Doctoral Dissertation
Essays on Tax Compliance in Indonesia

ENDRA IRAMAN

Graduate School for International Development and Cooperation
Hiroshima University

March 2022

Essays on Tax Compliance in Indonesia

D180565
ENDRA IRAMAN

A Dissertation Submitted to
the Graduate School for International Development and Cooperationof Hiroshima University in Partial Fulfillmentof the Requirements for the Degree ofDoctor of Philosophy
March 2022

ABSTRACT
There are two forms of tax compliance which are enforced compliance and voluntarycompliance. In enforced compliance, people are forced to comply with tax regulation by using
enforcement approaches from tax authorities. On the contrary, in voluntary tax compliance,
which is closely related to people’s willingness to pay taxes, people’s willingness to pay taxes
is closely related to their individual attributes, the provision of public goods and services, andgovernment strategies which mainly consist of deterrence and non-deterrence strategies.
Therefore, tax compliance literature mainly tries to explain the various pattern of tax noncompliance related to demographic characteristics of individuals and examines several factorsthat affect people’s willingness to pay taxes. The main objective of this study, thus, is to identify
the characteristics of taxpayers who engage in tax evasion (chapter 2), to explain the causal
effect of information on the types of public spending on people’s willingness to pay taxes(chapter 3) and the causal effect of government’s strategies on people’s tax-paying behaviors(chapter 4).
Chapter 2 aims to identify the patterns of non-compliance of the taxpayers who engage
in non-compliant behavior, which is crucial for tax authorities to determine appropriate taxation
schemes. Taxpayers have an incentive to conceal their actual income. Therefore, it is difficult
for tax authorities to uncover such behavior (social desirability bias). Our study mitigates thebias in responses to sensitive questions by employing the list experiment technique, whichallows us to identify the characteristics of taxpayers who engage in tax evasion. Using a dataset
obtained from a tax office in Jakarta, Indonesia, we conducted a computer-assisted telephoneinterviewing survey in 2019. Our results revealed that approximately 13 percent of the
taxpayers, old, male, had reported lower income than their actual income on their tax returns.
In addition, taxpayers who are old, male, corporate employees, and members of a particularethnic group tend to exhibit relatively low tax compliance. These findings suggest that ouriresearch design can be a useful tool for understanding tax evasion behavior and developing
more effective taxation schemes that promote tax compliance among taxpayers.
Chapter 3 investigates the effect of government spending on the willingness to pay taxes.
Governments coordinate people’s various interests through budget allocations for the provisionof public goods and services. To maintain the government’s budgetary power, it is vital tosecure revenues and increase people’s willingness to pay taxes. To understand whether
government measures exert any influence on the willingness of individual taxpayers to pay
taxes, we conducted a survey experiment that varied the information on the government’s fiscal
spending in a vignette experiment. Our results show that while providing information aboutpublic spending on healthcare and infrastructure development did not change the respondents’
willingness to pay taxes, emphasizing industrial subsidies reduced it significantly. Thesefindings imply that targeting specific groups without careful communication could weaken thereciprocal relationship between the government and the public, thus mitigating taxpayers’
cooperative behavior in terms of tax payment.
Chapter 4 examines the effect of various tax policy strategies to improve the likelihoodof taxpaying. It is important for the government to investigate particular strategies that
effectively increase people’s willingness to pay taxes. In the experiment, we design a novel
vignette experiment in which we provide different strategies (perceived audit probability,
reciprocity, and peer-effect) and a fictional subject’s characteristics (gender and ethnicity) toinfluence tax payment behaviors. The results indicate that perceived audit probability andpositive peer-effect information positively affect people’s tax payment behavior, while thenegative peer-effect and reciprocity information has a negative effect on people’s tax payment
behavior.

ii

ACKNOWLEDGEMENTS

This dissertation is available through great assistance, encouragement, and prayers from many
people. Thus, I would like to appreciate all this supports to the contributors.
First of all, I would like to express my sincere gratitude to my main supervisor Prof.
Makoto Kakinaka for the continuous support, advice, encouragement, and motivation
throughout my doctoral course at Hiroshima University. His guidance inspired me to complete
all the requirements for the degree of Doctor of Philosophy. I am also grateful to Prof.
Yoshikuni Ono for his helpful comments and suggestions during the research, particularly
related to the experiments in this dissertation. For my thesis committee, Prof. Masaru Ichihashi,
Prof. Singo Takahashi, and Prof. Daisaku Goto, I would like to thank them for their insightful
suggestions to enrich my research.
Secondly, I incredibly acknowledge the support from the Indonesian government
through Indonesia Endowment Fund for Education (LPDP) during my doctoral course.
For all my family, my wife, my daughter, my parents/parents-in-law, my brothers andsisters, I would like to appreciate their supports throughout the tough time of my study.
Lastly, I am indebted to the Ministry of Finance and Directorate General of Taxes whichallowed me to pursue a doctoral degree and several tax offices that helped me conduct
experiments. To my lab-mates in Kakinaka sensei’s lab, their supports are highly appreciated.

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Table of Contents

ABSTRACT……………………………….………………………………………………..

i

ACKNOWLEDGEMENTS ……………………………….………………………………

iii

Table of Contents ……………………………….………………………………………….. iv
List of Tables……………………………….…………………………………………… vi
List of Figures……………………………….………………………………………….. vii
Chapter 1 Introduction……………………………….……………………………………… 8
References……………………………….……………………………………………. .. 14
Chapter 2 Tax compliance and social desirability bias of taxpayers: Experimental evidence fromIndonesia ....…………………………….………………………………………………….. 17
2.1 Introduction……………………………….……………………………………….. 17
2.2 Taxpayers and their compliance behavior.………………………….……………… 19
2.3 Individual taxation in Indonesia……………………………….…………………… 23
2.4 Empirical analysis……………………………….…………………………………. 26
2.4.1 List experiment……………………………….………………………………... 26
2.4.2 Results……………………………….……………………………………….... 29
2.4.3 Multivariate analysis……………………………….………………………….

34

2.5 Conclusion……………………………….………………………………………... 38
References……………………………….…………………………………………….. 40
Appendix………………………………………………………………………………. 46
Chapter 3 When do people become more willing to pay taxes? The effects of government
spending information on the public’s willingness to pay taxes……………………………. 49
3.1 Introduction……………………………….……………………………………….. 49
3.2 The vignette experiment……………………………….…………………………… 53iv

3.3 Results and discussion……………………………….…………………………….. 58
3.4 Conclusion……………………………….………………………………………… 66
References……………………………….…………………………………………….. 69
Appendix………………………………………………………………………………. 73
Chapter 4 Which strategies promote attitudes toward income tax? Testing enforcement,
reciprocity, and peer-effect in the field ……………………………….…………………… 76
4.1 Introduction……………………………….……………………………………….. 76
4.2 Literature review……………………………….………………………………….

78

4.2.1 Deterrence approach……………………………….………………………….

78

4.2.2 Morale approach……………………………….……………………………… 79
4.3 Empirical analysis……………………………….………………………………… 81
4.3.1 Individual income tax……………………………….………………………… 81
4.3.2 The vignette experiment……………………………….……………………… 82
4.3.3 Results……………………………….………………………………………… 87
4.4 Conclusion……………………………….………………………………………… 90
References……………………………….…………………………………………….. 91
Appendix………………………………………………………………………………. 95
Chapter 5 Conclusion……………………………….……………………………………… 102v

List of Tables

Table 2.1 The Proportion of individual income tax to total income tax (billion rupiahs) …. 24
Table 2.2 Difference-in-means results by various sub-groups ……………………………

31

Table A2.1 Logit model test of balance in randomization ………………………………... 46
Table A2.2 Multivariate regression results (maximum likelihood constrained model) …... 47
Table 3.1 Balance test of randomization ………………………………………………….. 57
Table 3.2 Distribution of respondents and answers among groups ……………………….. 60
Table 3.3 The difference-in-means between the treatment groups and the control group … 62
Table 3.4 Regression results of the impact of treatments on people’s willingness to pay taxes……………………………………………………………………………………………… 64
Table A3.1 Ordered probit model …………………………………………………………. 74
Table A3.2 Multinomial logit model ……………………………………………………… 75
Table 4.1 Summary statistics ……………………………………………………………… 86
Table 4.2 OLS……………………………………………………… ……………………… 88
Table A4.1 Balance test of randomization - Gender and Ethnicity ………………………… 96
Table A4.2 Balance test of randomization – treatment groups vs control group …………... 97
Table A4.3 Balance test of randomization – between levels of the treatment groups …….. 98
Table A4.4 Robustnest check – Random Intercept model and Multi-level Ordered Logit
model ……………………………………………………………………………………… 100
Table A4.5 Full regression of the models in Table 4.2 and Table A4.4

vi………………… 100

List of Figures

Figure 2.1 Multivariate estimates of tax non-compliance ………………………………… 35
Figure A2.1 Percentage of respondents for each answer category in the list experiment … 48
Figure 3.1 Vignette example in the treatment group ……………………………………… 56
Figure A3.1 Difference-in-means across individual characteristics in industrial subsidy group……………………………………………………………………………………………… 73
Figure 4.1 The vignette's design ………………………………………………………….. 84
Figure A4.1 The effect of each treatment on the likelihood to pay tax …………………… 99

vii

Chapter 1
Introduction

There are three dimensions of tax compliance: timely filing, timely payment, and accurately
reporting (Slemrod et al., 2001). The first and second dimensions are related to formal complianceand the third dimension is related to material compliance. Within these dimensions, the literature
in tax compliance primarily aims to explain the pattern of tax non-compliance behaviors within
individuals and organizations and investigates strategies that effectively reduce tax-noncompliance and increase people’s willingness to pay taxes (Andreoni et al., 1998).
It is essential to acknowledge the different mechanisms which motivate the willingness to
pay taxes, tax compliance, and tax non-compliance. Therefore, tax compliance can bedifferentiated into enforced and voluntary compliance. In enforced compliance, people comply
with the tax regulations because the governments enforce the regulation by, for instance, tax
auditing. However, some studies examine that this approach alone is insufficient to improve tax
compliance (Kastlunger et al., 2010; Mittone et al., 2017). To overcome this issue, recent studies
find out that intrinsic motivation (tax morale) plays an essential role in shaping people’s behaviors
toward taxes (Alm et al., 1993; Lubian & Zarri, 2011; Torgler, 2012). This motivation affects
people’s willingness to comply voluntarily. Voluntary compliance, which is closely related towillingness to pay taxes, can be shaped through two mechanisms, reciprocal argument and social
norms argument. In these mechanisms, the sense of fairness plays a role. People’s trust in thegovernment will increase if they believe that the governments treat people equally and provide
public goods and services fairly, and in turn, their motivations to pay taxes will increase. Withinthese arguments, this study aims to examine the factors that motivate people’s willingness to pay
taxes in the context of a developing country. Because of the differences in tax compliance8behaviors among individuals, this study also tries to identify the characteristics of taxpayers who
engage in tax non-compliance.
Our second chapter extends the analysis of tax non-compliance by identifying thecharacteristics of taxpayers who do not comply with tax regulations. An effective tax collection is
an important issue in government finance because tax revenue contributes to a significant portionof a government’s revenue. However, tax evasion significantly reduces the government’s revenue
and will damage the fiscal balance, particularly in developing countries. Therefore, governments
are prompted to pursue effective taxation policies to minimize tax evasion. For this purpose, thefirst step is identifying the characteristics of taxpayers who are reluctant to comply with tax laws
(Slemrod, 2008). However, it is challenging to identify which kinds of individuals engage in thisbehavior since taxpayers have incentives to conceal their tax evasion (Alm 2012; Mascagni 2018).
Taxpayers may falsefully report socially desirable or acceptable answers if they are asked directly
if they comply with the tax payment rules.
We apply a list experiment to avoid social desirability bias from field surveys and elicit
sensitive information about taxation. This questionnaire design technique allows us to minimize
the social desirability bias in responses to sensitive questions. List experiments have been used tocontrol for the bias associated with sensitive topics in various social science fields, particularly inpolitical science. Despite the popularity of this experimental method, our study is the first attempt
to use the list experiment technique in a developing country to identify which taxpayers comply
when filing returns.
Using taxpayers list, we conducted a CATI survey in Jatinegara District of Jakarta Provinceof Indonesia in 2019. Our final responses are 879 taxpayers. The findings show that 13 percent of
taxpayers had engaged in tax evasion by reporting their income lower than the actual one. We alsofind that taxpayers’ characteristics, including age, gender, ethnicity, and employment statusinfluence taxpayers’ decision to comply. Our results may help tax authorities to design effective

9

tax auditing programs for specific groups of taxpayers. In addition, tax authorities could change
their taxpayers’ database structure and administrative management by collecting the necessary
information on individual taxpayers. Meanwhile, taxpayers’ privacy should be protected carefullyby the government.
The third chapter works on the causal relationship between the government’s spending andpeople’s willingness to pay taxes. Governments coordinate people’s various interests throughbudget allocations for the provision of public goods and services. To do so, securing revenues andensuring people’s willingness to pay is important to maintain budgetary power. If people canidentify high government spending performance in areas they are comfortable with, they arewilling to pay taxes (Alm et al., 1993; Glaser & Hildreth, 1999). This is because citizens generally
expect excellent performance from their governments, including high-quality public goods andservices. Moreover, rational budget allocation is considered one of the key factors that increase
trust in government and influence citizens’ attitudes toward tax payment (Alm et al., 2006).
Reciprocity shapes people’s taxation awareness, including their willingness to pay taxes.
People’s attitudes are affected by the interaction between the government and taxpayers throughbudget allocation. Accountability may also improve their perception of an exchange of fairness
between their contributions and the services they receive. This mechanism increases cooperative
behaviors on their tax obligations (Leder et al., 2010). On the other hand, the unfairness of fiscal
exchanges could discourage taxpayers from being cooperative. Taxation, which represents thestate’s ability to finance necessary public expenditures, is likely to promote a social contract
between the state and its citizens, which in turn is likely to increase revenues (Martin & Prasad,2014). In our study, we conducted a survey experiment in Jakarta, Indonesia, to examine what kindof information about government spending actually influences people’s willingness to pay taxes.
Our study has the distinctive features from previous studies: First, most studies, which haveinvestigated the connection between the types of public goods and services to tax compliance,10

examined cases from developed countries (Alm et al., 1993; Casal et al., 2016; Doerrenberg, 2015;
Glaser & Hildreth, 1999; Lamberton et al., 2017; Robbins & Kiser, 2018). However, there is a lackof study on the issue of willingness to pay taxes in developing countries. In fact, due to thelimitations on tax enforcement under weak institutional frameworks, developing countries
generally suffer from tax evasion more than developed countries (Crivelli et al., 2016). Second,most existing studies on identifying taxpayers’ preferences rely on laboratory experiments (Alm etal., 1993; Casal et al., 2016; Doerrenberg, 2015) or traditional surveys (Ali et al., 2014). However,
the observed attitudes of respondents in a laboratory experiment may not reflect their actual
decisions since they are aware of the artificial setting of the experiment (Mascagni, 2018).
A vignette experiment overcomes these problems by randomly exposing respondents to ashort story consisting of several characteristics of the actor mimicking real-life situations (Dulmer,2007). Because the respondents do not realize the aspects and conditions that are of interest in the
research, this design avoids social desirability bias problems on sensitive issues (Steiner et al.,2016). The vignette technique allows us to identify the causal effect of conditional factors, such as
the types of public goods and services and taxpayers’ characteristics, on taxpayers’ attitudes.
Therefore, to the best of our knowledge, this study is the first attempt at evaluating the effect of
the types of public spending information on people’s willingness to pay taxes, in the framework ofa vignette experiment in a developing country.
For these purposes, we include three types of public spending: infrastructure, healthcare,and industrial subsidy. By conducting a CATI survey in Jatinegara District of Jakarta Province ofIndonesia in 2019, we finally collected 879 responses from taxpayers. The results show that
exposing the information of budget allocation into subsidies to a large company reduce people’willingness to pay taxes more substantial than exposing the information of budget allocation into
healthcare sector and infrastructure sector. This result implies that industrial subsidies may have a11negative effect on people’s willingness to pay taxes although this policy is an important tool for
economic growth.
The fourth chapter investigates tax policy strategies to induce willingness to pay taxes. To
ensure high taxpaying behaviors, tax authorities utilize various tax policy strategies fromdeterrence to moral suasion. However, the effect of each policy varies. Therefore, identifying themost effective approach to motivate individuals to pay their taxes is one of the key topics forscholars and governments worldwide (Andreoni et al., 1998).
The questions related to deterrence effects, particularly in the scope of audit probability,
are central in the tax literature (Andreoni et al., 1998). Some studies argue that deterrence iseffective to motivate taxpaying (Castro & Scartascini, 2015; Pomeranz, 2015), while other studies
find that audit has little effect and may not persistently encourage tax payment (Kastlunger et al.,2009; Mittone et al., 2017).
Similarly, tax morale also contributes to a significant portion of taxpaying attitudes throughreciprocal argument and peer-effect argument. This chapter aims to identify the causal effect ofdeterrence strategy and moral suasion on an individual's taxpaying behavior by conducting avignette experiment in a developing country, Indonesia. We particularly utilize perceived audit
probability as a deterrence strategy and introduce two versions of moral suasions: reciprocal andpeer-effect arguments.
We contribute to the growing tax literature in several ways. First, little is known about theeffectiveness of perceived audit probability and moral suasion in improving tax payment in thecontext of individual income tax. The exception may include the work of Bott et al. (2020) whichanalyzes the strategies in the scope of foreign income tax in Norway. Our study provides clear
evidence of different effects of audit probability and moral suasion in individual income tax.
Second, to the best of our knowledge, no studies utilize actual taxpayers` responses and apply a12vignette experiment to explore tax-paying behaviors of individual income tax in developing
countries.
Our results find that the deterrence strategy encourages taxpaying behavior. In addition, we
also find that the effect of peer-effect information on individual’s taxpaying behavior depends onthe context of the messages. In addition, an individual’s taxpaying behavior is weakened by bothtypes of information indicating the government’s administrative efforts in improving
infrastructures and social services (positive reciprocity) and that indicating governments’
inefficiency in providing infrastructures and social services (negative reciprocity). These results
imply that deterrence strategies and positive peer-effect information effectively encourage people’s
willingness to pay taxes, particularly in Indonesia. Meanwhile, the societal benefit information that
discourages tax payment should carefully be applied to minimize the adverse effect on people’s
willingness to pay taxes.

