Compliant Attitude in Africa

 

Factors affecting tax compliant  attitude in  Africa:  Africa:  Evidence from Kenya, Tanzania, Uganda and South  Africa  Africa 

Merima  Ali  Ali  [email protected]  Odd‐Helge Fjeldstad  [email protected]  Ingrid Hoem Sjursen  [email protected]  Chr.Michelsen Insitute  Bergen, Norway  

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 Abstract  In  this  study,  we  explore  factors  that   determine  citizens’   tax   compliance  behavior   in  Kenya, Tanzania, Uganda and  South  Africa  Africa using attitude and   perception  perception data  from  from  the new  round   5   of   Afrobarometer   surveys.  Using  a  binary   logit   regression,  we  find   some  similarities,  but   also  differences  in  factors  that   are  correlated   with  tax   compliance  attitude  in  the  four   countries.  An  increase  in  the  perception  of   individuals  about   the  difficulty   of   evading  taxes  is  found   to  increase  the  likelihood   of   tax   compliant   attitude  in  Kenya  and   South  Africa.  We  also  find   evidence  that   individuals  who  are  more  satisfied   with  public  service  provision  are  more  likely   to  have  a  tax   compliant   attitude  in  all   the  four   four   countries.  However,  frequent   frequent   payment   payment   to  non‐state  actors,  e.g.  to  criminal    gangs  in  exchange   for    protection,  reduces  individual’s  tax   compliant   attitude.  Furthermore,  those  individuals  who  perceive  that   their   ethnic  group  is  treated   unfairly   are  less  likely   to  have  a  tax   compliant   attitude  in  Tanzania  and   South   Africa.  Tax   knowledge  is  also  significantly   correlated   with  tax   compliant   attitude  in  Tanzania  and   South  Africa.  These  findings  are robust   for   for  different  econometric specifications.  1. 

Introduction 

  Raising more domestic revenue is a priority for most sub‐Saharan African countries (Drummond et   al.  2012). Mobilizing revenue is a way for governments’ to create fiscal space, provide essential public services, and reduce foreign aid and single resource dependence. However, the domestic tax bases in most African countries are undermined by widespread tax avoidance and evasion (IMF 2011). Although taxpayer non‐compliance is a continual and growing global problem (McKerchar and Evans 2009), many indications suggest that developing countries, many of them in Sub‐Saharan Africa, are the hardest h ardest hit (Cobham 2005; Fuest and Riedel 22009). 009). Dealing with the problem of tax evasion requires at least some understanding of the factors underlying the individual taxpayer’s decision whether to pay or evade taxes. However, little is known about tax compliance behavior in developing countries (Andreoni  et   al.  1998; D'Arcy 2011; Fjeldstad and Semboja 2001). This study attempts to explore factors that determine citizens’ tax compliance behavior in selected African countries using attitude and perception

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data from a new round of Afrobarometer surveys (Round 5; 2011/12) 1. This survey includes a series of questions about tax that are new and not included in previous rounds of Afrobarometer. This allows for a more comprehensive empirical analysis of tax compliance attitudes based on nationally representative public opinion survey data from the selected African countries. Studying what factors determine tax compliance attitude and behavior in Africa is not only of academic interest; it is also important from a policy perspective. Attempts to broaden the tax base must build on insights into how citizens experience and perceive the tax administration and enforcement, and whether and how their tax behavior is correlated with how they perceive the state. More systematic and coherent information on taxpayer attitudes are therefore required for better analysis and a more informed tax policy design. By empirically establishing which factors affect tax compliance in the selected countries, the paper derives feasible policy recommendations for policy makers and revenue administrations. In the study, we use an indirectly phrased question to capture tax compliance attitude of individuals in order to avoid direct implication of “wrongdoing” by the respondent. In the questionnaire, respondents were asked to state their opinion about other people who do not pay taxes that they owe on their income. They were asked to state whether they think the action of other people who do not pay taxes on their income is “not wrong at all”, “wrong but understandable” considered as having or “wrong a tax compliant and punishable”. attitude if their Basedresponse on these is “wrong responses, and punishable’’ individuals and are non‐compliant attitude if their response is either “not wrong at all” or “wrong but understandable”. Using a binary logit regression, we find some similarities, but also differences in factors that are correlated with tax compliance attitude in the four countries. An increase in the perception of individuals about the difficulty of evading taxes is found to increase the likelihood of tax compliant attitude in Kenya and South Africa. We also find evidence that individuals who are more satisfied with public service provision are more likely to have a tax compliant attitude in all the four countries. However, frequent payment to non‐state actors, e.g. to criminal gangs in exchange for protection, reduces individual’s tax compliant attitude. Furthermore, those individuals who perceive that their ethnic group is treated unfairly are less likely to have a tax compliant attitude in Tanzania and South Africa. Tax knowledge is also significantly correlated with tax compliant attitude in Tanzania and South Africa. These findings are robust for differentother econometric specification, include the three responses of individuals regarding people’s action about tax t axwhere in an we ordered logitallregression. The remainder of the paper is structured as follows: The next section provides a brief presentation of theoretical perspectives on tax compliance. Section 3 presents the data and research design. Sections 4 and 5 present the results. Finally, section 6 summarizes and concludes.

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 Afrobarometer is an independent, nonpartisan research project which consists of national sample surveys on the attitudes of citizens in selected countries towards democracy, markets, civil society and other aspects of development. Because the instrument asks a standard set of questions, countries can be systematically compared. For further details, see www.afrobarometer.org   2 

 

2. 

