This recent article is likely of interest to tax crimes fans. Asher Schechter, How Insufficient Enforcement Led to Prevalent Tax Evasion and Contributed to American Inequality(U. Chicago Booth School Stigler Center Promarket 6/24/21), here. The article expands on the recent publication of IRS data on the very wealthy by ProPublica. See ProPublica Publishes Series Based on IRS Data Trove Produced by Anonymous Source (Federal Tax Crimes Blog 6/8/21), here; and Tax Crimes Core Concept Questions from ProPublica’s Publication of Tax Return Information (Federal Tax Crimes Blog 6/10/21), here.
About the ProPublica disclosed data, the author of this article discusses the tax evasion – yes, the crime – aspects of the phenomenon, citing a recent NBER publication, John Guyton, Patrick Langetieg, Daniel Reck, Max Risch & Gabriel Zucman, Tax Evasion at the Top of the Income Distribution(NBER Working Paper Series No. 28542 March 2021), here.
Excerpts from the article:
The other side of the coin is tax evasion, which unlike tax avoidance is illegal. How prevalent is tax evasion by the rich, and how significant is it to the overall picture of inequality? A working paper published in March by researchers John Guyton and Patrick Langetieg from the IRS, along with economists Daniel Reck (London School of Economics), Max Risch (Carnegie Mellon), and Gabriel Zucman (University of California, Berkeley) showed tax evasion at the top of the US income distribution is much worse than previously thought: while unreported or under-reported income is at 7 percent among the bottom 50 percent of the income distribution, the top 1 percent hide 21 percent of their true income.
Tax evasion by high-income people is notoriously difficult to measure due to the myriad ways in which wealthy individuals can evade taxes, from unreported offshore accounts to pass-through entities like partnerships and S-corporations. To study the extent of tax evasion, Guyton et al. used a trove of IRS tax return data, mainly from the IRS’ random audit program, the National Research Program (NRP). What they find is that of the 21 percent of true income that top earners don’t report to the IRS, 6 percent is due to these sophisticated tax evasion strategies.
In addition to the increasingly regressive US tax system (a trend that was also covered in Zucman’s 2019 book with Emmanuel Saez), the study also underscores how inadequate enforcement contributed to America’s current tax inequality, highlighting the asymmetry between high-income, high-wealth individuals, who have the funds to attempt ever more sophisticated methods of tax evasion, and the IRS auditors, who don’t have the resources to keep up.
Evasion Largely Goes Undetected
Cracking down on wealthy taxpayers who hide or underreport their income to avoid paying taxes is a big part of the Biden administration’s effort to raise taxes on the wealthy to fund its ambitious legislative agenda (Biden’s American Families Plan cites Guyton et al.’s estimates), but one thing that complicates these attempts at fighting tax evasion is just how widespread it has become among America’s richest households.
To measure the extent of tax evasion, the IRS relies on random audits that measure the amount of income that goes under-reported as a fraction of true income (under-reporting gap), and of the tax that is owed but not paid (tax gap).
In theory, random audits are supposed to provide a pretty accurate estimate of the scope of tax evasion. In the academic literature, as the authors note, it is considered “the gold standard for understanding tax evasion.” The problem, however, is that random audits were designed with common forms of tax evasion in mind: for instance, self-employed people who don’t report their full income, or taxpayers who abuse the tax credit system. When it comes to more sophisticated forms of tax evasion—ones that are used almost exclusively by the very rich—the evasive tactics tend to go undetected, which means that random audits end up underestimating tax evasion at the very top.
To show this, Guyton et al. looked into the thousands of individual tax returns of people who disclosed offshore assets as part of the government crackdown on offshore tax havens that followed the 2008 financial crisis. The authors tracked individuals who filed a Foreign Bank Account Report (FBAR) and individuals who participated in the Offshore Voluntary Disclosure Program (OVDP), an Obama-era program that enabled taxpayers to avoid prosecution by voluntarily reporting previously-undisclosed offshore accounts and paying a fine. Hundreds of these individuals were randomly audited prior to disclosing their foreign assets, and Guyton et al. compare these audits with the post-disclosure returns. What they find is that the auditors detected the hidden offshore wealth in just 7 percent of these cases.
