Tax Evasion and Religiosity in the Muslim World: The

Significance of Shariah Regulation

Abstract

Using the data from the shadow economy (1999–2007) and socio-economic theoretical

framework, this paper examines tax evasion and religiosity in 38 Muslim-dominated

countries across the globe. The study reveals that Shariah-regulated countries and high

inflation (representing lack of monetary freedom) are negatively correlated with tax evasion

(i.e. are correlated with less tax evasion). In line with the literature, the findings also suggest

that high corporate tax (less fiscal freedom) positively, and legal enforcement negatively, lead

to tax evasion. Interestingly, no relationship was found for corruption and public sector

governance in the Muslim world. This is the first study to examine tax evasion practices in

the Muslim world as the starting point for the development of an international tax framework.

The results of the study have implications for both future research and policy.

KeywordsTax evasion; Muslim countries; Religiosity; Shariah

JEL ClassificationH26; H73; K42; N30; Z12

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1. Introduction

Over the last three decades, tax evasion has been seen as pervasive and inexorable in the

world and policymakers have not been able to combat it. Most of the studies focus upon

mainly economic variables (Schneider and Enste, 2000; Kirchler, Maciejovsky and

Schneider, 2003; Borck, 2004; Riahi-Belkaoui, 2004; Richardson, 2006, 2008; Tsakumis,

Curatola, and Porcano, 2007; Torgler and Schneider, 2007, 2009; Schneider, Linsbauer and

Heinemann, 2015a; Schneider, Raczkowski, and Mróz, 2015b; Alm, Martinez-Vazquez, and

McClellan, 2015; Herwartz, Schneiderz, and Tafenau, 2015; Berger, Fellner-Röhling,

Sausgruber, and Traxler, 2016; Gobena and Dijke, 2016; Fochmann and Kroll, 2016;

Ivanyna, Moumouras, and Rangazas, 2016). The mainstream neoclassical approach to tax

evasion (Allingham and Sandmo, 1972) cannot account for socio-behavioural dynamics

(Gangl, Hofmann, and Kirchler, 2015). It is not the aim of the present study to discount

economic factors as irrelevant but rather to extend the focus to include religious and moral

dimensions.

Weber (1956)[1905], in The Protestant Ethic and the Spirit of Capitalism, discusses

how Protestant religious culture affects the economic performance and supports capitalistic

systems. Adam Smith (1976)[1759], in The Theory of Moral Sentiments, earlier also analyses

religiosity from a rational point of view and notes that religiosity acts as a kind of internal

moral enforcement mechanism. Sen (1977) regards religion as a moral commitment to acting

in a determinate way, and such behaviour can be judged as rational. Hardin (1997) states that

religious behaviour is shaped by cost and benefit considerations. Religion also offers firm

enforcement of accepted rules and acts as ‘supernatural police’ (Anderson and Tollison,

1992). Hence, religion inhibits illegal behaviour, and prior studies show that countries with

higher rates of religiosity are significantly less violent (Hull and Bold, 1994; Hull, 2000).

Marquette (2012, p. 11) argues that religious people are more concerned with ethics than are

the non-religious, despite the fact that many of the most corrupt economies in the world also

rank highly in terms of religiosity. Based on evidence from India and Nigeria, she finds that

‘religion may have some impact on attitudes towards corruption, but it has very little likely

impact on actual corrupt behaviour’ (p. 11). However, Davis (1949) and Stark, Iannaccone,

and Finke (1996) see religion as encouraging non-rational or even irrational behaviour.

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Very few studies focus upon religious issues as a variable that could discourage tax

evasion, but none of them focus on Muslim countries. Iannaccone (2002, p. 163) points out

that traditional research has neglected the aspect of religiosity. Discussing ‘Who benefits

from tax evasion’, Alm and Finlay (2013, p. 139) argue that future research is required. This

is because religious activities might support the norms of a larger community (Tittle and

Welch, 1983; Grasmick, Bursik, and Cochran, 1991). Torgler (2006) finds that Catholics,

Hindus and Buddhists have higher tax morale than people without a religious denomination.

Recently, Schneider et al. (2015a, p. 113), find that ‘general religiosity seems to increase the

shadow economy. Moreover, robust differences emerge across religions. Protestant countries

seem to have the lowest shadow economy whereas Orthodox Christian countries have the

highest one.’ According to the Pew Research Center (2014), religious diversity around the

world is shown in Fig. 1, and demonstrates that the Asia Pacific region has the most diverse

religion.

[Insert Fig. 1 about here]

A key question regarding tax evasion arising here is: what, then, of the Muslim

countries’ context? Accordingly, the research question in this study is: what are the key

determinants of taxpayers in Muslim countries for evading taxes?

The novelty of this study is that it is the first study to examine tax evasion practices in

the Muslim world. The results suggests that Shariah-regulated countries and high inflation

(lack of fiscal freedom) are negatively correlated with tax evasion (i.e. the lower level of tax

evasion). These results support the inclusion of non-economic factors in the analysis of tax

compliant behaviour.

The rest of the paper is structured as follows. Section 2 explains background of Islam

and tax. Section 3 discusses theory and hypotheses development. Section 4 provides

empirical specification and sample construction. Section 5 presents the results. Section 6

contains the conclusion.

2. Islam and tax

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According to Muslim tradition, ‘God will punish us if we do not pay to the state’ (Jalili, 2012,

p. 167). Accountability is first of all to Allah (Forster and Fenwick, 2015. The Islamic

religion applies directly to all spheres of life, including the conduct of trade and commerce

(Saleh, 1998, p. 540). Shariah principles come in two forms. First, the Quran is the

foundation of Islam, and as such is the authoritative source on life, values and the very word

of God. Values are explicitly identified in the Quran. Second, the Hadith (Sunnah) (traditions

stated or enacted by the Prophet Mohammed) sets out the practical application of the Quran’s

rules and lessons. For Forster and Fenwick (2015, p. 3), ‘Islamic values are the filter for

moral business behaviour’. Coulson (1964) highlights that the Quranic command is to ‘Obey

God and His Prophet and those who are given authority over you’. According to Shariah,

Muslims should engage in good deeds in their business, personal, social, and political life.