13References
Ali, M., Fjeldstad, O.-H., & Sjursen, I. H. (2014). To pay or not to pay? Citizens’ attitudes toward
taxation in Kenya, Tanzania, Uganda, and South Africa. World Development, 64, 828–842.
Alm, J., Jackson, B. R., & Mckee, M. (1993). Fiscal exchange, collective decision institutions, andtax compliance. Journal of Economic Behavior & Organization, 22(3), 285–303.
Alm, J., Martinez-Vazquez, J., & Torgler, B. (2006). Russian attitudes toward paying taxes Before, during, and after the transition. International Journal of Social Economics, 33, 832–
857.
Alm, J., & Torgler, B. (2006). Culture differences and tax morale in the United States and in Europe.
Journal of Economic Psychology, 27(2), 224–246.
Alm, J. (2012). Measuring, explaining, and controlling tax evasion: Lessons from theory,
experiments, and field studies. International Tax and Public Finance, 19(1), 54-77.
Andreoni, J., Erard, B., & Feinstein, J. (1998). Tax compliance. Journal of Economic Literature,36, 818-860.
Bott, K. M., Cappelen, A. W., Sørensen, E. Ø., & Tungodden, B. (2020). You've got mail: A
randomized field experiment on tax evasion. Management Science, 66(7), 2801–2819.
Casal, S., Kogler, C., Mittone, L., & Kirchler, E. (2016). Tax compliance depends on voice of
taxpayers. Journal of Economic Psychology, 56, 141–150.
Castro, L., & Scartascini, C. (2015). Tax compliance and enforcement in the pampas evidence froma field experiment. Journal of Economic Behavior & Organization, 116, 65–82.
Crivelli, E., Mooij, R. D., & Keen, M. (2016). Base erosion, profit shifting, and developing
countries. FinanzArchiv: Public Finance Analysis, 72(3), 268–301.
Doerrenberg, P. (2015). Does the use of tax revenue matter for tax compliance behavior?.
Economics Letters, 128, 30–34.
Dulmer, H. (2007). Experimental plans in factorial surveys: Random or quota design? Sociological
Methods & Research, 35(3), 382-409.
14

Glaser, M., & Hildreth, W. (1999). Service delivery satisfaction and willingness to pay taxes:
Citizen recognition of local government performance. Public Productivity & Management
Review, 23(1), 48-67.
Kastlunger, B., Dressler, S. G., Kirchler, E., Mittone, L., & Voracek, M. (2010). Sex differences
in tax compliance: Differentiating between demographic sex, gender-role orientation, andprenatal masculinization (2D:4D). Journal of Economic Psychology, 31, 542-552.
Kastlunger, B., Kirchler, E., Mittone, L., & Pitters, J. (2009). Sequences of audits, tax compliance,
and taxpaying strategies. Journal of Economic Psychology, 30(3), 405–418.
Lamberton, C., Neve, J.-E. D., & Norton, M. I. (2017). The power of voice in stimulating morality:
Eliciting taxpayer preferences increases tax compliance. Journal of Consumer Psychology,
28(2), 310–328.
Leder, S., Mannetti, L., Hölzl, E., & Kirchler, E. (2010). Regulatory fit effects on perceived fiscal
exchange and tax compliance. The Journal of Socio-Economics, 39(2), 271–277.
Lubian, D. & Zarri, L. (2011). Happiness and tax morale: An empirical analysis. Journal of
Economic Behavior & Organization, 80(1), 223-243.
Martin, I. W. & Prasad, M. (2014). Taxes and fiscal sociology. The Annual Review of Sociology,
40, 331–345.
Mascagni, G. (2018). From the lab to the field: A review of tax experiments. Journal of Economic
Surveys, 32(2), 273-301.
Mittone, L., Panebianco, F., & Santoro, A. (2017). The bomb-crater effect of tax audits: Beyond
the misperception of chance. Journal of Economic Psychology, 61, 225–243.
Pomeranz, D. (2015). No Taxation without information: Deterrence and self-enforcement in thevalue added tax. American Economic Review, 105(8), 2539–2569.

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Robbins, B. & Kiser, E. (2018). Legitimate authorities and rational taxpayers: An investigation ofvoluntary compliance and method effects in a survey experiment of income tax evasion.
Rationality and Society, 1-55.
Slemrod, J., Blumenthal, M., & Christian, C. (2001). Taxpayer response to an increased probabilityof audit: evidence from a controlled experiment in Minnesota. Journal of Public Economics,
79, 455-483.
Slemrod, J. (2008). Does it matter who writes the check to the government? The economics of tax
remittance. National Tax Journal, 61(2), 251-275.
Steiner, P. M., Atzmüller, C., & Su, D. (2016). Designing valid and reliable vignette experiments
for survey research: A case study on the fair gender income gap. Journal of Methods andMeasurement in the Social Sciences, 7(2), 52-94.
Torgler, B. (2012). Tax morale, eastern Europe, and European enlargement. Communist and PostCommunist Studies, 45, 11-25.

16Chapter 2
Tax compliance and social desirability bias of taxpayers:
Experimental evidence from Indonesia
2.1 Introduction
Effective tax collection is an important issue in government finance because taxes comprise asignificant portion of a government’s revenue. Tax evasion is an illegal behavior that reduces thegovernment’s revenue and can damage the fiscal balance, hindering economic growth especiallyin developing countries. Crivelli et al. (2016) estimate that worldwide revenue losses to tax evasion
amount to around $650 billion per year and that developing countries experience one third of thoselosses, while high income countries experience much smaller revenue losses, as indicated by
Cobham and Jansky (2018) that the great intensity of revenue losses occurs in low-income
countries. The revenue losses resulting from tax evasion attract public attention, which prompts
governments to pursue effective taxation policies. Identifying the characteristics of taxpayers who
are reluctant to comply with tax laws is the first step toward establishing effective tax enforcement
schemes (Slemrod, 2008).
Since the seminal work of Allingham and Sandmo (1972), many scholars have examinedfactors that affect taxpayers’ compliance behavior. Some studies have explored psychologicalfactors by conducting laboratory experiments (Christian & Alm, 2014; Fochmann & Kroll, 2016)
or field experiments (Dunn et al., 2018; Hasseldine & Hite, 2003). However, since taxpayers have
incentives to conceal their tax evasion, it is very difficult to identify which kinds of individuals
engage in this behavior (Alm, 2012; Korndörfer et al., 2014; Mascagni, 2018). When taxpayers are
asked directly if they comply with the tax payment rules, they may falsefully report sociallydesirable or acceptable answers. This response bias is said to occur when the research question
involves socially sensitive issues, including politics, religion, and taxation. In the context of17

taxation, tax evasion is more severe in developing countries than in developed countries because
the latter have advanced tax systems (Pomeranz, 2015).
Our study aims to identify the characteristics of taxpayers who do not comply with tax
payment rules. To avoid social desirability bias from field surveys and to elicit sensitive
information about taxation, we use a list experiment. This is a questionnaire design technique thatallows us to minimize the social desirability bias in responses to sensitive questions. List
experiments have been used to control for the bias associated with sensitive topics in various fields
of social science, particularly in political science. These studies have dealt with topics such assupport for a female president (Burden et al., 2017), voter turnout (Holbrook & Krosnick, 2010),
same-sex marriage (Lax et al., 2016), conservation crime (Nuno & John, 2015), and animal disease(Randrianantoandro et al., 2015). Despite the popularity of this experimental method, it has not so
far been applied in research on taxation to our knowledge. Our study is the first attempt to use thelist experiment technique in a developing country in order to identify which taxpayers comply
when filing returns.
For our research, we collaborated with the Directorate General of Taxes (DGT), which is
the tax authority in Indonesia. Using the list of taxpayers provided by the DGT, we implemented
a computer-assisted telephone interviewing (CATI) survey of taxpayers who had filed their income
tax forms in Jatinegara District, Jakarta Province, Indonesia. The survey was conducted between
January and March in 2019, and 879 taxpayers participated in our phone interviews.
To preview the results of our list experiment, we found that around 13 percent of taxpayers
had reported lower income on their tax returns than they actually earned. In particular, taxpayers
who were old, male, Sundanese, or corporate employees showed low tax compliance behavior. We
believe that these results can help the tax authority design audit programs targeting specific groupsof taxpayers to improve tax compliance. Based on our findings, the tax authority could design an18

effective taxation policy to increase tax revenues, including targeted groups of taxpayers thatshould be audited closely and continuously.
This article consists of five sections. In the next section, we review the previous literature
on tax compliance. The third section explains Indonesia’s tax structure. The fourth section
discusses the empirical analysis, including the survey design, data, and results of the study. In the
final section, we summarize our findings and provide our conclusions.

2.2 Taxpayers and their compliance behavior
Conventional studies of tax compliance have focused on efforts by tax authorities to deter noncompliance by taxpayers. Most of these studies investigate how taxpayers change their behavior
in response to changes in the probability of being detected and the levels of potential sanctions andpenalties. From a theoretical perspective, Allingham and Sandmo (1972) argue that tax complianceimproves as the probability of detection increases and the punishments become more severe.
However, recent studies criticize the traditional approach, emphasizing that other motivations play
important roles behind tax compliance behavior (Alm et al., 1992). People pay taxes out of arecognition of the social benefits of public services and public goods provided by the government.
Some studies point out that intrinsic motivation, including tax morale, also promotes tax
compliance (Lubian & Zarri, 2011; Torgler, 2012).
Taxpayers cannot be described as a single identical group because of the diversity in their
behaviors (Alm, 2012). The heterogeneity among them must be acknowledged in explaining
individuals’ tax compliance behaviors. Indeed, many empirical studies show that tax compliancebehavior varies across citizens depending on their demographic attributes and socio-economic
characteristics, including age, gender, income, and education (Brockmann et al., 2016; Hofmannet al., 2017; Kastlunger et al., 2010; Lago-Penas & Lago-Penas, 2010; Russo, 2013), culture (Alm& Torgler, 2006; Kountouris & Remoundou, 2013), employment status and religion (Lago-Penas
19

& Lago-Penas, 2010), and trust in and perceptions of government (Batrancea et al., 2019;
D’Attoma, 2020; Jimenez & Lyer, 2016; Kirchler et al., 2008; Kogler et al., 2013).
Regarding the link between age and tax compliance behavior, the existing literature gives
mixed results. Several works argue that older generations have different social values and behavior
toward the state and regulation from younger ones. For instance, Hofmann et al. (2017) claim thatold generations, who need social security and health care benefits, treasure the benefit of taxes andthus become more compliant than young generations do. Kirchler (2007) also argues that older
people tend to have a better financial situation as well as fewer budgetary constraints, which makethem become tax compliant. In contrast, however, some studies show the opposite, that older
people are less tax compliant. Russo (2013) argues that older people exhibit lower tax compliancebehavior because they are dissatisfied with public services.
Concerning the relationship between gender and tax compliance, most studies show thatwomen are more likely to be compliant than men (Betz et al., 1989; White, 1999). Hofmann et al.
(2017) claim that women are generally more ethical and have stronger morals than men, so thatthey are more tax compliant. Hasseldine (1999) also suggests that women tend to perceive
sanctions for misbehavior or non-compliant behavior as more severe and threatening than men.
People with different income levels may also behave differently in tax compliance, but
again the literature shows mixed results on the relationship between income level and tax
compliance behavior. Some studies show that lower-income people are less compliant since they
are more sensitive to their after-tax income (Hofmann et al., 2017). In contrast, other studies
demonstrate that higher-income people exhibit lower compliance because progressive tax schemes
affect higher-income earners more substantially (Andreoni et al., 1998; Chung & Trivedi, 2003;
Hofmann et al., 2017). The relationship between educational attainment and tax compliance is also
unclear. Some studies show that highly educated people tend to be less compliant because they
have an incentive to avoid taxes by utilizing their knowledge and understanding of financial

20

transactions (Hofmann et al., 2017) and because they are more critical of the state’s actions(Torgler & Schneider, 2007). However, less educated people are also said to have an incentive tocheat on their taxes because they have a limited understanding of their tax duties or lack financial
literacy (Hofmann et al., 2017).
Several studies show a strong relationship among culture, religiosity, and tax compliance.
Culture can significantly affect one’s tax compliance behavior by shaping the intrinsic motivation
to comply (tax morale) as the moral principle or value (Kountouris & Remoundou, 2013). Alm andTorgler (2006) suggest that differences in tax compliance behavior observed across countries isdue to differences in citizens’ tax morale. Religiosity can be one potential factor that shapes tax
morale because people tend to follow a particular religion’s guidance in forming their preferences(Mueller, 2001; Torgler, 2006). In addition, religion encourages moral commitments and theinternal enforcement of social norms (Anderson & Tollison, 1992; Torgler, 2007).
Tax compliance is also likely to be associated with employment status, because employees
generally pay income tax through the withholding system, which minimizes their tax evasion
opportunities (Yaniv, 1988). Citizens’ perceptions of the government is also important. Trusted
government institutions are likely to encourage many citizens to engage in social cooperation(Kreps, 1990) and thus improve their tax compliance behavior (Scholz & Lubel, 1998; Torgler,2007). The level of government institutional quality and trustworthiness certainly explains thevariation in tax compliance across countries (D’Attoma, 2020).
To identify which demographic attributes and socio-economic characteristics relate to tax
evasion or tax non-compliance behavior, empirical studies have used various methodologies.
Torgler (2007) notes that these methods have mainly consisted of surveys, laboratory experiments,and field experiments. Because tax data are confidential, surveys are popular among researchers(Torgler, 2007). Kountouris and Remoundou (2013) examine tax morale in Europe using data
drawn from the European Social Survey (ESS). Ali et al. (2014) utilize data from the21

Afrobarometer survey for five countries in Africa. Although these surveys enable researchers toanalyze tax compliance behavior empirically in numerous countries, they suffer from issues suchas low response rates and the inaccuracy of the responses due to the sensitive nature of tax
compliance, which demotivates people from participating in the surveys (Torgler, 2007).
Respondents may alter their answers to conform to the acceptable norms in society (Hallsworth,2014).
While laboratory experiments could be used to avoid the bias associated with the sensitive
issue of tax compliance, there are concerns about the external validity of this methodology. In thereal world, a lot of crucial factors other than those manipulated in experiments might also affect anindividual’s decision to comply (Hallsworth, 2014; Mascagni, 2018; Torgler, 2007). Moreover,when respondents are drawn from some specific groups, such as students (Alm et al., 2017;
Durham et al., 2014), their decisions are not representative of the overall population of taxpayers(Hallsworth, 2014). To avoid these issues, recent studies have conducted field experiments toinvestigate how tax compliance behavior is influenced by a government’s actions, such as social
norm letters (Biddle et al., 2018), third-party information (Carrillo et al., 2017), field inspections(Rincke & Traxler, 2011), deterrence letters (Shimeles et al., 2017), and audit paper trails(Pomeranz, 2015). Field experiments could mitigate the problems encountered in surveys andlaboratory experiments, as they use data from real taxpayers, reflecting the decisions they actually
make in real life.
To create effective taxation policy, including audit schemes, the government also needs
enough information about the characteristics of individuals who engage in tax evasion.
Nevertheless, taxation is a sensitive issue for taxpayers, making it generally difficult for thegovernment to obtain precise information about their behavior, because they may provide false
answers or even refuse to answer any questions from the government. To address these problems,
we conducted a field survey with an experimental component, a list experiment or an item count22

technique (ICT), which is an indirect question technique. The list experiment technique protects
respondents’ privacy by not requesting that they disclose their answers on sensitive issues. The list
experiment questions are designed such that the results show only the number of affirmative
answers rather than answers to sensitive questions which are socially undesirable (Corstange, 2009;
Blair & Imai, 2012, Gonzalez-Ocantos et al., 2012). Because of this advantage, list experiments
have grown in popularity in the social sciences.

