health programs require consistent financial input while its 

benefits can be observed only in the long run. In this context, when a government does not have the 

ability to stay in office, it may have less incentive to pursue such programs. Furthermore, political 

instability caused by riots, civil war or strikes can disrupt the health system in a country (Klomp & 

Haan, 2009).  



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This review shows that theoretically, several political factors are likely to affect public spending on 

health. Given that less empirical work has been devoted to the effects of these factors on public health 

expenditure in SSA, we will fill this gap in the literature. 

 

3. Method 

In this section, we present the model specification, the variables and the method used for empirical 

investigation. 

3.1 Empirical Model Specification 

To explore the link between political factors and public healthcare expenditure, we propose the 

following functional form. 

 
Equation (1) shows that Domestic Public Health Expenditure (DGHE) is a function political factor and 

a set of control variables (X). Taking into account the panel dimension and on the basis of empirical 

work on the determinants of public health spending determinants in Africa and developing countries 

(Murthy & Okunade, 2009; Farag, et al., 2012; Behera & Dash, 2019), we propose a panel data log-log 

specification as follows: 

 

where  is the error term; i represents the country and t the period. The coefficients of independent 

variables are interpreted as elasticities.  

DPHE stands for Domestic Public Health Expenditure per capita in $US in PPP (DPHEPC) or as share 

of GDP (DPHE_GDP). The control variables include Gross Domestic Product per capita in $US in PPP 

(PCGDP), Tax revenue as share of GDP (TR), population aged 65 and above as share of total 

population (Pop65), the tuberculosis incidence per 100,000 inhabitants (TBI) and the official 

development assistance for health sector per capita (PCODAH) $US in PPP. 

3.2 Variables Presentation 

We have in our model, three types of variables: the dependent variable, the variables of interest and 

variables of control.  

3.2.1 The Dependent Variable 

Our dependent variable is DPHE. Public expenditure on health from domestic sources include domestic 

revenue as internal transfers and grants, transfers, subsidies to voluntary health insurance beneficiaries, 

non-profit institutions serving households or enterprise financing schemes as well as compulsory 

prepayment and social health insurance contributions. They do not include external resources spent by 

governments on health (World Bank, 2020a). They are expressed in domestic Public Health 

Expenditure per capita in $US in PPP (DPHEPC) or as share of GDP (DPHE_GDP). 

 



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3.2.2 The Explanatory Variables of Interest 

Political factors are our independent variables of interest. In total, seven factors are considered. The 

first political factor used is democracy index. To this end, we use two indicators. The first is the 

Economist Intelligence Unit (EIU) Democracy Index (EIUDI). According to EIU (2011), the EIUDI, on 

a 0 to 10 scale, is based on the ratings for 60 indicators grouped in five categories: electoral process and 

pluralism, civil liberties, functioning of government, political participation, and political culture. The 

index provides a snapshot of the state of democracy worldwide for 165 independent states and two 

territories. The index values are used to place countries within one of four types of regimes : full 

democracies (scores of 8-10), flawed democracies (scores of 6 to 7.9), hybrid regimes (scores of 4 to 

5.9) and authoritarian regimes (scores below 4). The EIUDI is more comprehensive than other ordinal 

democracy scales because it includes sub-scores such as functioning of government and political 

culture that other indices do not (Walker, Anonson, & Szafron, 2015). The second democracy indicator, 

used as a robustness, is Polity2 of Polity IV. It ranges from -10 (strongly autocratic) to 10 (strongly 

democratic) and takes into account the free elections, the existence of legal limitations to the exercise 

of executive power by a government and its chief executives and inclusive participation and 

representation by political parties (Marshall, Gurr, & Jaggers, 2017). 

The second political factor is political competition. We use EIU sub-score of electoral process and 

pluralism as proxy of political competition. This sub-score includes among others free and fair 

elections, universal suffrage, exchange of power following elections, and ability to form political 

groups (Economist Intelligence Unit, 2011). 

The political rights and civil liberties are the third political factor used. The political rights are from 

Freedom House (2017) and comprise the electoral process, the political pluralism and participation, and 

the functioning of government. Two indicators are used to approximate civil liberties. The first is the 

civil liberties of Freedom House (2017) and are related to freedom of expression and belief, 

associational and organizational rights, rule of law and personal autonomy and individual rights. The 

indicators of political and civil right of Freedom House are calibrated from 1 to 7. A score of 1 

represents the greatest degree of freedom and 7 the smallest degree of freedom. The second indicator is 

EIU sub-score of civil liberties. It takes into consideration the freedoms of speech and protest, of the 

press, of information, freedom of and influence of the judiciary system by government among others 

(Economist Intelligence Unit, 2011). 

The fourth political factor is government effectiveness. This is approximated by two indicators. The 

first is EIU sub-score of the functioning of government. It measures public confidence in the 

government, influence of the government from outside sources, and the ability of the government to 

implement policies (Economist Intelligence Unit, 2011). The second is government effectiveness from 

Worldwide Governance Indicator (World Bank, 2020c). According to Kaufmann, Kraay and Mastruzzi 

(2010), this indicator captures the perceptions of the quality of public services, the quality of the civil 

service and the degree of its independence from political pressures, the quality of policy formulation 



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and implementation, and the credibility of the government’s commitment to such policies. 

Political participation and culture are the fifth factor and come from EIU Sub-scores of political 

participation and political culture. The political participation involves the degree to which the public 

engages in political matters while political culture involves public perception of leadership and 

democracy (Economist Intelligence Unit, 2011).  

The sixth factor relates to accountability and is measured through two indicators. The first is voice and 

accountability from WGI and relates the perceptions of the extent to which a country’s citizens are able 

to participate in selecting their government, as well as freedom of expression, freedom of association, 

and a free media (Kaufmann, Kraay, & Mastruzzi, 2010). The second, democratic accountability is 

taken from International Country Risk Guide (ICRG). It is a measure of how responsive government is 

to its people, on the basis that the less responsive it is, the more likely it is that the government will fall, 

peacefully in a democratic society, but possibly violently in a non-democratic one (Howell, 2012). 