For pass-through entities—partnerships, proprietorships, and S-corporations that are not subject to corporate taxes and whose taxes “pass through” their owners’ individual tax returns—the authors find that among individuals who were subject to a random audit and under-reported their pass-through income, auditors detected the tactic in only 3.8 percent of the cases. The result? “While the income of taxpayers in the bottom 99 percent of the income distribution is comprehensively examined, up to 35 percent of the income earned at the top is not comprehensively examined in the context of random audits.”
Because these forms of tax evasion are highly concentrated among the top earners, accounting for this unreported or under-reported income would significantly increase the income share of the top 1 percent, according to the authors by about 1.5 percent. Of the federal income taxes that are unpaid, they find, 36 percent are owed by the top 1 percent. Among the top 0.1 percent, taxes evaded are more than twice as large.
In fact, the richer you are, the less susceptible you are to get caught evading taxes during a random audit: detected evasion, the authors find, “declines sharply at the very top of the income distribution, with only a trivial amount of evasion detected in the top 0.01 percent.” The reason is that NRP audits detect very little evasion on dividends, capital gains, and interest, the top sources of income for members of the top 0.1 percent. Nevertheless, the authors suggest that 60 percent of the wealth hidden in offshore tax havens belongs to the top 0.1 percent of earners, and 35 percent belongs to the top 0.01 percent.
Such gains held in offshore accounts only became subject to reporting requirements in 2014, after the Foreign Account Tax Compliance Act [FATCA], enacted in 2010, went into effect; the period studied in the paper ends at 2013. When asked whether the picture would be significantly different today, post-crackdown on offshore havens, Reck wrote in an email to ProMarket that this is “a big open question that I am trying to understand better in other work. FATCA shows some promise but there’s a lot of uncertainty and disagreement out there about how optimistic we should be that it is making a big difference.”
The reason that the very wealthy often get away with evading taxes, the authors suggest, is simple: auditors attempting to wade through networks of pass-through business entities and offshore havens to determine whether the income reported in an individual tax return is correct face considerable challenges in deciphering byzantine ownership and partnership structures. It takes significant expertise, resources, and personnel to detect evasion at these levels—things the IRS, in its current diminished form, does not have enough of.
Also, readers interested further should read the NBER report cited by the author of the article and which I cited and linked above. From the article here are some key excerpts:
ABSTRACT
This paper studies tax evasion at the top of the U.S. income distribution using IRS micro-data from (i) random audits, (ii) targeted enforcement activities, and (iii) operational audits. Drawing on this unique combination of data, we demonstrate empirically that random audits underestimate tax evasion at the top of the income distribution. Specifically, random audits do not capture most tax evasion through offshore accounts and pass-through businesses, both of which are quantitatively important at the top. We provide a theoretical explanation for this phenomenon, and we construct new estimates of the size and distribution of tax noncompliance in the United States. In our model, individuals can adopt a technology that would better conceal evasion at some fixed cost. Risk preferences and relatively high audit rates at the top drive the adoption of such sophisticated evasion technologies by high-income individuals. Consequently, random audits, which do not detect most sophisticated evasion, underestimate top tax evasion. After correcting for this bias, we find that unreported income as a fraction of true income rises from 7% in the bottom 50% to more than 20% in the top 1%, of which 6 percentage points correspond to undetected sophisticated evasion. Accounting for tax evasion increases the top 1% fiscal income share significantly.
John Guyton
Internal Revenue Service
Research, Applied Analytics, and Statistics
77 K Street, NE
Washington, DC 20002
john.guyton@irs.govPatrick Langetieg
Internal Revenue Service
Research, Applied Analytics, and Statistics
77 K Street, NE
Washington, DC 20002
Patrick.T.Langetieg@irs.govDaniel Reck
London School of Economics
Department of Economics
Houghton Street
London WC2A 2AE
United Kingdom
d.h.reck@lse.ac.ukMax Risch
Tepper School of Business
Carnegie Mellon University
4765 Forbes Ave.
Pittsburgh, PA 15213
United States
mwrisch@andrew.cmu.eduGabriel Zucman
Department of Economics
University of California, Berkeley
530 Evans Hall, #3880
Berkeley, CA 94720
and NBER
zucman@berkeley.edu
And also worth considering, the Introduction and Conclusion:
1 Introduction
How much do high-income individuals evade in taxes? And what are the main forms of tax noncompliance of the top of the income distribution? Because taxable income and tax liabilities are highly concentrated at the top of the income distribution, understanding noncompliance by high-income taxpayers is critical for the analysis of tax evasion, for tax enforcement, and for the conduct of tax policy.
