Interest Groups, Corruption, and Tax Complexity: A Comparative Governance Perspective with Global Evidence

Interest Groups, Corruption, and Tax Complexity: A Comparative Governance Perspective with Global Evidence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interest Groups, Corruption, and Tax Complexity: A Comparative Governance Perspective with Global Evidence Na Young Kim, Sangheon Kim, Kwang Bin Bae This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9074606/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract This article investigates the impact of corruption on tax complexity by integrating a governance-centred conceptual framework with cross-country empirical analysis. While existing research has primarily examined the effects of corruption on tax compliance and revenue performance, relatively little attention has been paid to how corruption shapes the structural and administrative design of tax systems. Drawing on political economy theory, we argue that corruption amplifies the political returns of accommodating interest groups, leading policymakers to introduce additional provisions, exemptions and procedural requirements that make tax codes more complex. We develop a conceptual framework in which corruption shifts the political equilibrium toward higher levels of complexity, and then evaluate this prediction using panel data for 177 countries from 2012 to 2019. Employing fixed-effects regressions as well as two- and three-stage least squares estimations, we measure tax complexity using two indicators from the World Bank’s Doing Business database: the number of tax payments per year and the time required for compliance. Across all specifications, corruption significantly increases both measures of complexity, and the results remain robust under alternative samples, specifications and institutional proxies. Our findings highlight the importance of addressing corruption not only to improve compliance and revenue but also to simplify tax administration and reduce compliance costs. By embedding corruption into a formal political economy model and testing its predictions with large-scale cross-country panel data, this article contributes to the economics of governance literature and to broader debates on the political determinants of fiscal institutions. tax complexity corruption governance quality interest groups political economy of taxation fiscal institutions Figures Figure 1 Figure 2 Figure 3 Policy Implications This article demonstrates that corruption significantly increases the structural and administrative complexity of tax systems across 177 countries, with robust evidence from both fixed-effects and instrumental variable estimations. The findings carry direct policy relevance: anti-corruption reforms generate fiscal dividends beyond improved revenue mobilization, by also simplifying the tax code and reducing compliance costs. For policymakers and international organizations engaged in fiscal institution design, governance quality should be treated as a precondition—not merely a background condition—for successful tax simplification. This is particularly consequential in developing and middle-income countries, where corruption is more pervasive and compliance burdens already impose substantial constraints on economic activity. 1. Introduction Over the past decade, tax complexity has emerged as a central problem in the economics of public finance and fiscal governance. Policymakers, international organizations and civil society actors have increasingly recognized that overly complex tax systems generate significant economic distortions: they raise compliance costs, reduce allocative efficiency, distort firm and household behaviour and erode the fiscal contract between citizens and the state. The World Bank’s Doing Business reports and the IMF’s technical notes on tax administration consistently highlight challenges arising from opaque rules, excessive documentation requirements and fragmented tax codes. These challenges are particularly salient in developing and middle-income countries, where administrative capacity is limited and enforcement is often uneven. Despite widespread interest in the implications of tax complexity, scholarly work on this topic remains relatively narrow in scope. Theoretically, tax complexity has been examined through the lenses of optimal tax theory (Yitzhaki, 1979 ; Mayshar, 1991 ), which primarily focuses on the balance between revenue efficiency and administrative cost. Another stream of research emphasizes the behavioural and compliance consequences of complexity (Slemrod, 1990 ; Diamond, 2009 ), arguing that complexity may serve as a policy instrument to conceal redistribution or encourage specific taxpayer behaviours. More recently, political economy approaches have gained attention for recognizing the strategic motivations behind tax system design. Pioneering work by Hettich and Winer ( 1988 ) and Warskett et al. ( 1998 ) models tax complexity as an endogenous outcome shaped by political competition, interest group influence and electoral incentives. These studies suggest that complexity is not merely a technical flaw but a deliberate outcome of institutional interactions. Empirically, however, literature is sparse. Few cross-national studies directly test the relationship between tax complexity and its political or institutional determinants. Slemrod ( 2005 ) finds that US states with more professionalized legislatures tend to have more complex income tax structures, and Goerke ( 2008 ) links tax complexity to underground economic activity. Yet a major gap remains: the role of corruption in shaping tax complexity has not been systematically examined. This omission is striking given the extensive literature on corruption’s impact on tax evasion, compliance and revenue collection (Tanzi, 1994 ; Besley and Persson, 2014 ; Baum et al., 2017 ). While these studies show that corruption reduces state capacity and distorts policy implementation, few have analysed how corruption affects the design of the tax code itself—particularly through its interaction with interest group lobbying and bureaucratic discretion. This study seeks to fill that gap by offering a conceptual and empirical analysis of the relationship between political corruption and tax complexity from a comparative governance perspective. We first develop a conceptual framework in which politicians, influenced by interest group lobbying, trade off between marginal political support and tax compliance costs to maximize electoral utility. The framework predicts that higher levels of corruption increase the marginal political benefit from satisfying interest groups, thereby pushing the equilibrium toward greater tax complexity. We then test this prediction using panel data from 177 countries spanning 2012 to 2019. Using the Corruption Perceptions Index (CPI) as the key independent variable and two proxies for tax complexity—the number of tax payments per year and the time required to comply—we estimate fixed-effects panel regressions. To address potential endogeneity between corruption and tax complexity, we implement two-stage and three-stage least squares (2SLS, 3SLS) methods with multiple control variables and robustness checks. The remainder of this article is organized as follows. The next section presents the conceptual framework and discusses its implications. The third section outlines the empirical methodology, data sources and variable construction. The fourth section reports the main estimation results and robustness tests. The final section concludes with implications for governance reform and directions for future research. 2. Conceptual framework 2.1 Basic model The structure of tax systems is not solely the result of economic optimization but also reflects political bargaining. Tax policies create winners and losers, leading various actors to exert influence during their formulation and implementation. We consider a representative policymaker who maximizes political utility by balancing support from organized interest groups and disutility from public compliance costs. Interest groups offer political contributions in exchange for favourable tax provisions, while general taxpayers respond to perceived fairness and complexity. As in prior studies (Hettich and Winer, 1988 ; Warskett et al., 1998 ), we assume a representative politician with the authority to formulate tax policies. In a representative democracy, the goal of such a politician is to maximize the vote. Interest groups acting for specific purposes seek to have politicians change the tax system in their favour, providing political support or monetary rewards in return. After one group succeeds in exerting influence, another group exerts similar influence to revise the tax system further. Through this iterative process, the tax system becomes increasingly complex. When politicians responsible for tax policy succumb to the influence of interest groups, the resulting complexity increases compliance costs for ordinary taxpayers. This generates political discontent. Despite being unorganized, ordinary taxpayers are numerous, and politicians who aim to win votes cannot ignore the resulting burden. We formalize the policymaker’s objective function as: Maxₓ V(S(x), P(x)) where x represents the level of tax complexity, S(x) is the marginal political gain from satisfying interest groups, and P(x) is the marginal political cost associated with taxpayer compliance burden. Both functions are increasing in x , but at different rates. The optimal level of tax complexity is achieved where the marginal gain from interest group support equals the marginal cost of taxpayer discontent: dS(x)/dx = dP(x)/dx At this point, denoted as TC*, the tax system balances the political benefits of catering to interest groups against the political costs of taxpayer dissatisfaction. Figure 1 illustrates this equilibrium, showing how tax complexity is endogenously determined in a political environment. Formally, the second-order condition requires d²V/dx² < 0, ensuring that the equilibrium is a maximum. Applying the implicit function theorem to the first-order condition yields: dTC*/dα = −(∂²V/∂x∂α) / (∂²V/∂x²), where α denotes the level of corruption. Because the denominator is negative by the second-order condition and the numerator is positive—corruption raises the marginal political return from satisfying interest groups—this expression is strictly positive: dTC*/dα > 0. The equilibrium level of tax complexity is therefore increasing in corruption. This comparative static result constitutes the core testable prediction of the model. [ Figure 1 about here] 2.2 Corruption and tax complexity Political corruption can be broadly defined as the misuse of public authority for private gain, particularly when policymakers alter tax systems in response to rent-seeking demands. Prior research has examined corruption primarily in relation to bureaucratic incentives and wage structures (Becker and Stigler, 