Tax complexity and corruption: An analysis of Latin American countries

ABSTRACT

The objective of this article was to identify the relationship between tax complexity and corruption in Latin American countries. The relationship between tax complexity and corruption has been demonstrated in previous studies. However, no study has analyzed this relationship considering five dimensions of corruption for the Latin American context. The study therefore fills a gap and contributes to the study of the phenomenon by identifying the correlations between different representations of corruption and tax complexity in Latin American countries. The study contributes to government agendas and actions to simplify and modernize the tax system. Moreover, corruption is a long-standing problem in Latin America. Therefore, understanding and discussing it is a fundamental step for academia to use its expertise to support political, cultural and social change. This study contributes by providing evidence on the characteristics of the tax system that Latin American countries should act on to reduce its complexity in order to achieve greater social justice and reduce corruption. The generalized method of moments (GMM) model was used to regress tax complexity, measured by World Bank variables, and corruption, measured by the Corruption Perception Index and four of its constituent constructs, from 2005 to 2019. The results suggest that countries with higher levels of tax complexity have higher levels of corruption. Moreover, countries with higher tax rates on profits and more separate taxes also have higher corruption rates on average. Furthermore, countries with higher levels of democratic accountability have lower levels of corruption. This research contributes to the advancement of the literature by highlighting the phenomenon, relying on the methodologies, variables and premises adopted by the main investigations carried out in the field, in the light of the theory of fiscal illusion.

Keywords:
tax complexity; corruption; Latin America; theory of fiscal illusion; GMM

RESUMO

O objetivo deste artigo foi identificar a relação entre a complexidade tributária e a corrupção nos países da América Latina. A relação entre complexidade tributária e corrupção foi demonstrada em estudos anteriores. Todavia, nenhum estudo analisou essa relação considerando cinco dimensões da corrupção para o contexto da América Latina. Assim, o estudo preenche uma lacuna, contribuindo para o aprofundamento do fenômeno investigado ao identificar as correlações entre diferentes representações da corrupção e a complexidade tributária dos países latino-americanos. Este estudo auxilia agendas e ações governamentais de simplificação e modernização do sistema tributário. Além disso, a corrupção é um problema antigo na América Latina. Portanto, ao entendê-lo e discuti-lo, mostra-se uma etapa fundamental para que a academia possa usar sua expertise no apoio à transformação política, cultural e social. Este estudo contribui ao fornecer indícios sobre em quais características do sistema tributário os países da América Latina devem atuar, visando reduzir sua complexidade, buscando maior justiça social e redução da corrupção. Adotou-se o modelo generalized method of moments (GMM) para regredir a complexidade tributária, mensurada por variáveis do World Bank e a corrupção pelo Corruption Perception Index e por quatro de seus construtos formadores, no período de 2005 a 2019. Os resultados sugerem que países com um aumento nos níveis de complexidade tributária apresentam maior corrupção. Ademais, países com maiores alíquotas de tributos sobre o lucro e com mais tributos distintos também têm, em média, maiores índices de corrupção. Adicionalmente, os países com maiores níveis de responsabilidade democrática apresentaram menores níveis de corrupção. Esta investigação contribui para o avanço da literatura, enfatizando o fenômeno, apoiando-se nas metodologias, variáveis e premissas adotadas pelas principais investigações realizadas na área, à luz da teoria da ilusão fiscal.

Palavras-chave:
complexidade tributária; corrupção; América Latina; teoria da ilusão fiscal; GMM

1. INTRODUCTION

Corruption is a global phenomenon that has received much attention in academic, political and media circles (Liu & Feng, 2015). It is defined as the abuse of public power for private gain (Ajaz & Ahmad, 2010; Tanzi, 1998). This practice, which has several dimensions, undermines citizen trust, weakens democracy, harms economic development and exacerbates inequality, poverty, social division and the environmental crisis (International Transparency, 2021). Studies have shown that various factors influence corruption, including complex tax systems (Belitski et al., 2016; Tanzi, 1998).

The relationship between corruption and complex tax systems is endogenous. On the one hand, corruption occurs more creatively through the legislative process, as appointed parliamentarians can use their power to create oligopolies or act in favor of certain companies or economic groups (Di Vita, 2021). In addition, tax officials have discretionary power in the application of tax laws (Belitski et al., 2016). Thus, tax authorities can use legislation to create excessive bureaucracy that induces high procedural compliance costs for taxpayers and provides opportunities for public agents to sell facilities to comply with tax obligations (Awasthi & Bayraktar, 2015; Cabello & Nakao, 2021).

On the other hand, the complexity of the tax system can lead to a tax gap as a result of voluntary tax evasion on the part of taxpayers, since there are opportunities for multiple interpretations of tax laws and precedents for taxpayers to choose the most advantageous option (Awasthi & Bayraktar, 2015; Nguyen et al., 2022). Evasion can also occur as a result of involuntary disobedience, which is an error in calculating taxes and tax laws due to the difficulty and complexity of tax regulations (Gomes et al., 2023). Thus, the decision-making power to accept this option lies with the tax agent, who can take advantage of the situation to collect bribes and kickbacks (Awasthi & Bayraktar, 2015). The literature argues that taxes should be based on clearly written laws in order to avoid frequent contact between taxpayers, legislators and tax administrators, who would be more prone to acts of corruption (Borisov & Grupta, 2016).

The structure of the tax system is a determining factor in a country's economic performance because it is the main source of revenue for nations (Bunn & Asen, 2021). A poorly structured tax system can create a fertile substrate for politicians to opportunistically increase the tax burden on taxpayers in order to raise more revenue by suppressing their perceptions of the true cost of government (Wildowicz-Giegiel & Kargol-Wasiluk, 2020). This political opportunism aims to increase the level of public spending without the full perception of taxpayers, satisfying the needs of interest groups and justifying an increase in revenue through taxation (Prado & Almeida, 2021).

