Content uploaded by Sewordor Toklo
Author content
All content in this area was uploaded by Sewordor Toklo on Sep 04, 2022
Content may be subject to copyright.
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
70 ASIA & AFRICA TODAY 2022 № 9
ТРИБУНА СОИСКАТЕЛЯ POST-GRADUATE COLUMN
DOI: 10.31857/S032150750021787-7 Оригинальная статья / Original article
Factors influencing the perception of corruption
(a multilevel analysis in Africa)
© Sewordor Tokloa, 2022
a National Research University Higher School of Economics, Moscow, Russia
ORCID ID: 0000-0003-1914-2706; sewordortoklo1@gmail.com
Abstract. Many developing countries suffer high levels of corruption, which contributes to the divergence in economic develop-
ment between more developed and developing countries. Corruption perceptions play a key role in forming a culture that is more or less
tolerant of corruption, which contributes to its persistence. Individuals who have high perception of corruption believe that bribes must
be paid. Customers will be more likely to accept a bribe if they believe many people pay bribes. The importance of this research is that
it contributes to the micro-level research tradition by providing a deeper understanding of the factors that influence corruption percep-
tion.
What factors influence the perception of corruption? I conducted an empirical analysis using 2017 Afrobarometer survey data, fo-
cusing on 34 democratic African countries. The study finds that those who are relatively poor are more likely to have a high perception
of corruption and develop an unfavorable view of corruption than those with high income. The study also provides the potential mecha-
nisms involved in the perception of corruption, finding that individuals with high access to information through the media, and higher
education have a higher perception of corruption.
Keywords: Africa, corruption, corruption perception, government, poverty, media
For citation: Toklo S. (Ghana). Factors influencing the perception of corruption (a multilevel analysis in Africa). Asia and Africa
today. 2022. № 9. Pp. 70-76. DOI: 10.31857/S032150750021787-7
INTRODUCTION
Africa is one of the resource-richest continents in the world, however, it is the least developed. For decades,
there has been a dispute about how to account for Sub-Saharan Africa’s development issues. Scholars and other
policymakers have all made significant contributions to determining the appropriate factors that best explain the
condition. The impact of corruption on the well-being of the people of Sub-Saharan Africa is one of the main ex-
planatory factors. With few exceptions, corruption has persistently affected the post-independence development of
Sub-Saharan African countries [1]. Corruption also creates a less conducive environment for democracy, reduces
moral values, and disregards the legitimacy of authorities and constitutional institutions [2]. It erodes trust in
democratic institutions and may lead to their subversion [3]. Corruption hinders the economic development of
countries [4]. It may further worsen foreign direct investment [5].
While many studies have investigated the correlates of corruption at the macro-level, scholars have paid less at-
tention to the micro-level, especially in Africa. In this research, I investigate factors influencing individual percep-
tions of corruption and, therefore, it is a part of a micro-level research tradition. Based on the analysis, I offer pos-
sible implications for future researchers and policymakers.
Understanding these perceptions is important for several reasons. First, the perception of corruption does not
always reflect reality in society. For example, officials tend to hide corrupt behaviors especially when people find it
difficult to detect [6]. However, researchers have consistently used perception-based measures as proxies for
measuring actual corruption. As a result, providing an understanding of why corruption perceptions differ is im-
portant in knowing the potential biases [7]. Secondly, perception is noted for motivating other behavior and there-
by poses a problem for development. For instance, the perception of corruption creates mistrust in government
and institutions and further affects people’s willingness to participate in politics. Thirdly, the inability to deal with
the perception of corruption may lead to even larger societal consequences and acceptance of rule-breaking [3].
Furthermore, the perception of corruption could be self-reinforcing such that whenever there is a higher level of
the perception of corruption, it tends to make people engage in actual corrupt behaviors [8].
What explains the differences in the perceptions of corruption within the same societies? I conduct an empirical
analysis, finding that poor citizens are more likely to form a higher perception of corruption towards the institu-
tions of the state than high-income citizens. Secondly, those who have more access to the media, and those who are
educated are likely to form a higher perception of corruption than those who do not have access.
