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Han, J. Individual-Level Factors and Corruption. Encyclopedia. Available online: (accessed on 20 June 2024).
Han J. Individual-Level Factors and Corruption. Encyclopedia. Available at: Accessed June 20, 2024.
Han, Jinwon. "Individual-Level Factors and Corruption" Encyclopedia, (accessed June 20, 2024).
Han, J. (2023, July 14). Individual-Level Factors and Corruption. In Encyclopedia.
Han, Jinwon. "Individual-Level Factors and Corruption." Encyclopedia. Web. 14 July, 2023.
Individual-Level Factors and Corruption

Persistent corruption has been a long-standing challenge in South Asia. With few exceptions, most South Asian countries have ranked among the most corrupt countries in the world. For example, apart from Bhutan, the remaining seven countries (i.e., Afghanistan, Bangladesh, India, Nepal, Maldives, Pakistan, and Sri Lanka) received under 50 points out of 100 in Transparency International’s 2022 Corruption Perceptions Index (CPI).

corruption individual-level determinants of corruption multinomial logistic males

1. Introduction

An in-depth examination of prior studies indicates that the following individual-level factors have a significant association with corruption: (1) age, (2) gender, (3) marital status, (4) education, (5) religion, (6) trust, and (7) individualism/collectivism.

2. Age

Prior research on age differences is based on the theoretical assumption that, all other factors being equal, individuals have an increased likelihood of interacting with public officials as they age. Consequently, the probability of exposure to corrupt practices and the corresponding corruption justifiability are likely higher as individuals advance in age. Nevertheless, after surpassing a specific age threshold, they become less tolerant of corruption, resulting in a decreased likelihood of engaging in corrupt practices.
Through an analysis of micro-datasets, Swamy et al. (2001) discovered that the age variable exhibits a negative correlation with individuals’ tolerance for corruption, indicating that as individuals age, they are less likely to tolerate corrupt practices. Given that individuals’ justifiability of corruption is closely associated with their actual involvement in corrupt activities (Ajzen and Fishbein 1980) and statistically correlated with established corruption indices (Torgler and Valev 2006), it is reasonable to assert that one’s corruption justifiability can be a proxy for their engagement in corruption (Han 2022).
Using a more recent dataset collected in the mid-1990s, Torgler and Valev (2006) expanded on Swamy and colleagues’ research. The authors found that all age groups from 30 to 65+ report significantly lower corruption justifiability than the reference group below 30. This finding indicates that people are less likely to rationalize corrupt practices as they age. The same authors obtained a similar result from their analysis conducted in 2010 using survey data from eight Western European countries (Torgler and Valev 2010).
In a similar vein, Lavena (2013) examined the effects of various individual factors, including age differences, on people’s corruption permissiveness (justifiability) in six Latin American countries. The analysis demonstrated that age was negatively associated with corruption permissiveness, indicating that younger people are more likely to justify corruption, while older people are less likely to accept it. This result was consistent across all models and demonstrated strong robustness.
Hunady (2017) investigated the influence of age on respondents’ experiences of being victims of corruption and attitudes toward corruption. Regarding experiences of corruption, the author discovered that individuals up to the age of 34 are more prone to be victims of corruption, whereas the likelihood of experiencing corruption tends to decline after the age of 34. On the other hand, the analysis of corruption tolerance demonstrated that respondents are less inclined to accept corruption as they age.

3. Gender

In addition to age differences, numerous studies have investigated the relationship between gender and corruption. Researchers have posited that, holding all else constant, males are typically more susceptible to corruption than females due to their greater likelihood of being targeted for corrupt activities and their higher levels of tolerance for such behavior (Mocan 2008).
Consistent results have been obtained by scholars such as Swamy et al. (2001), Torgler and Valev (2006), Mocan (2008), Torgler and Valev (2010), and Hunady (2017). In contrast, Lavena (2013) found the contrary result that gender differences are insignificant to Latin American respondents’ tolerance toward corruption.
In contrast to the aforementioned scholars, Alatas et al. (2009) devised a one-shot experimental bribery game that featured three roles, namely, a firm, a government official, and a citizen. Their investigation revealed that men were more inclined to offer and accept bribes than women in the sample of a Western country. However, no statistically significant gender differences were observed in the other three Asian samples.
Frank et al. (2011) conducted a comprehensive review of various experimental studies on corruption to examine the impact of gender on the propensity to offer and accept bribes. After analyzing six studies, the authors noted a consistent pattern of results, suggesting that being female is associated with less exposure and/or lower tolerance toward corrupt practices.
Rivas (2013) employed a more refined approach by conducting a laboratory-based bribery experiment. The experimental design involved a repeated two-person game spanning 20 rounds, featuring two roles, namely, a firm and a public officer. The findings of this investigation demonstrated that when women played the role of a firm, they were less inclined to offer bribes than men. Moreover, even when women did offer bribes, the amount was substantially lower than the average amount offered by men. Furthermore, the frequency with which women accepted bribes when playing the role of a public officer was lower than that of men, and even when they did accept a bribe, women were less likely to engage in corrupt practices than men.