Othman, Hamzah, and Hashim (2014, p. 117) observed that various Quranic verses highlight

the importance of values, ethics, and equality. In Islam, Zakah (tax) is the third pillar of Islam

and is mandatory. Corruption is strictly prohibited in Islam, Allah says in Surat Hūd (11:85):

‘And O my people, give full measure and weight in justice and do not deprive the people of

their due and do not commit abuse on the earth, spreading corruption.’ Some key Quranic

verses relating to tax and corruption are given below:

- Indeed, those who believe and do righteous deeds and establish prayer and give

zakah will have their reward with their Lord, and there will be no fear

concerning them, nor will they grieve. (Surat Al-Baqarah, 2:277)

- And let not those who [greedily] withhold what Allah has given them of His

bounty ever think that it is better for them. Rather, it is worse for them. Their

necks will be encircled by what they withheld on the Day of Resurrection. And

to Allah belongs the heritage of the heavens and the earth. And Allah, with what

you do, is [fully] acquainted. (Surat ‘Ali `Imran, 3:180)

- Zakah expenditures are only for the poor and for the needy and for those

employed to collect [zakah] and for bringing hearts together [for Islam] and for

freeing captives [or slaves] and for those in debt and for the cause of Allah and

for the [stranded] traveller – an obligation [imposed] by Allah. And Allah is

Knowing and Wise. (Surat At-Tawbah, 9:60)

- And of them are some who made a covenant with Allah (saying): ‘If He

bestowed on us of His Bounty, we will verily, give Sadaqah (Zakah and

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voluntary charity in Allah’s Cause) and will be certainly among those who are

righteous.’ (Surat At-Tawbah, 9:75)

- Certainly will the believers have succeeded (Surat Al-Mu’minūn, 23:1). And

those who pay the Zakah. (Surat Al-Mu’minūn, 23:4)

- Those who do not give zakah, and in the Hereafter they are disbelievers. (Surat

Fuşşilat, 41:7)

- Verily, those who give Sadaqat [i.e. Zakah and alms, etc.], men and women,

and lend to Allah a goodly loan, it shall be increased manifold (to their credit),

and theirs shall be an honorable good reward [i.e. Paradise]. (Surat Al-Ĥadīd,

57:18)

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3. Theory and hypothesis

To achieve the objective of the study, I argue that socio-economic theory can shed light on

some of the socio-cultural driving forces laying the foundation to explain tax evasion

practices. Since taxation is a highly structured process of institutionalized entities like ‘the

state’ (as tax lawmakers), ‘tax authorities’, and ‘taxpayers’, individuals’ tax-paying behaviour

is influenced by social structures (Kirchler, Muehlbacher, Kastlunger, and Wahl, 2010).

Pickhardt and Prinz (2014, p. 2) also argue that the other players may influence ‘the game of

taxation’.

Several factors can affect socio-institutional norms (Habermas, 2006; Spolaore and

Wacziarg, 2013), and forms of government, which in turn play a vital role in explaining

socio-economic theory. In particular, cultural values (Guiso, Sapienza, and Zingales, 2003,

2006; Maridal, 2013; Petrakis and Kostis, 2013), religiosity (Barro and McCleary, 2003;

Guiso et al., 2006; McCleary, 2008), and governance quality (Dixit, 2009) may represent the

behaviour of a society. Barro and McCleary, 2003 (p. 760) argue that ‘successful

explanations of economic performance must go beyond narrow measures of economic

variables to encompass political and social forces’. Andrei, Comer, and Koehler (2014)

implement different social network structures and show that the number of connections

between agents very much affects the collective behaviour of agents. Grasmick et al. 1991 (p.

253) argue that when individuals realize that they are in violation of a rule or social norm,

they may feel guilt.

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[Insert Fig. 2 about here]

Fig. 2 represents the socio-economic theoretical model based on the ‘institutional

infrastructure’ (Pickhardt and Prinz, 2014) of the three major players in the tax social

networks. The state has the tax authority that is responsible for collecting taxes from

taxpayers. Within this iterative circular model, the state (1) acts as the lawmaker. The

taxpayers (3) may interact with the tax authority (2) and the state by cooperating on tax

evasion. This circular model explains how the behaviour and role of the three major players

contribute to tax evasion. In terms of the state’s role, this model presents it as a matter of law

enforcement, ensuring business, fiscal and monetary freedom, thus also guaranteeing

incentives for the citizens. The tax authority’s norms are defined as public sector governance

(institutional quality), whilst the taxpayers’ behaviour illustrates cultural values and

religiosity.

To sum up, from this theoretical model at the core of tax evasion the following

hypotheses have been developed for this study:

3.1 Culture (Hypothesis 1)

Moral norms (as cultural values) are described in the literature in terms of how an individual

behaves in relation to tax evasion evading taxes (Riahi-Belkaoui 2004; Alm et al., 2015).

Most research finds a significant negative association between tax morale and tax evasion,

indicating that societies with more tolerance of corrupt activities evade tax more (Richardson,

2006; Tsakumis et al., 2007; Ivanyna et al., 2016, p. 520). It was also found that societies (i.e.

collective society) with more uncertainty avoidance experience higher levels of corruption

and tax evasion (Husted, 1999). Many variables are used to describe cultural values, for

example, corruption (Treisman, 2000; Tsakumis et al., 2007; Alm et al., 2015; Célimène,

Dufrénot, Mophou, and N’Guérékata, 2016), crime rate (Riahi-Belkaoui 2004), cheating

behaviour (Célimène et al., 2016), and bribery (Husted, 1999; Alm et al., 2015). This

argument leads to the following two hypotheses:

Hypothesis 1a: The less corruption in a country, the less tax evasion there is, ceteris paribus.