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
АЗИЯ И АФРИКА СЕГОДНЯ 2022 № 9 71
CORRUPTION AND CONSEQUENCES
Corruption remains one of the dominant topics of public discussion in many countries. Nevertheless, what is of-
ten referred to as corruption remains debatable as there continues to be no universal definition of corruption. The
differences of each definition vary across countries, or even within them; such that many behaviors perceived as
corrupt in one country may not necessarily be perceived as corruption in others. As a result, academics and schol-
ars seeking to come up with a more rigorous assessment of what corruption means are faced with the overarching
problem of a clear terminology [9].
One of the most common definitions of corruption is that it is the misuse of public office for private gains [10]; a
situation that allows a public officer to benefit privately by either allocating the gains to himself or to the group
which he or she is a member [11] or by consciously taking advantage of his power to redirect the benefits to his
relations such as families, social group or political party [12]. Corruption is not only about public officials - it can be
among even individuals working for example in the private sector. When formal rules are violated for individual
gain, whether the behavior is within a public, private, or even non-profit organization, such behavior constitutes
corruption [13]. Corruption is a very negative social phenomenon that creates a less conducive environment for
democracy, reduces moral values, and disregards the legitimacy of authorities and constitutional institutions [14].
Bribery and embezzlement are examples of corruption. Institutional failure has been blamed for Africa’s low de-
velopment [15], and that corruption stifles economic progress and development in Africa [14; 16; 17]. Corruption is
proven to be widespread and considerable in all countries worldwide [18], yet there are considerable differences be-
tween them. The impact of corruption on governments and countries is a critical issue. For example, it makes it ex-
tremely difficult to change a corrupt government or judicial system [19]. Corruption also causes a loss of confidence
between a government and its population, making anti-corruption initiatives practically impossible [20].
The economic literature discusses several elements that facilitate corruption. This includes a lack of proper
legislation, weak law enforcement, cultural requirements, a lack of incentive for the government to fight corrup-
tion, low compensation for state employees, and other factors [21; 22]. Previous cross-country studies show
that levels of economic development and cultural factors influence the level of corruption [23]. The availability
of e-government [24], and the history of openness to trade also influence the level of corruption [10].
Since corruption is systemic and prevalent across many sectors [25], some researchers discuss the culture of
corruption and the complexity of corruption in Africa [26]. Others believe that apart from corruption other unique
socio-cultural traits in African countries, including ethnic differences [27], or ethnic violence [28], impede econo-
mic development.
Given the scant evidence of emerging literature on the topic has produced, the notion that there is a connection
between corruption and attitudes about government is open to question. The impact of corruption on ordinary
people’s opinions toward political systems in their country has received little systematic consideration from re-
searchers [29]. Previous literature in Africa for example lacks studies that examine the factors behind the percep-
tions of corruption, especially at the micro-level. As a result, I examine how corruption perceptions among African
citizens are formed. This is important because, in several societies, policymakers have constantly relied on percep-
tion-based measures in designing their policy frameworks. This means that an inability to understand various fac-
tors influencing the perception of corruption will result in incorrect policy design and corruption is likely to rise.
Although the perception of corruption does not always reflect reality, scholars on many occasions use perception-
based measures as proxies for actual corruption.
As [30] noted, corruption could be self-reinforcing. Whenever there is a higher level of the perception of cor-
ruption, it tends to make people engage in actual corrupt behaviors [8]. When corruption is perceived as wide-
spread, it creates a larger problem. This is because many officials see the practice of corruption as a normal thing,
and they do not feel guilty about their actions. Similarly, most officials’ fear of punishment begins to decline, and
they may even stop caring about their reputations. Such behaviors begin to spread widely among other officials
and workers in the long run and become acceptable behavior.
The way people perceive a behavior as corrupt varies from one person to another. Officials from the same or-
ganization may judge the existence of corrupt behavior in that same institution differently. Therefore, all these ne-
cessitate the need for an understanding of the perception of corruption. The next subsections discuss the hypothe-
ses for the paper.
THEORETICAL REVIEW AND HYPOTHESES
ThePoor
Corruption exacerbates inequities that are already present [12]. This is especially true when it comes to petty
corruption. Grand corruption, on the other hand, may lead to the formation of ideas that the country’s political sys-
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
72 ASIA & AFRICA TODAY 2022 № 9
tem is biased against the poor. The poor are more likely to suffer the repercussions of corruption. As a result, indi-
viduals develop a low level of trust in their political system and a negative attitude toward it [31]. Similarly, when
asked to pay a bribe, socioeconomically disadvantaged persons have no way out. M.K.Justesen and
C.Bjørnskov [32] argues that this system provides strong incentives for bureaucrats to target poor people and ex-
tort money from them.