Understanding taxpayer attitudes and behavior: theoretical foundations 

Models of taxpayer behavior, including the decision whether or not to pay taxes, tend to reflect one of five theories that can be referred to as: (1) economic deterrence; (2) fiscal exchange; (3) social influences; (4) comparative treatment; and (5) political accountability. These are to some extent interconnected, and some represent an evolution of others. Economic deterrence 

The economic deterrence theory states that taxpayer’s behavior is influenced by factors such as the tax rate determining the benefits of evasion, and the probability of detection and penalties for fraud which determine the costs (Allingham and Sandmo 1972; Becker 1968). 2 This implies that if detection is likely and penalties are severe, few people will evade taxes. In contrast, under low audit probabilities and low penalties, the expected return to evasion is high. The model then predicts substantial noncompliance. Although the model has been criticized for focusing exclusively on the coercive side of compliance, at the expense of the consensual (Sandmo 2005)3, there is some evidence to support the relevance of deterrence strategies to addressing non‐ compliance (McKerchar and Evans 2009). For example, the fear of getting caught, or the probability of detection, has been found in some contexts to be an effective strategy to induce truthful behavior. The theoretical principles of economic deterrence have also been widely adopted by tax administrations when developing enforcement strategies that rely principally on penalties and the fear of getting caught. Fiscal  exchange 

The fiscal exchange theory suggests that the t he presence of government expenditures may motivate compliance and that governments can increase compliance by providing goods that citizens prefer in a more efficient and accessible manner (Cowell and Gordon 1988; Levi 1988; Tilly 1992; Moore 2004; 1998). Alm et  al. (1992) note that compliance increases with (perceptions of) the availability of public goods and services. Accordingly, the main concern of taxpayers is what they get directly in return for their tax payments in the form of public services ( quid   pro  pro  quo). In this perspective, taxation and the provision of public goods and services are interpreted as a contractual relationship between taxpayers and the government (Moore 2004). Individuals may pay taxes because they value the goods provided by the government, recognizing that their payments are necessary both to help finance the goods and services and to get others to contribute (Fjeldstad and Semboja 2001). The existence of positive benefits may increase the probability that taxpayers withoutfrom direct coercion. Although taxpayers cannot assess the will exactcomply value ofvoluntarily, what they receive the government in returnmost for taxes paid, it can be argued that they have general impressions and attitudes concerning their own and others’ terms of trade with the government (Richupan 1987). It is then reasonable to assume that a taxpayer’s behavior is affected by his/her satisfaction or lack of satisfaction with his/her terms of trade with the government. Thus, if the system of taxes is perceived to be unjust, tax evasion may, at least partly, be considered as an attempt by the taxpayer to adjust his 2

 Nearly all economic approaches to tax evasion are based on this economics-of-c economics-of-crime rime framework (Becker 1968). Cowell (1990) offers an insightful review of this analytical framework. 3  For instance, empirical data from Western countries reveal that taxpayers pay much more tax than what could  be accounted for even by the highest feasible levels of auditing, penalties and risk-aversion. The question therefore has switched from “why do people not evade taxes” to “why do people pay?” Alm, J., G. H. of Public J.Economics, McClelland & W.Why D. people Schulzepay 1992. Why do people pay taxes?  Journal 48,  21-38,  In: Slemrod, Slemrod, J. 1992. taxes: tax compliance and enforcement. (ed.). Ann  Arbor: The University of Michigan Press.. 3 

 

terms of trade with the government. The fiscal exchange theory has received much attention and is well established theoretically. Empirical evidence to support the theory is, however, ambiguous (D'Arcy 2011: 5‐6). Social  influences 

In the social influence model, compliance behavior and attitudes towards the tax system is thought to be affected by the behavior and social norms of an individual’s reference group (Snavely 1990). It isinteractions reasonable reasonable much to assume human behavior vior informs the ofarea areabehavior of taxation influenced by social in thethat same way beha as other (ibid).is Compliance behavior and attitudes towards the tax system may therefore be affected by the behavior of an individual’s reference group such as relatives, neighbors and friends. Therefore, if a taxpayer knows many people in groups important to him who evade taxes, his/her commitment to comply will be weaker. On the other hand, social relationships may also help deter individuals from engaging in evasion in fear of the social sanctions imposed once discovered and revealed publicly. Theoretical research on herd behavior in economic situations (Banerjee 1992; Sah 1991) also indicates that social influences may affect compliance, in particular by affecting the perceived probability of detection. One of the most consistent findings about taxpayer attitudes and behavior in Western countries is that those who report compliance believe that their peers and friends (and taxpayers in general) comply, whereas those who report cheating believe that others cheat (Yankelovich  et   al.  1984). Evidence suggests that perceptions about the honesty of others o thers may affect compliance behavior. Comparative treatment  

The comparative treatment model is based on equity theory and posits that addressing inequities in the exchange relationship between government and taxpayers would result in improved compliance (McKerchar and Evans 2009). Citizens may not consider their relationship with the state in a vacuum where both parties are the only actors. Likewise, they may not think about their fellow citizens without considering their own relationship with the state. They may also consider how the state treats them relative to their fellow citizens. This judgment is likely to affect not only their judgment of the state, but also how they view their fellow citizens (D'Arcy 2011: 7). If the state treats certain groups preferentially, this may color the citizen’s relationship with the state and the group receiving favors. A crucial variable is then not just what a person gets relative fromtothethose state,who but what are inthetheperson person’s getswider from the national state (and community. how the state This social treats the psychology person) model highlights the importance of equity theory in the study of compliance and taxpayer behavior. Political  legitimacy  

Finally, according to the political legitimacy theory, tax compliance is influenced by the extent that citizens trust their government (Tayler 2006; Kirchler et  al. 2008; Fauvelle‐Aymar 1999). Legitimacy could be described as belief or trust in the authorities, institutions, and social arrangements to be appropriate, proper, just and work for the common good. Political scientists have addressed how political legitimacy and civic identification are fostered. (Persson 2008) argues that African countries that upon independence emphasized building national over ethnic identity have been more successful than those who allowed ethnicity to become the main animus of politics. 4 

 

In the following empirical analysis we will examine the extent to which the different theories of taxpayer compliance contribute to explaining people’s attitude towards taxation in the selected African countries. 3. 