The last factor is political stability. It is measured trough the indicator political stability and absence of 

violence/terrorism from WGI and captures perceptions of the likelihood that the government will be 

destabilized or overthrown by unconstitutional or violent means, including politically—motivated 

violence and terrorism. 

The EIUDI and its sub-score range from 0 to 10. The WGI indicators (government effectiveness, voice 

and accountability and political stability and absence of violence/terrorism) range from -2.5 (weak 

governance) to +2.5 (strong governance). Democratic accountability of ICRG ranges from 0 to 6. These 

indicators has been rescaled to assume values between 1 and 6 (WGI), 1 and 11 (EIUDI and its 

sub-scores), 1 and 21 (Polity2), 1 and 7 (democratic accountability), for practical needs (the use of 

logarithm) as it is often the case in the literature (McGuire, 2013; Karyani et al., 2015; Dianda & Sirpé, 

2020).  

3.2.3 The Control Variables 

Our control variables are five. They are macro-fiscal, epidemiological and demographic variables and 

are considered to be determinants of public health spending. They include Gross Domestic Product per 

capita in $US in PPP (PCGDP), Tax revenue as share of GDP (TR), population aged 65 and above as 

share of total population (Pop65), The Tuberculosis Incidence per 100,000 Inhabitants (TBI) and the 

Official Development Assistance for Health sector Per Capita (PCODAH) $US in PPP. 

Since the seminal work by Newhouse (1977) who found that in developed countries the variation of per 

capita GDP explains more than 90% of the variation in per capita healthcare expenditure, the wealth of 

countries is considered as the main determinants of their health spending. In line with this, we assume 

that income is positively linked to public health expenditure. Similarly, the level of tax revenue 

reflecting the fiscal capacity of the government, we anticipate that it positively affects the public health 

spending. We also assume that the official development assistance for health sector is complementary 

to domestic public spending due to the weakness of domestic spending and the health systems of SSA 

described in the introduction. An aging and sick population requires additional resources to provide 



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them with adequate health care. Therefore, we hypothesize that the proportion of the population whose 

age is greater than or equal to 65 years and the incidence of tuberculosis are factors that increase public 

spending on health.  

The data used are annual and cover 39 SSA countries listed in appendix for the period 2010-2016 due 

to their availability. The data on domestic public health expenditure, official development assistance for 

Health, the proportion of the population whose age is greater than or equal to 65 years, and the 

incidence of tuberculosis are taken from health, nutrition and population database of the World Bank 

(2020a). GDP per capita and tax revenue are respectively from world development indicators database 

of the World Bank (2020b) and Government Revenue Dataset of the International Centre for Tax and 

Development (2020). 

3.3 Estimation Method 

For empirical investigation, as previous studies on the determinants of health spending (Avelino, 

Brown, & Hunter, 2005; Gibson, 2018), we use panel-corrected standard errors method proposed by 

Beck and Katz (1995). In general, times-series cross-sectional data violate at least two of the basic 

assumptions that underlie Ordinary Least Squares (OLS) estimation (Avelino, Brown, & Hunter, 2005). 

These authors point out that temporal structure of the data increases the chance of autocorrelation, 

violating the OLS assumption that the errors are independent of each other. Similarly, the 

cross-sectional structure of the data increases the chance that the variance in the error terms may differ 

across countries and that there will be spatial processes that affect different panels simultaneously. 

Therefore, the presence of heterogeneity and autocorrelation renders OLS coefficient estimates 

inefficient. The panel-corrected standard errors method deals with these problems. 

 

4. Empirical Result 

In this section, we present and discuss the results in three stages. In the first subsection, the main 

descriptive statistics of the basic model and stylized facts are presented. The second subsection is 

devoted to the presentation and discussion of the results of the basic model which uses democracy as a 

political factor. The last subsection discusses the results of the effect of other political factors on public 

health spending. 

4.1 Summary Statistics and Stylized Facts 

 

Table 1. Below Summarizes Some Descriptive Statistics of the Variables Used over the Period 

2010-2016. 

 

 

 

 

 



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Table 1. Descriptive Statistics 

Variables Observations Mean  Standard deviation Minimum Maximum 

EIUDI 273 4.489 1.814 1.26 8.28 

Polity 2 273 2.897 5.160 -9 10 

DPHEPC ($ US in PPP) 273 95.779 151.194 1.878 599.923 

DPHE_GDP 273 1.822 1.281 0.196 5.800 

PCGDP ($US in PPP) 273 4554.236 6124.155 646.295 36576.09 

PCODAH ($US in PPP) 273 32.172 25.616 2.329 143.537 

TR (% of GDP) 273 15.455 7.319 4.406 46.757 

TBI (per 100.000 

inhabitants) 

273 283.776 232.746 11 1190 

Pop65 (% of total 

population) 

273 3.123 1.189 1.871 10.443 

Source: Author computation from data. 

 

This Table reveals that regional average score of the democracy index is 4.489, suggesting that the state 

of democracy in this panel is poor between 2010 and 2016. The region is characterised by the 

concentration of hybrid and authoritarian regimes (respectively 12 and 19 countries out 44 in 2016) 

with few countries considered as flawed democracies (7 countries out 44) and only one country 

(Mauritius) is a full democracy. Similarly, with a score of 4.37, Sub-Saharan Africa was the lowest 

democracy region against 5.52 for the world average. This fact is corroborated by the indicator Polity2 

which, although having a positive regional average over the period, remains weak (2.897). 