2.3 Individual taxation in Indonesia
This study employs Indonesia as the subject country. Indonesia is classified by the World Bank as
a lower middle-income country (LMIC), and the country shares common tax-related problems withother LMICs. In fact, Indonesia’s tax-to-GDP ratio is relatively small, reaching only 10.3 percent
in 2016. Among the ASEAN member countries, Indonesia is ranked the second lowest, following
Myanmar. The average of tax-to-GDP ratio over the ASEAN member countries is 12.6 percent in2016. Given this situation, the government has set its target for the tax-to-GDP ratio at around 13
to16 percent during the period of 2031-2035 as part of the Medium-Term Fiscal Macro Strategy
2020-2024.

23

Table 2.1 The Proportion of individual income tax to total income tax (billion rupiah)
Amount% of Total Income Tax% of Total Central Tax(billion Rupiah)
Income Tax
Individual
7,806
1.21%
0.58%
Corporate
206,550
31.93%
15.37%
Other Income Tax
432,437
66.86%
32.19%
Total Income Tax
646,793
100.00%48.14%
Total Central Tax
1,343,529
100.00%Note: Other income tax includes oil and gas income tax, income tax article 21,22, 22 Import, 23, 26, final income tax,
fiscal income tax, and income tax borne by the government.
Source: Central Government Financial Report-Audited.

24

This study focuses on taxes on individuals, particularly income tax, among various formsof taxes in Indonesia. Income tax is collected using a self-assessment system. There are two typesof individual taxpayers: self-employed individuals and employees. Self-employed individual
taxpayers calculate the amount of their own taxes and report it to the tax office. On the other hand,for employees, income tax is calculated and paid by their employers from their salary or wage,
using the withholding tax system. At the same time, employees often receive additional income
from their own business activities in addition to their salaries or wages. Thus, all employees needto report incomes from their employers, as well as their additional income in order to calculate thetotal amount of income tax they owe on their tax returns. However, due to the lack of third-party
reporting to capture additional incomes from their business activities, taxpayers might not reportall of their income on their tax returns, making honesty and willingness to pay taxes crucial for
individual tax collection.
Concerning the administrative structure of the tax authority in Indonesia, the DGT consistsof more than 340 tax offices in 34 provinces, which are responsible for collecting central taxes,
such as income taxes, value-added taxes, and land and building taxes in four sectors (forestry,
plantation, oil and gas, and mining). In addition to usual tax offices, there are two types of special
offices, large tax offices (LTOs) and special tax offices (STOs) in Jakarta. The LTOs’
responsibility is to serve and monitor large taxpayers in Indonesia, while the STOs are responsible
for handling special cases of corporations, such as state-owned enterprises and foreign
multinational corporations. The former consists of four offices and one regional office, and thelatter consists of nine offices and one regional office. According to a report from the governmentof Indonesia in 2018, individual and corporate income tax revenues represented 1 percent and 32
percent, respectively, of total tax revenue in 2017 (see Table 2.1). The low level of individual
income tax revenue has encouraged the tax authority to increase individual tax compliance.

25

According to BPS-Statistics Indonesia, Jakarta is the largest political and commercial city
in Indonesia. It also has the highest density of any city in Indonesia, with more than 15,000 people
per square kilometer. The population includes a variety of social, ethnic, and religious groups(BPS-Statistics Indonesia 2018). The amount of tax revenue collected in Jakarta is much larger
than in other provinces. According to the DGT, 18.5 percent of total central tax revenue in 2017
was collected from taxpayers located in this city. Jakarta consists of six regencies and 44
subdistricts, and 54 tax offices cover these areas. Our study area is the Jatinegara subdistrict ofJakarta province. According to BPS-Statistics of Jakarta Timur, Jatinegara subdistrict consists ofeight villages with 310,494 people living in a 10.25 square kilometer area. The land-use is mainly
for housing, which occupies 71.12 percent of the area, and the land-use for industry is around 5.19
percent of total land-use. This means that few industries operate in this subdistrict. On the other
hand, there are 116 markets, including traditional markets and restaurants, indicating that trade ingoods and services is the main business activity in this subdistrict.

2.4 Empirical analysis
2.4.1 List experimentThis study employed a list experiment or item count technique to mitigate respondents’ social
desirability bias when eliciting information about sensitive issues. To conduct a list experiment,
respondents were randomly separated into two groups: the control group and the treatment group.
Respondents were presented a list of statements and then asked to report how many statements on
the list pertain to them. The list of statements shown to the respondents in the control groupconsisted of four statements (we call them “control statements”) that are not directly related to our
research interest. We considered three issues when designing the control statements. First, there isa possibility that the respondents report all of the statements (or none of the statements) pertain tothem. This creates a ceiling and floor effect problem (Blair & Imai, 2012). A major concern over26

these effects is the lack of privacy protection for the respondents. To mitigate this issue, the four
control statements were designed so that few respondents in the control group would answer
affirmatively or negatively to all of them (see Blair & Imai, 2012; Glynn, 2013). Second, the list
experiment needs to satisfy a no-design effect assumption that responses to the control statements
are not affected by the additional treatment statement (Blair & Imai, 2012). To avoid this issue, assuggested by prior works, we carefully chose four control statements about which respondents
were likely to have strong opinions. Third, other potential problems include respondents rushing
to complete the survey or misinterpreting it, and administrators making coding errors (Ahlquist,2018). To avoid these problems, we trained the interviewers by conducting a pilot survey inadvance and confirmed the validity of our experimental design. The list of statements shown to the
respondents in the treatment group composed of five statements, adding one statement (we call it
a “treatment statement”) that directly related to our research interest. The treatment statement
might invite a social desirability bias, but with a large enough sample size, this design enabled us
to estimate the proportion of respondents to whom the treatment statement of interest pertained. It
is calculated by subtracting the average number of statements reported by the respondents in thecontrol group from the average number of statements reported by the respondents in the treatmentgroup. Arranging the statements in this way ensured a level of privacy for the respondents in thetreatment group because whether or not the treatment statement pertained to them cannot be
inferred by the researchers, unless they chose either all of the statements or none of them.
To reiterate, the objective of our study was to elicit taxpayers’ attitudes toward tax
compliance. By conducting a list experiment, we attempted to estimate the proportion of taxpayers
who had reported an amount for their income on their income tax forms lower than their actual
income. There were four control statements and one treatment statement. The treatment statement
was the item directly related to the respondent’s tax compliance behavior. We randomly separated
our respondents into two groups: a treatment group and a control group. Only the first four control

27

statements were presented to respondents in the control group, and all five statements were
presented to respondents in the treatment group. The order in which statements were presented wascompletely randomized across respondents to minimize the possibility of any order effect. After
presenting a list of these four or five statements, we specifically asked each respondent to identify
how many statements apply to her/him. It should be noted that, unlike traditional social surveys
that directly ask respondents to answer which statement(s) apply to them, the list experiment asks
respondents to state only the number of statements that apply to them. This may cause some
respondents to become suspicious about the objective of our survey and discourage theircooperation. To minimize this possibility, we followed the suggestions of Tsuchiya et al. (2007),and chose a control statement that has a similar degree of social desirability bias to the treatment
statement. This control statement is “I have paid a bribe to a police officer to get away with aviolation,” which occurs relatively frequently in Indonesia but is socially sensitive. By doing so,
we encouraged our respondents to cooperate with our survey without revealing the true purpose of
our study. The exact wordings of these statements are as follows:
Control statements•

I have more than one sister.

•I have paid a bribe to a police officer to get away with violation.

•

I went to a private high school.

•

I talked about politics with other people during the previous election.

Treatment statement•

I have reported an amount lower than my actual income in my tax report.

We used the unique list of all taxpayers obtained from the tax office in the Jatinegara
subdistrict of Jakarta province to conduct our list experiment. We obtained the approval of the
Head office of Jatinegara Tax Office to access to the taxpayers list. This list includes 121,330
individual taxpayers in the district. Among those taxpayers, we excluded non-effective taxpayers,28

non-filing taxpayers, and taxpayers without the information of their phone numbers. Non-effective
taxpayers are those who do not need to file tax returns and pay taxes, due to factors such as
unknown addresses or having gone out of business. However, these taxpayers’ statuses can beswitched into effective taxpayers if those factors change, either by the taxpayer’s requests or by
tax officers’ request. Non-filing taxpayers are those who have not filed tax returns in the past two
years consecutively. This leaves us a total of 14,428 taxpayers who have submitted their tax returns
from 2013 to 2017. Using the final list of the taxpayers, we implemented a survey including ourlist experiment question using computer-assisted telephone interviewing (CATI) from January
2019 to March 2019, and we collected responses from a total of 879 taxpayers (the response rate
is six percent). We collaborated with an Indonesia-based research company (PT. Kresna Abadi
Dinamika (KAD)) to conduct the interviews in our survey. About 86 percent of respondents did
not complete the survey, and about 8 percent of respondents simply refused to take part in thesurvey. In the survey, we also asked for additional information about respondents’ demographics
and socio-economic status, such as age, gender, income, ethnicity, religion, educational level, andemployment status.
2.4.2 Results
Table 2.2 presents the results of the univariate analysis of the list experiment. We found a
statistically significant difference between the treatment and control groups in their responses atthe 5 percent level. In the spirit of transparency, we provided information about the randomization.
We checked the effectiveness of randomization by conducting a balance test. We employed logistic
regression analysis to estimate the effect of various covariates on the likelihood of being in thetreatment group. The results are shown in Table A2.1. Only gender has a coefficient that issignificantly different from zero (p=0.1). This means that males were more likely to be assigned tothe treatment group unintentionally. The results show that 13.42 percent of taxpayers have reported
lower income than their actual income to the tax office. The issue of whether our sample accurately

29

represents the target population of taxpayers is obviously a crucial concern. To clarify this, we
compared our sample with the target population of taxpayers in the list of taxpayers, which was
obtained from the Indonesian tax office, and confirmed that our sample is consistent with the target
population in terms of at least two categories: employment status and tax payment history.
Regarding the employment status category, the proportion of taxpayers in our sample who areemployees is 67 percent, and that in the target population is 64 percent. Regarding the tax payment
history category, the proportion of taxpayers in our sample who had paid taxes in the last five years
is 12 percent, and that in the target population is 11 percent. These comparisons show the similarity
between our sample and the target population in terms of these two categories. Since the list of
taxpayers provided by the Indonesian tax office does not include reliable information on othercategories, such as age, gender, ethnicity, religion, and education, we could not confirm whether
or not our sample is consistent with the target population in terms of these other categories. While
we recognize that this latter issue is problematic, the consistency in terms of the two key categories
mentioned at least partially justifies our claim that our sample is representative of the target
population of taxpayers; this significantly mitigates the possibility of sample bias, and we feel
confident that our results are valid. Concerning individual characteristics, our univariate analysis
indicates several results. First, attitudes toward tax compliance differ across generations. Older
people tend to exhibit lower tax compliance behavior, with 31.3 percent of respondents

30

Table 2.2 Difference-in-means results by various sub-groups
Variable
No of obs.
Control
All respondents
879
1.653
(0.053)Age<30 years old
421
1.717
(0.074)
Between 30 and 40
208
1.626
(0.115)
Between 40 and 50
134
1.639
(0.136)> 50 years old
116
1.484
(0.145)
GenderFemale312
1.457(0.076)
Male
567
1.774
(0.070)
Income<4.5 mill
373
1.378(0.078)1.905
between 4.5 mill and 421
15 mill(0.075)> 15 mill
85
1.568(0.167)Ethnicity
Jawa
339
1.727
(0.084)
Sunda
106
1.104
(0.131)
Betawi197
1.600(0.107)237
1.814
Other ethnic groups(0.105)
Religion
Islam
Other religious
groups

680
199

1.572
(0.059)1.939(0.112)31

Treatment
1.787(0.056)

Difference
13.42%**(0.077)1.713(0.072)1.780(0.111)
1.952(0.160)1.889(0.202)-0.40%( 0.104)
15.36%(0.160)31.27%*(0.209)40.50%*(0.245)1.511(0.088)1.920(0.071)

5.41%(0.116)
14.59%*(0.099)1.617(0.089)1.925(0.079)1.854(0.174)23.84%**(0.118)1.92%(0.109)28.66%(0.246)1.577(0.079)1.810(0.185)1.908(0.133)1.975(0.104)-15.06%(0.116)70.62%***(0.235)30.80%**(0.169)16.12%(0.148)1.703(0.066)2.060(0.103)13.11%*(0.088)12.06%(0.152)

Table 2.2 Continued
Variable
Education
High school or below
College

No of obs.

Control

Treatment

Difference

365

1.505
(0.083)1.764(0.067)1.585(0.094)1.922(0.068)7.96%(0.125)15.83%**(0.096)1.662(0.062)1.864(0.128)1.323(0.139)1.842(0.066)1.786(0.128)1.471(0.184)18.03%**(0.091)-7.79%(0.181)14.75%(0.226)1.663(0.117)1.634(0.080)1.665(0.086)1.707(0.124)1.738(0.088)1.883(0.091)

4.31%(0.171)
10.41%(0.119)21.87%**(0.125)1.879(0.160)1.619(0.055)2.269(0.167)1.720(0.059)38.99%**(0.231)10.07%(0.081)

514

Employment status
Employee591

Self-employed172

Unemployed

116

Perception of corruption
Low

196

Medium

347

High

336

Payment status
With payment

110

Without payment

769

Notes: Standard errors are in parentheses.
***p<0.01, **p<0.05, *p<0.10.

32aged 40 to 50 years and 40.5 percent of respondents aged 50 or above having engaged in tax evasion.
These results are consistent with the findings of Russo (2013) in Italy that people aged 60 or above
exhibit low compliance behavior, partly due to their dissatisfaction with public services. Second,tax compliance behavior also differs between men and women, with 14.6 percent of male
respondents having engaged in tax evasion, while only 5.41 percent of female respondents did so.
Men tend to exhibit lower compliance than women, as suggested in multiple studies, including
Barber and Odean (2001), Batrancea et al. (2019), Brockmann et al. (2016), and Hofmann et al.
(2017). Third, low-income respondents tend to engage in tax evasion. Among respondents whose
income was below 4.5 million rupiahs, 23.8 percent underreported their income on their tax returns.
One possible reason may be that low-income people can more easily cheat on their taxes because
they suffer financially more than rich people do (Hofmann et al., 2017).
Fourth, a significant negative correlation exists between educational attainment and tax
compliance behavior. Among respondents with college education, 15.8 percent disclosed that they
had cheated on their taxes. These people may be able to utilize their knowledge to minimize or
avoid their tax liability (Hofmann et.al., 2017). Fifth, 18.0 percent of employees who were working
in private and public organizations engaged in tax evasion. Employees are generally under the tax
withholding system in which their tax is deducted from their salaries. Our results imply that some
employees have additional income from other sources, but they do not report it to the tax office.
Sixth, we examined the roles of respondents’ culture and religion, since they are expected to becorrelated to tax compliance behavior (Kountouris & Remoundou, 2013; Lago-Penas & LagoPenas, 2010; Russo, 2013). Specifically, we considered four ethnic groups (Jawa, Sunda, Betawi,
and a category specified as “other ethnic groups” in the survey) and two religious groups (Islamand a category specified as “other religious groups”). We categorize minority ethnic and religious
groups as “other ethnic groups” and “other religious groups”, respectively. The results show that
Sundanese and Muslims tend to engage in low tax compliance behavior.