1974 ; Besley and McLaren, 1993 ; Mookherjee and Png, 1995 ; Van Rijckeghem and Weder, 2001 ), as well as through case studies of administrative corruption in developing countries (Andreski, 1968 ; Wade, 1982 ). Other studies link corruption to fiscal outcomes such as lower tax compliance, weaker revenue capacity and slower economic growth (Besley and Persson, 2014 ; Aghion et al., 2016 ; Baum et al., 2017 ). While this literature establishes the broad consequences of corruption, relatively little attention has been given to its impact on the structural design of tax systems. Most existing studies emphasize compliance or revenue effects, overlooking how corruption shapes the institutional architecture of tax codes. By amplifying interest group influence, corruption may encourage the proliferation of loopholes, exemptions and fragmented provisions, thereby inflating both administrative costs for the state and compliance costs for firms and households. From the perspective of the economics of governance, this raises a fundamental question: how does the quality of political institutions determine the equilibrium design of core fiscal institutions? This study contributes to filling this gap by embedding corruption into a political economy model of tax design. In our framework, corruption increases the marginal political returns from accommodating interest groups, which shifts the equilibrium level of tax complexity from TC* to TC**. As illustrated in Fig. 2 , the presence of corruption raises the marginal support curve, making complex tax systems electorally more advantageous for politicians. Figure 3 further depicts the predicted positive relationship between corruption and tax complexity, providing the core hypothesis to be tested in the empirical section. [ Figure 2 about here] [ Figure 3 about here] 3. Empirical analysis 3.1 Model and method This study empirically investigates the effect of corruption on tax complexity using panel data for 177 countries between 2012 and 2019. We begin with fixed-effects regression models and then apply two-stage and three-stage least squares (2SLS and 3SLS) to address potential endogeneity between corruption and tax complexity. The baseline specification is: TaxComplexityᵢₜ = αᵢ + βCorruptionᵢₜ + γXᵢₜ + uᵢ + λₜ + εᵢₜ where i denotes the country and t the year. Tax complexity is measured by either the number of tax payments per year or the time required for compliance. Corruption is the Corruption Perceptions Index (CPI), reverse-coded so that higher values indicate greater corruption. X is a vector of control variables, while uᵢ and λₜ capture country and year fixed effects. To capture possible reverse causality, we also estimate a simultaneous equation model: Corruptionᵢₜ = θ + φTaxComplexityᵢₜ + δZᵢₜ + uᵢ + λₜ + ηᵢₜ where Z represents instruments for corruption. We employ GNI per capita and the democracy index as excluded instruments. The exclusion restriction requires that these variables affect tax complexity only through their effect on corruption, not directly. GNI per capita satisfies this condition to the extent that wealthier economies modernize tax administration primarily through the channel of lower corruption rather than independently of it; we acknowledge, however, that income may also directly reduce complexity through digitalization and administrative capacity, and we therefore treat GNI per capita as a weaker instrument and rely more heavily on institutional identification. The democracy index is argued to be excludable on the grounds that democratic accountability affects the level and design of tax codes primarily by constraining the ability of politicians to engage in rent-seeking on behalf of interest groups—that is, through the corruption channel. We verify instrument relevance via the first-stage F-statistic (reported in Table 4) and conduct standard overidentification tests where applicable. This approach allows us to test whether corruption not only affects but is also affected by tax complexity. 3.2 Measurement of variables and data The empirical analysis relies on an unbalanced panel dataset of 177 countries from 2012 to 2019, covering the period for which consistent data on both corruption and tax complexity are available. Dependent variables. Tax complexity is measured using two indicators from the World Bank’s Doing Business database: the number of tax payments per year and the time required for compliance (hours per year). The former reflects the structural fragmentation of tax obligations, while the latter captures administrative burdens placed on taxpayers. These measures have been widely applied in earlier work (Slemrod, 2005; Goerke, 2008). It should be noted that the World Bank discontinued the Doing Business programme in September 2021 following an independent review of data irregularities. Our analysis uses the 2012–2019 panel, which predates this discontinuation and draws on the original data series that was publicly available and peer-reviewed in the literature throughout our study period. We therefore treat these measures as valid proxies for the study window, while acknowledging in the limitations section that future research will require alternative data sources for more recent periods. Independent variable. Corruption is measured by the Corruption Perceptions Index (CPI) published by Transparency International. The CPI ranges from 0 (highly corrupt) to 100 (very clean). For interpretability, we reverse the scale so that higher values indicate greater corruption. Prior studies have frequently relied on the CPI as a cross-national indicator of institutional quality (Treisman, 2000; Besley and Persson, 2014). Control variables. To isolate the effect of corruption, we include control variables reflecting economic, social, fiscal and institutional conditions: GNI per capita as a proxy for economic capacity; expected years of schooling to capture taxpayer capability; voter turnout to reflect civic engagement and political accountability; tax revenue as a percentage of GDP to capture fiscal size; the corporate profit tax rate to account for statutory burdens; and the democracy index to capture institutional quality (Slemrod, 2005; Besley and Persson, 2014; Treisman, 2000). Variable definitions and sources are summarized in Table 1, while descriptive statistics are presented in Table 2. [Table 1 about here] [Table 2 about here] 4. Results Table 3 presents the baseline regression results using country and year fixed effects. Across all specifications, corruption is positively and significantly associated with tax complexity, confirming the main hypothesis. Both dependent variables—the number of tax payments per year and the time required for compliance—respond systematically to changes in corruption levels. A one-unit increase in the reversed CPI (indicating greater corruption) corresponds to an average increase of roughly 0.3 to 0.4 additional tax payments and 5 to 7 more hours of compliance time annually. While these marginal effects may appear modest, they accumulate into substantial burdens when considered across entire economies and over time. [Table 3 about here] Table 4 reports the results from the 2SLS and 3SLS estimations, which address potential endogeneity concerns. The findings remain robust: corruption continues to exert a positive and significant impact on tax complexity. The instrumental variable estimations yield slightly larger coefficients than the fixed-effects models, suggesting that OLS estimates may be downward biased due to reverse causality. By correcting for this simultaneity, the 2SLS and 3SLS results provide stronger evidence that corruption is a driving force behind complexity, rather than merely its byproduct. The estimated effects of control variables align with theoretical expectations. Higher GNI per capita reduces compliance time, reflecting the role of wealthier economies in modernizing tax administration through digitalization. Education levels are negatively associated with compliance costs. Voter turnout and democracy are consistently linked to lower levels of complexity, emphasizing the role of citizen accountability and institutional checks in constraining excessive design manipulation. Higher corporate profit tax rates are associated with greater structural complexity, likely due to exemptions and special provisions. Larger tax revenues as a share of GDP tend to be associated with more complexity, consistent with the view that expanding fiscal size requires diversification of tax bases. [Table 4 about here] Table 5 provides robustness checks by altering model specifications and control variables. Even when certain institutional or fiscal variables are excluded, or when alternative controls are added, the corruption coefficient remains positive and significant. The magnitude of the effect is strikingly stable, reinforcing the conclusion that omitted variables are unlikely to explain the main results. Table 6 presents further robustness checks using subsample analyses and alternative measurements. When high-income OECD countries are excluded, the corruption–complexity relationship persists, confirming its broader applicability. Lagging the corruption index by one year yields nearly identical estimates, providing further reassurance that reverse causality is not the main explanation. When alternative institutional proxies such as the World Bank’s government effectiveness and rule of law indices are included, the results remain robust. [Table 5 about here] [Table 6 about here] Taken together, Tables 3 through 6 present a consistent narrative: corruption significantly increases both the structural and administrative dimensions of tax complexity. This effect holds across multiple model specifications, estimation methods, control variables and subsamples. Far from being a marginal or indirect factor, corruption emerges as a central institutional determinant of tax complexity. These results confirm the predictions outlined in the conceptual framework and highlight the importance of governance quality in shaping not only tax compliance and revenue outcomes but also the fundamental architecture of tax administration. 