Based on this, hypothesis1 can be formed: H1:Thosewhoarepoorwillhave a higherperceptionofcorruption
thanthosewhoarerich.
Themedia
The media helps people become more aware of crucial issues. The agenda-setting theory is, theoretically, one of
the most important theories for explaining people’s perceptions of issues. This theory explains how the news me-
dia might impact the public’s perception of the importance of items on the agenda [33]. This demonstrates the me-
dia’s importance in shaping public opinion and raising public awareness of important topics. This means that the
media may play a role in shaping public perceptions of corruption.
Also, it was indicated [34] that the media is a crucial channel through which people create attitudes about their
government. The public’s attention is brought to the country’s corruption concerns because stories of corruption
are often repeated throughout a range of media platforms. People with increased access to radio or social media
are more likely to hear or read about corruption in their country.
H2:Thosewhoareexposedtothemediawillhaveahigherperceptionofcorruption.
Thesizeofthelocationofresidents
The size of an individual’s place of residence may have an impact on their perception of corruption. In smaller
communities, individuals and public officials are more likely to interact personally, and favoritism is more likely.
Those living in such areas have a high perception of corruption in such circumstances [29]. However, a larger town
may be an environment where corruption is more prevalent. The bigger the town, the more exposed it is to a cor-
rupt atmosphere [7]. Various reasons may explain the pervasive corruption in major cities, strengthening the
views. For instance, in large cities, public services are offered, which include activities such as those of the police
and other public officials. There is also more money allocated and decisions made in larger towns, numerous op-
portunities to spend, and political life is focused in large cities.
H3:Thosewholiveintheurbanareaswillhaveahigherperceptionofcorruption.
Education
Countries with more education have relatively less corruption, according to research focusing on corruption
convictions [35]. The levels of corruption reduce as people’s education levels improve. Also those with greater ac-
ademic credentials have a lower perception of corruption [36]. Since it is generally difficult for the ignorant to de-
tect corrupt activity, this study takes the position that authorities in many African countries who participate in cor-
rupt behavior have a tendency and numerous strategies to cover their corruption activities. To put it another way,
corrupt officers will not be able to hide their actions from an educated public and will be quickly detected. As a re-
sult, educated people are likely to have a higher perception of corruption than those who are less educated.
H4:Thosewithhigherlevelsofeducationwillhaveahigherperceptionofcorruption.
DATA AND METHODOLOGY
Data for the study were collected by the Afrobarometer1, a highly reputable research organization that collects
scientific survey data on democratic African countries to ensure quality democracy and good governance. The hy-
potheses of this research were tested using round 7 of the Afrobarometer survey data collected in 2017 and 2018.
This round was chosen because it contains the necessary questions that previous researchers have used to meas-
ure poverty.
These were self-reported data collected using a well-structured questionnaire with a stratified sampling tech-
nique to sample respondents in Africa. This micro-level data are nationally representative samples for 34 African
countries2. Participants of this survey were asked several questions about their experiences and opinions on the
quality of governance, and of which some of these questions include topics on corruption and bribery.
Due to the clustered nature of the data, I employed a multi-level hierarchical model, and this was performed on
the dependent variable. The multi-level hierarchical model is employed where the intercepts vary by country level.
This method allowed me to account for the relationship between individual perceptions of corruption and country-
1 A pan-African, independent, non-partisan research network.
2 Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Côte d'Ivoire, eSwatini, Gabon, Gambia, Ghana, Guinea, Kenya, Leso-
tho, Liberia, Madagascar, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, São Tomé and Príncipe, Senegal,
Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia, Zimbabwe.
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
АЗИЯ И АФРИКА СЕГОДНЯ 2022 № 9 73
level perceptions of corruption. The Model shows an intraclass correlation coefficient (ICC) of 0.13, indicating that
13% of the total variance of the variables in the study are predicted by the country-level predictors independently
of the fixed effects. The data was analyzed using R, and the findings were presented in a Table form. To ensure that
the models do not have highly correlated predictors, I checked for multicollinearity using tests x and y. The results
indicate no problem with multicollinearity.