33

Seventh, Kirchler et al. (2008) and Torgler (2007) examine the effects of people’s trust in
government on their tax compliance behavior, because the perception of corruption in government
institutions discourages them from paying tax. Consistent with these studies, our analysis reveals
that respondents who perceive a higher level of corruption in government (i.e., they have lower
levels of trust in government) are more likely to cheat on their income tax. Finally, our survey
sample was drawn from the population of those who have filed tax returns at least once in the past
five years. This implies that it includes people who have no actual income to report on their tax
returns and those who have never had an opportunity to cheat on their tax reports due to tax
withholding by their employers. These people are less likely to select the sensitive item indicating
tax evasion in their responses to our list experiment question. The results show that only 10.1
percent of people revealed that they have engaged in tax evasion among those who have no tax
payments on their reports, while among those who have paid some amount of tax at least once inthe past five years (not through the withholding scheme but directly to the tax office), 39.0 percent
of people have engaged in non-compliance.
2.4.3 Multivariate analysis
The univariate analysis captures the difference-in-means for each group separately without
considering overlap in the group memberships. This analysis uses data inefficiently. To overcome
these issues, we conduct a multivariate analysis, which basically generalizes the difference-inmeans approach by modeling the joint distribution efficiently to allow for control for multiple
variables concurrently. We apply maximum likelihood models with the constrained version of theestimator, assuming that the addition of the sensitive item does not influence the34Figure 2.1 Multivariate estimates of tax non-compliance.

Notes: The dots estimated proportions of respondents engage in tax non-compliance, and the lines show the 95%
confidence intervals from the regression model in Table A2. The vertical axis shows respondents’ attributes.

35

answers concerning the control items (Blair & Imai, 2012; Imai, 2011). We used statistical method
for the item count technique and list experiment that can be found at http://CRAN.Rproject.org/package=list. (Blair et al., 2018). We also checked for the existence of floor and ceiling
effects as a result of our design, following Blair and Imai (2012). Figure A2.1 presents thepercentage of respondents for each possible answer. The results show that the responses are
distributed normally. The extreme cases have relatively few responses in both the control groupand the treatment group. Blair and Imai (2012) proposed a test to detect the existence of a design
effect in which the addition of the one treatment statement would affect the answers to the control
items. Our test result shows that the Bonferroni-corrected p-value is 1.000. Therefore, we cannot
reject the null hypothesis that there is no design effect. The estimated coefficients together withstandard errors are shown in Table A2.2. We use several individual characteristics in the model.
To measure the variables, we reconstruct the data as follows: age (below 30=1; between 30 and
40=2; between 40 and 50=3; above50=4), gender (male=1; female=0), ethnic groups [Jawa(Jawa=1; non-Jawa =0), Sunda (Sunda=1; non-Sunda =0), Betawi (Betawi=1; non-Betawi =0)],income (below 4.5 mil=1; between 4.5 mil and 15 mil=2; above 15 mil=3), religion (Islam=1; otherreligious groups =0), education (elementary school-high school=1; college=2), employment status[employee (employee=1; non-employee =0), self-employed (self-employed=1; non-self-employed=0)], and perception of corruption (low corruption=1; medium corruption=2; high corruption=3).
Figure 2.1 illustrates the estimated proportions of respondents cheating on their taxes byreporting less income than they actually earned. The coefficients for several variables are
consistent with the findings in our univariate analysis discussed in the previous subsection. First,
we continue to find a tendency that older people, especially respondents in the age group between
40 and 50 years old, engage in tax evasion more than do those in the age group below 30 years old.
The difference between these age groups is statistically significant at the 5 percent level. Second,
our multivariate findings on gender are consistent with our univariate findings. Men engage more36

in tax evasion than women do, with an estimated difference of 11.6 percentage points, which is
marginally significant at the 10 percent level. Third, there are significant differences between
ethnic groups in tax evasion. The proportion of Sundanese engaging in tax evasion is higher thanthose of Jawa and Betawi respondents, with estimated differences of 36.9 and 27.5 percentage
points, respectively. These differences are statistically significant at the 5 percent level. Fourth, we
also find that employees engage in more tax evasion than self-employed individuals do, with anestimated difference of 12.9 percentage points. It is also statistically significant at the 5 percent
level.
On the other hand, some results in the multivariate analysis are less clear compared to thosein the univariate results. The univariate analysis suggests that the group of respondents with income
below 4.5 million rupiahs engage in more tax evasion than the group of higher income respondents.
However, the estimated differences across income levels disappear in the multivariate results. In
addition, while the univariate analysis also shows that Muslims and people with college educationor higher tend to engage more frequently in tax evasion, the multivariate results indicate no clear
evidence of differences across religious groups or education levels. Moreover, the univariate
analysis shows that people with a perception of high corruption tend to engage more frequently intax evasion, but the multivariate analysis does not confirm that tax evasion behavior depends on
the perception of corruption. Furthermore, the univariate analysis shows that people who have paid
some amount of tax directly to the tax office at least once in the past five years tend to engage more
frequently in tax evasion than do those who have never done so, but the difference between thetwo groups is not statistically significant in the multivariate analysis, partly due to the small sample
size of the former group of people.

37

2.5 Conclusion
Tax evasion is a sensitive problem at the individual level. Since taxpayers have a motivation tohide their tax evasion behavior, identifying their true behavior can be a crucial challenge forresearchers as well as tax regulators. This is related to social desirability bias, where respondents
attempt to answer survey questions in a socially desirable or acceptable manner, instead of
revealing their actual opinions or behavior. In the context of taxation, this bias emerges when
taxpayers pretend to meet their own obligations by underreporting their incomes to the tax office.
To identify the characteristics of taxpayers who engage in tax evasion behavior, this study
mitigated the influence of social desirability bias by conducting a list experiment in Jakarta,
Indonesia. The univariate analysis revealed that 13.4 percent of taxpayers have cheated on theirtaxes by underreporting their income on their tax returns. The results also uncovered clear evidence
that tax evasion behavior varies depending on individual characteristics, such as age, gender,
ethnicity, and employment status. The multivariate analysis generally confirmed the findings fromthe univariate analysis, though some differences found in the univariate analysis (such as thosebetween religious groups and education levels) disappeared in the multivariate analysis.
In a developing country like Indonesia, the percentage of taxpayers who actually cheatedon their taxes may be larger than estimated in this study because of weak auditing capacity andlegal system.
Our list experiment outcomes may still underestimate the proportion of taxpayers who haveengaged in tax evasion behavior. In a developing country like Indonesia, the percentage oftaxpayers who actually cheated on their taxes could be larger than estimated in this study becauseof weak auditing capacity and legal system. However, we believe that our study has important
implications for taxation policy because our results help identify potential targets for tax auditing
to overcome the issue of a government’s limited institutional capacities. For instance, in Indonesia,
tax offices identify potential targets of auditing mostly on an ad hoc, not a systematic, manner by38

merely comparing a particular tax return to others from a similar business environment. Since suchan ad hoc monitoring scheme does not take into account the characteristics of individual taxpayers,
tax offices are likely to fail to detect many taxpayers engaging in tax evasion behavior.
The Indonesia State Budget 2019 emphasizes that the tax authority (DGT) needs to raise
tax revenue by broadening the tax bases and also by improving tax compliance sustainability. The
Minister of Finance points out the importance of effective tax auditing to increase tax revenue tothe required level for supporting the country’s development which was delivered to the parliament
on July 27, 2017. It is important for tax offices to identify what types of taxpayers are more likely
to engage in tax evasion and to establish appropriate measures to tackle tax evasion through tax
auditing. Given that our results indicate that taxpayers who are old, male, corporate employees,
and members of a certain ethnic group tend to exhibit relatively low tax compliance, one possible
tax policy could be for the DGT to cluster these groups of taxpayers as potential targets for tax
auditing. However, the DGT currently does not have all the necessary information on individual
taxpayers due to constraints on its taxpayer database and administrative capacities. To address thispractical limitation, the DGT needs to collect the necessary information on individual taxpayers bychanging its taxpayer database structure and administrative management while at the same time
carefully protecting taxpayers’ privacy.
We believe that the relationship between tax evasion and individual characteristics foundin our study would be useful information for both researchers and tax authorities who are interested
in designing effective tax policies and auditing schemes to improve governance and revenue
collection. At the same time, the ethical issues involved in targeting specific groups in the tax
auditing process are also a matter of concern. The government and tax authorities need to be awareof these and set clear rules for the implementation of auditing and the appropriate handling of
personal data.

39

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45

APPENDIX

Table A2.1 Logit model test of balance in randomization
Variable
Coefficient
S.E.
Age-0.0270.075
Male
0.260*
0.149
Jawa-0.065
0.180
Sunda
0.248
0.247
Betawi-0.202
0.202
Income
0.032
0.119
Islam
-0.0870.181
Education
0.098
0.155
Employee
0.078
0.244
Self-employed
0.034
0.266
Government
0.011
0.090
Payment-0.1100.224
Constant-0.3430.479
Log-likelihood-604.619
Chi-squared
8.60
No of obs.
879.000
Notes: The dependent variable is the indicator of whether the respondent was assigned to the treatmentgroup.
*p<0.1, **p<0.05, **p<0.01.

46

Table A2.2 Multivariate regression results (maximum likelihood constrained model)
Est.
S.E.
Est.
Sensitive item
Control items(Intercept)-7.401
3.068(Intercept)-0.935
Age
1.157
0.512
Age
-0.052
Male
1.895
1.316
Male
0.290
Jawa
-2.1992.510
Jawa-0.031
Sunda
1.952
0.983
Sunda
-0.416
Betawi-0.3691.011
Betawi
0.017
Income-0.795
0.614
Income
0.132
Islam
1.269
1.056
Islam
-0.247
Education
0.882
0.821
Education
0.148
Employee
0.595
1.328
Employee
0.199
Self-employed-1.7501.502
Self-employed
0.252
Government
0.028
0.566
Government
0.033
Payment
2.183
1.296
Payment
0.161
Log-likelihood-1293.46
Notes: The outcome variable is whether a respondent reports income lower than actual one.

47

S.E.
0.247
0.043
0.081
0.099
0.143
0.110
0.064
0.096
0.085
0.138
0.145
0.049
0.124

Figure A2.1 Percentage of respondents for each answer category in the list experiment.
40%
35%
30%
25%
20%
15%
10%
5%
0%
0

1

2

3

control

45treatment

Note: Respondents were asked to report the number of statements that apply to them in the range ofzero to four (in the case of control group shown in gray) or zero to five (in the case of treatment group shown inblack).

48

Chapter 3
When do people become more willing to pay taxes? The effects ofgovernment spending information on the public’s willingness to pay taxes

3.1 Introduction
Governments coordinate people’s various interests through budget allocations for the provision of
public goods and services. In order for the government to maintain its budgetary power, securing
revenues and ensuring people’s willingness to pay are important. Citizens generally expect
excellent performance from their governments, including high-quality public goods and services.
Rational budget allocation is considered to be one of the key factors that increase trust in
government and influence citizens’ attitudes toward tax payment (Alm et al., 2006). Citizens are
said to show willingness to pay taxes when they can identify high government spending
performance in areas they are comfortable with (Alm et al., 1993; Glaser & Hildreth, 1999). In ourstudy, we conducted a survey experiment in Jakarta, Indonesia, to examine what kind of
information about government spending actually influences people’s willingness to pay taxes.
Reciprocity, a tax payment morale, shapes people’s taxation awareness, including their
willingness to pay taxes. Although the willingness to pay taxes shares similar features particularly
with voluntary tax compliance (Torgler, 2007), it can differ from tax compliance. We can easily
consider a scenario where individuals would be willing to pay more taxes if the spending were forprojects that they truly support, but they would continue to commit tax evasion as much possible.
In reciprocity, people’s attitudes are affected by the interaction between the government andtaxpayers through budget allocation. People’s perception of fairness between the amount of tax
paid and the amount of benefits received depends on their satisfaction with the budget allocation.
Accountability may also improve their perception of an exchange of fairness between theircontributions and the services they receive. Furthermore, if the government were to respond49

appropriately to taxpayers’ preferences, it would enhance their attitudes toward taxes (Alm &Torgler, 2006). This mechanism increases cooperative behaviors on their tax obligations (Leder etal., 2010). On the other hand, the unfairness of fiscal exchanges could discourage taxpayers frombeing cooperative. This reciprocal relationship involves an emotional tie within the framework of
a contract between the government and the citizens (Barone & Mocetti, 2011).
Sound taxation, which represents the state’s ability to finance necessary public
expenditures, is likely to promote a social contract between the state and its citizens, which in turnis likely to increase revenues (Martin & Prasad, 2014). In this regard, a number of studies have
explored the importance of information on the budget allocations for public expenditures inshaping people’s tax attitudes, including their willingness to pay taxes and tax compliance (Alm etal., 1993; Alm et al.,2006; Barone & Mocetti, 2011; Casal et al., 2016; Doerrenberg, 2015; Glaser& Hildreth, 1999; Leder et al., 2010). Glaser and Hildreth (1999) have demonstrated that there isa link between the performance of governments, the public services they provide to citizens, andcitizens’ willingness to pay.
Our study has the following distinctive features from previous literature: First, most studies
have covered the link between the types of public goods and services to tax compliance, having
examined cases from developed countries (Alm et al., 1993; Casal et al., 2016; Doerrenberg, 2015;
Glaser & Hildreth, 1999; Lamberton et al., 2017; Robbins & Kiser, 2018). However, there is stilla lack of empirical evidence for the issue of willingness to pay taxes in developing countries.
Developing countries generally suffer from tax evasion more than developed countries (Crivelli etal., 2016). Due to limitations on tax enforcement under weak institutional frameworks, tax revenue
in developing countries relies more on cooperation from taxpayers. Empirical studies on this issue
are needed in developing countries. Second, most existing studies on the identification of taxpayers’
preferences rely on laboratory experiments (Alm et al., 1993; Casal et al., 2016; Doerrenberg,
2015; Lamberton et al., 2017) or traditional surveys (Ali et al., 2014). However, the observed

50attitudes of respondents in a laboratory experiment may not reflect their actual decisions, since
they are aware of the artificial setting of the experiment (Mascagni, 2018). A traditional survey
also faces a similar problem in which the revealed attitudes inaccurately portray actual behaviors
because of the sensitivity of the tax compliance issue (Torgler, 2007).
A vignette experiment enables us to overcome these problems by randomly exposing
respondents drawn from a sample of taxpayers to a short story consisting of several characteristicsof the actor mimicking real-life situations (Dulmer, 2007). Since the respondents do not realize theaspects and conditions that are of interest in the research, this design avoids social desirability bias
problems on sensitive issues (Steiner et al., 2016). The vignette experiment has been used to
identify human choices and preferences in various fields, such as sociology, political science, andmedical science (Breeschoten et al., 2018; Kootstra, 2016; Ung et al., 2017). Moreover, vignette
experiments have high internal and external validities, which are a combination of the advantagesof laboratory experiments and traditional surveys (Gross et al., 2017). High internal validity canbe achieved by using multidimensional variables and a combination of several experiment
techniques, while high external validity can be achieved by incorporating heterogeneous
respondents (Auspurg & Hinz, 2015; Mutz, 2011). The vignette technique allows us to identify thecausal effect of conditional factors, such as the types of public goods and services and taxpayers’
characteristics, on taxpayers’ attitudes. To the best of our knowledge, this study is the first attempt
at evaluating the effect of information on the types of public spending on people’s willingness to
pay taxes, in the framework of a vignette experiment in a developing country. Few studies haveconducted vignette experiments in the field of taxation. An exception may include the works of
Abraham et al. (2018) and Gross et al. (2017), which focused on inheritance tax, Bornmann andStack (2015) on the relationships between reward and tax compliance, and Kwok and Yip (2018)
on tax education. Meanwhile, Robbins and Kiser (2018) used a vignette experiment to evaluate therelationship between the types of public spending and tax compliance in a developed country.

51

In the context of transparency and accountability, taxpayers pay attention to government
policies, including the allocation of the budget intended for public spending into various sectors.
In the case of Indonesia, the government’s primary targets include, but are not limited to, theimprovement of socio-economic infrastructure and human resources, such as education andhealthcare. The budget being allocated into these sectors tends to be accepted by the public because
they meet the basic needs of people and provide them with equal benefits. In contrast, some
portions of public spending are allocated to specific people and groups who do not receive equal
benefits from it. For example, the Indonesian government has recently given tax allowances andloan interest subsidies to some large-scale firms in specific industrial sectors. The subsidy policyin Indonesia State Budget 2019 targets only a small portion of industries which include geothermal,
fuel, and electricity sectors (Directorate General of Budget, 2018). Although this type of subsidy
can be justified for various economic reasons, it often triggers a lot of public debate about therationality of budget allocations because of the small coverage of beneficiaries receiving unequal
benefits. Thus, we examine how taxpayers’ willingness to pay taxes varies by information
provision on budget allocation into three areas of important public spending: (i) infrastructure, (ii)healthcare, and (iii) industrial subsidy. Article 31 of the 4th amendment of the Constitution of the
Republic of Indonesia of 1945 specifically states that a fixed portion of 20% of the government
budget is spent for education. Thus, we do not include this sector in this research, since we assume
that most taxpayers know the purpose and the portion of public spending allocated for the education
sector.
We conducted a vignette experiment through a computer-assisted telephone interviewing(CATI) survey from January to March 2019, where the respondents were taxpayers who filed
income tax returns in the Jatinegara District of the Jakarta Province. We recruited survey
respondents in collaboration with the tax authority, the Directorate General of Taxes (DGT) of theIndonesian government, and obtained responses from a total of 879 taxpayers. To give a preview

52

of the results of our experiment, the willingness of taxpayers to pay taxes was reduced when they
were exposed to information that the government allocates a significant portion of its budget as
subsidies for large firms. Respondents were less sensitive to the exposure of information about theallocation of government budget into healthcare and infrastructure development. These results
have important policy implications for taxation. Industrial subsidies are widely recognized as animportant tool for economic growth, but at the same time they provide unequal benefits to eachindividual and have a negative impact on their willingness to pay taxes. In the next section, we
discuss our research design and data in more detail.