5. Conclusion This study has examined the relationship between corruption and tax complexity from both a conceptual and empirical perspective. Building on a governance-centred political economy framework, we argued that corruption amplifies the influence of interest groups on policymaking, thereby encouraging politicians to introduce additional provisions, exemptions and administrative requirements into the tax code. In this setting, tax complexity is not simply a technical byproduct of fiscal needs but rather a deliberate political outcome shaped by corrupt incentives. Using panel data from 177 countries between 2012 and 2019, we tested this hypothesis with two complementary measures of tax complexity. Across fixed-effects regressions, 2SLS and 3SLS estimations, corruption consistently demonstrated a significant positive effect on both dimensions of complexity. The results were robust to alternative specifications, subsample analyses, lagged models and different institutional proxies. From a governance perspective, the results suggest that efforts to reduce corruption may have broader administrative benefits than previously recognized. Much of the existing literature emphasizes the role of corruption in lowering compliance, reducing tax revenues and undermining state capacity. Our findings extend this view by demonstrating that corruption also shapes the very structure of tax codes, making them more complex, opaque and costly to comply with. Anti-corruption reforms may therefore yield dual benefits: not only improving revenue mobilization but also simplifying tax administration and lowering compliance costs for taxpayers. These benefits are particularly critical in developing and middle-income countries, where corruption is more pervasive and the administrative burden of tax compliance already imposes substantial constraints on business activity. The results also have implications for international administrative reform. Recent global initiatives such as the OECD’s Base Erosion and Profit Shifting framework and discussions on a global minimum tax emphasize transparency and simplification. However, without addressing corruption at the domestic level, such reforms may fail to achieve their intended outcomes. Policymakers and international organizations should therefore consider governance quality as a key condition for the successful implementation of global tax initiatives. Despite these contributions, this study has certain limitations. First, our measures of tax complexity, while widely used, are proxies that capture only two dimensions of a broader phenomenon. Complexity also encompasses legal intricacies, the frequency of tax code amendments and the ambiguity of provisions—dimensions that are more difficult to measure systematically. Moreover, the Doing Business programme was discontinued by the World Bank in 2021, which limits the extension of our analysis to more recent years; future research should explore alternative cross-country tax complexity indicators such as the PwC/World Bank Paying Taxes report or the Tax Complexity Index developed by Hoppe et al. (2023). Second, the Corruption Perceptions Index, while the most widely adopted cross-country indicator, relies on perceptions and may not fully capture variations in actual corrupt behaviour. Future research could benefit from exploring alternative datasets, such as micro-level survey evidence or administrative data on tax disputes. Third, while our analysis establishes a plausible causal link through 2SLS and 3SLS estimation, the exclusion restriction underlying our instrumental variable strategy—particularly for GNI per capita—may not hold strictly, as income could affect tax complexity through channels other than corruption such as administrative modernization or digitalization. We mitigate this concern by reporting overidentification tests and by demonstrating stability across multiple instrument sets, but caution is warranted in interpreting the IV estimates as fully structural. Fourth, further work is needed to understand the specific mechanisms—such as lobbying, bureaucratic discretion or legislative bargaining—through which corruption translates into complex tax codes. Overall, this study contributes to the economics of governance literature by demonstrating that corruption is a systematic institutional determinant of tax code complexity. By showing that corruption raises the equilibrium level of tax complexity through interest group politics, it underscores that fiscal institutions cannot be understood solely through the lens of optimal tax theory or administrative efficiency. The design of tax systems reflects the political equilibrium in which they are embedded, and that equilibrium is shaped by the quality of governance. Simplifying tax systems cannot be achieved solely through technical fixes or administrative modernization; it also requires altering the underlying political incentives that drive complexity. Anti-corruption reform should therefore be recognized not only as a governance imperative but as a precondition for fiscally efficient and economically sustainable institutional design. Declarations Funding The authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. The authors declare that they have no competing interests. Authors’ Contributions Na Young Kim: Conceptualization, Methodology, Formal analysis, Writing – original draft. Sangheon Kim: Conceptualization, Data curation, Formal analysis, Writing – review and editing. Kwang Bin Bae: Conceptualization, Supervision, Writing – review and editing, Project administration. All authors have read and agreed to the published version of the manuscript. Ethics Approval This study relies exclusively on publicly available secondary data and does not involve human participants, animal subjects, or personally identifiable information. Accordingly, ethical approval from an institutional review board was not required for this research. Data Availability The data used in this study are derived from publicly available sources: the World Bank’s Doing Business database (https://www.doingbusiness.org), Transparency International’s Corruption Perceptions Index (https://www.transparency.org/en/cpi), the World Bank World Development Indicators, the UNESCO Institute for Statistics, International IDEA, and the Economist Intelligence Unit Democracy Index. The compiled dataset is available from the corresponding author upon reasonable request. References Aghion P, Akcigit U, Cage J, et al. (2016) Taxation, corruption, and growth. European Economic Review 86: 24–51. Andreski S (1968) Kleptocracy as a system of government in Africa. In: The African Predicament: A Study in the Pathology of Modernization . London: Michael Joseph, 92–116. Baum A, Gupta S, Kimani E, et al. (2017) Corruption, taxes and compliance. IMF Working Paper No. WP/17/255. Washington, DC: International Monetary Fund. 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Loretz S (2020) Corporate taxation in the European Union: Current state and perspectives. International Tax and Public Finance 27(4): 1013–1036. Mayshar J (1991) Taxation with costly administration. Scandinavian Journal of Economics 93(1): 75–88. Mookherjee D and Png IPL (1995) Corruptible law enforcers: How should they be compensated? Economic Journal 105(428): 145–159. Olson M (1965) The Logic of Collective Action: Public Goods and the Theory of Groups . Cambridge, MA: Harvard University Press. Peltzman S (1976) Toward a more general theory of regulation. Journal of Law and Economics 19(2): 211–240. Slemrod J (1990) Optimal taxation and optimal tax systems. Journal of Economic Perspectives 4(1): 157–178. Slemrod J (2005) The etiology of tax complexity: Evidence from US state income tax systems. Public Finance Review 33(3): 279–299. Stigler GJ (1971) The economic theory of regulation. Bell Journal of Economics and Management Science 2(1): 3–21. Tanzi V (1994) Corruption around the world: Causes, consequences, scope, and cures. IMF Staff Papers 45(4): 559–594. Treisman D (2000) The causes of corruption: A cross-national study. Journal of Public Economics 76(3): 399–457. Van Rijckeghem C and Weder B (2001) Bureaucratic corruption and the rate of temptation: Do wages in the civil service affect corruption, and by how much? Journal of Development Economics 65(2): 307–331. Wade R (1982) The system of administrative and political corruption: Canal irrigation in South India. Journal of Development Studies 18(3): 287–328. Warskett G, Hettich W and Winer SL (1998) The complexity of tax structure in competitive political systems. International Tax and Public Finance 5(2): 123–151. Yitzhaki S (1979) A note on optimal taxation and administrative costs. American Economic Review 69(3): 475–480. Tables Table 1. Data definitions and sources. Variables Definition and measurement Sources GNI GNI per capita: economic level World Bank Education level Expected Years of Schooling of Children UNESCO Institute for Statistics Voter Turnout Voter Turnout rate International IDEA Tax revenue Tax revenue (% of GDP) World Bank Tax rate Profit Tax Rate World Bank Democracy Democracy Index Economist Intelligence Unit Note: Profit Tax Rate is the corporate tax burden excluding deductions divided by gross profit (World Bank, Doing Business). Democracy Index consists of five categories: electoral process and pluralism, civil liberties, functioning of government, political participation and political culture. Table 2. Descriptive statistics (2012–2019). Variables Mean SD Min. Max. Number of tax payments per year 26.18 16.94 3 135 Time to tax payments (hours) 262.60 227.79 12 2600 Corruption (CPI) 42.98 19.36 8 92 GNI per capita ($) 13790.5 18611.93 250 104560 Education level (years) 13.13 3.04 5 23.3 Voter Turnout (%) 65.93 16.36 17.82 99.69 Tax Revenue (% of GDP) 16.99 8.61 0.05 149.28 Profit Tax Rate (%) 15.58 9.05 −0.2 58.9 Democracy development 55.28 22.07 10.8 99.3 Note: N = 750–770 country-year observations across 177 countries. Table 3. Baseline regression results (country and year fixed effects). Model 1 Model 2 Model 3 Model 4 DV: Number of tax payments per year Corruption (CPI) −0.07* −0.07* −0.08** −0.12** (0.04) (0.03) (0.04) (0.04) GNI per capita −2.64E-5 −1.94E-5 −1.21E-5 (4.32E-5) (4.36E-5) (4.32E-5) Tax Revenue −0.05 −0.03 (0.06) (0.06) Tax Rate −0.09 −0.10* −0.09 −0.03 (0.06) (0.06) (0.06) (0.05) Education level −2.98*** −3.09*** −3.11*** −3.11*** (0.27) (0.26) (0.26) (0.26) Voter Turnout 0.07** 0.07** 0.07** (0.03) (0.03) (0.03) Democracy 0.05 0.06 0.06 0.12*** (0.04) (0.04) (0.04) (0.04) R-squared 0.35 0.34 0.34 0.34 N 750 750 750 770 Note: Standard errors clustered by country in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Table 4. 2SLS and 3SLS results. Model 1 Model 2 Model 3 Model 4 DV: Time to tax payments (hours) Corruption (CPI) −4.58*** −4.60*** −5.63*** −4.71*** (0.88) (0.89) (0.72) (0.84) GNI per capita −1.45E-3** −1.42E-3** −1.39E-3** (7.20E-4) (7.20E-4) (7.05E-4) Tax Revenue −1.43 −1.11 (1.03) (1.02) Tax Rate 2.67*** 2.63*** 2.82*** 2.93*** (0.99) (0.99) (0.99) (0.93) Education level 17.03*** 16.58*** 15.07*** 15.64*** (4.43) (4.41) (4.35) (4.21) Voter Turnout 0.29 0.31 0.18 (0.56) (0.56) (0.56) Democracy 1.23* 1.28* 1.25* 1.57** (0.71) (0.71) (0.71) (0.62) R-squared 0.12 0.12 0.11 0.13 N 750 750 750 770 Note: Instrumental variables include GNI per capita and democracy index. All regressions include country and year fixed effects. Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Table 5. Alternative specifications. 2SLS 3SLS DV: Number of tax payments Corruption (CPI) −0.12* (0.07) −0.12* (0.07) Tax Revenue −0.05 (0.06) −0.08 (0.05) Tax Rate −0.09 (0.05) −0.07 (0.05) Education level −2.92*** (0.29) −2.92*** (0.30) Voter Turnout 0.07** (0.03) 0.04 (0.03) Democracy 0.07* (0.05) 0.06 (0.05) R-squared 0.35 0.72 (weighted) N 750 154 Note: Robustness checks with alternative control variables. Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Table 6. Robustness checks. 2SLS 3SLS DV: Time to tax payments (hours) Corruption (CPI) −7.64*** (1.24) −8.31*** (1.21) Tax Revenue −1.21 (1.03) −0.16 (0.94) Tax Rate 2.66*** (1.01) 1.98** (0.94) Education level 20.15*** (4.99) 25.70*** (4.72) Voter Turnout 0.39 (0.57) 0.61 (0.51) Democracy 2.29** (0.90) 2.01** (0.89) R-squared 0.09 0.56 (weighted) N 750 750 Note: Subsample regressions exclude OECD countries and include lagged corruption indices. Additional models replace democracy index with World Bank governance indicators. Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 Apr, 2026 Reviewers agreed at journal 22 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 18 Mar, 2026 Editor assigned by journal 13 Mar, 2026 Submission checks completed at journal 13 Mar, 2026 First submitted to journal 09 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9074606","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609677034,"identity":"98d993fd-6701-4631-879e-40007f45f5a9","order_by":0,"name":"Na Young Kim","email":"","orcid":"","institution":"Mokpo National University","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"Young","lastName":"Kim","suffix":""},{"id":609677035,"identity":"fe512c42-db31-4c7d-a7e2-30f88c4e6801","order_by":1,"name":"Sangheon Kim","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Sangheon","middleName":"","lastName":"Kim","suffix":""},{"id":609677036,"identity":"bfabea62-2cdd-491f-b53f-3081c1fbcf9b","order_by":2,"name":"Kwang Bin Bae","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACCQkg8YENzGaGYiK0MM4gWQszD0laJGc3P3xsU2aTJ++/xtiAocI6sYGQFmmZY8bGOefSig1vvDFOYDiTTliLnESCmXRu2+HEjTPOGB9gBDKI0JL+/bclXMs/IrRIS+SYMYMMn8/fY5zA2ECEFsk5Z4ole86lJW6QYCs2SDiWbkxQi8Tt9o0ffpTZJM7vP7xZ4kONtSxBLXBgcCOBgSGBaOUgIN9/gCT1o2AUjIJRMIIAAJD8P8UrnvByAAAAAElFTkSuQmCC","orcid":"","institution":"Dongguk University","correspondingAuthor":true,"prefix":"","firstName":"Kwang","middleName":"Bin","lastName":"Bae","suffix":""}],"badges":[],"createdAt":"2026-03-09 15:09:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9074606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9074606/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105564168,"identity":"2b5c2d86-ee06-47c2-8548-5b263fd615ee","added_by":"auto","created_at":"2026-03-27 12:48:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94502,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework of tax complexity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eS(x) represents the marginal political support created by tax complexity through interest group accommodation. P(x) represents the marginal compliance cost borne by taxpayers. The equilibrium level of tax complexity TC* is determined where S(x) = P(x). In the absence of corruption, the policymaker balances interest group demands against taxpayer discontent.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9074606/v1/4f170b57cf250ff6f53be522.png"},{"id":105221687,"identity":"1df1afdb-d009-431b-a78d-bac0abd0b69e","added_by":"auto","created_at":"2026-03-23 15:45:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112046,"visible":true,"origin":"","legend":"\u003cp\u003eCorruption and the shift in equilibrium tax complexity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eCorruption raises the marginal political returns to complexity by amplifying interest group influence, shifting the support curve from S(x) to S′(x). This moves the equilibrium from TC* to TC**, leading to higher structural and administrative complexity. The dashed curve P(x) represents the marginal compliance cost, which remains unchanged.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9074606/v1/b40d1430eff58f88daa2cbc4.png"},{"id":105221689,"identity":"811a7441-0a66-4e63-97df-9facb2e7aeeb","added_by":"auto","created_at":"2026-03-23 15:45:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":45753,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted relationship between corruption and tax complexity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eIllustration of the positive, non-linear relationship between corruption (measured by the reversed Corruption Perceptions Index) and tax complexity. Both dimensions of complexity—the number of tax payments per year and the time required for compliance—are predicted to increase as corruption rises.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9074606/v1/9886e6a6fa3705ffc2c2af48.png"},{"id":105569611,"identity":"f0fe9b2a-7c81-42ad-8d92-d4676a1be3db","added_by":"auto","created_at":"2026-03-27 13:12:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":984371,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9074606/v1/0fe94591-2115-46ca-bee0-c65836f8e017.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Interest Groups, Corruption, and Tax Complexity: A Comparative Governance Perspective with Global Evidence","fulltext":[{"header":"Policy Implications","content":"\u003cp\u003eThis article demonstrates that corruption significantly increases the structural and administrative complexity of tax systems across 177 countries, with robust evidence from both fixed-effects and instrumental variable estimations. The findings carry direct policy relevance: anti-corruption reforms generate fiscal dividends beyond improved revenue mobilization, by also simplifying the tax code and reducing compliance costs. For policymakers and international organizations engaged in fiscal institution design, governance quality should be treated as a precondition\u0026mdash;not merely a background condition\u0026mdash;for successful tax simplification. This is particularly consequential in developing and middle-income countries, where corruption is more pervasive and compliance burdens already impose substantial constraints on economic activity.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eOver the past decade, tax complexity has emerged as a central problem in the economics of public finance and fiscal governance. Policymakers, international organizations and civil society actors have increasingly recognized that overly complex tax systems generate significant economic distortions: they raise compliance costs, reduce allocative efficiency, distort firm and household behaviour and erode the fiscal contract between citizens and the state. The World Bank\u0026rsquo;s \u003cem\u003eDoing Business\u003c/em\u003e reports and the IMF\u0026rsquo;s technical notes on tax administration consistently highlight challenges arising from opaque rules, excessive documentation requirements and fragmented tax codes. These challenges are particularly salient in developing and middle-income countries, where administrative capacity is limited and enforcement is often uneven.\u003c/p\u003e \u003cp\u003eDespite widespread interest in the implications of tax complexity, scholarly work on this topic remains relatively narrow in scope. Theoretically, tax complexity has been examined through the lenses of optimal tax theory (Yitzhaki, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Mayshar, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), which primarily focuses on the balance between revenue efficiency and administrative cost. Another stream of research emphasizes the behavioural and compliance consequences of complexity (Slemrod, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Diamond, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), arguing that complexity may serve as a policy instrument to conceal redistribution or encourage specific taxpayer behaviours. More recently, political economy approaches have gained attention for recognizing the strategic motivations behind tax system design. Pioneering work by Hettich and Winer (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) and Warskett et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) models tax complexity as an endogenous outcome shaped by political competition, interest group influence and electoral incentives. These studies suggest that complexity is not merely a technical flaw but a deliberate outcome of institutional interactions.\u003c/p\u003e \u003cp\u003eEmpirically, however, literature is sparse. Few cross-national studies directly test the relationship between tax complexity and its political or institutional determinants. Slemrod (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) finds that US states with more professionalized legislatures tend to have more complex income tax structures, and Goerke (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) links tax complexity to underground economic activity. Yet a major gap remains: the role of corruption in shaping tax complexity has not been systematically examined. This omission is striking given the extensive literature on corruption\u0026rsquo;s impact on tax evasion, compliance and revenue collection (Tanzi, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Besley and Persson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Baum et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While these studies show that corruption reduces state capacity and distorts policy implementation, few have analysed how corruption affects the \u003cem\u003edesign\u003c/em\u003e of the tax code itself\u0026mdash;particularly through its interaction with interest group lobbying and bureaucratic discretion.\u003c/p\u003e \u003cp\u003eThis study seeks to fill that gap by offering a conceptual and empirical analysis of the relationship between political corruption and tax complexity from a comparative governance perspective. We first develop a conceptual framework in which politicians, influenced by interest group lobbying, trade off between marginal political support and tax compliance costs to maximize electoral utility. The framework predicts that higher levels of corruption increase the marginal political benefit from satisfying interest groups, thereby pushing the equilibrium toward greater tax complexity. We then test this prediction using panel data from 177 countries spanning 2012 to 2019. Using the Corruption Perceptions Index (CPI) as the key independent variable and two proxies for tax complexity\u0026mdash;the number of tax payments per year and the time required to comply\u0026mdash;we estimate fixed-effects panel regressions. To address potential endogeneity between corruption and tax complexity, we implement two-stage and three-stage least squares (2SLS, 3SLS) methods with multiple control variables and robustness checks.\u003c/p\u003e \u003cp\u003eThe remainder of this article is organized as follows. The next section presents the conceptual framework and discusses its implications. The third section outlines the empirical methodology, data sources and variable construction. The fourth section reports the main estimation results and robustness tests. The final section concludes with implications for governance reform and directions for future research.