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Hypothesis 1b: The least irregular payment of bribes in a country, the less tax evasion there

is, ceteris paribus.

3.2 Legal Enforcement (Hypothesis 2)

Legal enforcement based on the rule of law provides an important foundation that the extent

to which the government enforces the laws for the prevention of tax evasion (Allingham and

Sandmo, 1972; Schneider and Enste, 2000). The literature finds that weak and arbitrary

enforcement of laws and regulations encourages corruption and tax evasion (Erard and

Feinstein 1994; Riahi-Belkaoui, 2004; Richardson, 2008; Torgler and Schneider, 2009;

Schneider, Buehn, and Montenegro, 2010; Neck, Wächter and Schneider, 2012; Ivanyna et

al., 2016). Richardson (2008) points out that lack of law enforcement leads to a lack of

confidence in government, which in turn leads to tax evasion. Borck (2004, p. 725), however,

argues that ‘Stricter enforcement may make redistributive taxation more attractive to the

decisive voter. The tax rate and transfer may rise, which in turn may increase tax evasion.’

This discussion leads to the following hypothesis:

Hypothesis 2: The higher the rule of law and legal enforcement in a country, the less tax

evasion there is, ceteris paribus.

3.3 Monetary, Fiscal and Business Freedom (Hypothesis 3)

The literature also finds that monetary, fiscal, and business freedom may create significant

opportunities for being productive and in turn result in less tax evasion (Alm, Jackson, and

McKee, 1992). The major finding of the earlier studies was a positive association between

marginal corporate tax rates (as fiscal freedom) and tax evasion (Yitzhaki, 1974; Mason and

Calvin, 1984; Riahi-Belkaoui, 2004; Richardson, 2006). For instance, Fisman and Wei (2004)

find that a rise of 1 per cent in taxes increases tax evasion by more than 3 per cent.

Gorodnichenko, Martinez-Vazquez, and Peter (2009), who studied major tax reform in

Russia, find a huge positive elasticity of evasion relating to the tax rate. Kleven, Knudsen,

Kreiner, Pedersen, and Saez (2011) also find a positive association between tax rates and tax

evasion. Recently, Berger et al. (2016, p. 2) said that ‘our evidence strongly supports the

intuition that higher taxes trigger more evasion’. Additionally, Fishlow and Friedman (1994,

p. 105), in a study of Argentina, Brazil, and Chile over the last 40 years, confirm that these

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three countries have long experience of high inflation and tax evasion. Pappa, Sajedi, and

Vella (2015) also confirm similar findings in a study of Greece, Italy, Portugal, and Spain,

and argue that tax compliance declines when current income declines, expectations about

future income improve, or inflation rises. Contributing to this view is the finding that less

monetary freedom (a high inflation rate), less fiscal freedom (high corporate taxes), and less

business freedom lead to high levels of tax evasion. This study extends earlier studies by

including business freedom when considering overall business, economic, and fiscal freedom.

Thus, the study posits the following hypothesis: that more business freedom may lead to less

tax evasion.

Hypothesis 3a: The higher a country’s inflation (representing less monetary freedom), the

more tax evasion there is, ceteris paribus.

Hypothesis 3b: The higher a country’s corporate tax (representing less fiscal freedom), the

more tax evasion there is, ceteris paribus.

Hypothesis 3c: The higher business freedom in a country (shareholder governance), the less

tax evasion there is, ceteris paribus.

3.4 Public Sector Governance (Hypothesis 4)

Discussing the significance of public sector governance (institutional quality), Torgler,

Schneider, and Schaltegger (2010, p. 293) argue that:

Policymakers often propose strict enforcement strategies to fight the shadow

economy/tax evasion and to increase tax morale. However, there is an

alternative bottom-up approach that decentralises political power to those who

are close to the problems. … there is a positive (negative) relationship between

local autonomy and tax morale (size of the shadow economy).

Prior research like that of Wallschutzky (1984), Brooks and Doob (1990), Tanzi (2000), and

Richardson (2008) also addresses governance issues and confirms that a lack of institutional

quality may increase tax evasion. Good quality governance will ensure individuals believe

that the government will act in their interests and that its procedures are fair, and will increase

their trust in government (Rose-Ackerman, 1997; Feld and Frey, 2002). Torgler and

Schneider (2009, p. 231) state:

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If citizens perceive that their interests (preferences) are properly represented in

political institutions, their willingness to act in the underground economy

decreases. On the other hand, in an inefficient state where corruption is rampant

the citizens will have little trust in authority and thus a low incentive to

cooperate. A more encompassing and legitimate state may be an essential

precondition for a more adequate tax system.

Ultimately, this psychological contract enhances individuals’ incentive to commit themselves

to obedience and compliance with tax laws. Torgler and Schneider (2009) find strong support

for the idea that higher tax morale and higher institutional quality lead to a smaller shadow

economy/less tax evasion. This discussion leads to the following hypothesis:

Hypothesis 4: The higher the quality of a country’s public sector governance (institutional

quality), the less tax evasion there is, ceteris paribus.

3.5 Religiosity (Hypothesis 5)

As mentioned earlier due to limited research it is difficult to predict the religiosity association

with tax evasion. Tittle (1980) argues that religiosity is an important basis for social norms to

discourage deviant forms of behaviour. In terms of tax evasion and religiosity, Grasmick et

al. (1991, p. 255) find that both church attendance and high levels of individual religiosity

(i.e. personal religious beliefs and convictions) have a significant negative relationship with

tax evasion. Based on Stark’s (1996, p. 164) proposition ‘Religious individuals will be less

likely to commit delinquent acts than those who are not religious, but only in communities

where the majority of people are actively religious’, Richardson (2008) also found a negative

relationship between religiosity and tax evasion. Based on the World Values Survey 1995–

1997 and covering more than 30 countries, Torgler (2006, p. 81) also found a negative

association. However, Richardson (2006) finds no association. Similarly, Schneider et al.