In this context, several international organizations have highlighted the need to reform and simplify tax systems, warning of the urgency of these changes in developing countries, whose economic performance has been hampered by tax complexity (Bunn & Asen, 2021; TMF Group, 2021). According to data from the Global Business Complexity Index 2021, Latin American countries account for six out of the ten most tax complex economies in the world (TMF Group, 2021), with Brazil in first place (Nguyen et al., 2022; TMF Group, 2021; Hoppe et al., 2021). The other five countries are Mexico, Colombia, Argentina, Bolivia and Costa Rica (TMF Group, 2021). In addition, some of the countries in the region are considered the most corrupt in the world, according to the Corruption Perception Index 2023, such as Venezuela, Nicaragua and Haiti. Economically important countries in the region, such as Brazil, Argentina and Mexico, also have worrying corruption rates (International Transparency, 2023).

Against this backdrop, and in an effort to gain a deeper understanding of the phenomenon, this study poses the following research question: What is the relationship between tax complexity and corruption in Latin American countries? In light of the above, the general objective of this study is to identify the relationship between tax complexity and corruption in Latin American countries.

This research fills a gap in the literature by analyzing the relationship between tax complexity and five different dimensions of corruption, allowing us to delve deeper into this complex social phenomenon. As such, the results of this research may be useful in raising awareness among citizens, businesses, legislators and other non-governmental organizations about the importance of simplifying tax laws. In addition, the research is relevant as a way to combat tax evasion activities, improve the business environment, increase government tax collection and strengthen compliance and anti-corruption mechanisms. In this regard, this study can support potential government agendas and actions to simplify, modernize and reform the tax system.

Moreover, the phenomenon of corruption is an old and persistent problem in Latin America. For this reason, mapping, characterizing, understanding and discussing it is a fundamental step for academia to use its expertise to support the movement for political, cultural and social change. In this context, understanding the relationship between tax complexity and corruption will allow the development of more transparent and efficient policies, ensuring that public resources are properly allocated to social programs that directly benefit society, especially the poorest, and promote social justice.

2. THEORETICAL FRAMEWORK

2.1 Theory of Fiscal Illusion

The theory of fiscal illusion occurs when the structure by which revenues are generated affects taxpayers' perceptions of costs, leading to a change in the level of public spending (Wagner, 1976). In this way, citizens are led to systematically underestimate the cost of government programs because some public officials (including politicians) will manipulate the tax system to create the illusion that it is necessary to collect high amounts of revenue to cover large public expenditures (Liu & Mikesell, 2018; Wildowicz-Giegiel & Kargol-Wasiluk, 2020).

Since the concept was first introduced, a country's tax complexity has been considered one of the most important sources of fiscal illusion because it is seen as a measure of information costs (Heyndels & Smolders, 1995). The higher the cost of information, the lower the taxpayer's propensity to seek it (Wagner, 1976).

Fiscal illusion projects misperceptions about the tax structure onto taxpayers, which can be more easily exploited by politicians and public officials to hide their corrupt activities (Liu & Mikesell, 2018). This manipulation of perceptions occurs because policymakers adopt their own interests as guidelines and aim to favor certain groups of political supporters who can increase their chances of re-election by seeking larger amounts of campaign contributions (Abatemarco & Dell'Anno, 2020). Policymakers also use the strategy of improving the financial well-being of politicians through bribes and promises of appointments to future positions (Abatemarco & Dell'Anno, 2020). And precisely because of the high information costs in the 21st century, voters avoid investigating and disregard public accounts, making them vulnerable to the effects of fiscal illusion (Wildowicz-Giegiel & Kargol-Wasiluk, 2020).

Tax complexity is a natural substrate for fiscal illusion. It is seen as the result of two determinants: the fragmentation of total national tax revenues across different taxes and the individual visibility of these revenues across taxes, since both elements affect the information costs of taxpayers (Heyndels & Smolders, 1995). The higher the level of public spending in a country, the more fragmented and diversified are the sources of these revenues (Wagner, 1976). Visibility is supported in the form of taxation, that is, politicians tend to hide taxation and prefer indirect taxes over direct taxes (Liu & Feng, 2015). Therefore, the central issue is transparency, as opportunistic manipulation of a country's tax system is easier to carry out if the public finds it difficult to know the structure and distribution of the tax burden (Liu & Mikesell, 2018).

Studies show that the taxation of more corrupt countries has been built on a structure based on indirect taxes and with higher effective tax rates (Belitski et al., 2016; Liu & Feng, 2015). Moreover, countries with higher levels of corruption have greater tax complexity, and countries with more complex tax codes have higher corruption rates; in other words, the relationship between tax complexity and corruption is endogenous (Belitski et al., 2016; Liu & Feng, 2015; Liu & Mikesell, 2018). Thus, in light of the theory of fiscal illusion, the following research hypothesis is formulated:

H₁: Latin American countries with greater tax complexity have higher levels of corruption.

2.2 Tax Complexity

Tax complexity arises from the increasing sophistication of tax law (Nguyen et al., 2022). In this sense, the World Bank (2009) describes tax complexity as reflecting structural elements such as the tax base, the tax rate, deductions, exemptions, allowable credits and administrative appeals in the tax code. It is also associated with the size of the tax burden, the set of existing laws and regulations, the differentiation of tax rules and the forms of collection (Jacob, 2018; Souza et al., 2009).