4. Marital Status

In addition, many studies have examined the relationship between individuals’ marital status and their propensity toward engaging in corrupt activities. Scholars in this field have asserted that marital status is a significant factor of corruption based on the life-course theory. This theory posits that marriage is a critical juncture in an individual’s life, which can influence their public behavior (Swamy et al. 2001), as well as their ability to comprehend information and adhere to rules (Melgar et al. 2010). Thus, marriage can play a pivotal role in shaping an individual’s tolerance toward corruption, thereby impacting their likelihood of engaging in corrupt practices.
For instance, Swamy et al. (2001) and Torgler and Valev (2006) found that married individuals are less inclined to tolerate corruption. Specifically, Torgler and Valev (2006) observed a significant correlation between the marital status of individuals and their justifiability of corruption across all the regions they surveyed, ranging from Western Europe to Africa. In a subsequent study conducted in 2010, the same authors confirmed that being married is significantly associated with a lower level of the justifiability of corruption, even after accounting for country-specific heterogeneity.

5. Education

Scholars have also emphasized the role of individual education levels in shaping their perception of corruption and propensity to engage in corrupt behaviors. However, while these studies have substantially contributed to the field of corruption research, most have not provided a clear theoretical framework for the link between education and corruption.
Nonetheless, we can see a hint of the causal mechanism through which individuals’ education levels affect their perceptions and behaviors from Uslaner and Rothstein (2016). According to the authors, a high level of educational attainment matters for controlling corruption at the individual level because as people become more educated, they can be better at reading, establishing social bonds with different communities, having a sense of citizenship and loyalty toward the state, and complaining more about corruption, all of which are negatively associated with engagement in corruption.
Swamy et al. (2001) introduced a dummy variable for education as a control and found a negative correlation between the education variable and individuals’ corruption justifiability. This result supports the theoretical expectation that those with higher education are less likely to tolerate corrupt behaviors.
In addition to Swamy et al. (2001), Truex (2011) and Hunady (2017) also identified a significant negative association between individuals’ education levels and their tolerance toward corruption. Truex’s (2011) study is particularly noteworthy. The study found that higher education levels are significantly associated with lower justifiability of corruption in the country.
Consistent with Truex (2011), Hunady (2017) also obtained a similar result. The study found a significant positive association between respondents’ education levels and their experience of corruption, as well as a negative correlation between individuals’ education levels and their tolerance of corruption. These findings suggest that although more educated people are more likely to be at risk of becoming victims of corruption, they are less likely to tolerate it.