(2015a) find in a large survey that general religiosity seems to increase the shadow

economy/tax evasion. This is possibly because individuals in these countries face a

conflicting message, and suffer from widespread corruption (Marquette, 2013). No studies

were conducted on Muslim religiosity and hence this discussion leads to the following non-

directional hypothesis.

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Hypothesis 5: There is a significant association (positive or negative) between a country’s

religiosity (Shariah regulation) and its tax evasion.

4. Research design

4.1 Sample

At the outset, data were collected from 45 Muslim-dominant countries in the world (see

Table 1). The selection criterion were two: (1) the Muslim population will be more than 50

per cent indicating Muslim-dominant countries; and (2) the availability of data on tax

evasion. It was observed that 45 Muslim-dominant countries had a total population of 1.2769

billion (Pew Research Center, 2014). However, due to the unavailability of tax evasion data,

seven countries were excluded including Afghanistan (Asia Pacific), Djibouti (Africa), Iraq

(Middle East), Kosovo (Eastern Europe), Somalia (Africa), Turkmenistan (Eastern Europe),

and Uzbekistan (Eastern Europe). Hence the final sample consists of 38 countries with a total

population of 1.1963 billion. All sampled countries are also members of OIC (the

Organization of Islamic Cooperation).

[Insert Table 1 about here]

Table 1 presents the overview of the Muslim countries. The Herfindahl-Hirschman

Index of Religious Diversity Index (RDI) divides countries into four ranges: very high, high,

moderate, and low (Pew Research Center, 2014). From the sample of the study, it is found

that six countries (Bahrain, Lebanon, Qatar, Chad, Burkina Faso, and Malaysia) with scores

from 5.3 to 6.9 are categorized as having a ‘high’ level of diversity; seven countries

(Morocco, Somalia, Afghanistan, Iran, Tunisia, Yemen, and Iraq) with score from 3.1 to 5.2

are categorized as ‘moderate’ diversity; and 32 countries were categorized as ‘low’ diversity

with scores ranging from 0 to 3.0. None of the sampled countries was categorized as ‘high’

diversity. Again, according to the Corruption Perceptions Index (CPI) 2014, Afghanistan,

Sudan, Somalia, and Iraq were the most corrupt countries whilst the United Arab Emirates,

Qatar, Saudi Arabia, Malaysia, Bahrain and Jordan were the least corrupt countries in the

Muslim world in 2014 (Transparency International, 2014). Variation in the five-year GDP

growth rate (as a percentage), unemployment (as a percentage) and public debt (as a

percentage of GDP) were also observed (Heritage Foundation, 2015).

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4.2 Dependent variable

In this study, the dependent variable is represented by tax evasion (TEV), which is measured

based on a country’s mean estimation of the shadow economy as a percentage of GDP for the

ten years 1999–2007 (see Table 2). Table 2 lists the sample countries along with their mean

tax evasion scores across the years 1999–2007. Schneider et al. (2010, p. 5) defines the

shadow economy as:

includ[ing] all market-based legal production of goods and services that are

deliberately concealed from public authorities for any of the following reasons:

(1) [avoiding] payment of income, value added or other taxes, (2) [avoiding]

payment of social security contributions, (3) [avoiding] having to meet certain

legal labor market standards, such as minimum wages, maximum working

hours, safety standards, etc., and (4) [avoiding] complying with certain

administrative procedures, such as completing statistical questionnaires or other

administrative forms.

The literature follows a similar economic estimate of actual unreported income within a

country as a proxy for tax evasion (Schneider, 1997, 2005; Schneider and Enste, 2000;

Kirchler et al., 2003; Tsakumis et al., 2007; Richardson, 2008; Torgler and Schneider, 2009;

Halla, 2010; Schneider et al., 2010; Neck et al., 2012; Schneider, Linsbauer, and Heinemann,

2015; Schneider, Raczkowski, and Mróz, 2015; Herwartz et al., 2015). Measuring tax

evasion raises concerns about reliability due to error. However, measurement error can be

minimized by using average data for several years and hence this study uses tax evasion data

from Richardson, 2008 (p. 155).

[Insert Table 2 about here]

4.3 Independent variables

Measures for eight independent variables CORRUPT, INFL, CTAX, PRIGHT, DBUS,

BRIBES, GOVN, and SHARIAH are shown in Table 2 and are taken from various sources

including World Bank (2013, 2015), Transparency International (2014), Heritage Foundation

(2015), World Economic Forum (2015), Pew Research Center (2014), and government

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websites of sampled Muslim countries. Measures for the independent variables are shown in

Table 2.

4.4 OLS regression model

To examine potential relationships between culture, legal enforcement, freedom (business,

fiscal and monetary), public sector governance, religiosity, and tax evasion across Muslim

countries, the following OLS regression model is estimated:

TEV i=β0+β1CORRUPT i+β2 INFLi+β3CTAX i+β4 PRIGHT i+β5 DBUSi+β6 BRIBES i+ β7 GOVN i+β8 SHARIAH i+εi (1 )

Where

TEV i = tax evasion score for country i;

CORRUPT i = corruption score for country i;

INFLi = inflation rate for country i;

CTAX i = corporate tax rate for country i;

PRIGHT i = property rights score for country i;

DBUSi = doing business score for country i;

BRIBESi = irregular payments and bribes score for country i;

GOVN i = public sector governance score for country i;

SHARIAH i = religiosity legal framework for country i; and

ε i = error term for country i.

5. Results and discussions

Table 3 presents the descriptive statistics for the full sample of 38 countries. For the

dependent variable, TEV (as a percentage of GDP) has a mean of 32.69 per cent and a range

of 14.10 to 58 per cent over the nine-year period (1999–2007), which indicates considerable

variation with regard to tax evasion across countries. The mean of this study is considerably

higher than reported in the study of Tsakumis et al. (2007, p. 142), which is a mean of 27.22

per cent during the three-year period (2000–2002). Fig. 3 shows the variation of tax evasion

in different regions (four regions, namely, AP, AF, ME and EE) with Muslim-dominated

countries across the globe.

