Tax Evasion and Inequality

Tax Evasion and Inequality∗
Annette Alstadsæter (Norwegian University of Life Sciences) Niels Johannesen (University of Copenhagen and CEBI) Gabriel Zucman (UC Berkeley and NBER)
August 1, 2018

Abstract
Drawing on a unique dataset of leaked customer lists from offshore financial institutions matched to administrative wealth records in Scandinavia, we show that offshore tax evasion is highly concentrated among the rich. The skewed distribution of offshore wealth implies high rates of tax evasion at the top: we find that the 0.01% richest households evade about 25% of their taxes. By contrast, tax evasion detected in stratified random tax audits is less than 5% throughout the distribution. Top wealth shares increase substantially when accounting for unreported assets, highlighting the importance of factoring in tax evasion to properly measure inequality.
∗ Annette Alstadsæter: annette.alstadsater@nmbu.no; Niels Johannesen: niels.johannesen@econ.ku.dk; Gabriel Zucman: zucman@berkeley.edu. This paper is supplemented by an Online Appendix available at gabriel-zucman.eu/leaks. We thank the Scandinavian tax administrations (Skatteetaten, Skattever- ket, and SKAT), Statistics Sweden, and SVT Uppdrag granskning for their goodwill and cooperation; Sigurd Bjørnestad, Joachim Dyfvermark, Linda Larsson Kakuli, Fredrik Laurin, Petter Lundberg, Søren Pedersen, Gard Thomassen, and UiO Services for Sensitive Data (TSD) for exceptionally valuable assistance; Alan Auerbach, Brooke Harrington, Send Jonas, Patrick Kline, Adair Morse, Daniel Reck, Emmanuel Saez, Joel Slemrod, Daniel Waldenstr ̈om and numerous seminar and conference participants for helpful comments and reactions. We are grateful for financial support from the Nordic Tax Research Council and the FRIPRO-program of the Research Council of Norway. Johannesen gratefully acknowledges financial support from the Danish Council for Indepen- dent Research and the Danish National Research Foundation. Zucman gratefully acknowledges financial support from the Laura and John Arnold Foundation.

1 Introduction
The size and distribution of tax evasion is a source of sustained interest and controversy among the public. Some believe that the bulk of tax evasion is done by the wealthy, a view fueled recently by high-profile leaks from offshore financial institutions such as the “Panama Papers.” Others stress that poorer individuals may be more likely to evade taxes, highlighting fraud by the self-employed or abuse of refundable tax credits.
Who evades taxes—and how much—matters for both economists and policy-makers. First, and most importantly, it matters for the study of inequality. Over the last fifteen years, scholars have increasingly relied on tax data to study distributional issues, especially trends in top income and wealth shares (see Roine and Waldenstr ̈om, 2015, for a recent survey). Tax returns are the best available data source to study the top-end of the distribution, because they do not, contrary to surveys, suffer from sampling errors—everybody above a certain income level has to file a return. But they raise an obvious issue: since tax rates, tax evasion technologies, and tax enforcement strategies differ across countries and have changed dramatically over time, tax data may paint a distorted picture of the cross-country and time-series patterns in inequality. Second, tax evasion matters for analyzing the effects of governments intervention in the economy; it redistributes the tax burden and affects the costs of raising taxes, “bread-and-butter concerns of public economics” (Slemrod, 2017). Last, knowing how tax evasion is distributed would help tax authorities—which face tight budget constraints—to better target their enforcement effort.
Tax evasion is fundamentally hard to study because there is no single source of information capturing all of it. The key source used so far in rich countries is stratified random audits. These audits are a powerful way to uncover unreported self-employment income, abuses of tax credits, and more broadly all relatively simple forms of tax evasion. Tax authorities rely on random audits to estimate the tax gap, that is, the total amount of unreported income and unpaid taxes (e.g., IRS, 2016), and academics have fruitfully used them to gain insights on the determinants of tax evasion (e.g., Kleven et al., 2011). But random audits do not allow one to study tax evasion by the very wealthy satisfactorily, both because of insufficient sample sizes, and because they fail to capture sophisticated forms of evasion involving legal and financial intermediaries, the detection of which would require much more resources than available to tax authorities for their random audit programs. This limitation means that random audits need to be supplemented with other data sources to study tax evasion at the top of the distribution. Such data, however, have so far proven elusive.