There is evidence that tax complexity has increased in recent years (Hoppe et al., 2021). Hoppe et al. (2021) suggest that one possible explanation is that both the introduction and adaptation of tax measures to ensure a level playing field for businesses and the implementation of tax incentives and mechanisms to attract investment are the main factors attributed to this growth. Another possibility for this increase is the political use of tax collection to maintain the support of economic groups through the granting of tax benefits, special installment payments and legislation that makes it possible to reduce the payment of taxes by these groups (Burman & Gale, 2001; Gomes et al., 2023; James & Edwards, 2008).

Increased tax complexity can have a number of negative consequences for the country, such as the risk of economic bankruptcy (Collier et al., 2018), encouraging inappropriate tax planning and evasion (Evans & Tran-Nam, 2010; Gomes et al., 2023; Richardson, 2006), increasing enforcement costs (Awasthi & Bayraktar, 2015), increasing taxpayer compliance costs (Cabello & Nakao, 2021) and increasing corruption (Belitski et al., 2016; Di Vita, 2021; Liu & Feng, 2015; Liu & Mikesell, 2018). For this reason, international organizations have started a movement to encourage tax simplification in countries (Di Vita, 2021; Hoppe et al., 2021; Nguyen, et al., 2022; World Bank, 2009).

Tax simplification would have benefits in terms of reducing corruption. For the World Bank (2009), the main benefit is the reliability of the tax system, i.e. with tax simplification, states can rely on technological development and automate their computerization system, which helps both to reduce the time it takes to provide services to taxpayers and to resolve tax disputes. The first benefit minimizes corruption by analyzing and monitoring delays and services provided to taxpayers, making it easier to detect corrupt attitudes on the part of public officials. The second benefit, in turn, allows for greater speed in resolving disputes and makes the tax system more objective, reducing the windows of opportunity for corrupt actions (Awasthi & Bayraktar, 2015).

2.3 Corruption

Corruption is conceptualized as the abuse of public power for private gain (Ajaz & Ahmad, 2010; Awasthi & Bayraktar, 2015; International Transparency, 2021; Tanzi, 1998). It can take the form of bribery, embezzlement, theft, fraud, blackmail, extortion, collusion and nepotism (Doan et al., 2022).

Studies have shown that corruption harms economic growth (Christos et al., 2018) and negatively affects the development of democracy (Villoria et al., 2013). It also reduces tax collection when it encourages tax evasion, inappropriate tax exemptions or poor tax administration (Alm et al., 1991; Ivanyna et al., 2016). In addition, corruption negatively affects taxpayers' tax morality (Torgler et al., 2008) and distorts a country's tax structure (Liu & Mikesell, 2018).

Corruption also has a parallel effect. On the one hand, public servants are motivated to make processes overly bureaucratic in order to receive bribes to speed them up. On the other hand, the government's ability to design appropriate policies is reduced, leading to a loss of credibility for public institutions (Guillamón et al., 2021). Another detrimental effect of corruption is an increase in the concentration of income, as people or companies with more resources can use them to benefit themselves or obtain favors, which leads to an increase in inequality and also feeds back into corruption (Guillamón et al., 2021).

Tanzi (1998) argues that there are four ways to mitigate the harmful effects of corruption. The first is the honesty and commitment of the national leadership in the fight against corruption (the representative must show zero tolerance for cases). The second is to reduce regulations and tax incentives (the main, but not exclusive, guideline adopted in this study), making existing ones more transparent (fighting against the discretion of tax administrators). The third is to improve the public sector by increasing salaries, incentives for honest behavior, better controls and more effective penalties. And the fourth is to solve the problem of political party financing (avoiding lobbying and bribery).

2.4 Previous Studies

The listed previous studies with approaches to tax complexity and corruption were selected because of the important results found and similarities with this study, especially in the methodological construction (Table 1).

Table 1
Previous related studies

Authors	Sample	Objectives	Main results
Richardson (2006)	45 countries	To investigate the relationship between tax evasion and country characteristics.	(I) Tax complexity was the main factor influencing tax evasion. Countries with more complex tax systems have higher tax evasion rates. (II) Countries with higher levels of education, justice and morality have lower tax evasion rates.
Liu & Feng (2015)	150 countries	To discuss the determinants of corruption based on the tax structure.	(I) Countries that rely more on direct taxes tend to have less corruption than countries that rely more on indirect taxes. (II) Countries with more complex tax systems tend to be more corrupt than countries with fewer taxes.
Awasthi & Bayraktar (2015)	104 countries	To see if there is empirical evidence linking tax simplification and corruption in tax administrations.	(I) A strong relationship between tax corruption and tax complexity indicators. (II) A 10% reduction in the time to pay tax variable implies a 4% reduction in tax corruption. (III) A 10% reduction in the frequency of tax payment variable leads to a 6% improvement in tax corruption. (IV) The combined effect of a 10% reduction in both variables reduces tax corruption by 9.6%.
Belitski et al. (2016)	72 countries	To examine how tax rates and the interaction between corruption and these rates affect the variations of new business.	(I) Higher tax rates discourage new businesses. (II) Corruption can help offset these effects when tax rates are high.
Liu & Mikesell (2018)	50 US states	To examine the extent to which corruption affects the tax structure of US states.	(I) States with more corrupt public officials have a more complex tax structure and collect more taxes. (II) States with more corrupt public officials have a tax system with more indirect taxes than direct taxes and also less tax progressivity.
Botinha & Lemes (2019)	G20 countries (except the European Union)	To examine the relationship between the role of accounting and corruption in countries.	(I) The higher the level of information disclosure, the lower the perception of corruption. (II) Political institutional factors associated with voice and accountability indices, government effectiveness and the rule of law have greater weight in reducing corruption. (III) The higher the tax burden, the lower the perceived corruption of countries.
Gomes et al. (2023)	Theoretical model simulated over 13 years	To analyze how tax complexity and special installment plans affect the decision of Brazilian taxpayers to disobey tax laws.	(I) Tax complexity and repeated special installment plans encourage tax non-compliance.