\u003c/p\u003e"},{"header":"2. Conceptual framework","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Basic model\u003c/h2\u003e \u003cp\u003eThe structure of tax systems is not solely the result of economic optimization but also reflects political bargaining. Tax policies create winners and losers, leading various actors to exert influence during their formulation and implementation. We consider a representative policymaker who maximizes political utility by balancing support from organized interest groups and disutility from public compliance costs. Interest groups offer political contributions in exchange for favourable tax provisions, while general taxpayers respond to perceived fairness and complexity.\u003c/p\u003e \u003cp\u003eAs in prior studies (Hettich and Winer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Warskett et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), we assume a representative politician with the authority to formulate tax policies. In a representative democracy, the goal of such a politician is to maximize the vote. Interest groups acting for specific purposes seek to have politicians change the tax system in their favour, providing political support or monetary rewards in return. After one group succeeds in exerting influence, another group exerts similar influence to revise the tax system further. Through this iterative process, the tax system becomes increasingly complex.\u003c/p\u003e \u003cp\u003eWhen politicians responsible for tax policy succumb to the influence of interest groups, the resulting complexity increases compliance costs for ordinary taxpayers. This generates political discontent. Despite being unorganized, ordinary taxpayers are numerous, and politicians who aim to win votes cannot ignore the resulting burden. We formalize the policymaker\u0026rsquo;s objective function as:\u003c/p\u003e \u003cp\u003e \u003cem\u003eMaxₓ V(S(x), P(x))\u003c/em\u003e \u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ex\u003c/em\u003e represents the level of tax complexity, \u003cem\u003eS(x)\u003c/em\u003e is the marginal political gain from satisfying interest groups, and \u003cem\u003eP(x)\u003c/em\u003e is the marginal political cost associated with taxpayer compliance burden. Both functions are increasing in \u003cem\u003ex\u003c/em\u003e, but at different rates. The optimal level of tax complexity is achieved where the marginal gain from interest group support equals the marginal cost of taxpayer discontent:\u003c/p\u003e \u003cp\u003e \u003cem\u003edS(x)/dx\u0026thinsp;=\u0026thinsp;dP(x)/dx\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAt this point, denoted as TC*, the tax system balances the political benefits of catering to interest groups against the political costs of taxpayer dissatisfaction. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates this equilibrium, showing how tax complexity is endogenously determined in a political environment. Formally, the second-order condition requires d\u0026sup2;V/dx\u0026sup2; \u0026lt; 0, ensuring that the equilibrium is a maximum. Applying the implicit function theorem to the first-order condition yields: dTC*/dα = \u0026minus;(\u0026part;\u0026sup2;V/\u0026part;x\u0026part;α) / (\u0026part;\u0026sup2;V/\u0026part;x\u0026sup2;), where α denotes the level of corruption. Because the denominator is negative by the second-order condition and the numerator is positive\u0026mdash;corruption raises the marginal political return from satisfying interest groups\u0026mdash;this expression is strictly positive: dTC*/dα\u0026thinsp;\u0026gt;\u0026thinsp;0. The equilibrium level of tax complexity is therefore increasing in corruption. This comparative static result constitutes the core testable prediction of the model.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eabout here]\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Corruption and tax complexity\u003c/h2\u003e \u003cp\u003ePolitical corruption can be broadly defined as the misuse of public authority for private gain, particularly when policymakers alter tax systems in response to rent-seeking demands. Prior research has examined corruption primarily in relation to bureaucratic incentives and wage structures (Becker and Stigler, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Besley and McLaren, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Mookherjee and Png, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Van Rijckeghem and Weder, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), as well as through case studies of administrative corruption in developing countries (Andreski, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1968\u003c/span\u003e; Wade, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Other studies link corruption to fiscal outcomes such as lower tax compliance, weaker revenue capacity and slower economic growth (Besley and Persson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Aghion et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Baum et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile this literature establishes the broad consequences of corruption, relatively little attention has been given to its impact on the structural design of tax systems. Most existing studies emphasize compliance or revenue effects, overlooking how corruption shapes the institutional architecture of tax codes. By amplifying interest group influence, corruption may encourage the proliferation of loopholes, exemptions and fragmented provisions, thereby inflating both administrative costs for the state and compliance costs for firms and households. From the perspective of the economics of governance, this raises a fundamental question: how does the quality of political institutions determine the equilibrium design of core fiscal institutions?\u003c/p\u003e \u003cp\u003eThis study contributes to filling this gap by embedding corruption into a political economy model of tax design. In our framework, corruption increases the marginal political returns from accommodating interest groups, which shifts the equilibrium level of tax complexity from TC* to TC**. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the presence of corruption raises the marginal support curve, making complex tax systems electorally more advantageous for politicians. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e further depicts the predicted positive relationship between corruption and tax complexity, providing the core hypothesis to be tested in the empirical section.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eabout here]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eabout here]\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Empirical analysis","content":"\u003cp\u003e\u003cem\u003e3.1 Model and method\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study empirically investigates the effect of corruption on tax complexity using panel data for 177 countries between 2012 and 2019. We begin with fixed-effects regression models and then apply two-stage and three-stage least squares (2SLS and 3SLS) to address potential endogeneity between corruption and tax complexity. The baseline specification is:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTaxComplexityᵢₜ = \u0026alpha;ᵢ + \u0026beta;Corruptionᵢₜ + \u0026gamma;Xᵢₜ + uᵢ + \u0026lambda;ₜ + \u0026epsilon;ᵢₜ\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ewhere\u0026nbsp;\u003cem\u003ei\u003c/em\u003e denotes the country and\u0026nbsp;\u003cem\u003et\u003c/em\u003e the year. Tax complexity is measured by either the number of tax payments per year or the time required for compliance. Corruption is the Corruption Perceptions Index (CPI), reverse-coded so that higher values indicate greater corruption.\u0026nbsp;\u003cem\u003eX\u003c/em\u003e is a vector of control variables, while\u0026nbsp;\u003cem\u003euᵢ\u003c/em\u003e and\u0026nbsp;\u003cem\u003e\u0026lambda;ₜ\u003c/em\u003e capture country and year fixed effects. To capture possible reverse causality, we also estimate a simultaneous equation model:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCorruptionᵢₜ = \u0026theta; + \u0026phi;TaxComplexityᵢₜ + \u0026delta;Zᵢₜ + uᵢ + \u0026lambda;ₜ + \u0026eta;ᵢₜ\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ewhere\u0026nbsp;\u003cem\u003eZ\u003c/em\u003e represents instruments for corruption. We employ GNI per capita and the democracy index as excluded instruments. The exclusion restriction requires that these variables affect tax complexity only through their effect on corruption, not directly. GNI per capita satisfies this condition to the extent that wealthier economies modernize tax administration primarily through the channel of lower corruption rather than independently of it; we acknowledge, however, that income may also directly reduce complexity through digitalization and administrative capacity, and we therefore treat GNI per capita as a weaker instrument and rely more heavily on institutional identification. The democracy index is argued to be excludable on the grounds that democratic accountability affects the level and design of tax codes primarily by constraining the ability of politicians to engage in rent-seeking on behalf of interest groups\u0026mdash;that is, through the corruption channel. We verify instrument relevance via the first-stage F-statistic (reported in Table 4) and conduct standard overidentification tests where applicable. This approach allows us to test whether corruption not only affects but is also affected by tax complexity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2 Measurement of variables and data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe empirical analysis relies on an unbalanced panel dataset of 177 countries from 2012 to 2019, covering the period for which consistent data on both corruption and tax complexity are available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variables.\u0026nbsp;\u003c/strong\u003eTax complexity is measured using two indicators from the World Bank\u0026rsquo;s\u0026nbsp;\u003cem\u003eDoing Business\u003c/em\u003e database: the number of tax payments per year and the time required for compliance (hours per year). The former reflects the structural fragmentation of tax obligations, while the latter captures administrative burdens placed on taxpayers. These measures have been widely applied in earlier work (Slemrod, 2005; Goerke, 2008). It should be noted that the World Bank discontinued the Doing Business programme in September 2021 following an independent review of data irregularities. Our analysis uses the 2012\u0026ndash;2019 panel, which predates this discontinuation and draws on the original data series that was publicly available and peer-reviewed in the literature throughout our study period. We therefore treat these measures as valid proxies for the study window, while acknowledging in the limitations section that future research will require alternative data sources for more recent periods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent variable.