Data and descriptive analysis 

The main source of data for the analysis is the 5th round of Afrobarometer survey collected in 2011‐2012. The survey collects data on public attitudes on democracy, governance, markets, taxation and civil society, in more than 20 African countries. The questionnaire also includes a series of questions about tax, derived from the theories outlined in the previous section. Most of these questions are new and not included in the previous rounds of Afrobarometer. Because the questionnaires are similar across countries, the data allows a comprehensive empirical analysis of taxation theory in African societies and for testing the relevance of the various theories about taxpayer compliance. Nationally representative samples of individuals who are more than 18 years old are selected both in rural and urban areas of the different countries. 2399 randomly selected individuals were interviewed from 8 and 9 districts in Kenya and South Africa each, respectively. In Tanzania and Uganda, the sample size is 2400 in each countries and the respective number of districts is 26 and 5. Kenya, Tanzania and Uganda were chosen for this study because they are situated in the same 4

geographic and region and areinallattitudes members of thetaxation East African (EAC).could  Looking similarities disparities towards in theseCommunity three countries provideat useful information about where they can make a collective effort to improve tax compliance and where country specific policies are needed. South Africa makes an interesting comparison because it has a more developed and extensive tax system as well as significantly higher GNI per capita than the East‐African countries (see Table 1). As depicted in Table 1, there are also institutional and structural differences between between the four countries. Though South Africa is rated as the richest and most democratic country, it is also the most income unequal. Kenya has the second highest GNI per capita, but scores second worst in terms of democracy and inequality, while Tanzania is the second most democratic and has the lowest inequality. Uganda has the lowest GNI per capita, scores second best on inequality and second worst on the democracy index. [Table 1 here] 

Whit tax revenues accounting for 29% of GDP, South Africa has the highest tax to GDP ratio of the four countries. Since the abolishment of apartheid in 1994, the country has gone through major tax reforms (OECD‐DAC 2012). The ratio of tax to GDP rose from 25% in 2004 to 29% in 2010. Although tax avoidance and evasion are still considered to be major challenges, the implementation of popular taxpayer outreach and education programs by the South African Revenue Service (SARS), combined with new enforcement techniques, have led to t o improvements in public attitudes to the importance of paying taxes (OECD‐DAC 2012: 31; SARS 2011). Kenya has the second largest share of collected tax revenues with 19.5% of GDP. Although this is relatively high compared to many other African countries (World Bank 2012), the tax burden is unevenly distributed, leaving a large fraction of the economy untaxed (Waris et  al. 2009). 4

 We do not have access to data from the two other members of EAC, Burundi and Rwanda. 5 

 

Large efforts to improve taxpayer compliance have been made by Tanzania Revenue Authority in recent years. Despite this, the country comes third with a tax to GDP‐ratio of 14% in 2010. Tax evasion is a major challenge and coarse estimates suggest that loss in tax revenue due to tax evasion amounted to one sixth of the entire Tanzanian budget in the fiscal year 2009/10. As a result, the country remains heavily dependent on aid which, according to the African Development Bank, accounts for about 34% of the government’s budget (AfDB 2010a) . With 12% studied countries. of GDPWhile accruing the from tax share tax revenue, is almost Uganda doubled has fromthe1991/92 lowest when tax totheGDP‐ratio ratio wasofonly the 6.7%, the growth in tax t ax revenue collection has been slow the last decade (AfDB 2010b). 3.2 Measuring tax compliance attitude 

In the questionnaire, respondents were asked directly if they have refused to pay taxes or fees that they owed to the government during the last year. However, studies show that individuals tend to answer untruthfully when asked questions about sensitive issues such as their own tax payment. Tax compliance is therefore likely to be over‐reported in survey data using such measures. While some authors argue that obtaining reliable quantitative information about tax compliance behavior is practically impossible, others (Kaufmann (1997) and Reinikka and Svensson (2006)) maintain that application of appropriate survey methods and interview techniques comes a long way in solving the problem. Following the works of Reinikka and Svensson (2006)inonorder theirtowork corruption, we useofan“wrongdoing” indirectly phrased to capture tax compliance avoidondirect implication implication by the question respondent. In the questionnaire, respondents were asked to state their opinion about other people who do not pay taxes that they owe on their income. They were asked to state whether they think the action of other people who do not pay taxes on their income is “not wrong at all”, “wrong but understandable” or “wrong and punishable”. Based on these responses, individuals are considered as having a tax compliant attitude if their response is “wrong and punishable’’ and non‐compliant attitude if their response is either “not wrong at all” or “wrong but understandable”. Figure 1 shows the share of respondents with tax compliant attitudes against the natural logarithm of GNI per capita in the four countries together with Benin, Ghana, Malawi and Zimbabwe. The figure depicts that there is positive correlation between GNI per capita and share of individuals with tax‐compliant attitude, with relatively richer countries having a higher share. Figure 2 is equivalent to figure 1, but without the outlier, South Africa, which has a much higher GNI per capita than the other countries. [Figure 1 here]  [Figure   2 2 here] 

Table 2 further shows the share of respondents with compliant and non‐compliant attitudes across different socioeconomic indicators. The first row shows the share of respondents with a compliant and non‐compliant tax attitude in the countries of investigation. investigation. In both South Africa and Kenya, more than 50% of the respondents have a tax compliant attitude. In Tanzania and Uganda, on the other hand, the majority have a non‐compliant attitude and 54% of the respondents many as 68% of the Ugandans think that not paying taxes is “not wrong atinall”Tanzania, or “wrong,andbutasunderstandable”. 6 

 

[Table 1 here] 

Gender, employment statuses and urban location are measured in percentages, while age is measured in mean years. Level of schooling is measured by a range variable where 0= “no formal schooling” and 9= “postgraduate qualifications”, and wealth is measured by a composite variable consisting of ownership of radio, TV, car, water, latrine and roof material (0=respondent has none of the items, 1=respondent has all items). The only finding consistent in all four with a compliant countriestax is the attitude. tendency In alltowards countries a higher exceptmean Uganda, levelweofalso schooling find thatamong respondents respondents with a compliant tax attitude are older, relatively wealthier and to a larger degree live in urban areas than individuals with a non‐compliant attitude. In the questionnaire, respondents are also asked what they think is the main reason that some people evade taxes. As can be seen in Table 3, in all the four countries, “taxes are too high” and “taxes are unaffordable” are the most frequently stated reasons, the former ranging from 22% in South Africa to 28% in Uganda and the latter from 25% in Tanzania to 29% in Uganda. This indicates that tax rates are perceived as too high both in terms of what respondents can afford and in terms of what is reasonable. Another frequently mentioned reason is “poor public services”. In Tanzania as many as 16% of the respondents consider poor public services to be the main reason why some people evade taxes. The corresponding percentages are 12%, 11% and 9% in South waste/steal taxes”Africa, are also Uganda givenand as main Kenya,reasons respectively. why people “Unfairavoid tax system” taxes by and more“government than 8% of the respondents in all the countries. Very few respondents, 1% in South Africa and Uganda and 2% in Kenya and Tanzania, state “people know they won’t get caught”. [Table 3 here]  4. 