Measurementofdependentvariable
The dependent variable is “corruptionperception”. The Afrobarometer provided a specific question that in-
formed what “corruption perception” is (that is, Q45). The question is “Inyouropinion,overthepastyear,hasthe
levelofcorruptioninthiscountryincreased,decreased,orstayedthesame?” The responses were measured from a 5-
point scale “decreased a lot, decreased somewhat, stayed the same, increased somewhat, and increased a lot”. I
created an index for corruption perception; where (1=low corruption; 5= higher corruption).
Measurementofindependentvariables
Poverty
Estimating individual income from reliable source in Africa is challenging, making assessing poverty in Africa
problematic. As a result, I developed a poverty index from the Afrobarometer data by using the standard Index of
Lived Poverty used in previous studies such as [32].
Afrobarometer asked respondents, over the past years, how often, if ever, have you or anyone in your family:
(A) Gone without enough food to eat? (B) Gone without enough clean water for home use? (C) Gone without medi-
cines or medical treatment? (D) Gone without enough fuel to cook your food? (E) Gone without a cash income?
Responses were coded on a five-point scale ranging as ‘Never, Just once or twice, Several times, Many times,
and Always’. Based on these five items from Afrobarometer data, I constructed an additive poverty index, where
high values imply being poor and low value means being well-off, meaning such people can meet their basic needs.
NewsAccess
To determine how residents had access to news, I used the Afrobarometer data (Q12), which questioned re-
spondents about how often they obtain news from the following sources (A) Radio, (B) TV, (C) Newspapers,
(D) The internet, (E) Facebook and Twitter as examples of social media. The responses were coded from “Every-
day” to “Never” by Afrobarometer.
Ideally, an additive index is expected to be constructed in this kind of variables, like the one created for the
poverty variable. However, the idea here is to contrast individuals who have access to news media with those who
do not. Thus, how should those who have access to information through the news perceive corruption in compari-
son to those who do not? As a result, I created an index for media access and treated it as dummy variables where
“No media access” is the reference. I separated traditional media from new media to facilitate analysis. Thus, tradi-
tional media consists of radio, television, and newspapers, whereas new media consists of the internet and social
media (Facebook and Twitter). This category is required to compare persons who have access to traditional media
and new media to people who do not have access to these news channels.
Educationallevel. This question was posed to know the educational level of the respondents who took part in
the survey. In the Afrobarometer, these responses were coded in the data “no formal education” to “post-graduate
schooling”. I grouped these responses as either being educated or having no education with not having formal edu-
cation being the reference.
Urban. Individuals living in a specific area of society may perceive corruption differently based on wherever
they live. This is a dichotomous variable where the respondents were asked if they come from rural or urban areas.
Making the rural as the reference group the coding of the responses was coded as (0 = rural; 1 = urban).
ControlVariable
To be able to account for differences between countries, I included country-level variables. Controls at the
country level included democratic status and GDP per capita. There is a growing agreement among academics that
shows an inverse relationship between democracy and corruption hence the need to control democracy. Freedom
House is used to determine a country’s democratic status. After being equally weighted, the combination of the
total score granted for political rights and the total rating assigned for civil freedoms decides whether a country is
Free, Partly Free, or Not Free, according to Freedom House.
GDP per capita is also utilized as a country-level control variable in this study. This is significant since prior re-
search has found a substantial link between corruption and economic success. The World Bank’s World Develop-
ment Indicators provided the data for GDP per capita.
Gender
At the individual level, I introduce gender as a control variable. In the Afrobarometer data, question (Q101)
asked the respondents to state their gender. The respondent’s gender is coded as dummy variables where the ref-
erence group was females. The responses were coded as (0 = male; 1 = female).