\u0026nbsp;\u003c/strong\u003eCorruption is measured by the Corruption Perceptions Index (CPI) published by Transparency International. The CPI ranges from 0 (highly corrupt) to 100 (very clean). For interpretability, we reverse the scale so that higher values indicate greater corruption. Prior studies have frequently relied on the CPI as a cross-national indicator of institutional quality (Treisman, 2000; Besley and Persson, 2014).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eControl variables.\u0026nbsp;\u003c/strong\u003eTo isolate the effect of corruption, we include control variables reflecting economic, social, fiscal and institutional conditions: GNI per capita as a proxy for economic capacity; expected years of schooling to capture taxpayer capability; voter turnout to reflect civic engagement and political accountability; tax revenue as a percentage of GDP to capture fiscal size; the corporate profit tax rate to account for statutory burdens; and the democracy index to capture institutional quality (Slemrod, 2005; Besley and Persson, 2014; Treisman, 2000). Variable definitions and sources are summarized in Table 1, while descriptive statistics are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 1 about here]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 2 about here]\u003c/strong\u003e\u003c/p\u003e"},{"header":"4. Results","content":"\u003cp\u003eTable 3 presents the baseline regression results using country and year fixed effects. Across all specifications, corruption is positively and significantly associated with tax complexity, confirming the main hypothesis. Both dependent variables\u0026mdash;the number of tax payments per year and the time required for compliance\u0026mdash;respond systematically to changes in corruption levels. A one-unit increase in the reversed CPI (indicating greater corruption) corresponds to an average increase of roughly 0.3 to 0.4 additional tax payments and 5 to 7 more hours of compliance time annually. While these marginal effects may appear modest, they accumulate into substantial burdens when considered across entire economies and over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 3 about here]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 reports the results from the 2SLS and 3SLS estimations, which address potential endogeneity concerns. The findings remain robust: corruption continues to exert a positive and significant impact on tax complexity. The instrumental variable estimations yield slightly larger coefficients than the fixed-effects models, suggesting that OLS estimates may be downward biased due to reverse causality. By correcting for this simultaneity, the 2SLS and 3SLS results provide stronger evidence that corruption is a driving force behind complexity, rather than merely its byproduct.\u003c/p\u003e\n\u003cp\u003eThe estimated effects of control variables align with theoretical expectations. Higher GNI per capita reduces compliance time, reflecting the role of wealthier economies in modernizing tax administration through digitalization. Education levels are negatively associated with compliance costs. Voter turnout and democracy are consistently linked to lower levels of complexity, emphasizing the role of citizen accountability and institutional checks in constraining excessive design manipulation. Higher corporate profit tax rates are associated with greater structural complexity, likely due to exemptions and special provisions. Larger tax revenues as a share of GDP tend to be associated with more complexity, consistent with the view that expanding fiscal size requires diversification of tax bases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 4 about here]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 provides robustness checks by altering model specifications and control variables. Even when certain institutional or fiscal variables are excluded, or when alternative controls are added, the corruption coefficient remains positive and significant. The magnitude of the effect is strikingly stable, reinforcing the conclusion that omitted variables are unlikely to explain the main results.\u003c/p\u003e\n\u003cp\u003eTable 6 presents further robustness checks using subsample analyses and alternative measurements. When high-income OECD countries are excluded, the corruption\u0026ndash;complexity relationship persists, confirming its broader applicability. Lagging the corruption index by one year yields nearly identical estimates, providing further reassurance that reverse causality is not the main explanation. When alternative institutional proxies such as the World Bank\u0026rsquo;s government effectiveness and rule of law indices are included, the results remain robust.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 5 about here]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[Table 6 about here]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTaken together, Tables 3 through 6 present a consistent narrative: corruption significantly increases both the structural and administrative dimensions of tax complexity. This effect holds across multiple model specifications, estimation methods, control variables and subsamples. Far from being a marginal or indirect factor, corruption emerges as a central institutional determinant of tax complexity. These results confirm the predictions outlined in the conceptual framework and highlight the importance of governance quality in shaping not only tax compliance and revenue outcomes but also the fundamental architecture of tax administration.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study has examined the relationship between corruption and tax complexity from both a conceptual and empirical perspective. Building on a governance-centred political economy framework, we argued that corruption amplifies the influence of interest groups on policymaking, thereby encouraging politicians to introduce additional provisions, exemptions and administrative requirements into the tax code. In this setting, tax complexity is not simply a technical byproduct of fiscal needs but rather a deliberate political outcome shaped by corrupt incentives.\u003c/p\u003e \u003cp\u003eUsing panel data from 177 countries between 2012 and 2019, we tested this hypothesis with two complementary measures of tax complexity. Across fixed-effects regressions, 2SLS and 3SLS estimations, corruption consistently demonstrated a significant positive effect on both dimensions of complexity. The results were robust to alternative specifications, subsample analyses, lagged models and different institutional proxies.\u003c/p\u003e \u003cp\u003eFrom a governance perspective, the results suggest that efforts to reduce corruption may have broader administrative benefits than previously recognized. Much of the existing literature emphasizes the role of corruption in lowering compliance, reducing tax revenues and undermining state capacity. Our findings extend this view by demonstrating that corruption also shapes the very structure of tax codes, making them more complex, opaque and costly to comply with. Anti-corruption reforms may therefore yield dual benefits: not only improving revenue mobilization but also simplifying tax administration and lowering compliance costs for taxpayers. These benefits are particularly critical in developing and middle-income countries, where corruption is more pervasive and the administrative burden of tax compliance already imposes substantial constraints on business activity.\u003c/p\u003e \u003cp\u003eThe results also have implications for international administrative reform. Recent global initiatives such as the OECD\u0026rsquo;s Base Erosion and Profit Shifting framework and discussions on a global minimum tax emphasize transparency and simplification. However, without addressing corruption at the domestic level, such reforms may fail to achieve their intended outcomes. Policymakers and international organizations should therefore consider governance quality as a key condition for the successful implementation of global tax initiatives.\u003c/p\u003e \u003cp\u003eDespite these contributions, this study has certain limitations. First, our measures of tax complexity, while widely used, are proxies that capture only two dimensions of a broader phenomenon. Complexity also encompasses legal intricacies, the frequency of tax code amendments and the ambiguity of provisions\u0026mdash;dimensions that are more difficult to measure systematically. Moreover, the Doing Business programme was discontinued by the World Bank in 2021, which limits the extension of our analysis to more recent years; future research should explore alternative cross-country tax complexity indicators such as the PwC/World Bank Paying Taxes report or the Tax Complexity Index developed by Hoppe et al. (2023). Second, the Corruption Perceptions Index, while the most widely adopted cross-country indicator, relies on perceptions and may not fully capture variations in actual corrupt behaviour. Future research could benefit from exploring alternative datasets, such as micro-level survey evidence or administrative data on tax disputes. Third, while our analysis establishes a plausible causal link through 2SLS and 3SLS estimation, the exclusion restriction underlying our instrumental variable strategy\u0026mdash;particularly for GNI per capita\u0026mdash;may not hold strictly, as income could affect tax complexity through channels other than corruption such as administrative modernization or digitalization. We mitigate this concern by reporting overidentification tests and by demonstrating stability across multiple instrument sets, but caution is warranted in interpreting the IV estimates as fully structural. Fourth, further work is needed to understand the specific mechanisms\u0026mdash;such as lobbying, bureaucratic discretion or legislative bargaining\u0026mdash;through which corruption translates into complex tax codes.\u003c/p\u003e \u003cp\u003eOverall, this study contributes to the economics of governance literature by demonstrating that corruption is a systematic institutional determinant of tax code complexity. By showing that corruption raises the equilibrium level of tax complexity through interest group politics, it underscores that fiscal institutions cannot be understood solely through the lens of optimal tax theory or administrative efficiency. The design of tax systems reflects the political equilibrium in which they are embedded, and that equilibrium is shaped by the quality of governance. Simplifying tax systems cannot be achieved solely through technical fixes or administrative modernization; it also requires altering the underlying political incentives that drive complexity. Anti-corruption reform should therefore be recognized not only as a governance imperative but as a precondition for fiscally efficient and economically sustainable institutional design.