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[Insert Fig. 3 about here]

There is sufficient variation in the independent variables too. For example,

CORRUPT ranges from 11 to 70 (mean = 43.94), INFL ranges from 0.5 to 40.2 per cent

(mean = 7.69 per cent), CTAX ranges from 0 to 50 per cent (mean = 22.39 per cent),

PRIGHT ranges from 0 to 70 (mean = 31.45), DBUS ranges from 1.30 to 7.30 (mean = 4.42),

BRIBES ranges from 2.11 to 6.43 (mean = 3.70), GOVN ranges from -1.76 to 0.69 (mean = -

0.54), and SHARIAH ranges from 0 to 1 (mean = 0.63). A reasonable range of variation and

consistency was also observed in standard error and variance for all variables. It was also

found that skewness for all variables was no greater than +3 and kurtosis were well below

+10.0, meaning that data are normally distributed (Byrne, 2010).

[Insert Table 3 about here]

The Pearson correlation results are reported in Table 4, which shows that there are a

number of significant correlations between TEV and the independent variables. For instance,

there are fairly high correlations (p < 0.01) between TEV and CORRUPT (r = −0.445),

CTAX (r = 0.493), PRIGHT (r = -0.465), BRIBES (r = -0.556), and SHARIAH (r = -0.661).

However, no significant correlations are found between TEV and INFL, DBUS and GOVN.

In fact, the highest correlation coefficient of 0.889 is found between PRIGHT and CORUPT

(p < 0.01). Table 4 also shows that only moderate levels of collinearity exist between the

explanatory variables. According to Hair et al. (2006), if a value of the correlation coefficient

for a pair of explanatory variables lies between ±0.25 and ±0.75, then there is a moderate

level of collinearity between the two variables. Fig. 4 also shows the Scatterplot Matrix for

TEV relationship with independent variables.

[Insert Table 4 about here]

[Insert Fig. 4 about here]

Table 5 reports the OLS regression results for TEV model specified in Eq. (1). It

shows that the base regression model is highly significant at the p < 0.01 level (F-statistic =

11.377). The Durbin–Watson statistic (Durbin and Watson, 1950) of the OLS model is a

value of 2.020, which is within the acceptable range (1.5 to 2.5). This means that there is no

13

serious problem undermining the model’s inferential suitability (e.g. assessing the confidence

in the predicted value of a dependent variable), and hence no first‐order autocorrelation

(Pallant, 2013).

[Insert Table 5 about here]

The adjusted R2 = 0.728 (which is higher than in the study of Richardson (2008),

which reported a value of 0.60; and of Tsakumis et al. (2007), which reported a value of

0.585) indicates that the independent variables explain a relatively high percentage of

variation in the dependent variable. Based on the tolerance and the Variation Inflation Factor

(VIF), multicollinearity does not present a problem in this study (Pallant, 2013).

- Culture (Hypothesis 1) prophesied that a lower level of corruption and irregular

payment of bribes will lead to a lower level of tax evasion. However, no

significant relationships are found for CORRUPT (t = 0.614, p = 0.545) and

BRIBES (t = 0.994, p = 0.331).

- Legal enforcement (Hypothesis 2) expected that the lower level of rule of the law

and enforcement will lead to the lower level of tax evasion. As expected, the

coefficient for PRIGHT (t = -2.710, p < 0.012) is negative and significant. This

result supports hypothesis 2.

- Monetary, fiscal, and business freedom (Hypothesis 3) predicted that the higher

level of inflation rate (lack of monetary freedom) and corporate tax (lack of fiscal

freedom) are related to a higher level of tax evasion; and a higher level of business

freedom (shareholder governance) will lead to lower level of tax evasion. The

coefficient for INFL (t = -3.762, p < 0.001) is negative and significant. The

coefficient for CTAX (t = 3.187, p < 0.004) is positive and significant. However,

the coefficient for DBUS (t = 0.980, p = 0.337) is not significant. This result

implies the conformity of monetary and fiscal freedom are related to tax evasion

(Hypothesis 3a and 3b).

- Public Sector Governance (Hypothesis 4) predicted that a lower quality of public

sector governance quality is related to a lower level of tax evasion. The coefficient

for GOVN (t = -0.990, p = 0.333) is not significant. This is not in conformity with

hypothesis 5.

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- Religiosity (Hypothesis 5) predicted that the religiosity is related to tax evasion. A

direction was not hypothesized. The coefficient for SHARIAH (t = -4.175, p <

0.001) is negative and significant. Hence hypothesis 5 is supported (see also Fig. 5

for TEV relationship with Shariah and non-Shariah-regulated countries).

[Insert Fig. 5 about here]

Robustness tests are also used to ensure the results are not heavily influenced by a

single country. I re-estimate all regressions and all results stay qualitatively the same.

From the above analysis, we deduce a number of important and novel results. First,

overall, three variables (legal enforcement, monetary and fiscal freedom, and Shariah

regulation) support the hypothesis. The empirical results reported in this study suggest

strongly that Shariah regulation plays a significant role in determining the level of lower tax

evasion in the Muslim-dominant countries. Unlike prior studies (Fishlow and Friedman,

1994; Pappa et al., 2015), which document that high inflation is related to higher tax evasion,

this study implies that in countries with a high inflation rate (lack of monetary freedom), tax

evasion is lower.

Second, in line with the literature, the study supports a higher corporate tax rate

leading to a higher rate of tax evasion (Erard and Feinstein, 1994; Riahi-Belkaoui, 2004;

Richardson, 2008; Neck et al., 2012; Ivanyna et al., 2016), and a higher level of enforcement

contributing to lower tax evasion (Yitzhaki, 1974; Mason and Calvin, 1984; Fishlow and

Friedman, 1994; Riahi-Belkaoui, 2004; Richardson, 2006; Pappa et al., 2015; Berger et al.,

2016). It is recommended that instead of imposing corporate taxes, the government should

exert extra efforts to reduce tax evasion by creating more business freedom.