Correlates  of   factors  affecting  tax  compliance  attitude:  regression  model  and  variables 

In this section, we will look at factors that are correlated with tax compliance attitude in Kenya, Tanzania, Uganda and South Africa. We will specifically examine the extent to which the different theories of taxpayer compliance briefly outlined in section 2 contribute to explaining people’s attitude towards taxation. In order to capture factors that correlate with tax compliance attitude, we estimate the following logit model. (1)  __              __  is the dependent variable which is a dummy with a value of 1 for tax‐ compliant attitude and a value of 0 for non‐compliant attitude as measured in section 2 above.   is a vector for individual level characteristics; age, sex, education, employment status, wealth, ethnicity of the respondent and whether the individual is urban/rural resident;  is a vector for variables that capture different factors affecting tax compliance attitude;   is a vector for variables capturing regional fixed effects. The  ’s are the respective coefficients and   is the error term. The variables used to examine the different theories of tax compliance are described below.

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Economic deterrence 

As a measure of economic deterrence, we use a rank variable based on individuals’ responses to the question “Based on your experience, how easy or difficult is it to avoid paying the income or property taxes that you owe to the government?”. The variable ranges from 1=“very easy” to 4=“very difficult”. Fiscal  exchange 

A handful of variables government’s provisionareofincluded differentin goods the regression and services to capture that citizens respondent’s prefersatisfaction and that with may motivate compliance attitude. These include satisfaction with i) government’s provision of basic health services and addressing educational needs; ii) infrastructure (government provision of water and sanitation services, maintaining roads and bridges, and provision of reliable supply of electricity); and iii) government’s handling of crime, conflict and corruption. In addition to these variables, we also control for overall satisfaction with ease of getting basic services from the government such as issuing identity card, household services and police services. These variables all range from 1=“very badly” to 4=“very well”. Non‐state actors as service  providers  providers 

Non‐state actors such as powerful people or groups other than the government may provide basic infrastructure to citizens when governments become weak and fragile (Sacks 2012). This in turn maytoaffect payments non‐state the tax actors compliant in exchange attitude for ofprotecting individuals, them, especially their business if individuals and property. are making The role of non‐state actors like donors and NGO’s in providing basic infrastructure and how that in turn affects tax attitudes is explored in previous research (Fjeldstad 2001; Sacks 2012). However, the provision of public services by criminal organizations and gangs and its relation to tax compliance attitude has, to our knowledge, not been studied.5 In this paper, we include a variable that captures tax to non‐state actors, particularly to criminal organizations and gangs. The variable is measured by how often individuals make a payment to powerful people or groups other than the government, such as criminals or gangs in their community in return for protecting them, their property or their businesses. The variable ranges from 1= “never made payment”; 2= “only once”; 3= “a few times; and 4= “often”. Political  legitimacy  

Wetax useofficials, range ofoverall variables variables to capture politicalwith legitimacy such such and as trust in tax officials, corruption of level of satisfaction politicians, individual’s perception about their country’s level of democracy. Trust in tax officials is measured as a rank response for the extent of trust that individuals have in tax officials. The variable ranges from 1= “no trust at all” to 5= “trust a lot”. Corruption is captured by individuals’ response to how many tax officials they think are involved in corruption. The variable ranges from 1= “none of them” to 5= “all of them”. Overall satisfaction with politicians is captured as a rank response on individual’s opinion whether they approve or disapprove of the way the president, member of parliaments, the 5

 There is a large literature on how ‘protection’ or ‘security’ money can be extorted in the classical, well-known mafia style, where organised criminals use insecurity, harassment and intimidation to extort money from individual citizens, private businesses and public officials (Gambetta, 1993; Grossman, 1995). However, this literature does not address how these practises may impact on tax compliance.

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premium of the provinces and elected local officials performed their job in the past 12 months. The responses range from 1= “strongly disapprove” to 4= “strongly approve”. Based on these responses, factor analysis is made in order to have on indicator for individual’s satisfaction with politicians. Democracy is captured as a rank response on individual’s opinion on how much of a democracy their country is. The response ranges from 1= “no democracy” to 5= “a full democracy”.  

 

Social  influence

To measure the influence of other people’s behavior on tax compliance attitude, we use a dummy that has a value of 1 if individuals think that other people avoid taxed and 0 otherwise. Comparative treatment  

In order to capture inequities in the exchange relationship between government and taxpayers, we use a variable that is measured as a rank response on how often individuals believe that their own ethnic group is treated unfairly by the government. The variable ranges from 1= “never” to 4= “always”. Knowledge about  taxes 

In addition to the above stated factors, the knowledge base of individuals regarding the types of taxes to pay may also matter in affecting compliance attitude. We therefore control for tax knowledge, which is measured as a rank response for the extent of difficulty to know the type of taxes to pay. The response ranges from 1=very 1=v ery easy to 4=very difficult. 4.1 Results 

Results in table 4 show the marginal effects of the logit regression for the four countries. The standard errors are presented in brackets and are clustered at the district level. Table 5 further shows the Wald‐test for the fit of the logit model of the four countries. As can be seen in table 5, the null hypothesis that all the regressing coefficients are jointly zero is rejected at 1% level of significance. This implies that the variables included in the regression create a statistically significant improvement in the fit of the model for all the countries. [Table 4 here] 

Although there are some similarities in factors that are correlated with tax compliant attitude across the four countries, there are also differences. While employed people in Uganda are 7% more likely to have tax compliant attitude, we find the opposite effect in Kenya by almost the same percent. More years of schooling is found to increase the probability of having a tax compliant attitude by about 3% both in Kenya and Tanzania. We do not find significant variation in tax compliant attitude between male and female, with increased age or wealth of individuals in any of the four countries. An increase in the perception of individuals about the difficulty of evading taxes of one unit increases the likelihood of tax compliant attitude by 5% and 8% in Kenya and South Africa, respectively. This gives suggestive evidence for the economic deterrence theory, which posits that the perception of increased enforcement that makes more evasion difficult will increase tax compliance attitude at least in Kenya and [Table South  Africa. 5  here]  9 