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose. The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNa Young Kim:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Formal analysis, Writing \u0026ndash; original draft. \u003cstrong\u003eSangheon Kim:\u0026nbsp;\u003c/strong\u003eConceptualization, Data curation, Formal analysis, Writing \u0026ndash; review and editing. \u003cstrong\u003eKwang Bin Bae:\u0026nbsp;\u003c/strong\u003eConceptualization, Supervision, Writing \u0026ndash; review and editing, Project administration. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study relies exclusively on publicly available secondary data and does not involve human participants, animal subjects, or personally identifiable information. Accordingly, ethical approval from an institutional review board was not required for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study are derived from publicly available sources: the World Bank\u0026rsquo;s Doing Business database (https://www.doingbusiness.org), Transparency International\u0026rsquo;s Corruption Perceptions Index (https://www.transparency.org/en/cpi), the World Bank World Development Indicators, the UNESCO Institute for Statistics, International IDEA, and the Economist Intelligence Unit Democracy Index. The compiled dataset is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAghion P, Akcigit U, Cage J, et al. (2016) Taxation, corruption, and growth. \u003cem\u003eEuropean Economic Review\u003c/em\u003e 86: 24\u0026ndash;51.\u003c/li\u003e\n \u003cli\u003eAndreski S (1968) Kleptocracy as a system of government in Africa. In:\u0026nbsp;\u003cem\u003eThe African Predicament: A Study in the Pathology of Modernization\u003c/em\u003e. London: Michael Joseph, 92\u0026ndash;116.\u003c/li\u003e\n \u003cli\u003eBaum A, Gupta S, Kimani E, et al. (2017) Corruption, taxes and compliance. IMF Working Paper No. WP/17/255. Washington, DC: International Monetary Fund.\u003c/li\u003e\n \u003cli\u003eBecker GS (1983) A theory of competition among pressure groups for political influence.\u0026nbsp;\u003cem\u003eQuarterly Journal of Economics\u003c/em\u003e 98(3): 371\u0026ndash;400.\u003c/li\u003e\n \u003cli\u003eBecker GS and Stigler GJ (1974) Law enforcement, malfeasance and the compensation of enforcers.\u0026nbsp;\u003cem\u003eJournal of Legal Studies\u003c/em\u003e 3(1): 1\u0026ndash;18.\u003c/li\u003e\n \u003cli\u003eBesley T and McLaren J (1993) Taxes and bribery: The role of wage incentives.\u0026nbsp;\u003cem\u003eEconomic Journal\u003c/em\u003e 103(416): 119\u0026ndash;141.\u003c/li\u003e\n \u003cli\u003eBesley T and Persson T (2014) Why do developing countries tax so little?\u0026nbsp;\u003cem\u003eJournal of Economic Perspectives\u003c/em\u003e 28(4): 99\u0026ndash;120.\u003c/li\u003e\n \u003cli\u003eDiamond P (2009) Taxes and pensions.\u0026nbsp;\u003cem\u003eSouthern Economic Journal\u003c/em\u003e 76(1): 2\u0026ndash;15.\u003c/li\u003e\n \u003cli\u003eGoerke L (2008) Tax overpayments, tax evasion, and the role of penalties.\u0026nbsp;\u003cem\u003ePublic Finance Review\u003c/em\u003e 36(5): 567\u0026ndash;587.\u003c/li\u003e\n \u003cli\u003eHettich W and Winer SL (1988) Economic and political foundations of tax structure.\u0026nbsp;\u003cem\u003eAmerican Economic Review\u003c/em\u003e 78(4): 701\u0026ndash;712.\u003c/li\u003e\n \u003cli\u003eHuntington SP (1968)\u0026nbsp;\u003cem\u003ePolitical Order in Changing Societies\u003c/em\u003e. New Haven, CT: Yale University Press.\u003c/li\u003e\n \u003cli\u003eLoretz S (2020) Corporate taxation in the European Union: Current state and perspectives.\u0026nbsp;\u003cem\u003eInternational Tax and Public Finance\u003c/em\u003e 27(4): 1013\u0026ndash;1036.\u003c/li\u003e\n \u003cli\u003eMayshar J (1991) Taxation with costly administration.\u0026nbsp;\u003cem\u003eScandinavian Journal of Economics\u003c/em\u003e 93(1): 75\u0026ndash;88.\u003c/li\u003e\n \u003cli\u003eMookherjee D and Png IPL (1995) Corruptible law enforcers: How should they be compensated?\u0026nbsp;\u003cem\u003eEconomic Journal\u003c/em\u003e 105(428): 145\u0026ndash;159.\u003c/li\u003e\n \u003cli\u003eOlson M (1965)\u0026nbsp;\u003cem\u003eThe Logic of Collective Action: Public Goods and the Theory of Groups\u003c/em\u003e. Cambridge, MA: Harvard University Press.\u003c/li\u003e\n \u003cli\u003ePeltzman S (1976) Toward a more general theory of regulation.\u0026nbsp;\u003cem\u003eJournal of Law and Economics\u003c/em\u003e 19(2): 211\u0026ndash;240.\u003c/li\u003e\n \u003cli\u003eSlemrod J (1990) Optimal taxation and optimal tax systems.\u0026nbsp;\u003cem\u003eJournal of Economic Perspectives\u003c/em\u003e 4(1): 157\u0026ndash;178.\u003c/li\u003e\n \u003cli\u003eSlemrod J (2005) The etiology of tax complexity: Evidence from US state income tax systems.\u0026nbsp;\u003cem\u003ePublic Finance Review\u003c/em\u003e 33(3): 279\u0026ndash;299.\u003c/li\u003e\n \u003cli\u003eStigler GJ (1971) The economic theory of regulation.\u0026nbsp;\u003cem\u003eBell Journal of Economics and Management Science\u003c/em\u003e 2(1): 3\u0026ndash;21.\u003c/li\u003e\n \u003cli\u003eTanzi V (1994) Corruption around the world: Causes, consequences, scope, and cures.\u0026nbsp;\u003cem\u003eIMF Staff Papers\u003c/em\u003e 45(4): 559\u0026ndash;594.\u003c/li\u003e\n \u003cli\u003eTreisman D (2000) The causes of corruption: A cross-national study.\u0026nbsp;\u003cem\u003eJournal of Public Economics\u003c/em\u003e 76(3): 399\u0026ndash;457.\u003c/li\u003e\n \u003cli\u003eVan Rijckeghem C and Weder B (2001) Bureaucratic corruption and the rate of temptation: Do wages in the civil service affect corruption, and by how much?\u0026nbsp;\u003cem\u003eJournal of Development Economics\u003c/em\u003e 65(2): 307\u0026ndash;331.\u003c/li\u003e\n \u003cli\u003eWade R (1982) The system of administrative and political corruption: Canal irrigation in South India.\u0026nbsp;\u003cem\u003eJournal of Development Studies\u003c/em\u003e 18(3): 287\u0026ndash;328.\u003c/li\u003e\n \u003cli\u003eWarskett G, Hettich W and Winer SL (1998) The complexity of tax structure in competitive political systems.\u0026nbsp;\u003cem\u003eInternational Tax and Public Finance\u003c/em\u003e 5(2): 123\u0026ndash;151.\u003c/li\u003e\n \u003cli\u003eYitzhaki S (1979) A note on optimal taxation and administrative costs.\u0026nbsp;\u003cem\u003eAmerican Economic Review\u003c/em\u003e 69(3): 475\u0026ndash;480.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eData definitions and sources.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition and measurement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eGNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eGNI per capita: economic level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eWorld Bank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eExpected Years of Schooling of Children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eUNESCO Institute for Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eVoter Turnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eVoter Turnout rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eInternational IDEA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eTax revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eTax revenue (% of GDP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eWorld Bank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eTax rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eProfit Tax Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eWorld Bank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eDemocracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 277px;\"\u003e\n \u003cp\u003eDemocracy Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eEconomist Intelligence Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eProfit Tax Rate is the corporate tax burden excluding deductions divided by gross profit (World Bank, Doing Business). Democracy Index consists of five categories: electoral process and pluralism, civil liberties, functioning of government, political participation and political culture.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDescriptive statistics (2012\u0026ndash;2019).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eNumber of tax payments per year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e26.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e16.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eTime to tax payments (hours)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e262.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e227.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eCorruption (CPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e42.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e19.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eGNI per capita ($)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e13790.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e18611.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e104560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eEducation level (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e13.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eVoter Turnout (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e65.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e16.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e17.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e99.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eTax Revenue (% of GDP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e16.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e8.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e149.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eProfit Tax Rate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e15.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e9.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026minus;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 224px;\"\u003e\n \u003cp\u003eDemocracy development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e55.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e22.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eN = 750\u0026ndash;770 country-year observations across 177 countries.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eBaseline regression results (country and year fixed effects).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cem\u003eDV: Number of tax payments per year\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eCorruption (CPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.07*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.07*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.08**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.12**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eGNI per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;2.64E-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.94E-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.21E-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.32E-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.36E-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.32E-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eTax Revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eTax Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.10*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;2.98***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;3.09***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;3.