In this paper, we analyze new micro-data that make it possible to study tax evasion by 1

very rich individuals. These data come from recent, massive leaks from offshore financial institutions—HSBC Switzerland (“Swiss Leaks”) and Mossack Fonseca (the “Panama Papers”)— and tax amnesties conducted in the aftermath of the financial crisis of 2008–2009. Thanks to a cooperation with Scandinavian administrations, we were able to analyze the leaked and amnesty micro-data matched to population-wide administrative income and wealth records in Norway, Sweden, and Denmark.
The leaked and amnesty data we exploit in this paper reveal a number of consistent and striking findings. The probability of hiding assets offshore rises sharply and significantly with wealth, including within the very top groups of the wealth distribution. Conditional on hiding assets, the fraction of one’s true wealth hidden abroad is high (around 40%) and does not vary with wealth. As a result, the wealth in tax havens turns out to be extremely concentrated: the top 0.01% of the wealth distribution owns about 50% of it. When we apply this distribution to available estimates of the amount of wealth hidden in tax havens based on systematic ex- ploitation of the available macroeconomic statistics (Zucman, 2013), we find that the top 0.01% evades about 25% of its tax liability by concealing assets and investment income abroad. This estimate only takes into account the wealth held offshore that evades taxes; it excludes properly declared offshore assets: throughout the article, we maintain a clear distinction between legal tax avoidance and illegal evasion.
Our estimate of tax evasion at the top (25% of taxes owed) is an order of magnitude larger than the tax evasion detected by random audits in other wealth groups (less than 5% throughout the distribution). Of course, random audits are likely to miss some forms of tax evasion in the bottom and the middle of the distribution. Whenever there is no information trail, it is hard if not impossible for examiners to uncover non-compliance. It is important to note, however, that most individuals in rich countries truly have few possibilities to evade a lot of taxes, for the simple reason that most of their income derives from wages, pensions, and investment income earned in domestic financial institutions—income sources that are automatically reported to the tax authority. By contrast, tax evasion is possible for the very rich because there is an industry that helps them conceal wealth abroad, and most of their income derives from wealth.1 Tax evasion is also possible for the self-employed, and indeed random audits uncover widespread tax evasion among them. But because self-employment income is only a small fraction of total income in Scandinavia and because the self-employed are scattered throughout the wealth distribution,
1In recent years, for instance, a number of financial institutions have pleaded guilty of criminal conspiracies to defraud the IRS by helping American customers to hide assets in Switzerland or other tax havens; see Section 6 below.
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non-compliance by these individuals does not appear to be enough to generate sizable evasion rates in any specific segment of the wealth distribution.2 In that context, and although there was until recently no good data to study this issue, it is perhaps not too surprising that evasion rates at the top appear to be higher than those further down the wealth ladder.
Do our findings apply to other countries? We certainly do not claim that our estimates of evasion by wealth group in Scandinavia hold everywhere as a universal law. We note, however, that there is nothing unique to Scandinavia that could explain the high evasion rates we find at the top. Residents of all developed countries are typically, like in Scandinavia, taxable on their worldwide income. And although Scandinavian countries are high-tax in an international perspective, this owes more to their high value-added and payroll taxes than to high rates on personal capital incomes, which are in fact taxed at flat, relatively low rates in Norway and Sweden (Kleven, 2014). In our view, Scandinavian economies are an interesting laboratory, because they rank among the countries with the strongest respect for the rule of law (Kauffmann and Kraay, 2017) and highest “tax morale” (Luttmer and Singhal, 2014), suggesting that evasion among the wealthy may be even higher elsewhere. We stress, however, that in countries such as Greece and Mexico (and even more so in developing countries) where the self-employed generate a much higher fraction of output than in Scandinavia, the size and distribution of tax evasion is likely to be markedly different. Many tax authorities have access to random audit, amnesty, and leaked data similar to those we use in this research. In future work we plan to apply our methodology to estimate distributional tax gaps—i.e., how evasion across the distribution—in as many countries as possible.