3.2 The vignette experiment
We drew our sample from the list of taxpayers administered by the tax office covering the
Jatinegara subdistrict of the East Jakarta district in Jakarta province. We obtained the approval of
the Head Office of the Jatinegara Tax Office. We draw our sample from Jakarta province, whichplays an important role in Indonesia particularly because this province is regarded as the center ofthe economy. Being the capital of Indonesia, this province contributed 66% of national tax revenue
in 2019 and 17% of total GDP in 2017. In this study, we set our target in the East Jakarta region.
This is one of five regions of Jakarta province, and it covers 27% of the whole population in Jakarta
province. To make sure that our sample can represent people in this province, we compare thecharacteristics of people living in this region with those in the entire Jakarta province. Regarding
age, the proportion of people under 35 years old is 36% in the East Jakarta region and 40% in thewhole of Jakarta province. In terms of gender, the proportion of males is 51% in the East Jakarta
region and 50% in the whole of Jakarta province. Although it is impossible to compare otherattributes due to the lack of data, we can conclude that, at least for age and gender, the East Jakarta
region shares similar distribution to the whole of Jakarta province. Based on these arguments, we
believe that our sample from the East Jakarta region can represent the population of taxpayers in53

the whole Jakarta province. From a total of 121,330 individual taxpayers on the list, we identified
14,428 individuals who filed tax returns from 2013 to 2017. We excluded non-effective taxpayers,
non-filing taxpayers, and taxpayers without information of their phone numbers. Non-effective
taxpayers are taxpayers who do not need to report their tax returns nor pay taxes. Non-filingtaxpayers are those who never reported tax returns in the past two years sequentially. We
administered the CATI survey from January through March 2019 and obtained a total of 879
complete responses. We collaborated with an Indonesia-based research company to conduct a
computer-assisted telephone interviewing (CATI) survey. The response rate is around 6%. Such a
low response rate raises concerns about whether the respondents are representative of the taxpayers
population. To clarify this concern, we checked to see if the attributes of our 879 respondents
differed from those of 14,428 taxpayers in the targeted district who were selected and invited toparticipate in our survey. We confirm that the invited taxpayers share similar characteristics to theactual respondents in two categories: the employment status and that tax payment history. First,
regarding the employment status, 64% of the invited taxpayers are employees and 67% of the actual
respondents are also employees. Second, regarding tax payment history of 11%, the invited
taxpayers have a record of paying tax for the past five years, and the same was true for 12% ofactual respondents. Because the list of taxpayers did not include reliable information on othercategories, we could not verify whether our sample was representative of taxpayers in othercategories. However, we can expect that employment status and tax payment history are also
correlated with taxpayer attributes such as gender and annual income. Therefore, while we
acknowledge the limitations, we believe the consistency in two categories can partially justify theclaim that our sample is representative of the invited taxpayers.
We aim to explore how the extent to which taxpayers are willing to pay taxes changes
depending on the perceived fairness between their contributions and the benefits they receive. To
do so, our survey includes a vignette about the targeted sectors of government spending. There are54three treatment groups that provide respondents with information about any of the sectors thatpublic spending targets: (i) infrastructure, (ii) healthcare, and (iii) industrial subsidy. There is also
one control group that does not expose any information about government spending. We randomly
assigned our respondents to either one of the four groups (one control group and three treatmentgroups) and asked questions about their willingness to pay taxes. The exact wording of our vignette
experiment is shown in Figure 3.1. The procedure of random assignment was programmed using
Qualtrics in such a way that all the respondents were equally divided among the groups, to avoid
violating the assumption of independent observations (see Dickel & Graeff, 2018; Gross et al.,2017). To confirm the effectiveness of the randomization, we conducted a balance test by applying
the logit regression with the random assignment of treatment as the dependent variable. The results
generally show no significance for most variables, except the income variable for the infrastructuregroup (Table 3.1), which verifies the successful randomization of our variables across groups.

55

Figure 3.1 Vignette example in the treatment group
The government is currently spending 20% of taxpayers' money on infrastructure such as highways, bridges, andsubways/on healthcare such as hospital and health insurance/on industrial subsidies such as tax holiday and special
loan with low-interest rate to large corporations.
How much are you willing to pay taxes?

1

2

3

4

Not at all

56

5
A great deal

Table 3.1 Balance test of randomization
Infrastructure vs control
Healthcare vs control
Industrial subsidy vs control
Coef
S.E
Coef
S.E
Coef
S.E
Age
0.03
0.21
-0.13
0.22
0.05
0.22
Male
-0.18
0.21
0.27
0.21
0.10
0.21
Income0.48**
0.22
0.05
0.22
0.02
0.22
Major ethnic
0.07
0.20
0.29
0.20
0.25
0.21
Islam
0.28
0.24
0.22
0.24
0.36
0.25
Education-0.37*
0.22
0.10
0.21
0.08
0.22
Employee
-0.33
0.33
-0.19
0.34
-0.38
0.33
Self-employed
-0.05
0.37
0.08
0.38
0.13
0.37
Cons
-0.01
0.41
-0.43
0.41
-0.34
0.43
Log likelihood-297.78-303.57-300.82
Notes: Dependent variable is a binary indicator which equals one if a respondent is assigned to each treatment group.
***p<.01, **p<.05, *p<.157

3.3 Results and discussion
The willingness to pay taxes was measured using a Likert scale ranging from 1 (not at all) to 5 (agreat deal). Table 3.2 shows the summary statistics of our data. The mean of the Likert scale answer
for respondents in the control group is 3.20, while those in the three treatment groups(infrastructure, healthcare, and industrial subsidy) are 3.14, 3.27, and 2.82, respectively. It appears
that the mean of the answer in the industrial subsidy group is the smallest among other groups. We
applied the difference-in-means to confirm whether the differences between groups are statisticallysignificant.
We first examined the difference-in-means in our respondents’ willingness to pay taxes
between the treatment and control groups. The results shown in Table 3.3 indicate that the sectorof public spending targets described in our vignette affected the extent to which our respondents
were willing to pay taxes. The difference-in-means between the industrial subsidy and control
groups is the largest in terms of the magnitude (-0.38 point, p<0.01) among other treatment groups.
This suggests that the exposure to the information about industrial subsidies decreases the Likert
scale measure of respondents’ willingness to pay taxes by 0.38 points. Since the standard deviationof the Likert scale measure is 1.05 (shown in Table 2), the size of this effect is approximately onethird of the standard deviation, which is large enough to claim that it is substantively significant
and meaningful. Meanwhile, exposing the information about government spending on
infrastructure and healthcare sectors does not appear to influence our respondents’ willingness to
pay taxes.
Our results imply that taxpayers tend to view industrial subsidies negatively, which makes
them less willing to pay their taxes. Since industrial subsidies mostly target specific industries,
taxpayers would likely assume that they only benefit large-scale corporations, rather than relatively
small businesses. Such a negative perception of unfair treatment would reduce the motivation to
pay tax among taxpayers. Given the conventional argument that industrial policies help promote a58

country’s economic growth through various channels, particularly in developing countries, ourfinding suggests that industrial subsidies may have negative side effects in terms of the reductionin the willingness to pay taxes. Hence, the government should be cautious of policies targeting
specific groups. In contrast, public spending on infrastructure and healthcare is likely to be widely
accepted among the public because it usually benefits a large population in the country. Thus, suchpolicies do not seem to discourage taxpayers’ motivation to pay their taxes.

59

Table 3.2 Distribution of respondents and answers among groups
Full sample
Control
Infrastructure
Std.
Std.
Std.
N
Mean
Dev.
N
Mean
Dev.
N
Mean
Dev.
All
879
3.11
1.05
220
3.20
1.07
217
3.14
1.00
Age
<=35
516
3.10
1.01
132
3.16
1.07
123
3.12
0.94
> 35
363
3.12
1.11
88
3.26
1.07
94
3.16
1.07
GenderFemale
312
3.04
1.04
80
3.08
1.09
87
3.15
0.98
Male
567
3.14
1.06
140
3.27
1.05
130
3.13
1.01
Income< 4.5 million
373
2.99
1.07
95
3.20
1.01
82
2.89
1.11
> 4.5 million
506
3.19
1.03
125
3.20
1.11
135
3.29
0.89
Ethnic
Major
536
3.11
1.01
126
3.21
0.98
130
3.11
1.01
Minor
343
3.10
1.11
94
3.18
1.18
87
3.18
0.98
Religion
Islam
680
3.06
1.04
162
3.09
1.04
170
3.07
1.04
Others
199
3.26
1.07
58
3.50
1.10
47
3.38
0.80
Education
ESHighSchool
365
3.05
1.02
86
3.29
0.99
101
3.00
0.98
College
514
3.15
1.07
134
3.14
1.11
116
3.26
1.00
Employm
ent
Employee
591
3.13
1.02
157
3.23
1.01
142
3.21
1.00
Self
Employed
172
3.17
1.13
37
3.32
1.20
43
2.91
1.02
Unemployed
116
2.91
1.08
26
2.85
1.19
32
3.13
0.94
Note: Demographic of respondents with the number of respondents in subgroups, mean, and standard deviation

60

Healthcare
N
222

Mean
3.27

Std.
Dev.
0.99

137
85

3.23
3.33

69
153

Industrial subsidy
N
220

Mean
2.82

Std.
Dev.
1.09

0.94
1.07

124
96

2.87
2.76

1.05
1.15

3.25
3.27

0.85
1.05

76
144

2.68
2.90

1.12
1.08

96
126

3.19
3.33

0.98
1.00

100
120

2.68
2.94

1.09
1.09

142
80

3.25
3.29

0.97
1.03

138
82

2.87
2.74

1.05
1.17

173
49

3.25
3.31

0.98
1.04

175
45

2.84
2.76

1.08
1.17

86
136

3.13
3.35

1.05
0.95

92
128

2.80
2.84

1.02
1.15

154

3.19

0.97

138

2.85

1.07

42
26

3.52
3.31

1.11
0.88

50
32

3.00
2.44

1.11
1.11

Table 3.3 indicates that the difference-in-means between the industrial subsidy group and control
group are statistically discernible from zero for all the subgroups of respondents, except for those
who are self-employed or unemployed. All respondents were similarly less willing to pay taxes
when exposed to information about the government programs to disburse industrial subsidies.
Using the results in the third column of Table 3.3, we draw Figure A3.1 which shows the estimateddifference-in-means and their confidence intervals for each subgroup of respondents. The figuresuggests that the industrial subsidy treatment makes non-Muslim respondents much less willing to
pay taxes than Muslim respondents. One possible reason for this is that non-Muslims may believethat the Indonesian government’s policies are unfair and favor Muslims. However, we find no
significant heterogeneity of treatment effect outside of these groups. While a detailed discussionof within-group variation in attitudes toward different types of public spending is not the main
focus of our manuscript, we conducted multivariate regression analysis to see whether the negative
effect of industrial subsidies on willingness to pay taxes is larger for non-Muslims. To do so, weestimated a model with an interaction term between the industrial subsidy treatment variable andthe respondents’ religion variable (1 for Muslims and 0 for others). The results show that theinteraction term’s coefficient is positive and statistically significant, suggesting that the negative
effect of industrial subsidies on willingness to pay taxes is more substantial for non-Muslims.

61

Table 3.3 The difference-in-means between the treatment groups and the control group
Variable
Infrastructure
Healthcare
Industrial subsidy
Diff to Control
Diff to Control
Diff to Control
all respondents-0.0620.066-0.377***(0.099)(0.098)(0.103)<=35-0.0370.067-0.288**Age(0.126)(0.123)(0.133)> 35-0.1020.068-0.501***(0.159)(0.163)(0.164)
female0.074
0.171-0.391**
Gender
(0.160)(0.162)(0.177)male-0.141
0.003-0.376***(0.125)(0.123)(0.126)<4.5 mill-0.310*-0.013-0.520***
Income(0.159)(0.143)(0.150)> 4.5 mill
0.089
0.125
-0.258*(0.125)(0.134)(0.141)
Major ethnic-0.1070.039-0.345***Ethnic(0.124)(0.119)(0.125)
Minor ethnic
0.003
0.107
-0.437**(0.162)(0.170)(0.178)Islam-0.0220.162-0.253**
Religion(0.114)(0.110)(0.115)
Others-0.117-0.194-0.744***(0.191)(0.208)(0.224)High school or below-0.291**-0.163-0.486***
Education(0.145)(0.156)(0.151)
College
0.117
0.211*-0.306**(0.134)(0.126)(0.140)
Employee-0.018-0.041-0.381***(0.116)(0.112)(0.121)
Employment
Self employed-0.417*0.199-0.324status(0.248)(0.260)(0.249)Jobless
0.279
0.462-0.409(0.280)(0.291)(0.302)
Notes: To analyze the individual characteristics, we manipulated the independent variables as follows: age of
respondents (35 or below=0; above 35=1), gender (female=0; male=1), income (below 4.5 million=0; above 4,5
million=1), ethnic group (major ethnic (Java and Betawi)=1; minor ethnic (non-Java and non-Betawi)=0), religion(Islam=1; others =0), education (elementary school-high school=0; college=1), and employment status [[employee(employee=1; non-employee =0), self-employed (self-employed=1; non-self-employed =0)].
Standard errors are in parentheses. ***p<.01, **p<.05, *p<.162

As robustness tests for our findings of the univariate analysis, we performed multivariate
analyses using an ordinary least square (OLS), ordered probit, and multinomial logit regressions,while jointly controlling for the treatment conditions and the sets of individual attributes. Because
the results of all three multivariate analyses are consistent, particularly regarding the effect of eachtreatment on the willingness to pay taxes, we explain our results based on the OLS estimation
model, while the results of the ordered probit and multinomial logit models will be shown in the
appendix (Tables A3.1 and A3.2). Our whole sample is comprised of four groups: (i) control, (ii)infrastructure, (iii) healthcare, and (iv) industrial subsidy. This study applied the OLS regression
over each of the following three subsamples separately. The first subsample consists of the (i)control and (ii) infrastructure groups. The second consists of the (i) control and (iii) healthcare
groups. The third consists of the (i) control and (iv) industrial subsidy groups. As the second
robustness check, since our five-point Likert scale variable is an ordinal variable, we applied anordered probit regression, which is more suitable to analyze an ordinal dependent variable. As thethird robustness check, we applied multinomial logit regression, where we recoded the originalcoding of the five-point Likert scale of the answers (1 - not at all, 5 - a great deal) into a threecategorical variable. Choices 1 and 2 in the original coding were recoded into 1 (as the baseline
category), Choice 3 was recoded into 2, and Choices 4 and 5 were recoded into 3. We confirm theempirical validity of our main results that only industrial subsidy consistently reduces thewillingness to pay taxes.