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;3.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eVoter Turnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.07**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.07**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.07**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDemocracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.12***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eStandard errors clustered by country in parentheses. * p \u0026lt; 0.1, ** p \u0026lt; 0.05, *** p \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003e2SLS and 3SLS results.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cem\u003eDV: Time to tax payments (hours)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eCorruption (CPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;4.58***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;4.60***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;5.63***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;4.71***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eGNI per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.45E-3**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.42E-3**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.39E-3**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(7.20E-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(7.20E-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(7.05E-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eTax Revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eTax Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2.67***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2.63***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2.82***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e2.93***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e17.03***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e16.58***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e15.07***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e15.64***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(4.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eVoter Turnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDemocracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e1.23*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e1.28*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e1.25*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e1.57**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e(0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eInstrumental variables include GNI per capita and democracy index. All regressions include country and year fixed effects. Standard errors in parentheses. * p \u0026lt; 0.1, ** p \u0026lt; 0.05, *** p \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eAlternative specifications.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2SLS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3SLS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cem\u003eDV: Number of tax payments\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eCorruption (CPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.12* \u0026nbsp;(0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.12* \u0026nbsp;(0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eTax Revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.05 \u0026nbsp;(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.08 \u0026nbsp;(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eTax Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.09 \u0026nbsp;(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.07 \u0026nbsp;(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;2.92*** \u0026nbsp;(0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;2.92*** \u0026nbsp;(0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eVoter Turnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.07** \u0026nbsp;(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.04 \u0026nbsp;(0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eDemocracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.07* \u0026nbsp;(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.06 \u0026nbsp;(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.72 (weighted)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eRobustness checks with alternative control variables. Standard errors in parentheses. * p \u0026lt; 0.1, ** p \u0026lt; 0.05, *** p \u0026lt; 0.01.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eRobustness checks.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2SLS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3SLS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cem\u003eDV: Time to tax payments (hours)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eCorruption (CPI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;7.64*** \u0026nbsp;(1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;8.31*** \u0026nbsp;(1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eTax Revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;1.21 \u0026nbsp;(1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026minus;0.16 \u0026nbsp;(0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eTax Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e2.66*** \u0026nbsp;(1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e1.98** \u0026nbsp;(0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e20.15*** \u0026nbsp;(4.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e25.70*** \u0026nbsp;(4.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eVoter Turnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.39 \u0026nbsp;(0.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.61 \u0026nbsp;(0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eDemocracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e2.29** \u0026nbsp;(0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e2.01** \u0026nbsp;(0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e0.56 (weighted)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eSubsample regressions exclude OECD countries and include lagged corruption indices. Additional models replace democracy index with World Bank governance indicators. Standard errors in parentheses. * p \u0026lt; 0.1, ** p \u0026lt; 0.05, *** p \u0026lt; 0.01.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"economics-of-governance","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eogo","sideBox":"Learn more about [Economics of Governance](http://link.springer.com/journal/10101)","snPcode":"10101","submissionUrl":"https://submission.nature.com/new-submission/10101/3","title":"Economics of Governance","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"tax complexity, corruption, governance quality, interest groups, political economy of taxation, fiscal institutions","lastPublishedDoi":"10.21203/rs.3.rs-9074606/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9074606/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article investigates the impact of corruption on tax complexity by integrating a governance-centred conceptual framework with cross-country empirical analysis. While existing research has primarily examined the effects of corruption on tax compliance and revenue performance, relatively little attention has been paid to how corruption shapes the structural and administrative design of tax systems. Drawing on political economy theory, we argue that corruption amplifies the political returns of accommodating interest groups, leading policymakers to introduce additional provisions, exemptions and procedural requirements that make tax codes more complex. We develop a conceptual framework in which corruption shifts the political equilibrium toward higher levels of complexity, and then evaluate this prediction using panel data for 177 countries from 2012 to 2019. Employing fixed-effects regressions as well as two- and three-stage least squares estimations, we measure tax complexity using two indicators from the World Bank\u0026rsquo;s \u003cem\u003eDoing Business\u003c/em\u003e database: the number of tax payments per year and the time required for compliance. Across all specifications, corruption significantly increases both measures of complexity, and the results remain robust under alternative samples, specifications and institutional proxies. Our findings highlight the importance of addressing corruption not only to improve compliance and revenue but also to simplify tax administration and reduce compliance costs. By embedding corruption into a formal political economy model and testing its predictions with large-scale cross-country panel data, this article contributes to the economics of governance literature and to broader debates on the political determinants of fiscal institutions.\u003c/p\u003e","manuscriptTitle":"Interest Groups, Corruption, and Tax Complexity: A Comparative Governance Perspective with Global Evidence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-23 15:45:31","doi":"10.21203/rs.3.rs-9074606/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-03T21:29:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60416300334853185575139166422385121000","date":"2026-03-23T00:21:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289332829232624455507475822923580938832","date":"2026-03-19T08:10:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-18T15:42:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-13T05:27:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-13T05:27:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Economics of Governance","date":"2026-03-09T14:59:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"economics-of-governance","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eogo","sideBox":"Learn more about [Economics of Governance](http://link.springer.com/journal/10101)","snPcode":"10101","submissionUrl":"https://submission.nature.com/new-submission/10101/3","title":"Economics of Governance","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7d3831c1-cb03-4e67-b5fe-436be721d75d","owner":[],"postedDate":"March 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T15:45:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-23 15:45:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9074606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9074606","identity":"rs-9074606","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}