Our paper adds to the large body of work on tax evasion.3 Our main contribution to this literature is that we are able to document tax evasion by very rich taxpayers (e.g., with more than $50 million in net wealth) whose behavior could not be properly studied until now. Tax evasion at the top is important to study because wealthy taxpayers, although few in number, own a large share of total wealth and are liable for a large fraction of total taxes. In the United
2For example, using the same random audit data as we use in Section 5 below, Kleven et al. (2011) find that 44.9% of Danish self-employed evade taxes. But self-employment income only accounts for 6% of factor- cost GDP in Denmark, where—like in other advanced economies—the bulk of economic activity takes place in the corporate and public sectors (see Appendix Figure H.10). Moreover, one finds tax-evading self-employed individuals throughout the distribution: in the bottom or middle (e.g., plumbers) as in the top (e.g., lawyers).
3One strand of the literature uses random audit data; see for instance Bishop, Formby, and Lambert (2000), Johns and Slemrod (2010), and Kleven et al. (2011). Another strand uses a variety of methods to detect traces of tax evasion in micro or macro data; see Slemrod and Weber (2012) and Slemrod (2007, 2017) for surveys. Both of these sources find high rates of evasion for the self-employed, whose true income is found to be on average about 1.5 to 2 times their reported income (e.g., Pissarides and Weber, 1989; Feldman and Slemrod, 2007; Artavanis et al., 2015).
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States for instance, the top 0.1% owns about 22% of recorded household wealth, as much as the bottom 90% (Saez and Zucman, 2016).
We also contribute to the literature on top-end inequality. Over the last fifteen years, a number of studies have used tax data to construct top income and wealth shares for many countries.4 The literature discusses the problem raised by tax evasion (e.g., Atkinson, Piketty, Saez, 2011, pp. 36–40), but until recently there was little data that would allow to systematically quantify it. Zucman (2013) estimates that 8% of the world’s financial wealth is held in tax havens globally; a similar estimate is obtained by Pellegrini et al. (2016). Absent micro data on who owns the wealth hidden offshore, however, these studies could not assess the implications of tax havens for the measurement of inequality. Our contribution here is to study micro data that provide the first direct evidence on how hidden wealth is distributed.5
The rest of this paper proceeds as follows. Section 2 presents the HSBC, Panama Papers, and amnesty data, and Section 3 analyzes them. In Section 4 we combine these micro-data with macro estimates of the stock of wealth in tax havens to estimate the size and distribution of offshore evasion. Section 5 constructs distributional tax gaps taking into account offshore evasion and all other forms of evasion detected in random audits. Section 6 attempts to explain the high rates of tax evasion among the rich we uncover by studying the role played by the supply of tax evasion services. This paper is supplemented by an Online Appendix.6
2 Micro-Data on Households With Assets in Tax Havens
2.1 HSBC Switzerland Leak
The first micro-dataset used in this research is the leak from HSBC Private Bank Switzerland, the Swiss subsidiary of the banking giant HSBC. In 2007 a systems engineer employed by HSBC, Herv ́e Falciani, extracted the complete internal records of the 30,412 clients of this bank, a large fraction of whom were evading taxes. Falciani turned the data over to the French
4See, e.g., Piketty and Saez (2003) for U.S. top income shares, Saez and Zucman (2016) for U.S. top wealth shares, Atkinson et al. (2011) for a survey, Piketty (2014) for a broad interpretative synthesis, and Piketty, Saez and Zucman (2018) for an attempt at distributing all of U.S. national income (including legally tax-exempt income, but excluding income hidden abroad which is missed by the national accounts).
5Roine and Waldenstr ̈om (2008, 2009) study the distributional implications of hidden wealth for the recent period. They use an indirect method—residual flows in the balance of payments and financial accounts—to estimate the amount of wealth hidden by Swedish residents, and assume that this wealth primarily belongs to the top. The share of wealth owned by the top one percent rises from about 20 percent in the 2000s to a range of 25–30 percent depending on the methodology.