63

Table 3.4 Regression results of the impact of treatments on people’s willingness to pay taxes
Full sample
Infrastructure
Healthcare
(1)
(2)
(3)
Coef
S.E
Coef
S.E
Coef
S.E
Treatment
Infrastructure
-0.06
0.10
-0.05
0.10
Healthcare
0.06
0.10
0.06
0.10
Subsidy-0.37*** 0.10
Age
0.04
0.08
0.12
0.11
0.09
0.11
Male
0.07
0.08
0.07
0.10
0.07
0.11
Major ethnic
0.06
0.07
0.04
0.10
0.09
0.10
Income
0.14*
0.08
0.11
0.11
-0.00
0.11
Islam
-0.16*
0.09-0.36*** 0.12
-0.23*
0.12
Education
0.01
0.08
-0.07
0.11
0.02
0.11
Employee
0.13
0.12
0.24
0.16
0.17
0.17
Self-employed
0.18
0.13
0.04
0.19
0.34*
0.19
cons
3.00***
0.16
3.161*** 0.21
3.06***
0.21
R-squared
0.043
0.04
0.02
Adj R-Squared
0.031
0.02
0.00
N
879
437
442
Notes: ***p<.01, **p<.05, *p<.164

Industrial subsidy
(4)
Coef
S.E

-0.37***
0.03
0.12
0.14
0.08
-0.22*-0.15
0.41**
0.49**
2.86***

0.10
0.12
0.11
0.11
0.12
0.13
0.12
0.18
0.19
0.23
0.07
0.05
440

The dependent variable is the Likert scale of the answers given by the respondents. The
treatment condition is captured using a binary variable that equals one if a respondent is assigned
to each treatment group. The setting of our experiment introduced three binary variables:
infrastructure (infrastructure group=1, other groups=0), healthcare (healthcare group=1, othergroups=0), and industrial subsidy (industrial subsidy group=1, other groups=0). Table 3.4 displays
the estimated results of the models with all three binary variables (Column 1) and one binary
variable at a time (Columns 2, 3, and 4). These results confirm our finding in the univariate analysis
that industrial subsidies reduce people’s willingness to pay taxes (p<0.01).
In the slippery slope framework, tax compliance can be achieved through two mechanisms:
the power of the authorities, including deterring tax evasion through audits and fines, and trust in
the authorities (Kirchler et al., 2008; Prinz et al., 2014). While both mechanisms are relevant indetermining people’s tax attitudes, our study focuses on the second mechanism—the relationshipbetween trust in authorities and voluntary tax compliance. Based on the historical story of countries
that have collected tax revenue and prospered, the first mechanism relates to the power of theauthorities, which may be achieved by establishing strong tax administration capabilities to detect
tax evasion; and the second mechanism relates to trust in the authorities (Bergman & Steinmo,2018). They discuss the mechanism of how trust can develop to promote willingness to pay taxes.
Trust in authorities is more likely to be generated when governments perform efficiently andeffectively, forming perceptions of fairness and equity among citizens. People perceive fairness
and equity when governments have the ability to provide valuable public goods and services to all
citizens without discriminating against certain segments of society (Bergman & Steinmo, 2018;
Steinmo, 2018).
To explore how the mechanism of public goods and services works to shape people’s
perception of the government, we manipulated the information given to respondents about the
government’s public expenditure. In our study, we provided three different types of public

65spending: infrastructure, healthcare, and industrial subsidies. People are likely to perceive
infrastructure and healthcare services as collective public goods and services (Lieberman, 2009).
If taxpayers believe that these expenditures will benefit not only themselves but also society as awhole, they will establish trust in the authorities and be more willing to pay taxes (Bergman &Steinmo, 2018). However, our study did not find any empirical evidence to support this inIndonesia. In contrast, industrial subsidies targeting specific groups of people are more likely to beconsidered as a form of control of political relations, rather than as public goods and services.
Because they are not public goods and services, people will be concerned about the benefits ofthese subsidies, especially who the beneficiaries are and whether they are beneficial to their groups(Lieberman, 2009). Such perceptions are likely to reduce taxpayers’ trust in the authorities anddiscourage them from paying taxes (Martin et al., 2009).
Our study showed the effect of government policies, particularly those that may beperceived differently by different groups of citizens (such as industrial subsidies), on people’s
willingness to pay taxes compared to other policy conditions in the context of a developing country.
There are specific features of developing countries, such as low transparency in budgetary
information, immature tax systems, and less effective audit systems. In addition, because many
people are less educated, the public may not pay much attention to information about government
budgets and expenditures. Given these situations in developing countries, examining how
information about public spending affects people’s willingness to pay taxes would be importantfor central authorities who seek to increase budget transparency.

3.4 Conclusion
Implementing fiscal policies needs to be accompanied by government accountability to the public,
and people are interested in the relevance and implications of these policies. Some fiscal policies
that broadly benefit people tend to be supported by the public or taxpayers due to their fairness in66

the reciprocity between those who contributed and those who were rewarded. This reciprocal
balancing promotes a positive perception about the government’s responsibility for the prosperityof the people. This fosters cooperative behavior among them, particularly through their tax
payment contributions. Hence, the government needs to adequately address people’s preferences
to improve their motivation to pay taxes.
Given this argument, we conducted a vignette experiment with taxpayers who filed income
tax returns in the Jatinegara Province of Indonesia. We designed this experiment to identify how
people’s willingness to pay taxes responds to information provision on the government’s budget
allocation into three important sectors: (i) healthcare, (ii) infrastructure, and (iii) industrial subsidy.
One of the advantages our research design has over others, such as traditional surveys andlaboratory experiments, is that it minimizes social desirability bias. Social desirability bias is atypical problem when examining sensitive issues, such as people’s tax compliance behavior. The
results of our experiment indicate that taxpayers are not as willing to pay taxes if they learn thatthe government spends a large portion of the budget on industrial subsidies. In contrast, theexposure of information about public spending on infrastructure and healthcare does not affecttaxpayers’ willingness to pay taxes.
These results suggest that the government should be cautious if its fiscal policies target
specific groups. Although such policies may induce various favorable outcomes, such as promoting
income redistribution and protecting infant industries, they could unintentionally entail an adverse
effect on the reduction of tax payment behavior among citizens in the long run. Providing
information about the fairness of fiscal exchange enables the government to not only demonstrateaccountability and transparency, but also generates citizens’ trust in authorities, which is anotherimportant factor of taxpaying behavior.
Our survey participants were recruited from a taxpayers list provided by the tax office.
They consist of those who are registered by themselves or those identified by tax offices through67

administrative monitoring schemes. Since the current tax monitoring scheme cannot detect asignificant portion of non-compliant individuals in Indonesia, our sample does not include potential
tax non-compliers outside of our list; this is a limitation of our study. Future research needs to be
conducted to mitigate the potential problem of using narrower samples by including tax noncompliers into the sample, which could derive further insights into people’s willingness to pay
taxes.

68

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72

APPENDIX

Figure A3.1 Difference-in-means across individual characteristics in industrial subsidy group

Notes: Dots represent the estimated difference-in-means of the answers and lines show the 95% confidence interval.
The vertical axis shows the respondents’ attributes.

73

Table A3.1 Ordered probit model

Treatment
Infrastructure
Healthcare
Subsidy
Age
Male
Major ethnic
IncomeIslam
Education
Employee
Self-employed
/cut1
/cut2
/cut3
/cut3

Full sample
(1)
Coef
S.E

Infrastructure
(2)
Coef
S.E

-0.07
0.07
-0.37***
0.06
0.08
0.05
0.15*
-0.17*
0.02
0.14
0.20
-1.22
-0.55
0.33
1.81

Healthcare
(3)
Coef
S.E

Industrial subsidy
(4)
Coef
S.E

0.10
-0.06
0.10
0.10
0.07
0.10
0.10
-0.36***
0.08
0.14
0.11
0.09
0.11
0.02
0.08
0.07
0.11
0.09
0.11
0.13
0.08
0.03
0.11
0.07
0.11
0.11
0.08
0.11
0.12
0.02
0.11
0.09
0.09
-0.38*** 0.13
-0.27**
0.12-0.25*
0.08
-0.07
0.11
0.01
0.11
-0.13
0.12
0.25
0.17
0.16
0.18
0.38**
0.14
0.06
0.19
0.38*
0.20
0.47**
0.17
-1.34
0.23
-1.23
0.23
-1.07
0.16
-0.80
0.23
-0.67
0.22
-0.49
0.16
0.21
0.22
0.27
0.22
0.42
0.17
1.62
0.24
1.71
0.24
1.83
Log likelihood
1213.647-593.40-602.04
N
879
437
442
Notes: The dependent variable is the willingness to pay taxes, from 1 (not at all) to 5 (a great deal).
***p<.01, **p<.05, *p<.1

74

0.10
0.12
0.11
0.11
0.11
0.13
0.12
0.18
0.19
0.23
0.23
0.23
0.25
-615.91440

Table A3.2 Multinomial logit model
Full sample
Infrastructure
Healthcare
Industrial subsidy
(1)
(2)
(3)
(4)
Coef
S.E
Coef
S.E
Coef
S.E
Coef
S.E
Choice 2Treatment
Infrastructur
e
-0.42
0.26
-0.39
0.27
Healthcare-0.49*
0.27-0.49*
0.27
Subsidy-1.05*** 0.25
-1.10*** 0.26
Age
-0.22
0.20
-0.18
0.29
0.01
0.31
-0.03
0.29
Male
-0.09
0.19
-0.01
0.28
-0.15
0.29
-0.07
0.27
Major ethnic
0.03
0.19
-0.20
0.28
-0.01
0.29
0.32
0.27
Income
0.24
0.20
0.30
0.30
-0.20
0.30
-0.20
0.29
Islam
0.06
0.24
-0.69*
0.38
0.39
0.35
0.14
0.33
Education
-0.04
0.20
-0.27
0.29
0.49
0.30
-0.41
0.29
Employee
-0.11
0.29
0.02
0.42
-0.05
0.45
0.66
0.41
Self-employed
-0.05
0.34
-0.46
0.48
-0.19
0.54
0.86*
0.46
cons
0.79*
0.41
1.54***
0.59
0.39
0.57
0.27
0.55
Choice 3
Treatment
Infrastructure -0.29
0.26
-0.24
0.26
Healthcare
-0.06
0.26
-0.06
-0.06
Subsidy-0.98*** 0.25
-1.02*** 0.25
Age
0.17
0.19
0.36
0.29
0.32
0.32
0.24
0.28
Male
0.16
0.19
0.24
0.28
0.14
0.14
0.21
0.27
Major ethnic
0.16
0.18
0.08
0.28
0.18
0.18
0.47*
0.26
Income
0.23
0.19
0.18
0.29
-0.18
-0.18
0.02
0.28
Islam
-0.32
0.22
-1.05*** 0.37
-0.30
-0.30
-0.42
0.30
Education
0.11
0.19
0.04
0.29
0.22
0.22
-0.29
0.29
Employee
0.32
0.29
0.61
0.43
0.44
0.44
1.10**
0.43
Self-employed
0.49
0.33
0.09
0.48
0.82
0.82
1.32***
0.47
cons
0.29
0.40
0.73
0.59
0.24
0.24
-0.17
0.56
Log likelihood-923.55-450.44-450.67-574.26
N
879
437
442
440
Notes: We recoded the original coding of the Likert scale of the answers (1 - not at all, 5 - a great deal) into threecategorical variable. Choices 1 and 2 in the original dependent variable were recoded into 1 (as the baseline category),
Choice 3 was recoded into 2, and Choices 4 and 5 were recoded into 3.
***p<.01, **p<.05, *p<.175

Chapter 4Which strategies promote attitudes toward income tax? Testing enforcement,
reciprocity, and peer-effect in the field
4.1 Introduction
Identifying the most effective approach to motivate individuals to pay their taxes is one of the key
topics for scholars and governments worldwide (Andreoni et al., 1998). To ensure high taxpaying
behaviors, tax authorities utilize various tax policy strategies from deterrence to moral suasion.
However, the empirical evidence of each policy has not reached the same conclusion. The
questions related to deterrence effects, particularly in the scope of audit probability, are the central
in the tax literature (Andreoni et al., 1998). Some studies argue that deterrence is effective tomotivate taxpaying (Castro & Scartascini, 2015; Pomeranz, 2015), while other studies find that
audit has little effect and may not persistently encourage tax payment (Kastlunger et al., 2009;
Mittone et al., 2017).
Likewise, tax morale also contributes to a significant portion of taxpaying attitudes throughmainly two mechanisms. First, in a reciprocal argument, taxpayers expect that their tax money isspent appropriately by the government. The government provides the population's needs in returnfor the tax they paid (Feld & Frey, 2007). This mechanism will establish trust in the government.
Second, from a peer-effect argument, an individual is more likely to pay taxes if other people pay
taxes. There is a feeling of guilt if an individual behaves differently with others. There is muchevidence that these two mechanisms influence individuals' tax behaviors (Alm et al.,2006; Alm &Torgler, 2006; Glaser & Hildreth, 1999; Hallsworth et al., 2017; Torgler, 2007; Luttmer & Singhal,2014).
Relying upon different tax climates among countries, this study aims to identify the causal
effect of deterrence strategy and non-deterrence strategy on people’ perception of an individual's
taxpaying behavior by conducting a vignette experiment in a developing country, Indonesia. We
76

particularly utilize perceived audit probability as a deterrence strategy and introduce two versionsof the non-deterrence strategy: reciprocal and peer-effect arguments. We analyze the effect ofreciprocity and peer-effect in a developing country where tax evasion is high and willingness to
pay taxes is low, due particularly to low enforcement activities and a low level of trust in thegovernment (Castro & Scartascini, 2015). The developing countries generally indicate the low
performance of the government and its related outcome, including the quality of public goods andservices. In addition, these countries have a limitation to monitoring and detecting non-compliancebehaviors efficiently and effectively. Therefore, with this condition, people are reluctant to pay
taxes. The non-compliance behaviors are rampant since one’s behavior is followed by others, andeventually, this behavior becomes the norm (Andrighetto et al., 2016). On the other hand, in the
countries that successfully generate the willingness to pay taxes, people are willing to pay theirtaxes because they are more likely to be triggered by the quality of public goods and services andinfluenced by their peers (Bergman & Steinmo, 2018; Castro & Scartascini, 2015). In this situation,
the citizens perceive that the government matches their expectations, particularly concerning theprovision of public goods and services. Moreover, the government is also capable of reinforcing
the social norms of compliance in society. Since people already have higher compliance in thesecountries, some field experiments do not find significant results concerning the effect of reciprocity
and peer-effect on people's willingness to pay taxes (Luttmer & Shinghal, 2014).
This study contributes to the growing tax literature in several ways. First, little is known
about the effectiveness of perceived audit probability and moral suasion in improving people’s
perception of tax payment in the context of individual income tax. An exception may include thework of Bott et al. (2020) which analyzes the strategies in the scope of foreign income tax in
Norway. In particular, most empirical researches on the strategies taken by tax authorities discuss
only one particular strategy (Kleven et al., 2011; Lopez-Luzuriaga & Scartascini, 2019; PerezTruglia & Troiano, 2018). Our study provides clear evidence of different effects of audit

77

probability and moral suasion in individual income tax. Second, to the best of our knowledge, nostudies utilize real taxpayers` responses and apply a vignette experiment to explore people’s
perception on tax-paying behaviors of individual income tax in developing countries. Our study
enriches tax literature by utilizing a vignette experiment which is popular in sociology and politicalscience.
We conducted a vignette experiment applying a computer-assisted telephone interviewing(CATI) survey from November 2020 to March 2021. The respondents were individual taxpayersof the Bengkulu Province. We recruited survey respondents in collaboration with the tax authority,
the Directorate General of Taxes (DGT) of the Indonesian government, and obtained responses
from a total of 1,287 taxpayers. Our results find that the deterrence strategy encourages people’s
perception on tax-paying behavior. In addition, we also find that the effect of peer-effectinformation on the perception of an individual’s taxpaying behavior depends on the context of themessages. The perception of an individual taxpaying’s behavior is promoted by the information
indicating that a significant portion of taxpayers honestly pay income taxes (positive peer-effect),
while it is deteriorated by the opposite information indicating that a significant portion of taxpayers
is dishonest (negative peer-effect). Concerning the reciprocal argument, the perception of
taxpaying behavior is weakened by the information indicating governments’ inefficiency inproviding infrastructures and social services (negative reciprocity). On the other hand, theinformation indicating the government’s administrative efforts in improving infrastructures andsocial services (positive reciprocity) does not affect people’s perception on an individual’s tax
paying behaviors.
The remainder of this paper is organized as follows: Section 2 discusses the literature
review, Section 3 provides brief information about the tax system in Indonesia, Section 4 describes
the data, methodology and results, and Section 4 provides the conclusions.