The regional per capita government health spending from domestic sources is 95.77 $US in PPP which 

corresponds to 1.822 % of GDP. Given the challenges of funding the provision of preventive and 

curative health services in the region, and what is needed to achieve universal health coverage by 2030, 

this amount is small. Probably, it is related to region’s GDP per capita, which stood at 4554.23 $US in 

PPPA during this period. The low level of domestic public health financing necessitates the use of 

external resources as part of official development assistance. Thus, during the period under review, our 

panel countries benefited from public aid to improve the health of their population in the average 

amount of 32.17 per inhabitants. The countries of the region have mobilized through taxation an 

amount representing 15.45% of GDP. These financial resources were used in part to cope with 

tuberculosis, the incidence of which is 283.78 per 100.000 inhabitants, as well as the needs of people 

aged 65 and over, estimated at around 3.12% of the population. 

Table 2 below presents public expenditure by political regime according to the classification of EIU in 

2010 and 2016. 

 



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Table 2. Government Health Spending by Political Regime, 2010 and 2016 

Year 

Democracies  

(Full and flawed) 

Hybrid 

Regimes Authoritarian 

SSA 

Average 

DPHEPC ($ US in PPP) 2010 227.64 21.14 47.58 56.81 

2016 306.97 35.63 63.24 69.19 

DPHE_GDP 2010 2.97 1.30 1.38 1.93 

2016 3.21 1.86 1.47 1.83 

Source: Author computation from data. 

 

From this Table, it emerges that democracies (full and flawed) spend more financial resources on the 

health of their population than hybrid regimes and autocracies. Likewise, autocracies have higher levels 

of public spending on health both per capita and as a share of GDP than hybrid regimes. In 2010 for 

example, in the democracies of the region, public spending on health per capita amounted to 227.64 

$US per capita, or 2% of GDP against 21.14 $US per capita for hybrid regimes corresponding to 1.30 

% of GDP and 47.58 $US per capita equivalent to 1.93 % of GDP for autocratic countries. It should be 

noted that public health spending per capita in the region’s democracies is higher than the regional 

average in 2010 (56.81 $US) while hybrid regimes and autocracies have lower levels. The same is true 

for public spending as a share of GDP. This trend is also observed for the year 2016. If these facts are 

not sufficient to conclude on the nature of the link between the political system and public health 

spending, the econometric evaluation will allow us to detect it. 

4.2 Baseline Estimate Results and Discussion 

The estimates with EIUDI and Polity 2 are considered as baseline estimate. The results are shown in 

Table 3. 

 

Table 3. Democracy and Public Health Spending in SSA 

Dependent Variable: log (DPHEPC) log (DPHE_GDP) log (DPHEPC) log (DPHE_GDP) 

log (EIUDI) 0.387*** 

(0.000) 

0.326*** 

(0.000) 

  

log (Polity2)   0.111** 

(0.021) 

0.078* 

(0.097) 

log (PCGDP) 1.030*** 

(0.000) 

0.030** 

(0.017) 

1.047*** 

(0.000) 

0.042** 

(0.029) 

log (TR) 0.666*** 

(0.000) 

0.670*** 

(0.000) 

0.766*** 

(0.000) 

0.758*** 

(0.000) 

log (Pop 65) 0.320*** 

(0.000) 

0.333 

(0.437) 

0.395*** 

(0.000) 

0.401*** 

(0.00) 



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log (TBI) 0. 084** 

(0.010) 

0. 069** 

(0.032) 

0. 060 

(0.115) 

0. 048 

(0.201) 

log (PCODAH) 0.156*** 

(0.000) 

0.160*** 

(0.000) 

0.209*** 

(0.000) 

0.205*** 

 (0.000)  

Constant -8.234*** 

(0.000) 

-3.417*** 

(0.000) 

-8.389*** 

(0.000) 

-3.504*** 

(0.000) 

Countries 39 39 39 39 

Observations 263 263 263 263 

R-Squared 0.863 0.480 0.860 0.476 

Prob > CHI2 0.000 0.000 0.000 0.000 

Figures in parentheses are p-values; ***, ** and *denote respectively significance at 1%. 5% and 10%. 

Source: Author estimation. 

 

In general, the explanatory variables jointly and significantly explain the change in government 

spending on health, as the CHI2-statistics are statistically significant at 1% level (p-value < 0.00). In 

addition, R-Squared is between 0.47 and 0.86, suggesting that the independent variables capture 

between 47% and 86% of the variations in public health expenditures. 

In Table 3, results show that democratisation has a significant positive effect on government health 

spending at 1% level of significance. The consolidation of democracy, resulting in an increase in the 

economic intelligence unit democracy of 1% translates, all things being equal, by an increase in 

domestic public health expenditure per inhabitant of 0.38%. Similarly, the result implies that at 1% 

incremental change in democracy leads to 0.32% change in the share of public health spending in GDP. 

The extension of franchise to the low and middle-class citizens enables them to influence public 

policies and this force the elite to take into account their interest. Yet, these people have a preference 

for redistributive policies, including health (Baqir, 2002). Consequently, the democratization has a 

favourable effect on government health spending. The Afro barometer survey, which covered 36 

African countries in 2014/2015, revealed that for African citizens, problems related to health are the 

second most important problem (after unemployment) that their governments must tackle. Likewise, 

this sector is classified in second priority (after education) which requires an additional investment on 

the part of the government (Armah-Attoh, Selormey, & Houessou, 2016). The positive link between 

democracy and government health spending remains robust when polity2 is used as its proxy. 

This expected positive association between democratisation and government health spending is in 

accordance with the results in earlier studies especially in mixed sample of developed and developing 

countries (Ghobarah, Huth, & Russett, 2004; Gregorio & Gregorio, 2013; Kotera & Okada, 2017). 

Similarly, the crucial role that democracy plays in increasing public spending on health has been 

highlighted by studies based on developing countries, particularly in Eastern Mediterranean countries 

(Karyani et al., 2015), in Latin American countries (Kaufman & Segura-Ubiergo, 2001) and Southeast 



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Asia (Laiprakobsup, 2019). Likewise, an existing study on Latin American countries has shown a 

positive association between the stock of democracy (number of years of democracy accumulated since 

1945) and social spending, especially spending on health and education (Huber, Mustillo, & Stephens, 

2008). 