6The Appendix is available at gabriel-zucman.eu/leaks. All our code and data are posted online, excluding de-identified individual-level micro administrative data which cannot be publicly shared, but including a large number of tabulations of the raw data by bins of wealth which make our results fully replicable.
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government in 2008, who shared it with a number of foreign administrations when Christine Lagarde was Finance Minister in France (thus the “Falciani list” became known as the “Lagarde list”). The leaked files are not publicly available, but thanks to a cooperation with Scandinavian authorities, we were able to analyze the full portion of the Falciani/Lagarde list matched by the Scandinavian authorities to individual tax returns and administrative income and wealth data. From the complete set of leaked files, the authorities attempted to match all accounts potentially connected to Scandinavia (i.e., whose owner, controlling attorney, or other related party had an address in Scandinavia or Scandinavian nationality). They succeeded in about 90% of the cases, and we have access to all matched records.7
The HSBC leak has a number of key strengths for our purposes. First, it was not the result of specific enforcement effort by tax authorities and can be seen as a random event. The documents leaked by Falciani include the complete internal records—including the names and in the majority of cases account values—of the more than 30,000 clients (who controlled about 112,000 accounts) of this Swiss bank in 2007. Importantly, HSBC recorded the name of the beneficial owners of the wealth it managed, even when this wealth was held, as is frequently the case, through shell companies. Identifying beneficial owners is a requirement for banks under anti-money laundering regulations and it appears that HSBC complied with it. This is what made it possible for the authorities to link the accounts to their owners’ tax returns.
Second, at the time of the leak, HSBC Switzerland was a major player in the offshore wealth management industry. It managed 4.4% of all the foreign wealth in Swiss banks, $118.4 billion out of $2,667 billion. The $118.4 billion figure is the official value for 2007 published by HSBC (2015); the amount of offshore wealth managed by all Swiss banks is from the official statistics published annually by the Swiss central bank. Throughout this article, offshore wealth is defined as the sum of the bank deposits and portfolio securities (equities, bonds, mutual fund shares) managed by banks on behalf of non-resident investors. Since more than 200 banks operated in Switzerland at the time of the leak, the market share of HSBC Private Bank was significant; it was likely to be among the top 10 largest Swiss banks.8 Around $5.6 trillion of wealth was held
7Some of the unmatched accounts could belong to tax evaders (e.g., accounts owned by shell companies with Scandinavian attorneys, but whose beneficial owners were not known or recorded by HSBC) or to legitimate organizations (e.g., financial institutions or non-profit organizations). If these untraceable accounts are used by the wealthiest tax evaders, we under-estimate the concentration of tax evasion. Online Appendix E provides detailed background information about HSBC Switzerland, the leak, and the data we got access to in his research.
8Rankings of the world’s largest private banks (or private banking divisions of large bank holding companies) are regularly published in trade magazines (e.g., Scorpio partnership). At the time of the leak, other major players in this market included UBS, Credit Suisse, Julius Baer, Pictet, Royal Bank of Scotland, BNP Paribas, etc. To our knowledge, however, there are no reliable rankings for the Swiss wealth management industry alone (i.e., available rankings aggregate assets managed by banks in all their subsidiaries across the world, with no
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in tax havens globally at the time of the Falciani leak; HSBC Switzerland alone accounted for 2.1% of that total.9
Third, the available evidence suggests that HSBC was representative of the Swiss banking in- dustry. Importantly, there is no evidence that it was the “go-to” place for Scandinavians to park their wealth. A country-by-country breakdown of the wealth managed by HSBC Switzerland in 2007 is published by the International Consortium of Investigative Journalists (ICIJ), who obtained a copy of the complete set of files leaked by Falciani. An annual country-by-country breakdown of the amount of offshore wealth in all Swiss banks is published by the Swiss central bank. Figure 1 compares the two distributions; they look similar. Scandinavian residents, in particular, own in total about 1% of the wealth held at HSBC and 1% of all the wealth held in all Swiss banks.10 Moreover, we have not found evidence that HSBC was catering to very wealthy clients more than its peers. In the years before the leak it was in fact advertising its wealth management services in most of the world’s airports, so it is possible that its clientele was actually less wealthy than that of its more discrete competitors.