78

4.2 Literature review
4.2.1 Deterrence approach
Allingham & Sandmo (1972) discuss the key components of deterrence: fine rate, audit probability,
tax rate, income level, and taxpayers’ preferences. They argue that the level of tax evasion is highly
correlated with the risk of detection (audit probability), potential loss (fine rate), potential return(tax rate), and risk aversion. In this framework, taxpayers’ attitudes to comply are considered underrational taxpayers who mind the cost-benefit decision (Alm et al., 2012). If they perceive that thepotential return from evading taxes is higher than its potential loss, they will take the risk of being
uncompliant. The probability of tax audit also is taken into account and becomes theirconsideration. If the probability of being caught is high, taxpayers are less likely to engage in tax
evasion (Heinemann & Kocher, 2013).
It is noted that the effect of pecuniary approaches on tax attitudes is often shown with mixed
results (Alm et al., 2012). However, an audit is consistently argued to ensure high tax compliance(Kirchler et al., 2008). A strong and positive effect of audit on tax attitudes is found in many tax
literature (Ali et al., 2001; Alm et al., 1995; Pommerehne & Weck-Hannemann, 1996).
Tax fines is the consequences and results from tax audits, but the relationship between fines
and tax compliance remains unclear. High tax fines give a signal that taxes are hazardous for
taxpayers. The supporters of the positive correlation between tax fines and tax compliance(Friedland et al., 1978; Park & Hyun, 2003) argue that fines interact with higher audit probability(Alm et al., 1995). Yet, low- and high- income respond differently to the amount of tax fines which
contributes to the less salient effect of fines on tax compliance (Ali et al., 2001; Kirchler et al.,2008). The more extreme case that fines encourage tax evasion is observed in several studies. It
seems that either taxpayers look for the benefit from declaring lower tax due in return for highfines that they will be forced to pay later (Schwartz & Orleans, 1967) or tax enforcement increase
the resistance among taxpayers (Fjeldstad & Semboja, 2001).

79

4.2.2 Morale approach
Regardless of the importance of economic consequences of deterrence approach, several criticisms
are addressed that the enforcement solely is not sufficient to explain tax compliance in the realworld (Christian & Alm, 2014). The scholars also recognize the issue of the high cost of
enforcement (Slemrod, 1992), and thus, they consider another possible motivation to enhance tax
compliance. As a result, there is an increasing interest in tax morale to explain the high level ofvoluntary tax compliance.
In the early phase, Schwartz & Orleans (1967) find out that moral suasions are muchstronger than punishment, but this topic is under study. However, during the years, there have beentendencies of stressing tax morale in tax compliance literature. Erard & Feinstein (1994) point out
that other motivations, namely moral sentiment, play an important role in shaping tax compliance.
Therefore, there is an interesting piece of puzzle in this issue, such as the type of moral suasion
that can influence moral sentiment and to what extent the level of compliance can be achieved.
There is much evidence that individuals’ behaviors and their perception on tax paying
behaviors are influenced by the social context in addition to financial context. Social norm
characterizes behaviors that are judged in a similar way and are continued to exist in part in regard
to social acceptance (Alm et al., 2012). They argue that social norm is consistent with a range ofconceptual frameworks from various disciplines, including social influences, compliance, fairness,trust, and tax morale. From a tax compliance point of view, if other people comply, then an
individual will also comply, and thus, the concept of peer effect is likely to work. In this way, there
is a feeling of guilt if an individual behaves differently with others, particularly by cheating his tax.
The social norm is then defined as intrinsic motivation to comply or tax morale because taxpayers'
behavior to comply is generated by the concerns internally and not externally regulated by thegovernment’s enforcement (Alm et al., 2012; Braithwaite & Ahmed, 2005; Orviska & Hudson,2003).

80

A good relationship between government and taxpayers should be maintained in a mutual
environment where both parties are seen as partners. The government provides the needs for the
population in return for the tax that they paid (Feld & Frey, 2007). In the norm reciprocity, a similarcommitment and expectation from both parties are required and this is more important than a legal
regulation (Alm et al., 2012). Here, taxpayers expect that their tax money is spent appropriately by
the government. If the government spends the tax money wisely, trust in the government is more
likely to increase. On the other side, the government trusts the taxpayers that they contribute to theprovision of public goods and services by paying tax honestly. Any mistrust from each side will
discourage the psychological contract of this relationship.
Several studies investigate the existence of tax morale, including social norm (or peereffect) and the benefit from paying taxes that taxpayers receive in the form of public goods andservices (reciprocity) in tax compliance with mixed results. Hallsworth et al. (2017) show thatsocial norms and a positive reciprocity message work to accelerate tax payments. Bott et al. (2020)
report that morale letters are only effective in increasing the amount of tax payment and robust
across various groups of people. However, some studies show the ambiguity of peer effectinformation on an individual’s compliance (Alm et al., 2017; Castro & Scartascini, 2015). Theysuggest that the various factors, including information context, respondents, and methodology,
contribute to these results.

4.3 Empirical analysis
4.3.1 Individual income tax
This study focuses on taxes on individuals, particularly income tax, among various formsof taxes in Indonesia. Income tax is collected using a self-assessment system. There are two typesof individual taxpayers: self-employed individuals and employees. Self-employed individual
taxpayers calculate the amount of their own taxes and report it to the tax office. On the other hand,81for employees, income tax is calculated and paid by their employers from their salary or wage,
using the withholding tax system. At the same time, employees often receive additional income
from their own business activities in addition to their salaries or wages. Thus, all employees needto report incomes from their employers and their additional income to calculate the total amountof income tax they owe on their tax returns. However, due to the lack of third-party reporting tocapture additional incomes from their business activities, taxpayers might not report all of theirincome on their tax returns, making honesty and willingness to pay taxes crucial for individual tax
collection.
4.3.2 The vignette experiment
The vignette experiment describes brief scenarios which consist of dimensions and levels tomanipulate respondents’ perceptions. In our design, we presented the scenarios of hypotheticalprofit of a given fictional subject to all respondents. In addition, we manipulated the scenarios byadding several dimensions and several levels within a dimension. Specifically, we constructed
three dimensions. The first and second dimensions correspond to two fictional subjects'
characteristics: gender and ethnicity. There are two levels for gender (male/female) and ethnicity(Chinese/non-Chinese). We presented the first and the second dimensions to all respondents. The
third dimension corresponds to the government’s strategies: no-condition, perceived audit
probability, reciprocity, and peer effect. For the no-condition strategy, we did not present any
information of the government’s strategies to a respondent. For the perceived audit probability
strategy, we considered two levels and randomly presented a respondent with one of two audit
probabilities, 5 percent (low probability) and 40 percent (high probability). Concerning thereciprocity strategy, we considered two levels and randomly presented a respondent with one of
two types of information: one indicating high governments’ administrative efforts with substantial
improvement of infrastructure and social service (positive reciprocity) and the other indicating
governments’ inefficiency with less improvement of infrastructure and social service (negative82

reciprocity). Regarding the peer effect strategy, we also considered two levels and randomly
presented one of two types of information: one indicating that a significant portion of taxpayers
pays income taxes (positive peer-effect) and the other indicating that a significant portion of
taxpayers does not pay income taxes (negative peer-effect). Thus, for the third dimension, we haveseven levels and we presented only one out of two audit probabilities strategies, two reciprocity
strategies, or two peer-effect strategies. From our design, we have 28 vignette combinations (2 x 2x 7). After these scenarios, we then asked all respondents to provide their opinions on the likelihoodof whether the fictional subject paid income tax into a 10-point Likert scale (0 = "not at all" to 10= "very sure").1 By asking the respondents’ perception of other people’s behaviors, the vignette
design tries to reduce the pressure among respondents to answer socially acceptable, and thus, it
minimizes socially desirable responses (Blum et al., 2019; Finch, 1987).
We designed the vignette such that each level of dimension is randomly assigned to each
respondent for each round (see Figure 4.1). The random assignment was programmed using
Qualtrics in such a way that all the respondents were divided equally for all vignette combinations.
To confirm the effectiveness of the randomization procedure, we conducted a balance test of
randomization by applying the logit regression with the random assignment of the levels of first
dimension (male/female) and second dimension (Chinese/non-Chinese) as dependent variable. For
the third dimension (strategies), we checked the randomization between one of the three strategies(deterrence, reciprocity, or peer-effect) and no-condition, and between high probability and low
deterrence, between positive reciprocity and negative reciprocity, and between positive peer-effectand negative peer-effect.2

12

See appendix A1 for the vignette’s wording.
See appendix A2 for the balance test randomization.

83

Figure 4.1 The vignette's design.

No-condition
Audit Probability

Male/Female

NonChinese/Chinese

Reciprocity

Peer-effect

84

5%

40%
High efforts and highquality
Inefficiency and low
quality
Positive information
Negative information

We obtained approval from the Directorate General of Taxes (DGT) to access the taxpayers'list. The population included all 24,608 taxpayers regardless of their tax payments and filing status.
In our sample, we excluded some categories (non-effective taxpayers and taxpayers with inaccurate
phone numbers) as these taxpayers are unlikely to be contacted. Non-effective taxpayers do notneed to file tax returns and pay taxes due to factors such as unknown addresses or having gone outof business. However, these taxpayers’ statuses can be switched into effective taxpayers if thesefactors change, either by the taxpayer’s requests or by tax officers’ requests. This procedure
resulted in 12,134 effective taxpayers with complete phone numbers. We experimented by sending
messages to all 12,134 taxpayers linked to the Qualtrics platform in which we embedded thevignettes. We assigned vignettes in three rounds for each participant, and thus, with 1,287
respondents, we obtained 3,861 vignettes. The survey was conducted from November 2020 toMarch 2021. Our population was taxpayers in Bengkulu province, covering the capital city of
Bengkulu and the other three regions. This province has nine regencies and an independent city of
Bengkulu. The other two tax offices administer taxpayers in the six remaining regencies in theprovince.
To check whether our sample represents the population of individual taxpayers in theprovince, we compared our sample to the population of individual taxpayers in two categories,
gender and age. The proportion of males is 64 %, similar to the taxpayers’ population which is60%. Regarding age, the proportion of taxpayers between 17 and 30 years old is very similar inboth our sample and the population, which is 26%. Therefore, we believe that our sample could
represent individual taxpayers’ population, at least in these two categories. Taxpayers’ data
provided by tax offices did not include other individual characteristics, and thus we could not claim
whether our sample may represent taxpayers’ population in regard to other categories. The
distribution of the sample is displayed in Table 4.1.

85

Table 4.1 Summary statistics
Variables
Respondent’s age (in years)
Respondent’s gender (0= female, 1=male)
Respondent's ethnic
Jawa
Batak
Sunda
MaduraBetawiOther ethnic
Income(0= below 4.5 mil, 1= between 4.5 mil to 15 mil,
2= above 15 mil)Religion
Islam
Christian
Buddhism
Hinduism
Other religions
Employment status
Employee
Self employed
Unemployment
Education(0=ES, 1=HS, 2= Bachelor”s degree, 3=
Graduate degree)

Obs
3,861
3,861

Mean
32.68
0.60

SD
10.92
0.49

Min
0
0

Max
69
1

3,861
3,861
3,861
3,861
3,861
3,861
3,861

0.16
0.05
0.03
0.01
0.01
0.68
0.77

0.37
0.21
0.18
0.12
0.10
0.47
0.62

0
0
0
0
0
0
0

1
1
1
1
1
1
2

3,861
3,861
3,861
3,861
3,861

0.78
0.04
0.02
0.03
0.02

0.42
0.21
0.15
0.17
0.16

0
0
0
0
0

1
1
1
1
1

3,861
3,861
3,861
3,861

0.70
0.17
0.06
2.74

0.46
0.38
0.24
0.69

0
0
0
0

1
1
1
3

86

4.3.3 Results
Data gathered via vignette experiment is hierarchically nested because the same participant gives
three vignettes' judgments. To address this, we applied OLS regression with clustered standard
error. The results of the OLS models are displayed in Table 4.2. We use several individual
characteristics in our model. To measure the variables, we reconstruct the data as follows: gender(male=1; female=0), ethnic groups [Jawa (Jawa=1; non-Jawa =0), Batak (Batak=1; non-Batak=0),
Sunda (Sunda=1; non-Sunda =0), Madura (Madura=1; non-Madura =0), Betawi (Betawi=1; nonBetawi =0)], income (below 4.5 mil=0; between 4.5 mil and 15 mil=1; above 15 mil=2), religion[Islam (Islam=1; non-Islam =0), Christian (Christian=1; non-Christian =0), Buddhism(Buddhism=1; non-Buddhism =0), Hinduism (Hinduism=1; non-Hinduism =0),] education(elementary school =0; high school=1; bachelor’s degree=2; graduate degree=3), employment
status [employee (employee=1; non-employee =0), self-employed (self-employed=1; non-selfemployed =0)].

87

Table 4.2 OLS
Models
DV: The likelihood to pay
Chinese
Male
Audit probability
High - 40%-

Low - 5%

Reciprocity
positive-

Negative

Peer-effectPositive-

Negative

R2
Observations
Number of groups
Individual attributes
Models(1)
Coef-0.15*(0.08)
0.03(0.08)(2)
Coef-0.16*(0.08)
0.04(0.08)

2.32***(0.16)
1.41***(0.14)

2.15***(0.16)
1.26***(0.14)-0.07(0.17)-0.75***(0.16)-0.19(0.16)-0.91***(0.15)

0.95***(0.14)-0.38**(0.15)
0.12
3,861

0.79***(0.14)-0.53***(0.15)
0.16
3,861

No
OLS
(clustered std
error)Yes
OLS(clustered std
error)

Notes: *p<0.1, **p<0.05, ***p<0.01.
Reference categories: no conditions, female, non-Chinese, other ethnicities, other religions, and unemployment.
Full regressions are in Table A4.5.

88

The coefficient can be interpreted as the absolute changes of the dependent variable (theperception on the likelihood of paying income tax). In the first column (model 1), we run a
regression with vignette dimensions only, while in the second column (model 2), we controlled for
respondents' attributes.
First, as suggested by Alm and Malézieux (2021), we found that with both high and low audit
probabilities approaches, people perceive that other people are more likely to pay tax compared tothe control group, significantly at the 1% level. In particular, it was clear that the effect of highaudit probability (40%) on the perception on tax-paying behavior was larger than low audit
probability (5%). In other words, people’s perception on tax-paying behaviors were enhanced
significantly by higher audit probability information. Second, interestingly, the information
regarding the high administrative efforts of government and the substantial improvement of theinfrastructure and social services does not affect people’s perception on tax-paying behavior.
Perhaps some people did not believe the information presented about the high efforts of thegovernment and the improvement of infrastructure and social services. However, the information
regarding the inefficiency of government and less improvement of the infrastructure and social
services negatively affected the perception on tax-paying behaviors, significant at a 1% level.
Third, similar to Hallsworth et al. (2017), the information on positive peer-effect significantly
affected people’s perception on tax-paying behavior positively, and it was 0.6 points larger thanthe control group. On the other hand, the negative peer-effect information negatively affected
people’s perception on tax-paying behavior. It was 0.6 points smaller than the control group. These
results suggest that if a taxpayer believes that other taxpayers pay their taxes, an individual isperceived be more likely to pay its tax, vice versa. From model 2 of Table 4.2, we construct Figure
A4.1, which clearly shows the estimated values and its confidence intervals for all conditions. This
study also revealed that Chinese were perceived to have a lower likelihood to pay tax than nativeIndonesian and males’ attitudes in tax-paying were not perceived differently than females’ attitudes.

89

As robustness tests for our main findings, we performed random intercept regression(columns 3 and 4) and multilevel mixed-effect ordered logistic regression (columns 5 and 6) asshown in Table A4.4 (for full regression, see Table A4.5). Our robustness regressions mainly
support the main findings of the OLS regression. One small difference is that positive reciprocity
negatively affect people’s perception on tax-paying attitudes in the random intercept model andmulti-level ordered logit.

5 Conclusion
Analyzing various strategies to improve tax payment is crucial for tax authorities, particularly indeveloping countries. We employ a vignette experiment, where we inform different strategies totaxpayers.
Our results show that the deterrence strategy with perceived audit probability is consistentin pursuing higher perception of the people on tax payment. Intuitively, the negative reciprocity
messages discourage the perception on tax payment and the peer-effect messages affect people’s
perception on tax payment behavior depending on the context of the message.
The results clearly will help the Directorate General of Taxes (DGT). Our results suggestthat Indonesia’s tax authority needs to employ enforcement and positive peer-effect information
because it is highly effective in pursuing high tax-paying behavior in Indonesia. However, thegovernment should bear in mind that societal benefit information may induce the opposite results.
Therefore, this information should carefully be applied to minimize an adverse effect on people’s
attitudes toward tax payment.