Unlike these studies and ours, Avelino, Brown, and Hunter (2005) and McGuire (2010) found that 

democracies do not influence government spending on health respectively in Latin American countries 

and a sample of developing countries. In the same perspective, Adolf (2011) suggested that government 

spending on social programs (such as health and education) is independent of the nature of the political 

system. In addition to these empirical investigations, some stylized facts from history have questioned 

the propensity of democracies to allocate more resources to health compared to nondemocratic regimes. 

These facts show that democratic countries do not spend necessarily more on social sector and deliver 

such service to population than autocratic ones. Datta (2020) cites the India’s case as one compelling 

example where a practicing democracy did not lead to better healthcare policy as measured by level of 

public healthcare spending and improved health outcome. This country, in spite of being the world’s 

largest democracy since its independence in 1947, spent only 1.27% of its GDP on public healthcare in 

2015. In a historical and comparative analysis, Joshi and Yu (2014) corroborate this point of view by 

noting that from independence to 2011, the public investment in health of the different Indian 

governments remained low despite the existence of a democratic regime. Conversely, China, considered 

to be an autocracy, alternated high (1949-1978), low (1979-2000) and intermediate levels of public 

health investment. For Joshi and Yu (2014), it is less the political regime than the political implication of 

lower class, namely organized political pressure from the lower classes, and the development ideology of 

political leaders that explains the difference in public health investment in low-income countries. 

In agreement with these authors, Grépin and Dionne (2013) noted that it is not simply the level of 

democracy that makes governments more likely to adopt health policies that benefit the population in the 

broadest sense, but rather the extent to which democratic development is perceived as meaningful by 

citizens and is manifested in electoral competition that puts pressure on political parties to pursue 

universal, rather than more targeted, health policies. Kumah and Brazys (2016) posited that rather than 

considering ‘democracy’ as a unitary whole, it is the related, but distinct, concept of accountability that 

yields positive public spending outcomes. Wigley and Akkoyunlu-Wigley (2017) argued that it is 

possible that democratic governments will not target welfare transfers and public goods to low-income 

citizens because their votes are not required in order to secure a winning majority. 

If the positive relation between democracy and government health spending is established, we do not 

know from what dimension of democracy it results. This does not enable, in a context where the increase 

in domestic public health funding is more than necessary to ensure the sustainability of interventions and 

move towards UHC, to make strong recommendations for the attention of policy makers. Hence, the 

need for democracy key aspects and broadly more detailed political factors. This is the subject matter of 

the next subsection. 



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On the whole, the coefficients of most control variables have the expected sign. Meanwhile, the 

estimation results in Table 3 indicate that the income per capita has the anticipated sign. Its coefficient 

is positive and significant at the 1% level for government health spending per capita model and 5% 

level for government health spending as share of GDP model. This result means that the increase in 

GDP leads to increased government health spending. All other things being equal, a 1% increase in 

GDP per capita is associated with government health spending increases between 0.04 % and 1.04%. 

Thus, the more countries develop, the more they are able to allocate more resources to health. When we 

use public spending on health in proportion to the GDP as dependent variable, the income elasticity is 

less than one, suggesting that public provision of health care in SSA is considered as a necessity. This 

result is in line with those obtained in panel studies of developing countries led by Farag et al. (2012) 

and Sub-Saharan countries (Dianda & Sirpé, 2020; Micah et al., 2019). In contrast, when we use 

domestic public health spending per capita as the dependent variable, the income elasticity is greater 

than 1, suggesting that health care is a luxury good. This result is empirically highlighted in Sub-Sahara 

African context (Jaunky & Khadaroo, 2008; Ramashamole & Thamae, 2015; Ly et al., 2017) and in 

low income countries (Xu, Saksena, & Holly, 2011). As Okunade (2005) pointed out, African countries 

historically spent a more than proportionate increase in their GDPs on health care. This can be 

explained by the fact that in the context of Africa, the public sector has to strive hard to provide basic 

health care to the poor majority (Jaunky & Khadaroo, 2008). In view of the difference in elasticities 

obtained in the two models, this study does not allow us to conclude on the nature of health care.  

The fiscal capacity and government health spending are positively, statistically and significantly 

associated at 1% level. It is of prime importance in determining the level of government health spending. 

A 10% rise in public revenue as proportion of GDP is associated with a 6.6% to 7.7% increase in 

government health spending, all else being equal. The improvement of fiscal capacity enables the 

government to spend more on health. This result corroborates previous one that fiscal capacity favours an 

increase of public health spending (Hooda, 2016; Dianda & Sirpé, 2020). 

The incidence of tuberculosis is found to be positive as expected and significant at the 5 % level in two 

of the four equations in explaining public health spending. The 1% increase in tuberculosis incidence 

translates into between 0.06%-0.08% increase in government health spending. The sicker the 

population, the more resources are needed for medical care. This is especially for contagious diseases 

as they generate negative externalities. This result calls into question that of the authors who have 

shown that the epidemiological profile is not a significant determinant of public health spending (Xu, 

Saksena, & Holly, 2011; Sirag, Nor, & Abdullah, 2017). Nonetheless, this result is in agreement with 

that obtained with the population aged 65 and over. The coefficient of this variable is positive and 

significant at the 1% level. In general, this segment of the population is very vulnerable to disease, 

demands more health services and requires more frequent and more costly medical treatment than 

younger people (McGuire, 2010). Our results are similar to those who find a positive and statistically 

significant relationship between the share of population aged over 65 and public health expenditures in 



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low-and middle-income countries (Behera & Dash, 2019). However, this result contradicts those 

according to which the elderly population and more generally demographic factors have no significant 

effect on public health expenditure (Fosu, 2008; McGuire, 2010; Kumah & Brazys, 2016; Sirag, Nor, & 

Abdullah, 2017; Dianda & Sirpé, 2020; Micah, et al., 2019). 