A last strength of the HSBC leak is that it provides a clear-cut way to assess whether tax evasion is involved. All developed countries tax residents on their worldwide income. Owning offshore accounts is legal, as long as any interest, dividend, or capital gain earned is duly declared by the account’s owner on his individual income tax return. Moreover, offshore accounts must typically be reported to tax authorities (in the United States, using the electronic Foreign Bank and Financial Account form if the account value is $10,000 or more). In Denmark and Norway, the tax authorities, after detailed investigations, found that 90% to 95% of all HSBC account- holders had failed to report the income earned on their account (and the wealth held there in the case of Norway, where a wealth tax exists) and were thus evading taxes.11 This result
country-by-country breakdowns).
9The $5.6 trillion estimate for the world’s offshore wealth in the middle of 2007 is from Zucman (2013). We
return to the computation of the global amount of wealth in tax havens in Section 4 when we try to estimate the size and distribution of total offshore tax evasion (i.e., at HSBC and other offshore banks).
10Some countries are slightly over-represented in the HSBC leak, notably Venezuela, the United States, and Brazil. This can be explained as follows. In 1999, HSBC Switzerland merged with the Republic National Bank of New York and Safra Republic Holdings, two private banks with a large customer base in the United States and Brazil respectively. In addition, according to the ICIJ, the biggest account at HSBC Switzerland was a US$ 11.9 billion account registered in the name of Venezuela’s National Treasurer (who started off as a bodyguard for the late Venezuelan President Hugo Ch ́avez).
11This does not imply that all taxpayers with undeclared HSBC accounts have been convicted of tax evasion. In prosecuting the cases, the tax authorities face constraints. In particular, the nature of the evidence (a leaked file) raises legal issues and is generally insufficient to prove in court the existence of a hidden account. To circumvent this issue, tax authorities can ask for information from the Swiss tax authority and to HSBC. We know that in Denmark, in many instances neither the taxpayers nor the Swiss authorities cooperated, forcing the tax authority to drop cases. Note that it is optimal for the tax authority to focus its resources on prosecuting the largest cases; analyzing the sub-sample of cases that eventually led to conviction would thus introduce a
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is consistent with a body of evidence suggesting that more than 90% of Swiss accounts were undeclared around 2007; this includes two US Senate (2008, 2014) reports finding that 85– 95% of US-owned accounts at UBS and Credit Suisse were undeclared in 2007–2008, Roussille (2015) who estimates that more than 90% of the wealth held by Europeans in Switzerland was undeclared before 2010, and Johannesen and Zucman (2014) who obtain a similar estimate.
We construct our working sample of HSBC tax evaders as follows. Starting with all Scandi- navians linked by the tax authorities to an HSBC account, we exclude taxpayers who claimed to be non-residents, hence not taxable in Scandinavia.12 Some accounts are linked to several members of a single household; we remove any double-counting by conducting all our analysis at the household level. Last, we exclude the Norwegians who properly declared their accounts (we were not able to remove the few, around 20–30, properly declared Danish and Swedish accounts13). This leaves us with a sample of 520 households who owned at least one account at HSBC Switzerland, declared themselves as taxable in Scandinavia in 2006, could be matched to a tax return (and, for the Norwegian portion of the list, did not declare their account).
2.2 Panama Papers Leak
The second leak we use in this research is the Panama Papers. In the Spring of 2016, the ICIJ published the names and addresses of the owners of shell companies created by the Panamanian law firm Mossack Fonseca.14 The leak provides information on shell corporations that were created over two decades, many of which were still active at the time of the leak in 2015. Just like for HSBC, this leak is valuable as it can be seen as a random event that involves a prominent
selection bias and would lead us to over-estimate the concentration of tax evasion. We therefore do not base our assessment of whether tax evasion occurred on what was the legal outcome of the case, but instead on whether the account and the income it generated were declared on individual income tax returns (and wealth tax returns when a wealth tax exists). This is similar to what is done in random audit studies where non-compliance is estimated based on an examiner’s assessment—not a court decision.