• Source: Prepared by the authors.

The studies listed in Table 1 show a relationship between tax complexity and corruption in line with the construction of research hypothesis H₁. However, most of them examine this relationship on a global scale. Therefore, regional, social, economic and cultural specificities are not captured. As a result, the dynamics of taxation and corruption in developed countries are being treated in the same way as in developing countries. Therefore, this study sought to contribute to the advancement of the literature by emphasizing the phenomenon in the context of Latin America, relying on the methodologies, variables and premises adopted by the main studies already carried out in this area.

3. METHODOLOGY

This descriptive and quantitative study is classified as archival (Smith, 2022).

3.1 Population, Sample and Research Data

The study population includes all Latin American countries. In this context, the research sample consisted of the 24 largest economies in Latin America for which it was possible to obtain data from the World Bank (2023) for the years 2005 to 2019.

The data used to study the phenomenon analyzed in the study were obtained from several publicly available databases, namely World Bank Database, CPI, Bertelsmann Stiftung Sustainable Governance Indicators, Global Insights Business Conditions and Risk Indicators, World Bank Country Policy and Institutional Assessment, World Justice Project Rule of Law Index, Varieties of Democracy Project, and Tax Complexity Index.

It is important to note that several variables collected by the study to form the corruption constructs had missing data for the time window covered by the research. In this sense, the econometric models used in the research had different compositions, ranging from 147 to 331 year-observations. The following subtopic provides details on the number of observations per variable used in the research.

3.2 Variables

3.2.1 Dependent variables

The dependent variables were selected based on the literature on corruption and taxation in countries (Awasthi & Bayraktar, 2015; Belitski et al., 2016; DeBacker et al., 2015; Irawan & Utama, 2021; Liu & Feng, 2015; Tanzi, 1998). The results and country rankings presented in the CPI are based on data collected from 13 international reports. The data are mathematically processed and manipulated to construct the CPI. After analyzing the 13 reports, four were selected to represent different dimensions of the corruption phenomenon. The selected constructs play an important role in calculating the CPI and capture different aspects of corruption. In addition, their databases come from international organizations that act independently and are credible and reliable, as described in Table 2.

Table 2
Dependent variables of the model

Name	Acronym	Scale	Construction	Source of Report	Number of observations
Corruption prevention	BF	From -2 ("public officials abuse their positions") to 2.3 ("strong mechanisms to prevent corruption")	Factor analysis	Bertelsmann Stiftung Sustainable Governance Indicators	285
Risk of bribery	GI	From 0 (maximum corruption) to 1 (minimum corruption)	Direct use of the indicator	Global Insights Business Conditions and Risk Indicators	318
Absence of public corruption	WJP	From -1.59 ("low adherence to the rule of law") to 2.53 ("high adherence to the rule of law")	Factor analysis	World Justice Project Rule of Law Index	147
Political corruption	VDEM	From -2.10 ("very corrupt") to 2 ("not very corrupt")	Factor analysis	Varieties of Democracy Project	324
Corruption perception index	CPI	From 0 ("very corrupt") to 100 ("very clean")	Direct use of the indicator	International Transparency	331

• Source: Prepared by the authors.

The indicators that were not selected were discarded because they either do not have a significant weight according to the methodology used to calculate the CPI, or they belong to private entities and are not independent in their actions (they may be influenced by entities that fund the research, for example), or because they do not have data from Latin American countries for the period covered by the research. The dependent variable, CPI, was also chosen to give greater robustness and consistency to the other models, since it is commonly used as a corruption metric in other studies on the subject. Thus, five regression models were run, one for each of the dependent variables described in Table 2.

Also according to the data presented in Table 2, it should be noted that three corruption constructs were measured using the factor analysis technique because they were made up of more than one indicator related to the corruption factor captured, namely: corruption prevention (BF), absence of public corruption (WJP) and political corruption (VDEM). Two other indicators, however, were made up of a single indicator and in this context their values did not need to undergo any transformation, namely: risk of bribery (GI) and CPI. The constructs (dependent variables) are arranged on an ascending scale from "high corruption" to "low corruption"; therefore, lower values indicate high corruption, while higher values indicate low corruption. Table 3 shows the countries with their respective corruption indices in 2019 (International Transparency, 2021).

Table 3
List of Latin American countries with their corruption indices in 2019

Country	CPI	Country	CPI	Country	CPI
Argentina	45	Ecuador	38	Panama	36
Bahamas	64	Guatemala	26	Peru	36
Bolivia	31	Guyana	40	Paraguay	28
Brazil	35	Honduras	26	El Salvador	34
Chile	67	Haiti	18	Suriname	44
Colombia	37	Jamaica	43	Trinidad & Tobago	40
Costa Rica	56	Mexico	29	Uruguay	71
Dominican Republic	28	Nicaragua	22	Panama	36

• CPI = corruption perception index.
• Source: Prepared by the authors.

3.2.2 Independent variables

Tax complexity has been measured at the country level in international research using metrics from the World Bank Database and the Tax Complexity Index (Audretsch et al., 2022; Awasthi & Bayraktar, 2015; Belitski et al., 2016; DeBacker et al., 2015; Hoppe et al., 2021; Irawan & Utama, 2021; Lawless, 2012; Liu & Feng, 2015; Richardson, 2006). In this study, two representative metrics of tax complexity were adopted, as shown in Table 4. These variables were tested together in the econometric models due to the multidimensional nature of the tax complexity construct, i.e. it is not possible to measure the phenomenon in question with a single variable (Di Vita, 2021; Evans & Tran-Nam, 2010). The tax complexity of countries is shown in Table 5 (World Bank, 2023).