As expected, the estimated effect of donor assistance for health is positive and significant at the 1% 

level. A 1% increase in heath aid per capita induces, ceteris paribus, an increase in public health 

spending per capita between 0.15% and 0.20% and in public health spending as share of GDP between 

0.16% and 0.20%. The more countries receive health aid, the more they spend domestically resources 

on health, thus highlighting the complementarity between health aid and domestic government health 

spending. In Sub-Saharan Africa countries with limited resources, increased health aid leads to higher 

allocation of resources to health sector. This result is in line with the authors who found that health aid 

is not totally fungible in Africa (Kumah & Brazys, 2016; Dianda & Sirpé, 2020) but contrasts with the 

result that health aid does not influence government health spending or is fungible in developing world 

(Lu et al., 2010; Micah et al., 2019). 

4.3 Other Political Factors Effects on Government Health Spending 

The discussion of the effects of other political factors on public health expenditure will be done in three 

stages. First, we consider the political competition, the political right and the civil liberties. Then we 

take into account the dimensions government functioning, political participation and political culture. 

Finally, we analyse the effects of accountability and political stability on government health spending. 

4.3.1 Political Competition, Political Right and Civil Liberties 

In all the Tables which follow in the even columns, the logarithm of domestic public health spending 

per capita is the dependent variable while in the odd columns, the share of domestic public health 

spending in GDP is the dependent variable. 

Table 4 shows the results of the estimates with political competition (columns 1 et 2), political right 

(columns 3 et 4) and civil liberties (columns 5 to 8) as political variable.  

 

Table 4. Political Competition, Political right, Civil liberties and Public Health Spending in SSA 

Model (Note 

1) 

(1) (2) (3) (4) (5) (6) (7) (8) 

log(EIUEPP) 0.117*** 

(0.000) 

       

log(EIUEPP)  0.110*** 

(0.001) 

      

log (FHPR) 

 

  -0.271*** 

(0.000) 

     

log (FHPR)    -0.248***     



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 (0.000) 

log (FHCL) 

 

    -0.382*** 

(0.000) 

   

log (FHCL)      -0.347*** 

(0.000) 

  

log (EIUCL)       0.595*** 

(0.000) 

 

log (EIUCL)        0.510*** 

(0.000) 

log(PCGDP) 1.052*** 

(0.000) 

0.050*** 

(0.004) 

1.035*** 

(0.000) 

0.034** 

(0.011) 

1.036*** 

(0.000) 

0.353*** 

(0.007) 

1.032*** 

(0.000) 

0.032** 

(0.016) 

log (TR) 0.728*** 

(0.000) 

0.715*** 

(0.000) 

0.740*** 

(0.000) 

0.727*** 

(0.000) 

0.678*** 

(0.000) 

0.672*** 

(0.000) 

0.602*** 

(0.000) 

0.612*** 

(0.000) 

log (Pop 65) 0.365*** 

(0.066) 

0.364** 

(0.037) 

0.173* 

(0.066) 

0.190** 

(0.037) 

0.192** 

(0.020) 

0.209*** 

(0.009) 

0.217** 

(0.018) 

0.243*** 

(0.006) 

log (TBI) 0. 072** 

(0.026) 

0. 060* 

(0.055) 

0.089*** 

(0.003) 

0. 076** 

(0.011) 

0. 089** 

(0.010) 

0. 075** 

(0.027) 

0.103*** 

(0.000) 

0.085*** 

(0.003) 

log(PCODAH) 0.183*** 

(0.000) 

0.179*** 

(0.000) 

0.179*** 

(0.000) 

0.176*** 

(0.000) 

0.163*** 

(0.000) 

0.162*** 

(0.000) 

0.123*** 

(0.000) 

0.131*** 

(0.000) 

Constant -8.171*** 

(0.000) 

-3.374*** 

(0.000) 

-7.401*** 

(0.000) 

-2.666*** 

(0.000) 

-7.066*** 

(0.000) 

-2.367*** 

(0.000) 

-8.348*** 

(0.000) 

-3.518*** 

(0.000) 

Countries 39 39 39 39 39 39 39 39 

Observations 263 263 263 263 263 263 263 263 

R-Squared 0.861 0.482 0.866 0.497 0.867 0.501 0.872 0.513 

Prob > CHI2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

Figures in parentheses are p-values; ***, ** and *denote significance at 1%. 5% and 10% respectively. 

Source: Author estimation. 

 

As expected, the political competition affects positively the government health spending. The political 

competition variable is statistically significant at 1% in both model (1 and 2). A 1% increase in political 

competition indicator lead to 0.11% increase in public health spending per capita and as share of GDP. 

The result shows that a competitive political environment is associated with an increase in the per 

capita government health spending and the percentage share of government health spending on GDP. 

Health is an electoral issue and if the political environment is competitive, the rulers are forced to 

spend more on health in order to get the support necessary for their re-election. In addition, a 

contestable political market minimizes the rent seeking activities (Polo, 1998), thus favouring the 



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general interest. In these conditions, given that health is a priority in the region, political competition 

generates an increase in public spending on health. This finding is corroborated in some studies where 

political competition is found to have a strong positive influence on education spending in Africa and 

public healthcare expenditure in India (Stasavage, 2005; Datta, 2020). A panel analysis of the 16 India 

major states undertaken by Datta (2020) found that political competition has a strong positive influence 

on public healthcare expenditure. In an environment where government is facing high degree of 

political competition in election from the opposition parties, it increases spending on public healthcare 

to maximize his chances of winning in the next election. Stasavage (2005) also found that when they 

are subject to multiparty competition, African governments have indeed tended to spend more on 

education and more on primary education in particular. 