 

In Kenya, individuals who are more satisfied with government provision of infrastructure such as roads and electricity are more likely to have tax compliant attitude by about 10%. In Uganda and Tanzania, individuals who are more satisfied with the government’s provision of basic health services and educational needs are more likely to have compliant attitude by 8% and 10%, respectively. In addition to basic health services and education, satisfaction with government’s handling of crime, conflict and corruption increases the likelihood of having a compliant attitude in Uganda with 7%. In South Africa, individuals who are more satisfied with the ease ofservices gettingand various the likely government as issuing attitude of identity card, household policeservices servicesfrom are more to havesuch a tax‐compliant by about 8%. The different results from the four countries suggest that government expenditures may motivate compliance and that governments can increase compliance by providing goods that citizens prefer in a more efficient and accessible manner (Cowell and Gordon 1988; Levi 1988; Tilly 1992; Moore 2004). Frequent payment to non‐state actors such as criminals and gangs reduces the likelihood of having a tax compliant compliant attitude in all the four countries. The effect ranges from a decline in compliant attitude from 6% in Kenya, to 8% in Uganda and South Africa and as high as 12% in Tanzania. We do not find strong evidence on political legitimacy except for a few variables in South Africa and Tanzania. attitude by 5%Corruption in South Africa. of tax Inofficials Tanzania, is found increased to reduce level the of satisfaction likelihood ofwithtaxthe compliant overall performance of politicians is found to increase the likelihood of tax compliant attitude by 3%. The extent to which individuals think that their own ethnic group is treated unfairly compared to others is also significantly correlated with compliant attitude in Tanzania and South Africa. As the extent to which individuals think that their own ethnic group is treated unfairly increases by one point, the probability of having a tax compliant attitude decreases by 5% and 4% in Tanzania and South Africa, respectively. This may provide indication towards the comparative treatment model, which is based on equity theory and posits that addressing inequities in the exchange relationship between government and taxpayers matters for tax compliance (Persson, 2008; Rothstein 2003). Tax knowledge is significantly correlated with tax compliant attitude in Tanzania and South Africa. An increase in the extent of difficulty to know the type of taxes to pay by one point reduces the probability of tax compliance attitude by 4% and 10% in Tanzania and South Africa respectively. This is equivalent to reducing the current share of people with tax compliant attitude, which is 54% in Tanzania and 57% in South Africa, to close to 51% in both countries due to lack of appropriate tax knowledge. 5. 

Robustness check  

In our previous measure of tax compliance attitude, we use a dummy variable where we categorize individuals who responded that not paying tax is “not wrong” and “wrong, but understandable” as having a non‐compliant attitude. However, it could also be the case that individuals who responded that not paying tax is “wrong and understandable” have a compliant attitude. In this section we conduct a robustness check where we include all the three responses: “not wrong at all”, “wrong, but understandable” and “wrong and punishable” in a regression. Given the ordinal nature of the responses, we use ordered logit model. 10 

 

We re‐formulate the econometric model in equation (1) as follows. The dependent variable (__ ) in equation (2) is an ordered categorical variable which ranges from 1 to 3 (1=not wrong at all, 2=wrong but understandable, and 3=wrong and punishable). We assume that there is a latent variable __∗  given by the following expression; __∗             (2)   is a random, normally distributed, variable, the link between the observed and Assuming that  the latent variable is given by;

     1|   Ф         2|   Ф     Ф         3|   1  Ф   , where Ф is a cumulative normal distribution function of   ,   , , , are the coefficients of the explanatory variables in equation 2, and   and  are the unknown threshold parameters that differentiate the categories. The model is estimated by maximum likelihood for each country. 5.1 Results 

Table 6 shows the marginal effects of the ordered logit regression for the three responses of the four countries. Most of our results are consistent with the findings of the binary logit regression presented in table 5. However, we find even stronger evidence for the economic deterrence theory for all the four countries in the regression. An increase in the perception of individuals about the difficulty of evading taxes by one point increases the likelihood of responding “wrong not to pay taxes” by 4% in Kenya, 5% in Uganda, 6% in Tanzania and 7% in South Africa. On the other hand, an increase in difficulty of evasion reduces the likelihood of responding “wrong but understandable” and “not wrong at all” in all the four f our countries. Similar to findings in the logit regression, in Tanzania and Uganda Uganda individuals who are more satisfiedarewith needs morethelikely government’s to respondprovision “wrong not of basic to payhealth taxes”,services and areand alsoaddressing less likelyeducational to respond “wrong but understandable” and “not wrong at all”. In Uganda, satisfaction with government’s handling of crime, conflict and corruption is more likely to make individuals respond “wrong not to pay taxes”, and less likely to respond “wrong but understandable” and “not wrong at all”. Again, similar to the findings in the logit regression, respondents in Kenya who are more satisfied with government handling of infrastructure such as roads and electricity are more likely to respond “wrong not to pay taxes” and less likely to respond “wrong and understandable” and “not wrong at all”. In South Africa, satisfaction with government provision of basic services such as issuing identity card, household services and police services make people more likely to respond that “wrong not to pay taxes” and less likely to respond “wrong and understandable” and “not wrong at all”.    

[Table 6 here]

 

11 

 

Consistent results are also found with non‐state actors as in the logit regression. Individuals who make frequent payment to non‐state actors such as criminals and gangs are less likely to respond “wrong not to pay taxes” and more likely to respond “wrong and understandable” and “not wrong at all”. In the ordered logit regression, we do not find much evidence on political legitimacy except for corruption in South Africa, which depicts similar results as in the logit regression. Individuals who think more likelythat to respond tax officials “wrong areand corrupt understandable” are less likely andto“not respond wrong“wrong at all”. not to pay taxes” and Knowledge about tax is still important and an increase in the extent of difficulty to know the type of taxes to pay reduces the likelihood of individuals to respond “wrong not to pay taxes” and increases the likelihood to respond “wrong and understandable” and “not wrong at all” in South Africa, Kenya and Tanzania, although the latter is significant only at 10%. 6. 