Table 4
Independent variables

Name	Acronym	Definition	Expected sign	Theoretical foundation
Total rate of taxes and contributions on profit	TTCR	The total tax rate measures the number of compulsory taxes and contributions payable by companies, after taking into account deductions and exemptions allowed as part of business profits in relation to profit. It excludes taxes that are withheld (such as personal income tax) or collected and remitted to the tax authorities (such as VAT, sales taxes or taxes on goods and services).	(-)	Audretsch et al. (2022), Belitski et al. (2016), Liu & Feng (2015), Nguyen et al. (2022)
Payment of taxes	TPAY	Tax payments are the total number of taxes paid by companies, including electronic filings. Taxes are counted as paid once a year, even if payments are made more frequently.	(-)	Awasthi & Bayraktar (2015), Belitski et al. (2016), Lawless (2012), Liu & Feng (2015), Nguyen et al. (2022)

• Note: Variables collected from the World Bank Database.
• Source: Prepared by the authors.

Table 5
List of Latin American countries, their corruption indices in 2019, and independent variables

Country	TPAY	TTCR	Country	TPAY	TTCR	Country	TPAY	TTCR
Argentina	9.0000	106.3000	Ecuador	8.0000	34.4000	Panama	36.0000	37.2000
Bahamas	20.0000	33.8000	Guatemala	8.0000	35.2000	Peru	8.0000	36.8000
Bolivia	42.0000	83.7000	Guyana	35.0000	30.6000	Paraguay	19.0000	35.0000
Brazil	9.6100	65.1000	Honduras	59.0000	39.1000	El Salvador	7.0000	36.4000
Chile	7.0000	34.0000	Haiti	47.0000	42.7000	Suriname	30.0000	27.9000
Colombia	10.0000	71.2000	Jamaica	11.0000	35.1000	Trinidad & Tobago	39.0000	40.5000
Costa Rica	10.0000	58.3000	Mexico	6.0000	55.1000	Uruguay	20.0000	41.8000
Dominican Republic	7.0000	48.8000	Nicaragua	43.0000	60.6000	Panamá	36,0000	37,2000

• TPAY = payment of taxes; TTCR = total rate of taxes and contributions on profit.
• Source: Prepared by the authors.

3.2.3 Control variables

The control variables were selected based on the social, cultural, legal and economic characteristics identified as influencing corruption in Latin American countries, as shown in Table 6.

Table 6
Control variables

Name	Acronym	Scale	Expected sign	Source	Theoretical underpinning
Gross domestic product per capita	GPC	Gross domestic product per capita in dollars (US$)	(+/-)	World Bank Database	Awasthi & Bayraktar (2015), Belitski et al. (2016), Hoppe et al. (2021), Lawless (2012), Liu & Feng (2015)
Democratic accountability	DEM	0 (low democratic accountability) to 1 (high democratic accountability)	(-)	International Country Risk Guide	Awasthi e Bayraktar (2015), Liu & Feng (2015), Pommerehne & Weck-Hannemann (1996), Richardson (2006)
Proportion of women in the labor market	GEN	Percentage of women over 15 in the labor market (0 to 100%)	(-)	World Development Indicators	Liu & Feng (2015), Richardson (2006)
Ease of doing business	ENT	New business density (new registrations per 1,000 people aged 15 to 64)	(-)	World Bank Database	Belitski et al. (2016), Lawless (2012)

• Source: Prepared by the authors.

3.3 Estimation Method and Methodological Process

STATA® software was used to perform the econometric estimations. First, the distribution and characteristics of the dependent, independent and control variables of the countries were studied using descriptive statistics and outlier identification (BACON method). In the second stage of the methodological process, the generalized method of moments (GMM) was used to achieve the objective of this study. The variables included in the GMM model were validated using Fisher's stationarity test. This benchmark was used because it is a necessary condition for estimating the GMM model, avoiding and limiting estimation errors that could consequently lead to misinterpretation of the result. The GMM model was defined according to Equation 1 below.

$${\text{Corruption}}_{\text{it}}\text{= α+}{\text{β}}_{\text{1}}\text{.}{\text{TTCR}}_{\text{it}}\text{+}{\text{β}}_{\text{2}}\text{.}{\text{TPAY}}_{\text{it}}\text{+}{\text{β}}_{\text{3}}\text{.}{\text{GPC}}_{\text{it}}\text{+}{\text{β}}_{\text{4}}\text{.}{\text{DEM}}_{\text{it}}\text{+}{\text{β}}_{\text{5}}\text{.}{\text{GEN}}_{\text{it}}\text{+}{\text{β}}_{\text{6}}\text{.}{\text{ENT}}_{\text{it}}\text{+}{\text{ε}}_{\text{it}}$$ (1)

where Corruption it are the dependent variables (BF, GI, WJP, VDEM and CPI, according to Table 2), TTCR_it is the total rate of taxes and contributions (independent variable), TPAY_it is the payment of taxes (independent variable), 𝐺𝑃𝐶 it is the gross domestic product (GDP) per capita (control variable), DEM_it is the democratic accountability (control variable), GEN_it is the female labor force (control variable), ENT_it is the density of new businesses (control variable), α is the linear coefficient of the regression, β_N are the angular coefficients of the variables, and ɛ_it is the error term.

4. RESULTS AND DISCUSSION

4.1. Detection of Variable Outliers

The limit of 85% was adopted as the standard percentile of the chi-squared distribution, from which the threshold for separating outliers from non-outliers was defined (Fávero & Belfiore, 2017). Based on this procedure, no outliers were identified in the data observed for the research. Therefore, the final sample for the construction of the factors, in the case of the dependent variables and in the case of the independent and control variables, were the year-observations of the countries that had no missing data.