6. Religion

Previous studies have also highlighted the significance of religion in relation to corruption.6 Nevertheless, it is essential to distinguish between two distinct strands of this inquiry, one that examines the influence of individuals’ religious affiliations on the justifiability of corruption and the other that explores the impact of their level of religiosity (Gokcekus and Ekici 2020).
The theoretical basis for the first branch of this religious study was mainly drawn from La Porta et al. (1996) and Treisman (2000). These researchers highlighted the role of religion in shaping people’s conduct by contending that a person’s religious affiliation affects their perceived costs of engaging in corrupt activities, whether it is the fear of being caught or the fear of punishment. They further suggested that in regions where more hierarchical religions, such as Catholicism, Eastern Orthodoxy, and Islam, are prevalent, people are more likely to justify corruption than those in regions dominated by egalitarian or individualistic religions, such as Protestantism.
In a similar vein, Paldam (2001) conducted a comprehensive analysis of the influence of various religious traditions on corruption. Categorizing Christianity into pre-reformation Christians (i.e., Catholic and Eastern Orthodox) and reform Christians (i.e., Protestant and Anglican), the author reported that reform Christianity and Tribal religion reduce corruption, while the remaining religions increase it.
Gerring and Thacker (2004) documented a negative correlation between Protestantism and corruption across all models. Consistent with Gerring and Thacker’s findings, You and Khagram (2005) found a negative link between Protestantism and corruption in all their estimations. Additionally, this relationship was upheld in further analysis using instrumental variables, albeit with a reduced level of significance.
Sommer et al. (2013) noted a significant and negative correlation between Protestantism/Confucianism and corruption, indicating that nations with a legacy of Protestantism or Confucianism tend to have lower levels of corruption. Conversely, Hinduism was found to be positively associated with corruption, suggesting that countries in which Hinduism is predominant are more prone to corruption. However, none of these associations were significant in the individual-level analysis. Instead, Catholicism and Orthodoxy emerged as the key factors associated with an increased tolerance for corruption.
The second strand of research on religion and corruption shifted its focus from religious affiliation to individual religiosity. Scholars in this strand critically reviewed the earlier literature and argued that belonging to a religious group does not necessarily imply full obedience and practice of the teachings of that group (Gokcekus and Ekici 2020). Instead, they suggested that the level of devotion to religion (religiosity) may be more directly and negatively associated with corruption than one’s religious affiliation.
Drawing on this theoretical expectation, Yeganeh and Sauers (2013) and Gokcekus and Ekici (2020) examined the effects of religiosity on corruption. In their analyses, they similarly found an insignificant relationship between religious denominations and corruption as anticipated, but also an unexpected positive correlation between religiosity and corruption.
In Zakaria (2018), a similar noteworthy finding was observed. The author measured religiosity using two proxies: the frequency of attending religious services and private prayer outside of religious services. The analysis revealed a significant negative correlation between the frequency of private prayer and tolerance of corruption, indicating that individuals who pray less frequently are more likely to tolerate corruption. Meanwhile, the author found a positive correlation between the frequency of attendance at religious services and tolerance of corruption. Despite this unexpected finding, the author did not offer an in-depth explanation as to why this correlation is established.

7. Trust

Several studies have examined the impact of trust on corruption as well. This strand of literature is grounded in the theoretical perspective that corruption is a type of collective action problem (Persson et al. 2013; You 2017).
Suppose that in a certain society, corruption is the expected behavior. In such a circumstance, even though people condemn corrupt behaviors or recognize that they would be better off jointly refraining from corruption, they have no reason to cooperate to minimize it because there are no benefits but rather substantial costs of acting fairly. Hence, people will likely choose corrupt alternatives rather than non-corrupt ones in this setting (Persson et al. 2013).
Here, it is important to note that such a cost–benefit calculation is ultimately derived from the individual (dis)trust in the truthfulness of other people and the existing monitoring institutions. More specifically, people are likely to rationalize their own corrupt behaviors in thoroughly corrupt settings because they cannot easily trust that most others and the existing institutions will act fairly. However, if individuals trust that others will refrain from corrupt practices and that monitoring institutions will be fair, they are more likely to resist corruption to pursue the long-term benefits of impartiality (You 2017).
Uslaner (2004) was the first attempt to investigate an association between trust and corruption.7 The author analyzed the causal impact of trust on corruption and vice versa. The results revealed that trust has a greater effect on corruption than the reverse causal relationship. Drawing from these findings, the author asserted that the causal direction between trust and corruption runs from trust to corruption.
Consistent with Uslaner’s findings, Bjørnskov (2003) also observed a negative correlation between trust and corruption. This result implies that a society with a high level of trust tends to exhibit low levels of corruption. This finding was so strong that it was robust to the inclusion of multiple confounding variables.
Chang (2012) examined the relationship between trust and corruption in a more nuanced manner by differentiating between two types of trust: (1) generalized trust and (2) institutional trust. Generalized trust refers to an individual’s trust in other members of society, whereas institutional trust pertains to one’s trust in a country’s institutions and civil services. The analysis revealed that generalized trust was significantly and negatively associated with corruption, suggesting that societies in which individuals have higher levels of trust in one another are less likely to experience corruption. In contrast, institutional trust was found to have no significant relationship with corruption.
Kubbe (2013) examined the impacts of interpersonal (generalized) and institutional trusts on corruption. However, the author took a slightly different approach by formulating a hypothetical causal model, where corruption mediates the relationship between interpersonal trust and institutional trust. This model posits that interpersonal trust influences corruption, and, in turn, corruption influences institutional trust. The analysis demonstrated that interpersonal trust is negatively associated with corruption and, as expected, corruption is also negatively associated with institutional trust.


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