90

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APPENDIX
A1. Vignettes' wordings and questions
1. Base/no condition.
Imagine Mr./Ms. A/B/C/D run a family business in Bengkulu. Last year, he/she earned enoughprofit. Thus, he/she should pay his/her income tax.
How likely does he/she pay income tax this year?
(The answer is a scale from 0 (not at all) to 10 (very sure).
2. Audit probability.
Imagine Mr./Ms. A/B/C/D run a family business in Bengkulu. Last year, he/she earned enoughprofit. Thus, he/she should pay his/her income tax.
In the beginning of this year, tax office announced that they will audit on individual taxpayers.
If he/she is identified by tax office that he/she cheats on his/her income tax, he/she will bepunished by fined and penalty. There is a probability of 5%/40% that he/she is being audited.
How likely does he/she pay income tax this year?
(The answer is a scale from 0 (not at all) to 10 (very sure).
3. Reciprocity.
Imagine Mr./Ms. A/B/C/D run a family business in Bengkulu. Last year, he/she earned enoughprofit. Thus, he/she should pay his/her income tax.
Due to the government's administrative efforts/inefficient government, tax revenue has/has
not been efficiently used, so that there has been a substantial/less improvement of
infrastructure (such as high/low quality of the highways and subways) and social services (suchas large/small coverage of medical hospitals and national insurance programs). If/Even he/she
pays income tax, he/she contributes/does not contribute to the socio-economic development of
the country.
How likely does he/she pay income tax this year?
(The answer is a scale from 0 (not at all) to 10 (very sure).
4. Peer-effect.
Imagine Mr./Ms. A/B/C/D run a family business in Bengkulu. Last year, he/she earned enoughprofit. Thus, he/she should pay his/her income tax.
Recent researches confirmed that a significant portion of taxpayers pays/do not pay theirincome taxes.
How likely does he/she pay income tax this year?
(The answer is a scale from 0 (not at all) to 10 (very sure).

95

A2. Balance test of randomization.
Table A4.1 Balance test of randomization - Gender and Ethnicity
Variables
GenderEthnicity
Male vs. Female
Chinese vs. Non-Chinese
Coef
s.e
Coef
s.e
Respondent’s age
-0.00
0.00
0.00
0.00
Respondent’s gender
0.15**
0.07
0.03
0.07
Respondent's ethnic
0.29
0.33
-0.13
0.33
Jawa
0.35
0.37
-0.34
0.36
Batak
0.33
0.37
-0.38
0.37
Sunda
0.43
0.42
-0.25
0.42
Madura
0.37
0.46
0.10
0.46
Betawi
-0.03
0.27
0.10
0.27
Other ethnic
Income
-0.02
0.07
0.11*
0.07
Religion
0.14
0.18
-0.09
0.18
Islam
-0.02
0.24
0.22
0.24
Christian
0.10
0.28
-0.23
0.28
Buddhism
0.03
0.26
-0.38
0.26
Hinduism
0.21
0.33
-0.21
0.32
Other religions
Employment status-0.51*
0.28
0.37
0.28
Employee
-0.36
0.29
0.34
0.29
Self employed
-0.31
0.31
0.32
0.31
Unemployment
Education
0.08
0.05
-0.06
0.05
Log likelihood-2668.14-2668.44
Notes: *p<0.1, **p<0.05, ***p<0.01.

96

Table A4.2 Balance test of randomization – treatment groups vs control group
Variables
Deterrence vs. control
Reciprocity vs. control
Coef
s.e
Coef
s.e
Respondent’s age
0.02
0.00
-0.01
0.06
Respondent’s gender-0.18*
0.10
0.02
0.10
Respondent's ethnic
0.39
0.49
0.05
0.50
Jawa
0.16
0.54
0.17
0.53
Batak
0.16
0.53
-0.03
0.54
Sunda
0.47
0.59
-0.18
0.62
Madura
-0.21
0.67
-0.03
0.63
Betawi
0.47
0.48
0.15
0.49
Other ethnic
Income
0.05
0.09
0.09
0.09
Religion
0.16
0.24
0.06
0.24
Islam
0.25
0.35
0.39
0.32
Christian
0.48
0.41
0.34
0.41
Buddhism
0.19
0.37
-0.10
0.38
Hinduism
0.42
0.37
0.10
0.38
Other religions
Employment status
-0.28
0.39
0.01
0.42
Employee
-0.36
0.41
-0.06
0.43
Self employed
-0.05
0.44
0.40
0.46
Unemployment
Education
-0.11
0.07
-0.11
0.07
Log likelihood-1300.88-1296.63
Notes: *p<0.1, **p<0.05, ***p<0.01.

97

Peer-effect vs. control
Coef
s.e
-0.01
0.00
-0.12
0.10
0.48
0.48
0.08
0.15
-0.24
0.61
0.09

0.49
0.54
0.54
0.62
0.68
0.48
0.09

0.36
0.51
0.73*
0.67*
0.21

0.26
0.34
0.42
0.37
0.39

-0.46
-0.57
-0.21
-0.13*-1296.74

0.39
0.41
0.44
0.07

Table A4.3 Balance test of randomization – between levels of the treatment groups
Variables
Audit probability
Reciprocity
Peer-effectHigh vs. Low
Positive vs. Negative
Positive vs. Negative
Coef
s.e
Coef
s.e
Coef
s.e
Respondent’s age
0.01
0.01
0.00
0.01
-0.01
0.01
Respondent’s gender
-0.11
0.14
-0.12
0.15
0.10
0.14
Respondent's ethnic
Jawa
1.10
0.73
0.10
0.74
1.10
0.72
Batak
1.88**
0.83
-0.30
0.78
0.82
0.79
Sunda
1.27
0.79
1.49*
0.81
0.76
0.80
Madura
1.48*
0.87
0.22
0.93
2.00**
0.98
Betawi
1.56
1.06
1.28
0.96
2.56*
1.31
Other ethnic
0.08
0.51
0.69
0.54
-0.78
0.59
Income
-0.19
0.13
-0.16
0.14
-0.29**
0.14
Religion
Islam
-0.11
0.35
0.34
0.36
-0.57
0.39
Christian-0.96*
0.55
0.78*
0.47
-0.75
0.51
Buddhism
-0.71
0.58
0.56
0.56
-0.32
0.57
Hinduism
0.08
0.52
0.52
0.56
-0.79
0.52
Other religions
1.02
0.71
0.39
0.73
0.87
0.71
Employment status
Employee
-0.74
0.56
-0.92
0.62
-0.38
0.55
Self employed
-0.61
0.58
-1.00
0.65
-0.58
0.58
Unemployment
-0.94
0.63
-0.98
0.67
-0.56
0.62
Education
0.06
0.10
-0.03
0.10
0.11
0.10
Log likelihood-643.36-636.12-643.70
Notes: *p<0.1, **p<0.05, ***p<0.01.

98

A3. The effect of each treatment on the likelihood to pay tax
Figure A4.1 The effect of each treatment on the likelihood to pay tax.

Notes: The dots are the coefficients of the treatments, and the lines show the 95% confidence intervals from theregression model in column 2 of Table 4.2.

99

Table A4.4 Robustness check – random intercept model and multi level ordered logit
Models
(1)
(2)
(3)
(4)
(5)
DV: The likelihood to pay Coef
Coef
Coef
Coef
Coef
Chinese-0.15*-0.16*-0.19*** -0.19*** -0.20***(0.08)(0.08)(0.07)(0.06)(0.07)
Male
0.03
0.04
-0.04
-0.03
-0.01
(0.08)(0.08)(0.07)(0.06)(0.07)
Audit probability
2.32***
2.15***
2.11***
2.06***
2.43***High - 40%(0.16)(0.16)(0.12)(0.12)(0.14)
1.41***
1.26***
1.16***
1.11***
1.23***
Low - 5%(0.14)(0.14)(0.11)(0.11)(0.12)
Reciprocity
-0.07
-0.19
-0.32*** -0.37*** -0.43***
positive(0.17)(0.16)(0.12)(0.12)(0.12)-0.75***-0.91***-0.94***-0.99***-1.13***
Negative(0.16)(0.15)(0.11)(0.11)(0.12)
Peer-effect
0.95***
0.79***
0.67***
0.62***
0.67***
Positive(0.14)(0.14)(0.11)(0.11)(0.12)-0.38**-0.53*** -0.57*** -0.61*** -0.69***
Negative(0.15)(0.15)(0.11)(0.11)(0.12)
R2
0.12
0.16
Observations
3,861
3,861
3,861
3,861
3,861
Number of groups
1,281
1,281
1.281
Individual attributes
No
Yes
No
Yes
No
ModelsOLS
OLS
RandomRandom multiintercept intercept level
orderedlogit
Notes: *p<0.1, **p<0.05, ***p<0.01.

(6)
Coef
-0.20***(0.07)-0.01(0.07)
2.38***(0.13)
1.20***(0.12)-0.46***(0.12)-1.19***(0.12)
0.63***(0.12)-0.72***(0.12)
3.861
1.281
Yes
multilevel
orderedlogit

A4. Full regression of Table 4.2 and Table A4.4.
Table A4.5 Full regression of the models in Table 4.2 and Table A4.4
Models(1)(2)(3)
DV: The likelihood to pay Coef
Coef
Coef
Vignettes (Level 1)
Chinese-0.19***-0.19***-0.15*(0.07)(0.06)(0.08)
Male
-0.04
-0.03
0.03
(0.07)(0.06)(0.08)
Audit probability
2.11***
2.06***
2.32***High - 40 %(0.12)(0.12)(0.16)
1.16***
1.11***
1.41***
Low - 5 %(0.11)(0.11)(0.14)
Reciprocity-0.32***-0.37***-0.07
Positive(0.12)(0.12)(0.17)-0.94***-0.99***-0.75***
Negative(0.11)(0.11)(0.16)
Peer-effect
0.67***
0.62***
0.95***
Positive(0.11)(0.11)(0.14)-0.57***-0.61***-0.38**
Negative(0.11)(0.11)(0.15)
Respondents (Level 2)Age
0.02***(0.01)

100

(4)
Coef

(5)
Coef

(6)
Coef

-0.16*(0.08)
0.04(0.08)-0.20***(0.07)-0.01(0.07)-0.20***(0.07)-0.01(0.07)

2.15***(0.16)
1.26***(0.14)

2.43***(0.14)
1.23***(0.12)

2.38***(0.13)
1.20***(0.12)-0.19(0.16)-0.91***(0.15)-0.43***(0.12)-1.13***(0.12)-0.46***(0.12)-1.19***(0.12)

0.79***(0.14)-0.53***(0.15)

0.67***(0.12)-0.69***(0.12)

0.63***(0.12)-0.72***(0.12)

0.02**(0.00)

0.03***(0.01)

Male
Jawa
Batak
Sunda
MaduraBetawi
IncomeIslam
Christian
Buddhism
Hinduism
Employee
Self employed
Education
R2
Intercept
Observations
Number of groups
Models

0.12
5.41***(0.09)
3,861
1,281
Randomintercept

0.03(0.13)
0.43***(0.16)
0.10(0.34)-0.63*(0.33)-0.10(0.49)-0.20(0.59)-0.35***(0.11)
0.46**(0.22)
0.64*(0.38)
0.60(0.45)
0.12(0.41)
0.31(0.21)-0.00(0.25)-0.05(0.09)
0.16
4.58***(0.35)
3,861
1,281
Randomintercept

0.03(0.12)
0.36**(0.18)
0.08(0.28)-0.64***(0.28)-0.11(0.28)-0.21(0.51)-0.34***(0.12)
0.41**(0.19)
0.60**(0.30)
0.53*(0.31)
0.06(0.32)
0.30**(0.24)-0.00(0.27)-0.02(0.10)
5.19***(0.12)
3,861

4.40***(0.41)
3,861

OLS

OLS

Notes: *p<0.1, **p<0.05, ***p<0.01.

101

0.06
(0.15)
0.56***(0.20)
0.14(0.41)-0.65(0.40)-0.20(0.59)-0.18(0.72)-0.45***(0.14)
0.72***(0.27)
0.88*(0.46)
0.90(0.55)
0.32(0.49)
0.51**(0.26)
0.11(0.30)-0.05(0.11)

3,861
1.281
multilevel
ordered
logit

3.861
1.281
multi-level
orderedlogit

Chapter 5
Conclusion

Tax evasion is a sensitive problem at the individual level. Since taxpayers have a motivation tohide their tax evasion behavior, identifying their true behavior can be a crucial challenge forresearchers as well as tax regulators. This is related to social desirability bias, where respondents
attempt to answer survey questions in a socially desirable or acceptable manner, instead of
revealing their actual opinions or behavior. In the context of taxation, this bias emerges when
taxpayers pretend to meet their obligations by underreporting their incomes to the tax office. To
identify the characteristics of taxpayers who engage in tax evasion behavior, this study mitigated
the influence of social desirability bias by conducting a list experiment in Jakarta, Indonesia. The
univariate analysis revealed that 13.4 percent of taxpayers have cheated on their taxes by
underreporting their income on their tax returns. The results also uncovered clear evidence that tax
evasion behavior varies depending on individual characteristics, such as age, gender, ethnicity, andemployment status. The multivariate analysis generally confirmed the findings from the univariate
analysis, though some differences found in the univariate analysis (such as those between religious
groups and education levels) disappeared in the multivariate analysis.
Our list experiment outcomes may still underestimate the proportion of taxpayers who haveengaged in tax evasion behavior. In a developing country like Indonesia, the percentage oftaxpayers who actually cheated on their taxes could be larger than estimated in this study becauseof weak auditing capacity and legal system. However, we believe that our study has important
implications for taxation policy because our results help identify potential targets for tax auditing
to overcome the issue of a government’s limited institutional capacities. Given that our results
indicate that taxpayers who are old, male, corporate employees, and members of a certain ethnic102

group tend to exhibit relatively low tax compliance, one possible tax policy could be for the DGT
to cluster these groups of taxpayers as potential targets for tax auditing.
However, the DGT currently does not have all the necessary information on individual
taxpayers due to constraints on its taxpayer database and administrative capacities. To address thispractical limitation, the DGT needs to collect the necessary information on individual taxpayers bychanging its taxpayer database structure and administrative management while at the same time
carefully protecting taxpayers’ privacy.
We believe that the relationship between tax evasion and individual characteristics foundin our study would be useful information for both researchers and tax authorities who are interested
in designing effective tax policies and auditing schemes to improve governance and revenue
collection. At the same time, the ethical issues involved in targeting specific groups in the tax
auditing process are also a matter of concern. The government and tax authorities need to be awareof these and set clear rules for the implementation of auditing and the appropriate handling of
personal data.
Implementing fiscal policies needs to be accompanied by government accountability to the
public, and people are interested in the relevance and implications of these policies. Some fiscal
policies that broadly benefit people tend to be supported by the public or taxpayers due to theirfairness in the reciprocity between those who contributed and those who were rewarded. This
reciprocal balancing promotes a positive perception about the government’s responsibility for theprosperity of the people. This fosters cooperative behavior among them, particularly through theirtax payment contributions. Hence, the government needs to adequately address people’s
preferences to improve their motivation to pay taxes.
Given this argument, we conducted a vignette experiment to identify how people’s
willingness to pay taxes responds to information provision on the government’s budget allocation
into three important sectors: (i) healthcare, (ii) infrastructure, and (iii) industrial subsidy. The

103

results of our experiment indicate that taxpayers are not as willing to pay taxes if they learn thatthe government spends a large portion of the budget on industrial subsidies. In contrast, theexposure of information about public spending on infrastructure and healthcare does not affecttaxpayers’ willingness to pay taxes.
These results suggest that the government should be cautious if its fiscal policies target
specific groups. Although such policies may induce various favorable outcomes, such as promoting
income redistribution and protecting infant industries, they could unintentionally entail an adverse
effect on the reduction of tax payment behavior among citizens in the long run. Providing
information about the fairness of fiscal exchange enables the government to not only demonstrateaccountability and transparency, but also generates citizens’ trust in authorities, which is anotherimportant factor of taxpaying behavior.
Our survey participants were recruited from a taxpayers list provided by the tax office.
They consist of those who are registered by themselves or those identified by tax offices throughadministrative monitoring schemes. Since the current tax monitoring scheme cannot detect asignificant portion of non-compliant individuals in Indonesia, our sample does not include potential
tax non-compliers outside of our list; this is a limitation of our study. Future research needs to be
conducted to mitigate the potential problem of using narrower samples by including tax noncompliers into the sample, which could derive further insights into people’s willingness to pay
taxes.
Identifying an effective approach to motivate individuals to pay their taxes is one of the
key topics for scholars and governments worldwide. To ensure high taxpaying behaviors, tax
authorities utilize various tax policy strategies from deterrence to moral suasion. However, theeffect of each policy varies. Therefore, analyzing various strategies to improve tax payment is
crucial for tax authorities. To do this, we employ a vignette experiment, where we inform different
strategies to taxpayers.

104

Our results show that the deterrence strategy with perceived audit probability is consistentin pursuing higher tax payment. While the two types of reciprocity messages discourage tax
payment, the peer-effect message affects tax payment behavior depending on the context of themessage.
The results clearly will help the Directorate General of Taxes (DGT). Our results suggestthat enforcement and positive peer-effect information are effective in pursuing high taxpaying
behavior. In contrast, societal benefit information may induce different results. Therefore, thisinformation should carefully be applied to minimize an unexpected effect on people’s attitudes
toward tax payment.

105