4.2 Factor Analysis

This study examined five dimensions of the Corruption phenomenon: BF, GI, WJP, VDEM and CPI. Of these, three (BF, WJP and VDEM) required the creation of a representative construct because they were measured by more than one explanatory variable. Factor analysis was used to create the constructs. The results of the operationalization of this technique are presented in Table 7.

Table 7
Factor parameters

Construct	Variance	Proportion	KMO	Bartlett
BF	1.91516	0.9576	0.500	0.000
WJP	3.19455	0.7986	0.678	0.000
VDEM	5.35739	0.8929	0.903	0.000

• BF = corruption prevention; KMO = Kaiser-Meyer-Olkin; VDEM = political corruption; WJP = absence of corruption.
• Source: Prepared by the authors.

In general, Bartlett's sphericity test showed that the null hypothesis was rejected at the 5% significance level, suggesting that the constructs created are valid and significant.

4.3 GMM model

4.3.1 Stationarity of the series - Fisher's test

The GMM estimator imposes the assumption that the first differences of the instrumental variables are not correlated with the unobserved individual effect (Policardo & Carrera, 2018). This is guaranteed if the stochastic process generating 𝑥 𝑖𝑡 is stationary (Barros et al., 2020). The stationarity of the series was therefore tested by applying Fisher's test to the regressor variables. The results of the p-values for the five constructs are presented in Table 8. The absence of stationarity was adopted as a criterion for the variables that would form the final models of the constructs, i.e., only those variables whose null hypothesis was rejected at 5% were included in the GMM model (Policardo & Carrera, 2018).

Table 8
Fisher's stationarity test

	BF	GI	WJP	VDEM	CPI
TTCR	0.0000	0.0000	0.0000	0.0000	0.0000
TPAY	0.0000	0.0000	0.0001	0.0000	0.0000
GPC	0.4745	0.0000	0.0010	0.0098	0.0209
DEM	0.0000	0.9985	0.0004	0.0000	0.0000
GEN	0.7032	0.2700	0.0000	0.1843	0.1909
ENT	0.0000	0.0000	0.0000	0.0000	0.0000

• BF = corruption prevention; CPI = corruption perception index; DEM = democratic accountability; ENT = new business density; GEN = female workforce; GI = risk of bribery; GPC = gross domestic product per capita; TPAY = number of payments; TTCR = total tax and contribution rate; VDEM = political corruption; WJP = absence of corruption.
• Source: Prepared by the authors.

In Fisher's test, the null hypothesis is that the panels have a unit root, while the alternative hypothesis is that at least one panel is stationary.

The results in Table 8 show that for the BF construct, the variables TTCR, TPAY, DEM and ENT had their null hypothesis rejected and were therefore used in the estimation of this factor. With the same number of stationary variables, the GI construct had TTCR, TPAY, GPC and ENT.

For the VDEM and CPI constructs, the variables TTCR, TPAY, GPC, DEM and ENT were stationary according to Fisher's test. Finally, the variables TTCR, TPAY, GPC, DEM, GEN and ENT had their null hypothesis rejected and were used in the regression of the WJP construct, i.e., this construct had the highest number of stationary variables.

It is also important to note that the independent variables of interest to the research (TTCR and TPAY) passed Fisher's test in all the estimated models.

4.3.2 Analysis of the relationship between corruption and tax complexity

Table 9 shows the results of the estimation of the GMM model, where the dependent variables are the factors representing the phenomenon of corruption, while the independent variables are divided into variables representing tax complexity (TTCR and TPAY) and control variables (GPC, DEM, GEN and ENT).

Table 9
GMM model result

	BF	GI	WJP	VDEM	CPI
TTCR	-0.0034***	-0.0043***	0.0016	-0.0202***	-0.2137***
TPAY	-0.0120***	-0.0038***	-0.0053	-0.0249***	-0.2367***
GPC	-	0.000014***	0.000036	0.00007***	0.0009***
DEM	2.2133***	-	1.6508*	2.1543***	21.4980***
GEN	-	-	0.0845**	-	-
ENT	0.0318***	-0.0041***	0.0571	0.0653***	-0.5242**
AR(1) (p-value)	(0.1700)	(0.1610)	(0.9490)	(0.0690)	(0.0760)
AR(2) (p-value)	(0.5000)	(0.4640)	(0.3330)	(0.4790)	(0.1590)
Sargan (p-value)	(0.0000)	(0.0000)	(0.0000)	(0.0000)	(0.0000)
Hansen (p-value)	(0.7540)	(0.4610)	(0.1470)	(0.7080)	(0.5370)
Dif-Hansen (p-value)	(0.9260)	(0.3250)	(0.0510)	(1.0000)	(0.8270)
Wald (p-value)	(0.0000)	(0.0000)	(0.0000)	(0.0000)	(0.0000)
Observations (n)	285	318	147	324	331
Instruments (n)	25	19	13	26	26
Groups (n)	21	24	22	23	24

• Notes: The Sargan test indicates that the instruments are correlated with the residuals, while the Hansen test indicates that the instruments are not correlated with the residuals. AR(1) and AR(2) indicate that there is no first or second order autocorrelation. Dif-Hansen attests to the orthogonality of the subset of instruments. Standard errors are in parentheses in the tests.
• BF = corruption prevention; CPI = corruption perception index; DEM = democratic accountability; ENT = new business density; GEN = female workforce; GI = risk of bribery; GMM = generalized method of moments; GPC = GDP per capita; TPAY = number of payments; TTCR = total tax and contribution rate; VDEM = political corruption; WJP = absence of corruption.
• The value of statistical significance is indicated by the symbols *10%, **5% and ***1%.
• Source: Prepared by the authors.