Third, most strikingly, cultural values (corruption and irregular bribes) and public

sector governance quality have no influence in determining tax evasion in the Muslim world.

As Treisman (2000) earlier points out, even corruption ratings that are constructed by

different methodologies generally show a high correlation. Torgler and Schneider (2009) also

reported corruption and governance as key variables to understand what shapes the tax

evasion. Policymakers in the Muslim world should focus on establishing good governance in

15

public sector because the overall mean score was -0.54 (on a scale from -2.5 to 2.5, with

higher values corresponding to better governance). Han, Khan, and Zhuang (2014, p. 1)

stated: ‘Good governance is associated with both a higher level of per capita GDP as well as

higher rates of GDP growth over time. This suggests that good governance, whilst important

in and of itself, can also help in improving a country’s economic prospects.’ Additionally,

business freedom (in terms of shareholder governance) should be increased through

transparency, which might help to reduce tax evasion.

6. Conclusions and policy implications

The study investigates the tax evasion practices and religiosity in 38 Muslim-dominant

countries across the globe. The most important contribution of this paper has been to extend

the previous empirical studies on religiosity by showing that Shariah-regulated countries and

high inflation (lack of monetary freedom) are negatively correlated with tax evasion (i.e. the

lower level of tax evasion). Overall, the regression results in the present study also indicate

that a higher corporate tax rate (representing a lack of fiscal freedom) are positively, and legal

enforcement are negatively associated with tax evasion. Unlike earlier research, the present

study do not find any association between corruption and public sector governance with tax

evasion in the Muslim world.

This result suggests that Shariah-regulated countries might have high inflation but tax

evasion is low due to religious faith and belief, which lead individuals to obey the state law.

This study could also have major policy implications for local governments and international

policymakers when considering tax reform and tax evasion issues in Muslim countries.

The empirical findings of the study reaffirm the utmost need for future research.

Future research could be carried out on the dynamics of Shariah regulation in relation to tax

evasion in all 57 Muslim countries of the OECD, which may shed further light on the

findings of the present study. To find out the generalizability of the religiosity literature,

future research could also focus on comparing tax evasion between Muslim and other

religions in more depth.

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Table 1. Overview of sample Muslim countries

Country Region Muslim (%)

Religious Diversity Index (RDI)

Christian (%)

Hindu (%)

Buddhist (%)

Jewish (%)

Unaffiliated (%)

Population (millions)

5 year GDP Growth Rate (%)

Unemployment (%)

Public debt (% of GDP)

CPI index 2014 (ranking of 175 countries)

Tax evasion

Afghanistan AP 99.7 0.1 0.10 < 0.1 < 0.1 < 0.1 < 0.1 32.0 9.9 35 N/A 172 N/AAlbania EE 80.3 3.7 18.0 < 0.1 < 0.1 < 0.1 1.40 3.2 3.7 15.0 60.6 110 34.3Algeria ME 97.9 0.5 0.20 < 0.1 < 0.1 < 0.1 1.80 36.5 2.4 9.7 9.9 100 32.5Azerbaijan EE 96.9 0.7 3.00 < 0.1 < 0.1 < 0.1 < 0.1 9.2 5.4 6.0 11.6 126 58Bahrain ME 70.3 5.4 14.5 9.80 2.50 0.60 1.90 1.2 4.0 3.4 33.7 55 17.9Bangladesh AP 89.8 2.1 0.20 9.10 0.50 < 0.1 < 0.1 150.0 6.2 5.0 31.7 145 35.3Brunei AP 75.1 4.8 9.40 0.30 8.60 < 0.1 0.40 0.4 0.5 2.7 2.4 N/A 30.9Burkina Faso AF 61.6 6.2 22.5 < 0.1 < 0.1 < 0.1 0.40 17.4 5.7 77.0 27.7 85 40.5Chad AF 55.3 6.0 40.6 < 0.1 < 0.1 < 0.1 2.50 10.7 3.7 N/A 34.5 154 43.7Comoros AF 98.3 0.4 0.50 < 0.1 < 0.1 < 0.1 0.10 0.7 1.9 20.0 42.6 142 38.7Djibouti AF 96.9 0.7 2.30 < 0.1 < 0.1 0.20 0.20 0.9 4.7 59.0 38.6 107 N/AEgypt ME 94.9 1.1 5.10 < 0.1 < 0.1 < 0.1 < 0.1 82.5 4.2 12.3 80.2 94 34.9Gambia AF 95.1 1.1 4.50 < 0.1 < 0.1 < 0.1 < 0.1 1.8 3.6 N/A 77.2 126 44.3Guinea AF 84.4 3.1 10.9 < 0.1 < 0.1 < 0.1 1.80 10.9 2.9 N/A 43.0 145 39Indonesia AP 87.2 2.6 9.90 1.70 0.70 < 0.1 < 0.1 244.5 5.9 6.2 24.0 107 18.9Iran ME 99.5 0.1 0.20 < 0.1 < 0.1 < 0.1 0.10 76.1 2.3 12.5 10.7 136 18.3Iraq ME 99 0.2 0.80 < 0.1 < 0.1 < 0.1 0.10 33.7 7.1 16.0 34.2 170 N/AJordan ME 97.2 0.6 2.20 0.10 0.40 < 0.1 < 0.1 6.4 4.1 12.2 79.6 55 18.5Kazakhstan EE 70.4 5.0 24.8 < 0.1 0.20 < 0.1 4.20 16.7 4.8 5.4 12.3 126 41.1Kosovo EE 87 2.6 11.4 < 0.1 < 0.1 < 0.1 1.60 1.8 4.1 45.3 5.5 110 N/AKuwait ME 74.1 4.8 14.3 8.50 2.80 < 0.1 < 0.1 3.8 0.8 2.1 7.3 67 19.4Kyrgyzstan EE 88 2.4 11.4 < 0.1 < 0.1 < 0.1 0.40 5.6 3.0 7.7 48.9 136 40.4Lebanon ME 61.3 5.5 38.3 < 0.1 0.20 < 0.1 0.30 4.0 5.5 N/A 139.5 136 33.1