Conclusion 

In this paper, we explore factors that determine citizens’ tax compliance behavior in Kenya, Tanzania, Uganda and South Africa using attitude and perception data from the new round 5 of Afrobarometer surveys. The survey includes a series of theoretically rooted questions about citizens’ views about taxation. A main challenge was to find an accurate proxy for taxpayer compliance since individual’s reportingonof respondent’s own compliance is likelyabout to beother over‐reported. Thus weof used an indirectly phrased question opinion people’s action whether not paying taxes is wrong or o r not. Results from the logit regression provide robust results for two determinants of tax compliance. We find that individuals are more likely to express tax compliant attitude if they perceive that enforcement makes evasion more difficult in South Africa and Kenya. This is in line with the prescription of the standard economic theory of deterrence. The analysis also finds evidence that those who are more satisfied with public service provision are more likely to support the government’s right to tax in all the four countries, supporting certain elements of the fiscal exchange theory. However, the link between tax compliance attitude and public service provision depends on the specific service in question and differs between countries. While access to infrastructure such as roads and electricity encourage tax compliant attitude in Kenya, respondents in Tanzania and Uganda refer to education and health services as key to their tax compliance. In South Africa, government provision of issuing identity cards and police services are more likely to support tax compliant attitude. A key finding of the study that applies to all the selected countries is that payment to non‐state actors such as criminal gangs for protection reduces tax compliant attitude. Previous research suggests that the way the state treats individuals or groups relative to their fellow citizens is an important factor in determining taxpayer compliance compliance attitude (D’Arcy 2011). We have tested this hypothesis by examining how citizens’ perceive their ethnic group is treated by the government compared to other groups. Only in South Africa and Tanzania this seems to matter for tax compliant attitude. The study finds no strong evidence that political legitimacy, e.g. trust in government policy and institutions, impacts on taxpayers’ compliance attitude. These findings are robust for a different econometric estimation, where we include all the responses of individuals regarding other people’s action about tax t ax in an ordered logit regression. 12 

 

The study provides us with some directions for further research. For an improved understanding of tax compliance attitude and behavior in Africa, there is a need for a more thorough examination of the concept of fairness in fiscal exchange, i.e., the contractual relationship between taxpayers and the government. In this context it is also relevant to analyze if – and when – user charges are to be preferred instead of general taxes to finance public services. Critical factors in this respect are citizens' perceptions about the role of the state, how the tax law is administrated, perceptions about enforcement, government trustworthiness, and impacts payments to non‐state actors maycollection have onand taxcomparative compliance. treatments Furthermore, there is a need for ofresearch focusing on fairness i n tax in of taxpayers. Can, and under what conditions, compliance be established in African countries without an extensive and costly enforcement apparatus? This question is important because it is likely that governments, seeking power on the basis of popular consent, face restrictions in their use of coercion in tax collection. Thus, the challenge for taxation in Africa is to raise domestic revenues from consenting citizens.

13 

 

References 

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Drummond, Daal, N.norms Srivastava Oliveira 2012.IMF  Mobilizing revenue in sub‐Saharan Africa:P., W. empicial and &keyL. E.determinants.   Working  Paper   WP/12/108.  .  Washington DC.: International Monetary Fund. Economist Intelligence Unit 2011. Democracy index 2011: Democracy under stress. Fauvelle‐Aymar, C. 1999. The political and tax capacity of government in developing countries. Kyklos, 52, 391‐413. Fjeldstad, O.‐H. 2001. Taxation, coercion and donors. Local government tax enforcement in Tanzania. The  Journal   Journal  of  Modern  African  African Studies, 39, 289‐306. Fjeldstad, O.‐H. & J. Semboja 2001. Why people pay taxes: The case of the development levy in Tanzania. World  Development, 29, 2059‐2074. Fuest, C. & N. Riedel 2009. Tax evasion, tax avoidance and tax expenditures in developing countries: A review of the literature. Report    prepared    for   the  UK   Department    for   International  Development. Oxford: Oxford University Centre for Business and Taxation. IMF 2011. Revenue mobilization in developing countries. Policy   Paper   prepared   by   the  Fiscal    Affairs Department  (8 March). Washington D.C.: International Monetary Fund. Kaufmann, D. 1997. Corruption: Some myths and facts. Foreign Policy , 114‐131. Kirchler, E., E. Hoelzl & I. Wahl 2008. Enforced versus voluntary tax compliance: The “slippery slope” framework. Journal  of  Economic Psychology, 29, 210‐225. Levi, M. 1988. Of  rule and  revenue, Berkeley: University of California Press. McKerchar, M. & C. Evans 2009. Sustaining growth in developing economies through improved taxpayer compliance: Challenges for policy makers and revenue authorities. eJournal  of   Tax  Research, 7, 171‐201. Moore, M. 1998. Death without taxes: Democracy, state capacity, and aid dependence in the fourth world. In: White, G. & Robinson, M. (eds.) Towards  a  democratic  developmental   state. Oxford: Oxford University Press. Moore, M. 2004. Revenues, state formation, and the quality of governance in developing countries. International  Political  Science Review, 25, 297‐319. OECD‐DAC 2012. Tax and development. Aid modalities for strengthening tax systems. Paris: institutional  statehood    sources  of   and   ‐  Assimilation,   multiculturalism  and   Persson,Organisation A. 2008. The for  Economic Co‐Operation Development (August). taxation in Sub‐Saharan  Africa  Africa Doctoral Thesis, Gothenburg University. 14 

 