The columns 3-4 and 5-6 of Table 4 report the estimations in which the political rights and civil 

liberties of Freedom House are used as proxy indicators of political factors. In the columns 7 and 8, the 

results of estimates with civil liberties of Economist Intelligence Unit as political factor are reported. 

Note that unlike the other political variables used, in the case of these Freedom House indicators, a low 

level indicates that in the country political and civil liberties are guaranteed while a high score indicates 

a confiscation of these freedoms. The results show that the coefficients of political right and civil 

liberties from Freedom House are negative and significant at 1% threshold, as expected. Similarly, the 

coefficient of civil liberties of economic Intelligence unit is positive and significant at 1% level. The 

results reveal that better guarantee of political rights and better protection of civil liberties, contribute to 

an increase in public health spending. These findings are in line with what has been found in other 

similar studies done in mixed sample and developing world which show that the improvement of 

political liberties and freedom in the press and increased civil liberties protection are positively related 

to government health spending (Habibi, 1994; Profeta, Puglisi, & Scabrosetti, 2013; Karyani et al., 

2015). Habibi (1994) shows empirically that the improvement of political liberties leads to an increase 

of public spending on health and social security in proportion to GDP, but reduces the share of public 

spending devoted to defence in a sample of 67 developed and developing countries. This result in 

consistent with those of Karyani et al. (2015), who found that political freedom measured by freedom 

in the press index positively affect government health expenditures in a panel of 20 Eastern 

Mediterranean countries. Similarly, Profeta, Puglisi, and Scabrosetti (2013) present empirical evidence 

from developing countries in three geographical areas (South-East Asia, Latin America and European 

Union) showing that increased civil liberties protection to higher health expenditure over GDP. 

4.3.2 Government Functioning, Political Participation, Political Culture and Public Health Spending 

The Table 5 reports the results of estimates with the EIU Sub-score of functioning of government 

(columns 1 and 2), WGI government effectiveness (columns 3 and 4), EIU sub-score of political 

participation (columns 5 and 6) and EIU sub-score of political culture (columns 7 and 8) as political 

factors. 

 



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Table 5. Government Functioning and Effectiveness, Political Participation and Culture and Public 

Health Spending in SSA 

Model (Note 2) (1) (2) (3) (4) (5) (6) (7) (8) 

log(EIUFOG) 0.205*** 

(0.000) 

       

log(EIUFOG)  0.208*** 

(0.000) 

      

log (WGIGE)   1.167*** 

(0.000) 

     

log (WGIGE)    1.176*** 

(0.000) 

    

log (EIUPP)     0.093 

(0.114) 

   

log (EIUPP)      0.491 

(0.431) 

  

log (EIUPC)       0.207** 

(0.041) 

 

log (EIUPC)        0.117 

(0.265) 

log (PCGDP) 1.004*** 

(0.000) 

0.003 

(0.805) 

1.184*** 

(0.000) 

1.186*** 

(0.008) 

1.030*** 

(0.000) 

0.030** 

(0.025) 

1.023*** 

(0.000) 

0.026** 

(0.042) 

log (TR) 0.685*** 

(0.000) 

0.666*** 

(0.000) 

0.322*** 

(0.000) 

0.302*** 

(0.000) 

0.767*** 

(0.000) 

0.763*** 

(0.000) 

0.765*** 

(0.000) 

0.761*** 

(0.000) 

log (Pop 65) 0.396*** 

(0.000) 

0.391*** 

(0.000) 

0.110* 

(0.083) 

0.130** 

(0.019) 

0.411*** 

(0.000) 

0.416*** 

(0.000) 

0.415*** 

(0.018) 

0.418*** 

(0.006) 

log (TBI) 0.082** 

(0.016) 

0.073** 

(0.029) 

-0.06 

(0.930) 

-0.011 

0.873 

0. 511 

(0.155) 

0. 041 

(0.240) 

0. 067* 

(0.095) 

0. 050 

(0.203) 

log (PCODA) 0.168*** 

(0.000) 

0.161*** 

(0.000) 

0.067*** 

(0.002) 

0.057** 

(0.011) 

0.209*** 

(0.000) 

0.206*** 

(0.000) 

0.191*** 

(0.000) 

0.195*** 

(0.000) 

Constant -7.823*** 

(0.000) 

-3.029*** 

(0.000) 

-8.078*** 

(0.000) 

-3.357 

(0.000) 

-8.091*** 

(0.000) 

-3.290*** 

(0.000) 

-8.280*** 

(0.000) 

-3.398*** 

(0.000) 

 Countries 39 39 27 27 39 39 39 39 

Observations 263 263 185 185 263 263 263 263 

R-Squared 0.963 0.492 0.861 0.454 0.858 0.473 0.859 0.474 

Prob > CHI2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

Figures in parentheses are p-values; ***, ** and *denote significance at 1%. 5% and 10% respectively. 



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Source: Author estimation 

 

As it is evident in the Table 5, the functioning of government has a significant and positive effect on 

government health spending. Specifically, the results indicate that when the indicator of the functioning 

of government increases by 1 % public health spending rises by about 0.20 %. This finding is in line 

with what has been found with government effectiveness are from Worldwide Governance Indicators as 

political variable. The Table reveals that the coefficient of government effectiveness is positive and 

statistically significant at 1%. These results demonstrate that a better functioning of the government and 

increased effectiveness is an ingredient conducive to increased public spending on health. When the 

government is honest and competent, not only rent seeking activities are limited and the public interest 

is much more likely to be saved, but also public policies are better implemented. In the quest for 

general interest, given that health is a priority in SSA, public spending on health is expected to increase. 

This finding is supported by previous studies on developing countries (Sirag, Nor, & Abdullah, 2017; 

Gibson, 2018). Gibson (2018) examining the determinants of public health spending in the countries of 

the Arab League between 1996 and 2014, found that the government effectiveness is positively 

associated with public health spending. In the same vein, Sirag, Nor, and Abdullah (2017) found that in 

developing countries, government effectiveness tends to improve public health financing. However, in 

developed countries, the authors did not find a significant link between government effectiveness and 

public health financing. 