A key difficulty in studying tax evasion by the wealthy is the complexity of the forms of tax evasion at the top, which can involve legal and financial intermediaries, sometimes in countries with a great deal of secrecy. This complexity means that one single data source is unlikely to uncover all forms of noncompliance at the top. In this paper, we attempt to overcome this limitation in the U.S. context by combining a wide array of sources of micro data, including (i) random audit data, (ii) the universe of operational audits conducted by the IRS, and (iii) targeted enforcement activities (e.g., on offshore bank accounts). Drawing on this unique combination of data, we show that random audits underestimate tax evasion at the top-end of the income distribution. We provide a theoretical explanation for this fact, and we propose a methodology to improve the estimation of the size and distribution of tax noncompliance in the United States.
The starting point of our analysis is the IRS random audit program, known as the National Research Program. Random audits are commonly used to study and measure the extent of tax evasion. Researchers use random audits to test theories of tax evasion (Kleven et al., 2011), and tax authorities use them to estimate the overall extent of tax evasion and target audits (IRS, 2019). The academic notion of the random audit as the gold standard for understanding tax evasion comes from the traditional appeal of random sampling, combined with the classic deterrence model of tax evasion (Allingham and Sandmo, 1972), an implicit assumption of which is that audits lead to the detection of all tax evasion. In the real world, however, random audits do not detect all forms of tax evasion. Random audits are well designed to detect common forms of tax evasion, such as unreported self-employment income, overstated deductions, and the abuse of tax credits. But, we argue, these audits may not detect sophisticated evasion strategies, because doing so can require much more information, resources and specialized staff than available to tax authorities for their random audit programs.
Our first contribution is to document and quantify the limits of random audits when it comes to detecting top-end evasion in the United States. We find that detected evasion declines sharply at the very top of the income distribution, with only a trivial amount of evasion detected in the top 0.01%. Our analysis uncovers two key limitations of random audits which can account for much of this drop-off: tax evasion through foreign intermediaries (e.g., undeclared foreign bank accounts) and tax evasion via pass-through businesses (e.g., partnerships). First, we find that offshore tax evasion goes almost entirely undetected in [*3] random audits.1 To establish this result, we analyze the sample of U.S. taxpayers who disclosed hidden offshore assets in the context of specific enforcement initiatives conducted in 2009–2012. A number of these taxpayers had been randomly audited just before this crackdown on offshore evasion. In over 90% of these audits, the audit had not uncovered any foreign asset reporting requirement, despite the fact that these taxpayers did own foreign assets. Second, we find that tax evasion occurring in pass-through businesses (whose ownership is often highly concentrated) is substantially under-detected in individual random audits. Examiners usually do not verify the degree to which pass-through businesses have duly reported their income, especially for the most complex businesses. Thus, while the income of taxpayers in the bottom 99% of the income distribution is comprehensively examined, up to 35% of the income earned at the top is not comprehensively examined in the context of random audits.
n1 Our data cover the period prior to the collection of third-party reported information on foreign bank accounts, which started in 2014; we analyze how our results can inform knowledge about post-2014 evasion in Section 4.
Our second contribution is to propose improved estimates of how much income (relative to true income) the various groups of the population under-report—and to investigate the consequences of this underreporting for the measurement of inequality. We do so by starting from evasion estimated in random audits and proposing a correction for sophisticated evasion that goes undetected in these audits. Although our corrected series feature only slightly more evasion on aggregate than in the standard IRS methodology, our proposed adjustments have large effects at the top of the income distribution. Our adjustments increase unreported income by a factor of 1.1 on aggregate, but by a factor of 1.3 for the top 1% and 1.8 for the top 0.1%.