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
74 ASIA & AFRICA TODAY 2022 № 9
Table.RegressionAnalysisofFactorsinfluencingcorruptionperception
Model1
Model2
Predictors
Estimates
CI
Estimates
CI
Intercept
1.40
***
1.34
-
1.46
1.23
***
0.90
-
1.55
Poor
0.01
***
0.01
-
0.01
0.01
***
0.01
-
0.01
Traditional Media Access
0.03
***
0.01
-
0.04
0.02
***
0.01
-
0.04
New Media Access
0.03
***
0.02
-
0.05
0.03
***
0.02
-
0.04
Urban
-
0.00
-
0.01
-
0.01
-
0.00
-
0.01
-
0.01
Primary Education
0.03
***
0.02
-
0.05
0.03
***
0.02
-
0.05
Secondary Education
0.07
***
0.05
-
0.08
0.06
***
0.05
-
0.07
Tertiary Education
0.08
***
0.07
-
0.10
0.07
***
0.06
-
0.09
Female
-
0.00
-
0.01
-
0.00
-
0.00
-
0.01
-
0.01
Country
-
level Poverty
0.57
*
0.11
-
1.03
Democratic Status
-
0.11
*
-
0.20
-
-
0.02
GDP per capita
-
0.01
-
0.02
-
0.01
RandomEffects
σ
2
0.22
0.22
τ
00
0.02
COUNTRY
0.02
COUNTRY
ICC
0.10
0.10
N
34
COUNTRY
31
COUNTRY
Observations
45823
42223
Marginal R
2
/ Conditional R
2
0.009
/ 0.111
0.036 / 0.131
*p<0.05
;
**p<0.01
;
***p<0.001
Table presents the results of the multi-level hierarchical model developed to test the hypothesis. Model 1 dis-
plays the results for the predictors while Model 2 states the predictors and controls for the individual level varia-
bles; gender as well as country-level variables; GDP per capita, and democratic status.
There is evidence to support H1 that there is a relationship between poverty and perceptions of corruption.
Those who are considered poor frequently believe that corruption is rampant in the country. Model 1 shows that
there is a significant positive relationship that exists between poverty and perception of corruption (β=0.01,
p<0.001). 1% increase in poverty will lead to an increase in corruption perception by 1%. This means that when
people become poorer, they begin to have high corruption perceptions. This is robust in Model 2 as well.
H2, about individuals with greater access to news, is also supported. The result in Model 1 revealed that there is
a significant positive relationship between both traditional and new media access and corruption perception. For
instance, in Model 1 the traditional media shows (β=0.03,95%CI=0.01-0.04,p<0.001). Thus, increasing access to
traditional media by 1 unit will lead to an increase in the perception of corruption by 3%. The result is also signifi-
cant for having access to new media when compared to people who do not have access. This means that those who
have media access (regardless of the type of media) are likely to have a higher perception of corruption.
The results also provide evidence that supports H4, that educational level predicts individuals’ perception of
corruption. This means that compared with those who have no formal education, having obtained at least a prima-
ry level education will lead to a higher perception of corruption.
In line with H1, poverty is a predictor of corruption perception: poor people have higher corruption percep-
tions compared to rich people. This current study also supports the theoretical framework that those who suffer
from the actions of bad governance are likely to have a negative view of the government [37].
Those who have more access to news (whether traditional or new media) will perceive corruption to be higher.
Information obtained from the media influences people so that they are more likely to think that there is corrup-
tion. Most African countries, during revolutionary periods and military takeovers, have built a culture of silence
where private media were restricted [38]. However, over the decades, the continent has seen an increase in the
number of media outlets, especially private radio stations and televisions. This suggests that the more people have
access to news media, the more information they have on issues including corruption. This can subsequently influ-
ence people to generally perceive that there is high corruption in the country. This argument is therefore in line
with the agenda-setting theorists [33] that see the media as shaping public opinion.
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
АЗИЯ И АФРИКА СЕГОДНЯ 2022 № 9 75
Educated people may also perceive corruption to be high since they may figure out corrupt officials attempting
to hide corrupt practices from them. This is contrary to those who suggest that having high academic qualifications
means having a lower perception of corruption [39]. As a result, educated people are more likely than less-
educated people to have a higher perception of corruption.
This article makes two main contributions to the micro-level level cross-country research paradigm in Africa.
Using 34 African nations, I find that poor people may have a higher perception of corruption. This study contra-
dicts the findings [40], which indicated that such intuition is true only in wealthy nations. As demonstrated
throughout this paper people within the developing world who are poor are more likely to have a negative view of
the country compared to the people who are well-off.
Secondly, people who obtain their news from the media are more likely to feel that there is high corruption. The
media should be taken seriously as a source of corruption perceptions, and honest reporting should be practiced.
This is important because the media may be a proponent of corruption in most African countries, where corruption
scandals rarely result in court processes. Since media firms are frequently owned by politicians in most African
countries, depending on who is in power, these outlets’ reporting may lack neutrality. If the media portrays corrup-
tion in a more negative light than reality, it may lead individuals to feel that they must pay bribes.