The model estimates were validated using the tests shown in Table 9. The results indicate that there is no autocorrelation of the first differences, either first or second order. Roodman (2009) suggests investigating the second-order serial correlation, AR(2). Therefore, the results presented behave as expected, i.e. there is negative first-order autocorrelation, but no second-order autocorrelation was detected.

The instruments were validated using the Hansen difference test. According to Roodman (2009), if there is a suspicion of non-sphericity of errors, the statistic developed for Sargan is considered inconsistent, so the Hansen difference test is preferred because it is considered a superior identification test whose estimation is done in two stages (greater robustness). Therefore, the Hansen difference test showed that the subsets of the instruments are exogenous, since its null hypothesis was not rejected, demonstrating that the additional conditions for using the systemic GMM are valid.

The results show that in almost all the models there is a statistically significant relationship between one of the constructs that make up tax complexity and the aspect of corruption analyzed (except for the WJP construct). In these models, the average increase in the level of tax complexity is associated with higher levels of corruption, also on average, confirming the research hypothesis: Latin American countries with higher levels of complexity have higher levels of corruption, in line with the findings of Liu and Feng (2015). It should be noted that all the constructs (dependent variables) are arranged on an increasing scale, ranging from "high corruption" to "low corruption"; therefore, lower values indicate high corruption while higher values indicate low corruption.

The results for the TTCR variable suggest that for Latin American countries, a one-unit increase in TTCR is associated, on average, with a deterioration of 0.0034 units in BF, 0.0043 units in GI, 0.0202 units in VDEM and 0.2137 units in CPI. The evidence that a higher tax rate is associated with higher levels of corruption is in line with the findings of DeBacker et al. (2015), who conducted a comparative study between countries participating and not participating in the Organization for Economic Cooperation and Development (OECD).

For Belitski et al. (2016), high tax rates can deter firms and discourage entrepreneurship. Thus, on the one hand, high TTCRs in high-corruption environments increase the likelihood that companies will find ways to try to avoid and/or reduce their tax obligations (Liu & Mikesell, 2018). On the other hand, in these scenarios with higher TTCRs, politicians can reap greater personal benefits precisely because this rate is an incentive to pay bribes to compensate for it (Belitski et al., 2016; World Bank, 2009). According to Awasthi and Bayraktar (2015), experience has shown that reforming tax legislation, especially in terms of reducing rates and eliminating exemptions, is a difficult and time-consuming process because it brings the interests of different economic and political groups into conflict.

The other variable representing tax complexity that was significant in the models was TPAY. According to the regression results, the addition of a tax to be paid by companies in a Latin American country in a year would reduce corruption prevention by 0.012 units on average, while worsening the bribery risk, VDEM and perceived corruption indices by 0.0038, 0.0249 and 0.2367 units on average, respectively.

In contrast, Botinha and Lemes (2019) found that G20 countries with higher TTCR rates are associated with lower corruption rates. The authors suggest that through higher tax rates, the state could increase its revenues, which would promote better infrastructure and public services. These improvements would meet the needs of the population, which would discourage the search for alternative means, such as corruption.

In the models, TPAY is generally more associated with the number of different taxes paid than with the tax rate. Awasthi and Bayraktar (2015) concluded that a 10% reduction in the number of payments could reduce corruption rates by 6.2% in Latin American countries. Belitski et al. (2016) found that reducing the amount of tax paid could reduce corruption by 33%, using the CPI as a metric for measuring corruption. Lawless (2012) found that increasing a tax paid could reduce the control of corruption by 49%, indicating that there is potential for corruption and informal payments when a very complex tax system is in place.

In light of the theory of fiscal illusion, this result may suggest that the monitoring of tax collection and public accounts by the taxpayers of the country may be made more difficult when there are a greater number of taxes to be audited. The destination of the funds, the range of tax benefits and the way in which they are collected can be diverse, making it more difficult for taxpayers to monitor the collection and use of the funds in the financing and investment activities of the state. In this context, the corrupt may see opportunities to mislead taxpayers' perceptions and act to satisfy the demands of their political allies and interest groups (Abatemarco & Dell'Anno, 2020; Prado & Almeida, 2021). On the other hand, taxpayers may abuse the state's successive attempts to rebalance revenues, such as successive special installments, to evade taxes and finance themselves with the resources from this practice (Gomes et al., 2023).

Among the control variables, the results for GDP per capita (GPC) indicate that countries with a higher GPC have, on average, lower corruption rates, taking into account the GI, VDEM and CPI constructs (the Bahamas, Uruguay and Chile represent this behavior well, as they have high GPC scores and generally low corruption scores). An increase of US$ 1 per capita in a country's income can reduce GI by an average of 0.000014 units, VDEM by 0.000036 units and CPI by 0.0009 units. The results are in line with the findings of Awasthi and Bayraktar (2015), Belitski et al. (2016), DeBacker et al. (2015), Lawless (2012), Policardo and Carrera (2018) and Richardson (2006), who showed that income inequality is responsible for increased corruption, because when poverty is widespread and people are poorly paid, there are incentives to seek wealth (even unfairly and illegally) and thus to engage in corruption.