20

Country Region Muslim (%)

Religious Diversity Index (RDI)

Christian (%)

Hindu (%)

Buddhist (%)

Jewish (%)

Unaffiliated (%)

Population (millions)

5 year GDP Growth Rate (%)

Unemployment (%)

Public debt (% of GDP)

CPI index 2014 (ranking of 175 countries)

Tax evasion

Libya ME 96.6 0.7 2.70 < 0.1 0.30 < 0.1 0.20 6.4 -3.7 30.0 0.0 166 33.7Malaysia AP 63.7 6.3 9.40 6.00 17.70 < 0.1 0.70 29.5 4.2 3.0 55.5 50 30.9Maldives AP 98.4 0.4 0.40 0.30 0.60 < 0.1 < 0.1 0.3 5.1 28.0 77.5 N/A 29.5Mali AF 92.4 1.6 3.20 < 0.1 < 0.1 < 0.1 2.70 16.3 3.3 30.0 32.0 115 40.7Morocco ME 99.9 0.0 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 32.5 4.4 8.8 59.6 80 34.9Niger AF 98.4 0.4 0.80 < 0.1 < 0.1 < 0.1 0.70 16.1 6.4 N/A 31.1 103 40.4Oman ME 85.9 2.9 6.50 5.50 0.80 < 0.1 0.20 3.1 6.3 15.0 6.1 64 18.4Pakistan AP 96.4 0.8 1.60 1.90 < 0.1 < 0.1 < 0.1 178.9 3.0 7.7 62.1 126 35.7Qatar ME 67.7 5.7 13.8 13.8 3.10 < 0.1 0.90 1.8 13.1 0.5 37.8 26 14.1Saudi Arabia ME 93 1.5 4.40 1.10 0.30 < 0.1 0.70 29.0 6.6 10.6 3.6 55 18.1Senegal AF 96.4 0.8 3.60 < 0.1 < 0.1 < 0.1 < 0.1 13.1 3.3 48.0 45.0 69 43.7Sierra Leone AF 78 4.0 20.9 < 0.1 < 0.1 < 0.1 0.10 6.2 7.8 N/A 44.5 119 45.6Somalia AF 99.8 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 N/A N/A N/A N/A 174 N/ASudan ME 90.7 2.0 5.40 < 0.1 < 0.1 < 0.1 1.00 33.5 0.8 10.8 97.6 173 34.1Syria ME 92.8 1.6 5.20 < 0.1 < 0.1 < 0.1 2.00 N/A N/A 18.0 52.2 159 19.1Tajikistan EE 96.7 0.7 1.60 < 0.1 < 0.1 < 0.1 1.50 8.0 6.7 2.5 32.5 152 42.2Tunisia ME 99.5 0.1 0.20 < 0.1 < 0.1 < 0.1 0.20 10.8 2.5 18.9 44.5 79 37.2Turkey EE 98 0.4 0.40 < 0.1 < 0.1 < 0.1 1.20 74.9 3.1 9.2 36.4 64 31.3Turkmenistan EE 93 1.5 6.40 < 0.1 < 0.1 < 0.1 0.50 5.6 11.1 60.0 15.8 169 N/AUnited Arab Emirates

ME 76.9 4.4 12.6 6.60 2.00 < 0.1 1.10 5.5 2.1 2.4 17.6 25 25.9

Uzbekistan EE 96.7 0.7 2.30 < 0.1 < 0.1 < 0.1 0.80 29.4 8.4 0.2 8.6 166 N/AYemen ME 99.1 0.2 0.20 0.60 < 0.1 < 0.1 0.10 25.9 0.8 35 46.7 161 27.1

Notes: N/A – Not available; Region: AF - Africa, AP - Asia Pacific, EE - Eastern Europe, ME - Middle East; Religious Diversity Index (RDI score, Muslim (%), and other religious data are from Pew Research Center (2014); Population (millions), 5 year GDP growth rate (%), unemployment (%) and public debt (% of GDP) are from the Heritage Foundation (2015); CPI index 2014 (ranking of 175 countries) are from Transparency International (2014); Tax evasion score is based on Schneider et al. (2010)’s “Shadow Economies All over the World”.

21

Table 2. Variable description and sources

Variable Description Sources

Tax evasion (TEV) The tax evasion scores are mean estimates of each country’s shadow economy (i.e., estimates of all market-based legal production of goods and services that are deliberately concealed from public authorities) as a percentage of GDP for the years 1999–2007 and are taken from Schneider, Buehn and Montenegro (2010)’s “Shadow Economies All Over the World”. Countries with larger (smaller) shadow economies (as a percentage of GDP) represent higher (lower) tax evasion countries. This variable is averaged for 1999–2007.