The coefficient of political participation is positive but is insignificant at the conventional level. 

Contrary to what is expected, the political participation in SSA does not affect government health 

spending. The result challenges the authors’ finding that political participation is a determinant of 

government health spending (Miller, 2008; Joshi & Yu, 2014; Braendle & Colombier, 2016; Hooda, 

2016). Some authors have highlighted the positive effect of close involvement of the populations in the 

budget process on the allocation of public spending to health programs. This is particularly the case of 

Brazilian communities through the adoption at the decentralized level of the participatory budgeting 

since the beginning of the 1990s. In this context, Gonçalves (2014) found significant differences in the 

allocation of expenditures associated with adoption of participatory budgeting. The municipalities with 

a greater share of participatory budgeting spend a larger proportion of their total budget on health and 

sanitation. The author highlights an average difference of above 3% points, between a municipality 

without participatory budgeting and a municipality that adopts participatory budgeting, of the budget 

share allocated to health and sanitation.  

Along the same lines, Hooda (2016) explores the relationship between political participation and the 

variation in government spending on health, including expenditure on water and sanitation, in 16 states 

in India over the period 1987-1988 to 2011-2012. Political participation is approximated by a 

composite indicator constructed using the Principal Component Analysis (PCA) from several variables. 

These include, among other things, the percentage of total voter turnout in assembly election of a state, 



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the total number of women who voted in assembly election as percentage of men who voted in 

assembly election, the percentage of women contestants in assembly election. Similarly, are taken into 

account in the calculation of the composite indicator of index of political participation, the percentage 

of women contestants elected in assembly election of a state and the women and reserved class 

Panchayat representatives as a share of total panchayat representatives in a state. According to his 

analysis, the author validates the hypothesis that the widening of political participation and a greater 

representativeness of various population groups, notably the most vulnerable and minorities in the 

political sphere, leads to a significant rise in government spending on health. This result reflects the 

fact that a large involvement of minority populations in the electoral process allows leaders to align 

their decisions with the interests and priorities of the population, especially the needs in terms of health 

care. In the same way, Joshi, and Yu (2014) emphasize on the political implication of lower class, 

namely organized political pressure from the lower classes, in addition to the development ideology of 

political leaders in determining levels of public health investment in low-income countries instead of 

regime type.  

The hypothesis that a rise in women’s political participation is associated with greater health care 

spending is highlighted by empirical investigations. From an analysis of Swiss cantons, Braendle and 

Colombier (2016) found that cantonal health care expenditure growth increases with the presence of 

women in parliament. This indicates a stronger preference of elected women for public health care 

spending for health spending. Similar findings from a panel of the United States municipalities 

indicated that extension of suffrage rights to American women increases local public health spending 

(Miller, 2008).  

Our counterintuitive result can be explained by the quality of the participation and the profile of the 

participants. In studies that have found the positive link between participation and public health 

expenditure, this participation has generally been the work of women and vulnerable people with 

obvious health benefits. As political culture takes hold, public health spending increases. Indeed, as the 

results recorded in columns 7 and 8 of Table 5 show, the sign of political culture is positive, significant 

at 5% level for public health spending per capita and not significant for public health spending as a 

percentage of GDP. The coefficient indicates that when the indicator of political culture increased by 

1%, public health spending per capita raised by 0.20%. 

4.3.3 Accountability, Political Stability and Public Health Spending 

Table 6 presents the results of the estimates considering accountability and political stability as political 

variables. 

 

Table 6. Accountability, Political Stability and Public Health Spending in SSA 

Model (Note 3) (1) (2) (3) (4) (5) (6) 

log (WGIVA) 1.446***      



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(0.000) 

log (WGIVA)  1.320*** 

(0.000) 

    

log (ICRGDA)   1.045*** 

(0.000) 

   

log (ICRGDA)    0.963*** 

(0.000) 

  

log (WGIPSAVT)     0.572*** 

(0.000) 

 

log (WGIPSAVT)      0.710*** 

(0.000) 

log (PCGDP) 1.275*** 

(0.000) 

0.281*** 

(0.000) 

1.392* 

(0.000) 

0.389*** 

(0.042) 

1.237*** 

(0.000) 

0.222*** 

(0.001) 

log (TR) 0.141** 

(0.045) 

0.174* 

(0.051) 

0.372*** 

(0.000) 

0.357*** 

(0.000) 

0.346*** 

(0.000) 

0.308*** 

(0.001) 

log (Pop 65) -0.027 

(0.744) 

0.017 

(0.822) 

0.027 

(0.752) 

0.066 

(0.405) 

0.240** 

(0.010) 

0.257*** 

(0.004) 

log (TBI) 0. 036 

(0.566) 

0. 022 

(0.720) 

-0. 186** 

(0.048) 

-0.181** 

(0.048) 

-0.043 

(0.530) 

-0.044 

0.478 

log (PCODAH) -0.031 

(0.281) 

-0.024 

(0.403) 

0.057** 

(0.011) 

0.055** 

(0.014) 

0.082*** 

(0.000) 

0.056** 

(0.041) 

Constant -8.508*** 

(0.000) 

-3.773*** 

(0.000) 

-9.093*** 

(0.000) 

-4.313*** 

(0.000) 

-7.978*** 

(0.000) 

-3.176*** 

(0.004) 

Countries 27 27 27 27 27 27 

Observations 185 185 185 185 185 185 

R-Squared 0.873 0.483 0.874 0.490 0.854 0.447 

Prob > CHI2 0.000 0.000 0.000 0.000 0.000 0.000 

Figures in parentheses are p-values; ***, ** and *denote significance at 1%, 5% and 10% respectively.  

Source: Author estimation. 