Reinikka, R. & J. Svensson 2006. Using micro‐surveys to measure and explain corruption. World   Development, 34, 359‐370. Richupan, S. 1987. Determinants of income tax evasion: Role of tax rates, shape of tax schedules and other factors. In: Gandhi, V. P. (ed.). International Monetary Fund. Sacks, A. 2012. Can donors and non‐state actors undermine citizens' legitimating beliefs? World   Bank  Policy  Research Working Paper  No. 6158. World Bank. Sah, R. K. 1991. Social osmosis and patterns of crime.  Journal   of   Political   Economy,  99,  1272‐ 1295.     National  Tax   Journal, 58 , 643‐ Sandmo,633. A. 2005. The theory of tax evasion: A retrospective view. SARS 2011. SARS’s core outcomes and its philosophy on taxpayer and trader compliance Leaflet   based  on SARS  Strategic Plan  2011/12  2011/12‐ 2013/14. Pretoria: South African Revenue Services Slemrod, J. 1992. Why people pay taxes: tax compliance and enforcement. In: Slemrod, J. (ed.). Ann Arbor: The University of Michigan Press. Snavely, K. 1990. Governmental policies to reduce tax evasion: coerced behavior versus services and values development. Policy  Sciences, 23, 57‐72. Tayler, T. R. 2006. Psychological perspectives on legitimacy and legitimation.  Annual  Review  of   Psychology, 57, 375‐400. Tilly, C. 1992. Coercion,  capital   and   European  states:   AD  990‐1992,  Malden, Massachusetts: Blackwell Publishers Inc. Waris, A., M. Kohonen, J. Ranguma & A. Mosioma 2009. Taxation and statebuilding in Kenya: Enhancing revenue capacity to advance human welfare. Kenya  Report.  Tax Justice Network for Africa. World  Development  Indicators  2011, Washington D.C.: World Bank. World Bank Bank 2012. 2011. World  World  Development  Indicators  2012,  2012, Washington, D.C.: The World Bank. Yankelovich, Skelly & White 1984. Taxpayer attitudes study: Final report. Public opinion survey    prepared   for   the  Internal   Revenue  Services.  Washington, DC: Internal Revenue Service, U.S. Department of the Treasury.

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Tables 

Table 1: Macroeconomic indicators In Indi dica cato tor6 r6 So Sout uthh Afri Africa ca Keny Kenyaa Population (million) GNI per capita (current USD) Tax revenue of GDP (%) Urban population (% of total) Gini index Democracy index8, 2011

50 6 090 29 62 0.63 7.8

Tan anzzan aniaia

Uga Ugand ndaa

SSA SSA

45 530 14 26 0.38 5.6

33 500 12 13 0.0.44 5.1

88440 1 127 187 37 … 4.3

41 790 19.5 22 0.0.48 4.7

Table 2: Differences in background variables between respondents with tax compliant and non‐ compliant attitude South Africa

  Total Male Employed Self‐ employed Urban ALevel ge (mofean) schooling (mean) Wealth

Kenya

Tanzania

Uganda

Non‐ Compliant Non‐ Compliant Non‐ Compliant Non‐ compliant compliant compliant complian Compliant attitude attitude attitude attitude attitude attitude t attitude attitude

43 % 50 % 35 %

57 % 50 % 39 %

46 % 47 % 47 %

54 % 53 % 45 %

54 % 51 % 39 %

47 % 51 % 34 %

68 % 52 % 48 %

32 % 49 % 51 %

15 %

13 %

68 %

65 %

52 %

55 %

83 %

77 %

68 %

69 %

38 %

40 %

30 %

35 %

16 %

13 %

37.7 4.2

40.5 4.4

35.4 3.8

36.2 4.1

38.1 2.9

39.1 3.2

35.4 3.3

34.4 3.4

0.58

0.65

0.49

0.54

0.39

0.41

0.21

0.20

 

6

 All numbers are from World Development Indicators 2012 (World Bank 2012) unless else is specified

7

 World Development Indicators 2011 (World Bank 2011)

8

 Economist Intelligence Unit (EIU) democracy index 2011, 0 = authoritarian regime and 10= full democracy (EIU 2011: 30) 16 

 

Table 3: Reasons why some people evade taxes, % South Africa Kenya Tanzania Uganda Unfair tax system 8 8 11 11 Taxes are too high 22 23 25 28 Taxes are unaffordable 27 26 25 29 Poor public services 12 9 16 11 The government waste / steal taxes 11 10 9 8 People know they won't get caught 1 2 2 1 Other 20 23 12 12 Total 100 100 100 100 Table 4: Wald test for binary logit regressions   South Africa Keny Kenyaa Tanzania Tanzania Ugand Ugandaa Chi2 578 542 610 1348 Degrees of freedom 34 33 52 31 Prob > chi2 = 0.00 0.00 0.00 0.00  

17 

 

Table 5: Binary logistic regressions with marginal effects South Africa Individual  characteristics 

Kenya

Tanzania Uganda

Age

‐0.00 (0.01)

0.00 (0.01)

0.01* (0.01)

0.00 (0.01)

Age2 Male (d)

0.00 (0.00) 0.02 (0.03) ‐0.01 (0.04) 0.02 (0.04) 0.00 (0.01) 0.07 (0.05) ‐0.02 (0.04) 0.08*** (0.03)

0.00 (0.00) 0.01 (0.03) ‐0.01 (0.04) ‐0.08** (0.04) 0.03** (0.01) 0.10 (0.06) ‐0.04 (0.04) 0.05** (0.02)

‐0.00 (0.00) ‐0.03 (0.02) ‐0.00 (0.03) ‐0.05 (0.03) 0.03** (0.01) 0.03 (0.08) ‐0.02 (0.04) 0.04 (0.03)

‐0.00 (0.00) ‐0.02 (0.03) ‐0.08 (0.07) 0.07** (0.04) ‐0.01 (0.01) 0.08 (0.08) ‐0.06 (0.06) 0.03 (0.02)

0.00 (0.03) 0.00 (0.04) 0.04 (0.04) 0.08***

‐0.01 (0.03) 0.09*** (0.03) ‐0.03 (0.03) ‐0.03

0.10*** (0.02) ‐0.00 (0.03) 0.01 (0.03) ‐0.01

0.08*** (0.02) 0.01 (0.03) 0.07** (0.03) 0.01

(0.02) ‐0.05 (0.03)

(0.03) 0.01 (0.04)

(0.03) ‐0.09*** (0.03)

(0.02) 0.02 (0.04)

‐0.04* (0.02)

‐0.02 (0.01)

‐0.05** (0.02)

0.03 (0.03)

0.01 (0.02) ‐0.05*** (0.01) ‐0.01 (0.02) ‐0.02

0.02 (0.02) 0.02 (0.02) 0.01 (0.02) 0.02

‐0.01 (0.01) 0.00 (0.01) 0.03* (0.02) 0.01

‐0.01 (0.01) ‐0.02 (0.02) 0.01 (0.03) 0.00

Self‐employed (d) Employed (d) Schooling Wealth Urban (d) Economic  deterrence 

Difficulty of evading tax Fiscal  exchange 

Health and education Infrastructure Crime, conflict and corruption Basic services from the government  Social  influence 