After these adjustments, we find that under-reported income as a fraction of true income rises from about 7% in the bottom 50% of the income distribution to 21% in the top 1%. Out of this 21%, 6 percentage points correspond to sophisticated evasion that goes undetected in random audits. We also show that accounting for under-reported income increases the top 1% fiscal income share significantly. In our preferred estimates, the top 1% income share rises from 20.3% before audit to 21.8% on average over 2006–2013. The result that accounting for tax evasion increases inequality is robust to a wide range of robustness tests and sensitivity analysis (for instance, it is robust to assuming zero offshore tax evasion).
Our third contribution is to explain why general-purpose random audits are not uniformly able to detect noncompliance across the income distribution. We present a model in which high-income taxpayers adopt sophisticated evasion strategies. We show that introducing this element in the canonical Allingham and Sandmo (1972) tax evasion model changes our understanding of tax evasion by high-income persons.
The model allows a taxpayer to adopt some costly form of tax evasion that is unlikely to be discovered on audit at some cost. We show that adoption of such an evasion technology is likely to be concentrated at the top of the income distribution for two reasons. First, high-income taxpayers have a greater demand [*4] for sophisticated evasion strategies that reduce the probability of detection if (i) the desired rate of evasion does not become trivial at large incomes, and (ii) the cost of adopting becomes a trivial share of income at large incomes. This is true even holding the probability of audit by income fixed. Second, overall audit rates and scrutiny of tax returns are substantially higher at the top than at the bottom of the distribution, making evasion that is less likely to be detected and corrected on audit more attractive at the top. We can also reinterpret the model to think about situations where the outcome of an audit, if it occurs, is uncertain. With this interpretation, for the same reasons as before, we show that high-income people are then more likely to adopt positions in the “gray area” between legal avoidance and evasion. From the point of view of the tax authority, we show theoretically that high resource costs of pursuing sophisticated forms of tax evasion, such as protracted litigation or more sophisticated audits of a complex network of closely-held businesses, can pose practical limits on the extent to which the tax authority can pursue these types of tax evasion by high-income people. This is especially the case when resource constraints are exogenous and not changed when sophisticated evasion becomes more prevalent.
These findings have implications for the academic literature, for policymakers, and for the public debate over income taxes at the top. Academically, our findings show that the existing framework for thinking about tax evasion has limitations when it comes to top-end tax evasion. The increasingly conventional wisdom is that taxpayers seldom evade taxes supported by third-party information (Kleven et al., 2011; Carrillo et al., 2017; Slemrod et al., 2017; IRS, 2019), and that deterring evasion where taxes are not supported by third-party information requires increasing the audit rate, or the penalty rate, or, arguably, increasing tax morale (Luttmer and Singhal, 2014). This characterization works well for the middle and bottom of the income distribution. However, it misses the importance of the concealment of evasion (even from auditors) at the top, and the adoption of aggressive interpretations of tax law for sheltering purposes. From a government revenue perspective, the top of the income distribution is the sub-population where understanding the extent of tax evasion is the most important, due to the high and increasing concentration of income in the United States (Piketty and Saez, 2003; Piketty et al., 2018).
From a policy perspective, our results highlight that there is substantial evasion at the top which requires administrative resources to detect and deter. We estimate that 36% of federal income taxes unpaid are owed by the top 1% and that collecting all unpaid federal income tax from this group would increase federal revenues by about $175 billion annually. There has been much discussion in the United States about the fact that the audit rate at the top of the income distribution has declined. Our results suggest that such low audit rates are not optimal. As standard audit procedures can be limited in their ability to detect some forms of evasion by high-income taxpayers, additional tools should also be mobilized to effectively combat high-income tax evasion. These tools include facilitating whistle-blowing that can uncover sophisticated evasion [*5] (which helped the United States start to make progress on detection of offshore wealth) and specialized audit strategies like those pursued by the IRS’s Global High Wealth program and other specialized enforcement programs. Additionally, our results suggest that data beyond conventional random audits may be useful for risk assessment, audit selection, and the allocation of resources to alternative types of enforcement. The IRS currently does many of these things to some degree, but resource constraints limit its capacity to do so (see, e.g., TIGTA, 2015). Our results suggest that investing in improved tools and increasing resources to support tax administration at the top of the distribution could generate substantial tax revenue (a point also made by, e.g., Sarin and Summers, 2020).