 

The results of the estimates presented in columns 1 to 4 of the Table taught us that accountability 

promotes increased spending on health. The coefficients of voice and accountability (WGI) and 

democratic accountability (ICRG) are both positive and significant at the 1% threshold. More exactly, 

per capita government health spending went up respectively by 14.46 % and 10.45% when the 

indicators of voice and accountability from WGI and democratic accountability from ICRG increased 

by 10%. Likewise, for 1% increase in democratic accountability and voice and accountability towards a 



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more accountable government, the share of government health spending in GDP increases from 0.96 % 

to 1.32%. The positive effect of government accountability on public health spending is confirmed by 

previous empirical work done in mixed panel (Farag et al., 2012; Cockx & Francken, 2014; Liang & 

Mirelman, 2014) and African countries (Fosu, 2008; Kumah & Brazys, 2016). By investigating a mixed 

sample of 120 countries between 1995 and 2010, Liang and Mirelman (2014) suggested a positive 

association between democratic accountability and government health expenditure (total and 

domestically funded). Farag et al. (2012), using a panel data set for 173 countries for the 1995-2006 

period, find that the voice and accountability has a significant positive influence in mobilizing more 

resources for health. These results are in line with those obtained by Cockx and Francken (2014) whose 

study focused on a sample of 136 and 137 countries over the period 1995-2009. They show that a 

higher level of constraints on executive, which corresponds to more restrictions on executive actions 

and greater accountability, is associated with higher public health expenditures. In the same vein, Fosu 

(2008), using five-year averages from 35 countries in sub-Saharan Africa over the period 1975-1994, 

pointed out that constraint on the government executive shifts the budget in favour of health. Likewise, 

in the context of Africa, Kumah and Brazys (2016) highlighted the crucial role of public accountability 

in budgetary arbitration for the benefit of the health sector. In particular, they show that the presence of 

an opposition (political and/or civil society), transparency or even the independence of the judiciary, is 

favourable to an increase in public health expenditure as a percentage of GDP in a sample of 46 to 48 

African countries. 

The estimates also highlight a positive association between political stability and absence of 

violence/terrorism and public health spending, since the coefficient of political stability and absence of 

violence/terrorism from WGI is positive and significant at the 1% level. The more stable the political 

environment, the higher the domestic public resources allocated to the health of the populations. For 

1% increment in political stability and absence of violence/terrorism indicator toward a more stable 

political environment, our estimates give a significant increment in the percentage of GDP expended on 

health care by government from domestic resources (+0.71%) and per capita government health 

spending (+0.57%). This result is consistent with the finding of previous studies in mixed sample 

(Liang & Mirelman, 2014) and in Lesotho case study (Ramashamole & Thamae, 2015). Liang and 

Mirelman (2014) found that government stability is positively correlated with government health 

expenditure. Echoing with the finding of Liang and Mirelman (2014), Ramashamole and Thamae (2015) 

found that in Leshoto, political instability affects negatively public health spending. However, its 

contrast with the finding that in developing country context like Nigeria, political instability has no 

significant influence on public spending allocated to the health sector (Imoughele & Ismaila, 2013; 

Olawunmi, 2014).  

 

 

 



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5. Conclusion 

In Sub-Saharan Africa, access to essential health care services remains problematic and communicable 

diseases are the cause of more than half of deaths. The financing of health care is mainly provided by 

private sources, mainly out-of-pocket payments which represent respectively 53.12% and 36.73% of 

total health expenditure. As for public health expenditure, essential for ensuring universal health 

coverage, it represents only about 35% of health expenditure. Thus, the increase in public spending on 

health proves to be a major challenge for the countries of the region in the prospect of reaching the 

SDG relating to health by 2030. Hence, the importance of identifying the determinants of public health 

spending. 

The purpose of this paper was to analyse the political determinants of domestic public health spending 

in SSA. We used data of 39 countries over the period 2010-2016 and panel-corrected standard errors 

method for empirical investigation. It turns out that democracy promotes increased public spending on 

health. Besides democracy, the other political determinants are: political competition, civil and political 

liberties, accountability, government effectiveness and political stability. The results also showed that 

political participation does not affect public health spending. Beyond political factors, GDP per capita, 

official development aid to health, fiscal capacity, the proportion of the population aged 65 and over 

and the incidence of tuberculosis positively affect public spending on health. 

In the light of these results, the deepening of democracy, the strengthening of political competition and 

accountability mechanisms, the guarantee of political rights and civil liberties, the improvement of 

government effectiveness and the assurance of a stable political environment are essential for 

increasing public spending on health. This increase, coupled with better use of resources, will enable 

health systems to provide health care to the population, thereby enabling them to have a better health 

and be more productive for the benefit of the region. 

 

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Notes 

Note 1. EIUEPP is the EIU Sub-score Electoral Process and Pluralism, FHPR is the Political Right of 

Freedom House, FHCL is the civil liberties of Freedom House and EIUCL is the EIU Sub-Score civil 

liberties. 

Note 2. EIUFOG is EIU sub-Score of functioning of government, WGIGE is the government 

effectiveness retrieved from WGI, EIUPP and EIUPC are EIU sub-scores political participation and 

political culture. 



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Note 3. WGIVA is voice and accountability from WGI; ICRGDA is the democratic accountability 

retrieved from ICRG; WGIPSAVT is WGI indicator of political stability and absence of violence and 

terrorism. 

  

Appendix 1. 

List of Countries 

Angola Equatorial Guinea Mauritania 

Benin Eswatini Mauritius 

Botswana Ethiopia Mozambique 

Burkina Faso Gambia Namibia 

Burundi Ghana Niger 

Cabo Verde Guinea Rwanda 

Cameroon Guinea-Bissau Senegal 

Central African Republic Kenya Sierra Leone 

Chad Lesotho South Africa 

Comoros Liberia Tanzania 

Democratic Republic of Congo Madagascar Togo 

Republic of Congo  Malawi Uganda 

Cote d’Ivoire Mali Zambia 

 

 

 