Schneider, Buehn and Montenegro (2010), https://openknowledge.worldbank.org/bitstream/handle/10986/3928/WPS5356.pdf?sequence=1

Corruption Score (CORRUPT) The corruption score as a measure of cultural value is derived from Transparency International (2014)’s “The Corruption Perceptions Index (CPI) 2014”. The score indicates the perceived level of corruption on a scale of 0–100, where 0 means that a country is perceived as highly corrupt and a 100 means that a country is perceived as very clean

Transparency International (2014), http://files.transparency.org/content/download/1856/12434/file/2014_CPIBrochure_EN.pdf

Inflation (INFL) The weighted average inflation rate for the most recent three years serves (2012–2014) as the primary input into an equation that generates the base score for monetary freedom. Higher inflation indicates higher level of inflation and lower monetary freedom

The Heritage Foundation (2015), http://www.heritage.org/index/excel/2014/index2014_data.xls

Corporate Tax (CTAX) The top marginal tax rate on corporate income, as the basis for fiscal freedom in 2014. higher tax rate indicates lower level of fiscal freedom

The Heritage Foundation (2015), http://www.heritage.org/index/excel/2014/index2014_data.xls

Property Rights (PRIGHT) As legal enforcement, it measures the degree to which a country’s laws protect private property rights and the extent to which its government enforces those laws. The score ranges between 0 and 100 in the year of 2014. A score of 100 indicates private property is guaranteed by the government, the court system enforces contracts efficiently and quickly, the justice system punishes those who unlawfully confiscate private property. A score of 0 private property indicates “is outlawed, and all property belongs to the state. People do not have the right to sue others and do not have access to the courts, and corruption is endemic.

The Heritage Foundation (2015), http://www.heritage.org/index/excel/2014/index2014_data.xls

Doing Business Score (DBUS) As business freedom, the extent of shareholder governance index is the average of the extent of shareholder rights index, the extent of ownership and control index and the extent of corporate transparency index derived from the World Bank (2013)’s Doing Business 2014. The index ranges from 0 to 10, with higher values indicating stronger rights of shareholders in corporate governance.

World Bank (2013), https://openknowledge.worldbank.org/bitstream/handle/10986/16204/19984.pdf?sequence=1

Irregular payments and bribes (BRIBES)

As cultural value, the World Economic Forum (2015)’s The Global Competitiveness Report 2014–2015, provides an average score across the five components of Executive Opinion Survey question: ‘In your country, how common is it for firms to make undocumented extra payments or bribes connected with (a) imports and exports; (b)

World Economic Forum (2015), http://www3.weforum.org/docs/GCR2014–15/GCI_Dataset_2006–07–2014–15.xlsx

22

public utilities; (c) annual tax payments; (d) awarding of public contracts and licenses; (e) obtaining favorable judicial decisions?’ In each case, on a scale from 1 to 7 where 1 represents ‘very common’ and 7 indicates ‘never occurs’.

Governance (GOVN) As public sector governance, the average score of the World Bank (2015)’s six dimensions of Worldwide Governance Indicators (WGI) for the year of 2014, on a scale from -2.5 to 2.5, with higher values corresponding to better governance. 

World Bank (2015), http://data.worldbank.org/data-catalog/worldwide-governance-indicators

Shariah Law (SHARIAH) As religiosity, it is a dummy variable where a country is having Shariah Law indicates 1 otherwise 0

Government websites of sampled countries and Pew Research Center (2014)

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Table 3. Descriptive statistics (N = 38)

 Variablea Min Max Mean SD VarTEV 14.10 58 32.69 10.07 101.48CORRUPT 11 70 34.89 13.05 170.39INFL 0.50 40.20 7.69 9.13 83.27CTAX 0 50 22.39 12.66 160.21PRIGHT 0 70 31.45 16.10 259.34DBUS 1.30 7.30 4.42 1.35 1.81BRIBES 2.11 6.43 3.70 1.21 1.46GOVN -1.76 0.69 -0.54 0.63 0.40SHARIAH 0 1 0.63 0.49 0.24

Notes: a Variable definitions are shown in Table 2.

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Table 4. Pearson correlations for dependent and independent variables

 Variablesa 1 2 3 4 5 6 7 8 91. TEV 1                2. CORRUPT -0.445** 1              3. INFL -0.165 -0.526** 1            4. CTAX 0.493** -0.602** 0.296 1          5. PRIGHT -0.465** 0.889** -0.596** -0.475** 1        6. DBUS -0.080 0.140 -0.011 -0.125 0.247 1      7. BRIBES -0.556** 0.876** -0.432* -0.674** 0.805** 0.108 1    8. GOVN -0.312 0.904** -0.621** -0.528** 0.819** 0.172 0.808** 1  9. SHARIAH -0.661** 0.161 0.177 -0.170 0.190 -0.122 0.387* 0.093 1

Notes: a Variable definitions are shown in Table 2.*, and ** denote statistical significance at 5% and 1% levels, respectively.

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Table 5. OLS regression results

Independent variablesa

Expected signUnstandardized coefficients

Standardized coefficients

t –statistic p-value

B Std. Error BetaCONSTANT 30.143 12.811   2.353 0.028CORRUPT Negative 0.157 0.255 0.189 0.614 0.545INFL Positive -0.817 0.217 -0.452 -3.762 0.001***CTAX Positive 0.367 0.115 0.413 3.187 0.004***PRIGHT Negative -0.405 0.149 -0.609 -2.710 0.012***DBUS Negative 0.847 0.865 0.109 0.980 0.337BRIBES Negative 1.980 1.993 0.226 0.994 0.331GOVN Negative -4.602 4.650 -0.254 -0.990 0.333SHARIAH Positive/negative -9.902 2.372 -0.468 -4.175 0.001***Observations 38R2 0.798Adjusted R2 0.728F-statistic 11.377p-value 0.01Durbin-Watson 2.020

Notes: a Variable definitions are shown in Table 2;*, ** and *** denote statistical significance at 10%, 5% and 1% levels, respectively.

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Figure 1. Religious diversity around the world

Source: Pew Research Center (2014)

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State (1)

Tax Authority (2)

Tax Payers (3)

Tax Evasion

Institutional Norms (+/-):Public sector governance

Rule of the Law& Enforcement (+/-)

Business, Fiscal and Monetary Freedom (Incentive)

Figure 2. Socio-Economic Theoretical Model of Tax Evasion

Source: Own depiction based on Pickhardt and Prinz (2014) (integrative model

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Figure 3. Tax evasion by four regions (AP, AF, ME and EE)

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Figure 4. Scatterplot Matrix for dependent and independent variables

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Figure 5. Tax evasion by Shariah regulated countries

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