The rest of this paper is organized as follows. Section 2 studies the distribution of noncompliance in random audit data. Section 3 provides direct evidence that some forms of evasion are (i) highly concentrated at the top of the income distribution, (ii) effectively invisible in random audits, and (iii) quantitatively important for the measurement of income at the top. In Section 4 we present our new estimates of the distribution of noncompliance and we investigate their implications for the measurement of inequality. Section 5 presents our theory of why some noncompliance goes undetected, and Section 6 concludes.
* * * *
6 Conclusion
We find that substantial evasion at the top of the income distribution goes undetected in random audits. Investigating taxpayers who voluntarily declared hidden wealth or started reporting foreign bank accounts in 2009–2012 and who had been randomly audited just before, we find that in the vast majority of cases, the audits had failed to uncover offshore tax evasion. Focusing on taxpayers who earn business income through partnerships and S-corporations, we find that due to the resource constraints inherent to the conduct of random audits, a large fraction of this business income is not examined in the context of these audits, biasing detected evasion downward at the top.
Theoretically, we show that modelling the choice to conceal tax evasion from auditors can explain why random audits do not detect all evasion especially at the top. Empirically, we provide corrected estimates of the size and distribution of tax evasion in the United States. In our benchmark scenario, we find that under-reported income rises from about 7% of true income in the bottom 50% of the income distribution to 21% in the top 1%. Out of this 21%, about 6 percentage points correspond to sophisticated evasion that is seldom detected in random audits. Accounting for tax evasion increases the top 1% income share in the United States.
It is important to note that random audit programs were not designed to estimate the tax gap for very high-income, high-wealth individuals. To experts who are familiar with these audits, our results may be unsurprising. However, we nevertheless view these results as important in light of an increased academic and policy interest in top income shares and tax evasion at the top. Countries around the world use random audits to estimate the tax gap (see, e.g., OECD, 2017, chapter 14). Our findings suggest that due to the limitations of random audits, more work is needed to estimate the extent of tax evasion at the top of the income distribution globally.
We stress that our estimates are likely to be conservative with regard to the overall amount of evasion at the top. From public reporting and anecdotal evidence, it seems likely that there are other specific forms of tax evasion that have the same properties as those we examine in this paper—sophistication and concentration among high income/wealth individuals. Such forms of evasion could include the abuse of syndicated conservation easements, micro-captive insurance schemes, private inurement in tax-exempt organizations, and the use of offshore trusts to evade tax. Many of these strategies involve pass-through businesses or other entities controlled by the taxpayer. The potential existence of many more such schemes underscores the main point of our theoretical results, that we should expect sophisticated evasion to be concentrated at the top of the income and wealth distribution. More research is needed to improve estimates of noncompliance at the very top in the United States.
[*51]
We identify several other potentially fruitful avenues for future work. First, it would be valuable to consider the importance of sophisticated evasion and gray area avoidance strategies for optimal tax administration policies involving high-income, high-wealth taxpayers. Second, more research is needed to fully understand the gray area between avoidance and evasion, a line which can be blurry at the top of the income distribution and for large corporations. Future work could consider the implications of this notion for taxpayer behavior. Third, future research could consider strategic interaction between the tax authority and high-income individuals. We stopped short of such strategic, game-theoretic questions in our analysis, focusing separately on decisions by the individual taxpayer and by the tax authority. However, such strategic interactions may be empirically relevant and merit exploration in the future. Finally, future work could consider the implications of the theoretical ideas pursued here for white collar, financial crime more broadly, beyond sophisticated tax evasion.
Finally, readers might want to review the section titled “3 What Random Audits Miss: Evidence” which covers the following subjects of interest to blog readers:
- 3.1.1 Background and Data on Offshore Evasion (NBER Report pp. 15-25)
- 3.2 Evasion on Pass-Through Business Income (NBER Report pp. 25-32)
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