The surveys are only done in countries that are at least nominally democratic and are not involved in violent
conflicts. Due to this, the countries are not typical for the whole of Africa, and the findings cannot be applied entire-
ly to the entire region.
CONCLUSION
Corruption perceptions can have a significant impact on the extent of corruption. Individuals with a high per-
ception of corruption believe they must pay bribes. Customers are more confident that a bribe will be accepted if
they believe many individuals pay bribes [8].
In this research, I analyze factors influencing citizen perception of corruption in Sub-Saharan Africa. I found out
that the poor - the most marginalized in society - are more likely to form a higher perception of corruption than
those who are richer. I also found out that those who have access to the media and have a high level of education
are more likely to perceive that corruption is higher in their country.
This research suggests that in Sub-Saharan Africa, where poverty is a growing problem, it is expected that a
large segment of the citizens will develop a negative attitude including having a corrupt perception of the state.
This may create further problems such as mistrust of their institutions and in the long run, can affect development.
Future research, especially in Africa, should investigate how corruption perceptions may influence citizens’ ten-
dency to engage in actions such as ballot stuffing, vote-buying, and violence which has been characterized in many
African elections.
REFERENCES
1. Mlambo D.N., Mubecua M.A., Mpanza S.E., Mlambo V.H. 2019. Corruption and its implications for development and good gov-
ernance: A perspective from post-colonial Africa. Journal of Economics and Behavioral Studies. Vol. 11, № 6, pp. 39-47.
2. Bratton M., Mattes R. and Gyimah-Boadi E. 2005. Public opinion, democracy, and market reform in Africa. Cambridge University
Press.
3. Villoria M., Van Ryzin G.G., Lavena C.F. 2013. Social and political consequences of administrative corruption: A study of public
perceptions in Spain. Public Administration Review. Vol. 73, № 1, pp. 85-94.
4. Mauro M.P. 1996. The Effects of Corruption on Growth, Investment, and Government Expenditure. International Monetary Fund.
5. Wei S.J., Shleifer A. 2000. Local corruption and global capital flows. Brookings papers on economic activity. Vol. 2000, № 12,
pp. 303-354.
6. Olken B.A. 2009. Corruption perceptions vs. corruption reality. Journal of Public economics. Vol. 93, № 7-8, pp. 950-964.
7. de Lancer Julnes P., Villoria M. 2014. Understanding and addressing citizens’ perceptions of corruption: The case of Spain. Inter-
national Review of Public Administration. Vol. 19, № 1, pp. 23-43.
8. Cabelkova I. 2001. Perceptions of Corruption in Ukraine: Are they correct? CERGE-EI working paper series. № 176.
9. Johnston M. 1986. Right & wrong in American politics: Popular conceptions of corruption. Polity. Vol. 18, № 3, pp. 367-391.
10. Treisman D. 2000. The causes of corruption: a cross-national study. Journal of public economics. Vol. 76. № 3, pp. 399-457.
11. Bardhan P. 1997. Corruption and development: a review of issues. Political Corruption. Vol. 35, pp. 1320-1346.
12. Tanzi V., 1998. Corruption around the world: Causes, consequences, scope, and cures. Staff papers, Vol. 45, № 4, pp. 559-594.
13. Luo Y., 2005. An organizational perspective of corruption1. Management and Organization Review. Vol. 1, № 1, pp. 119-154.
14. Gyimah-Boadi E. 2002. Confronting corruption in Ghana and Africa. Ghana Center for Democratic Development. Vol. 4, № 2.
15. Acemoglu D., Johnson S., Robinson J.A. 2001. The colonial origins of comparative development: An empirical investigation.
American economic review, Vol. 91, № 5, pp. 1369-1401.
16. Dreher A., Herzfeld T. 2005. The economic costs of corruption: a survey and new evidence.
17. Mironov M. 2005. Bad corruption, good corruption and growth. University of Chicago. Miméo.
Toklo S. Factors influencing the perception of corruption (a multilevel analysis in Africa)
76 ASIA & AFRICA TODAY 2022 № 9
18. Shleifer A., Vishny R.W. 1993. Corruption. The quarterly journal of economics. Vol. 108, № 3, pp. 599-617.
19. Rose-Ackerman S., Palifka B.J. 2016. Corruption and government: Causes, consequences, and reform. Cambridge university press.