Another significant control variable in the models studied was DEM, which indicates that an increase in a country's level of democratic accountability tends to improve corruption indicators on average (the Bahamas, Jamaica and Costa Rica have been shown to have low levels of corruption and high DEM rates). Santos and Takamatsu (2018) found a negative correlation between the absence of corruption and the "strength of the law," i.e. countries with stricter laws have lower corruption rates. As democratic accountability increases and the law is applied more strictly, corruption decreases in response to these improvements. However, as countries' democratic accountability and rule of law indicators decline, they begin to face greater corruption problems (Awasthi & Bayraktar, 2015; Liu & Feng, 2015). Di Vita (2021) concludes that developed countries with higher levels of democracy, which is associated with high legislative complexity and high levels of social control over politicians' behavior, have lower levels of corruption and lower economic growth rates. However, for developing countries, Di Vita (2021) suggests that this result should not be replicated because they are further away from high legislative complexity due to having younger liberal democracies.

The ENT variable was significant in almost all the models (except WJP). This result suggests that countries with a higher commitment to entrepreneurship (higher number of new businesses opened per thousand inhabitants) are less prone to corruption. One possible explanation for this result is that in countries where it is easier to do business, entrepreneurs are less dependent on the public system and thus avoid getting involved in the corrupt activities of public officials. In this sense, Belitski et al. (2016) concluded in their study that there is a need for legislators to make progress in the fight against corruption and that researchers should focus in particular on the indirect effects of corruption on the different regulatory dimensions. In this context, Picur and Riahi-Belkaoui (2006) warn of the need for developing countries to reduce corruption and bureaucracy in order to develop a kind of tax morale that leads to tax compliance and economic progress.

However, this result should be interpreted with caution, as many Latin American countries had values of zero or close to zero, i.e. they generally had a density of less than 1 new business per 1,000 inhabitants. The region's main economies, Mexico and Brazil, have an average of 1.8196 and 0.7492 new businesses per 1,000 inhabitants, respectively. It also suggests that the private sector is not very dynamic and perhaps the opportunities for doing business are more related to the presence of the state than private sector agents. Asiedu and Freeman (2009) presented empirical evidence that corruption provides benefits even before a business is opened in emerging economies (the phenomenon of structural corruption).

5. CONCLUDING REMARKS

The objective of this study was to identify the relationship between tax complexity and corruption in Latin American countries. The sample consisted of a panel of 24 Latin American countries from 2005 to 2019.

The results of the study are consistent with the research hypothesis that Latin American countries with greater tax complexity have higher levels of corruption. The findings also suggest that countries with higher tax rates on profits have higher corruption rates. It is believed that in an environment of greater corruption, high tax rates increase the likelihood that companies will find ways to avoid or reduce their tax obligations through illicit means (e.g., paying bribes). In addition, in environments with higher tax burdens, politicians may be able to obtain greater personal benefits by negotiating for legal favors.

The evidence also suggests that the total number of taxes is directly related to the level of corruption, i.e. the more taxes a country has, the higher the level of corruption. This finding suggests that a greater number of taxes can mislead taxpayers' perceptions and be used to serve political interests, especially in the part of tax collection that is not earmarked by law or in the budget. In other words, the more different taxes there are, the greater the difficulty and information cost for taxpayers to monitor their destination.

Another way would be to create more taxes in order to increase revenue, with the goal of increasing the amount of money at hand so that politicians can negotiate its allocation to suit their allied bases and interest groups. From this perspective, in light of the theory of fiscal illusion, politicians would take advantage of a greater number of taxes to circumvent and manipulate taxpayers' monitoring and perceptions of tax collection and its destination, under the justification of increasing state costs and the need to raise funds for new investments. In this way, politicians could maneuver the surplus revenue to suit their interest groups.

Overall, the results suggest that Latin American countries need a tax reform that simplifies the structure and clarifies the legislation for taxpayers. In addition to increasing revenues and simplifying the rules, the reform must promote social justice, combat regressivity and ensure isonomy, proportionality and full universality. It is also essential to improve the control and transparency of public resources, combat tax evasion and reduce loopholes and excessive benefits in the legislation. The success of the reform will depend on the participation of society and the effective use of technological tools.

This study contributes by providing evidence on some of the characteristics of the tax system. Latin American countries need to act to reduce their tax complexity. Tax rates and the number of taxes are important in the tax systems of this bloc of countries, and a change in favor of greater social justice could lead to indirect gains, especially in terms of reducing corruption. In addition, it reinforces that democratic accountability, with the application of the law, is fundamental in the fight against illegal activities. This may indicate that the problem of corruption and tax complexity in Latin American countries is not necessarily the law, but its application.

This study does not attempt to exhaust the topic of corruption and tax complexity in South America, but rather to explore these problems in a diverse and unequal region. Moreover, this study is limited by the choice of variables and by its inability to capture all the nuances of corruption and tax complexity. Nevertheless, the study makes progress by focusing on an understudied part of the region and by breaking down corruption and tax complexity into different metrics. Future research could deepen the study by exploring new dimensions of these phenomena and comparing the impact before and after the tax reforms adopted by countries in the region.

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• 4
  This is a bilingual text. This article was originally written in Portuguese and published under the DOI https://doi.org/10.1590/1808-057x20242114.pt
• 5
  This article is based on a Master's thesis defended by the author Bernardo Fernandes Lott Primola in 2023.
• Paper presented at the XVII ANPCONT Congress, São Paulo, SP, Brazil, November 2023.
• Funding
  Bernardo Fernandes Lott Primola declares that he received funding from the Minas Gerais State Research Foundation (FAPEMIG) for the research that led to this article.

Edited by

• Editor-in-Chief:
  Andson Braga de Aguiar

• Associate Editors:
  Márcia Martins Mendes De Luca and Eduardo da Silva Flores

Publication Dates

• Publication in this collection
  12 Sept 2025
• Date of issue
  2025

History

• Received
  11 Mar 2024
• Reviewed
  25 Apr 2024
• Accepted
  18 Nov 2024