Perceived compliance of others

Comparative treatment  

Unfair treatment of own ethnic group Political  legitimacy  

Trust

Corruption Satisfaction with politicians Democracy

18 

 

Non‐ state actors 

Payments to non‐state actors Knowledge about  taxes 

Difficulty finding out what taxes to pay

Value added tax Region fixed effects Ethnicity fixed effects Religion fixed effects Number of observations Pseudo R2

(0.02)

(0.02)

(0.01)

(0.02)

‐0.08** (0.04)

‐0.06** (0.03)

‐0.12*** (0.04)

‐0.08** (0.04)

‐0.10*** (0.03) 0.19*** (0.05) Yes Yes Yes 1308 0.12

‐0.03 (0.02) 0.30*** (0.05) Yes Yes Yes 1452 0.13

‐0.04** (0.02) 0.17*** (0.04) Yes Yes Yes 1900 0.12

0.00 (0.02) 0.17*** (0.04) Yes Yes Yes 1410 0.10

19 

 

Table 6 : Ordered logistic regressions with marginal effects South  Africa  Africa

Wrong

  Individual fixed effects

 

Kenya

Wrong, but Not Wrong, but Not understand wrong Wrong understand wrong able able Yes

Yes 

Wrong, but Not Wrong understan wrong dable

Wrong, but Not Wrong understand wrong able

Yes

Yes

Yes

0.007* 7** (0.03)

‐0 ‐0..06 06** ** (0.02)

‐0 ‐0..01 01** ** 0.05 0.05**** ‐0 ‐0..04 04**** (0.00) (0.02) (0.01)

‐0 ‐0.0 .01* 1*** 0.06* 0 6*** ‐0.0 ‐0.03* 3**** (0.01) (0.02) (0.01)

Health and education

‐0.01 (0.03)

0.01 (0.02)

0.00 (0.00)

0.01 (0.03)

‐0.01 (0.02)

‐0.00 (0.01)

Infrastructure

0.01 (0.04)

‐0.01 (0.03)

‐0.00 0.09*** (0.01) (0.03)

‐0.06*** (0.02)

‐0.02*** ‐0.00 (0.01) (0.03)

Crime, conflict and corruption

0.03

‐0.02

‐0.00

Yes

Yes

Yes

Yes 

‐0.0 ‐0.03* 3*** ** 0.05* 0 5** (0.01) (0.03)

‐0. ‐0.02** 02** (0.01)

‐0.0 ‐0.03* 3* (0.02)

‐0.04*** 0.07*** (0.01) (0.02)

‐0.03*** ‐‐00.04*** (0.01) (0.01)

0.00 (0.01)

0.00 (0.01)

0.01 (0.02)

‐0.01 (0.01)

‐0.01 (0.01)

 

Di Difffficicul ulty ty of evad evadiing tax Fiscal  exchange

Yes

Uganda

Yes 

Economic  deterrence

Yes

Tanzania

 

(0.04) 0.08*** (0.02)

Basic services

0.08*** ‐0.04*** (0.02) (0.01)

‐0.02

0.01

0.01

‐0.02

0.01

0.01

0.08**

‐0.04**

‐0.05**

(0.03) (0.01) (0.03) ‐0.07*** ‐0.01*** ‐0.04 (0.02) (0.00) (0.03)

(0.02) 0.03 (0.02)

(0.01) 0.01 (0.01)

(0.03) 0.02 (0.03)

(0.01) ‐0.01 (0.01)

(0.01) ‐0.01 (0.01)

(0.03) ‐0.02 (0.02)

(0.02) 0.01 (0.01)

(0.02) 0.01 (0.01) 20 

 

 Social  influence

 

Compliance of others

‐0.05 (0.03)

0.04 (0.03)

0.01 (0.01)

0.04 (0.04)

‐0.03 (0.03)

‐0.01 (0.01)

‐0.08** (0.03)

0.04** (0.02)

0.04** (0.02)

0.02 (0.04)

‐0.01 (0.02)

‐0.01 (0.02)

‐0.06**

0.05** 0.05**

0.01*

‐0.02

0.01

0.01

‐0.03

0.01

0.02

0.03

‐0.01

‐0 ‐0.01 .01

(0.03)

(0.02)

(0.00)

(0.01)

(0.01)

(0.00)

(0.02)

(0.01)

(0.01)

(0.02)

(0.01)

(0.01)

0.01 (0.02) ‐0.04*** (0.01)

‐0.01 (0.01) 0.04*** (0.01)

‐0.00 0.02 (0.00) (0.01) 0.01*** 0.01 (0.00) (0.02)

‐0.01 (0.01) ‐0.00 (0.01)

‐0.01 (0.00) ‐0.00 (0.01)

‐0.01 (0.01) 0.01 (0.01)

0.00 (0.01) ‐0.00 (0.01)

0.00 (0.01) ‐0.00 (0.01)

‐0.01* (0.01) ‐0.02 (0.02)

0.01 (0.00) 0.01 (0.01)

0.01 (0.00) 0.01 (0.01)

Satisfaction with politicians

0.01

‐0.01

‐0.00

0.01

‐0.01

‐0.00

0.02

‐0.01

‐0.01

0.01

‐0.00

‐0.00

Democracy

(0.02) ‐0.02 (0.01)

(0.02) 0.01 (0.01)

(0.00) 0.00 (0.00)

(0.01) 0.0.03 (0.02)

(0.01) ‐0.02 (0.02)

(0.00) ‐0.01 (0.01)

(0.02) 00..02 (0.01)

(0.01) ‐0.01 (0.01)

(0.01) ‐0.01 (0.01)

(0.03) ‐‐00.01 (0.02)

(0.01) 0.01 (0.01)

(0.02) 0.01 (0.01)

‐0.09***

0.08***

0.01*** ‐0.07**

0.05*

0.02** ‐0.12*** 0.06***

0.07*** ‐0.06**

0.02*

0.03**

Comparative  treatment  

Own ethnic group treated unfairly Political  lecitimacy 

 

Trust Corruption

Non‐ state actors

Payments to non‐state actors

 

21