20. Damania R., Fredriksson P.G., Mani M. 2004. The persistence of corruption and regulatory compliance failures: theory and evi-
dence. Public choice. Vol. 121, № 3, pp. 363-390.
21. Tanzi V. 1998. Corruption around the world: Causes, consequences, scope, and cures. Staff papers. Vol. 45, № 4, pp. 559-594.
22. Rose-Ackerman S. 1997. The political economy of corruption. Corruption and the global economy. Vol. 31, № 60, p. 54.
23. Seleim A., Bontis N. 2009. The relationship between culture and corruption: A cross‐national study. Journal of Intellectual Capital.
Vol. 10, № 1, pp. 165-184.
24. Setyobudi C.R., Setyaningrum D. 2019. E-government and corruption perception index: a cross-country study. Journal Akuntansi
dan Auditing Indonesia. Vol. 23, № 1, pp. 11-20.
25. Znoj H. 2017. Deep corruption in Indonesia: discourses, practices, histories. Corruption and the Secret of Law. Routledge. Pp. 53-
74.
26. Blundo G., De Sardan JPO. 2001. Everyday Corruption in West Africa. African Politics. Vol. 3, pp. 8-37.
27. Easterly W., Levine R. 1997. Africa’s growth tragedy: policies and ethnic divisions. The quarterly journal of economics. Vol. 112,
№ 4, pp. 1203-1250.
28. Collier P., Hoeffler A. 2002. On the incidence of civil war in Africa. Journal of conflict resolution. Vol. 46, № 1, pp. 13-28.
29. Anderson C.J., Tverdova Y.V. 2003. Corruption, political allegiances, and attitudes toward government in contemporary democra-
cies. American journal of political science. Vol. 47, № 1, pp. 91-109.
30. Persson A., Rothstein B., Teorell J. 2013. Why anticorruption reforms fail - systemic corruption as a collective action problem.
Governance. Vol. 26, № 3, pp. 449-471.
31. Gupta S., Davoodi H., Alonso-Terme R. 2002. Does corruption affect income inequality and poverty? Economics of governance.
Vol. 3, № 1, pp. 23-45.
32. Justesen M.K., Bjørnskov C. 2014. Exploiting the poor: Bureaucratic corruption and poverty in Africa. World Development.
Vol. 58, pp. 106-115.
33. McCombs M.E., Shaw D.L. 1993. The evolution of agenda-setting research: Twenty-five years in the marketplace of ideas. Journal
of communication. Vol. 43, № 2, pp. 58-67.
34. Costas-Pérez E., Ollé A.S., Navarro P.S., 2011. Corruption scandals, press reporting, and accountability: Evidence from Spanish
mayors. Documents de treball IEB. № 9, pp. 1.
35. Glaeser E.L., Gyourko J., Saks R. 2005. Why is Manhattan so expensive? Regulation and the rise in housing prices. The Journal of
Law and Economics. Vol. 48, № 2, pp. 331-369.
36. Melgar N., Rossi M., Smith T.W. 2010. The perception of corruption in a cross-country perspective: Why are some individuals
more perceptive than others? Economia Aplicada. Vol. 14, № 2, pp. 183-198.
37. Kim S. 2010. Public trust in government in Japan and South Korea: Does the rise of critical citizens matter? Public Administration
Review. Vol. 70, № 5, pp. 801-810.
38. Gyimah-Boadi E. 1994. Ghana’s uncertain political opening. Journal of Democracy. Vol. 5, № 2, pp. 75-86.
39. Glaeser E.L., Gyourko J., Saks R. 2005. Why is Manhattan so expensive? Regulation and the rise in housing prices. The Journal of
Law and Economics. Vol. 48, № 2, pp. 331-369.
40. Maeda K., Ziegfeld A. 2015. Socioeconomic status and corruption perceptions around the world. Research & Politics. Vol. 2, № 2,
Pp. 1-9.
INORMATION ABOUT THE AUTHOR / ИНФОРМАЦИЯ ОБ АВТОРЕ
Sewordor Toklo (Ghana), Post-graduate student, Doctoral
School of Political Science, HSE University, Moscow, Russia.
Севордор Токло (Гана), аспирант, Аспирантская школа
по политическим наукам, ВШЭ, Москва, Россия.
Поступила в редакцию
(Received) 18.04.2022
Доработана после рецензирования
(Revised) 10.05.2022
Принята к публикации
(Accepted) 26.07.2022