12Note that some of them might in fact be taxable in Scandinavia: claiming to be non-resident is a form of tax evasion sometimes practiced by wealthy individuals, which we cannot detect with the data at our disposal. If true, we would under-estimate tax evasion at the top.
13This is unlikely to bias our findings significantly, since we know that close to 95% of the matched Danish and Norwegian accounts were undeclared. If anything, the inclusion of the duly reported Danish and Swedish accounts may lead us to slightly under-estimate the actual concentration of hidden wealth, as the available evidence suggests that declared accounts may belong to less wealthy evaders than hidden accounts. As shown by Appendix Figure E.5, the wealth held by Norwegians at HSBC—which excludes accounts properly declared— is more concentrated than than held by Swedish and Danish households—which includes properly declared accounts. The small size of the sample of declared accounts, however, does not give us enough power to reject the hypothesis that duly reported and undeclared accounts are distributed similarly. To simplify the exposition, in the rest of the analysis we consider that all matched Swedish and Danish households evade taxes.
14Online Appendix F provides background information about the Panama Papers and analyzes the data made public by the ICIJ. In contrast to the HSBC leak, all the names and corporate structures appearing in the Mossack Fonseca files have been disclosed by the ICIJ.
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provider of offshore financial services.
We matched the names of the shareholders of these shell companies to individual wealth data
in Norway and Sweden (but were not able to do so in Denmark). Although Mossack Fonseca is a major provider of offshore services, our working sample is smaller than for the HSBC leak (165 vs. 520). Beyond the exclusion of Denmark, one other factor contributes to the smaller sample size: a number of shell companies cannot be linked to their ultimate owner. A company created by Mossack Fonseca can be owned by another shell created by another incorporation agent, in which case ultimate owners remain untraceable—while they are usually identifiable at HSBC. Another limitation of the Panama Papers is that we do not know whether the Scandinavian individuals appearing in the leak evaded taxes. There are legal uses of shell companies, and the investigations conducted by the tax authorities are still ongoing. Despite these limitations, the Panama Papers provide valuable corroborating information on the extensive use of tax havens at the top of the distribution, as we shall see.
2.3 Tax Amnesty Participants
Our third micro-dataset is a large sample of individuals who voluntarily declared previously hidden assets in the context of tax amnesties. In recent years, governments have encouraged tax evaders to declare hidden wealth in exchange for reduced penalties. In the United States for example, beginning in 2009 the IRS has established a series of voluntary disclosure programs under which cooperating tax evaders pay reduced penalties and can avoid criminal sanctions (Johannesen et al., 2018). In Norway and Sweden we have access to all the voluntary disclosures made since 2006.15 The number of amnesty participants picked up significantly in 2009, when G20 countries compelled tax havens to exchange bank information upon request with foreign authorities (Johannesen and Zucman, 2014); it was negligible before.
A key advantage of the amnesty dataset is the large sample size: 1,422 households in Norway and 6,811 in Sweden. Another strength is that we know that tax evasion is, by definition, involved. This data source suffers from one limitation, however: there may be selection into the amnesty based on wealth. According to the canonical Allingham and Sandmo (1972) model of tax evasion (and assuming risk neutrality for simplicity), tax evaders should continue evading
15Appendix G discusses the specifics of the Norwegian and Swedish amnesties. In Norway we can observe the amounts disclosed, but in Sweden we cannot (that is, we can only see who used the amnesty, but not the amount of wealth these participants disclosed). Moreover, in Norway we have access to details on the origin and composition of the wealth disclosed. About half of it was held in Switzerland and most of the rest in other tax havens such as Luxembourg. More than 95% of the wealth disclosed was financial wealth (equities, bonds, mutual fund shares, bank deposits) and less than 5% housing. Anderrson, Schroyen and Torsvik (2018) analyze the characteristics of Norwegian amnesty participants.
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as long as τ, the marginal tax rate they face, is greater than p × θ, the probability to be detected times the penalty if detected.16 In 2009, when the number of households participating in amnesties starts rising, the only parameters that changes is the perceived probability to get caught, which increases. The increase may depend on wealth—and the effect could go either way. Only unsophisticated, moderately rich individuals with inherited offshore accounts might have perceived an increase in p in 2009, while very rich evaders may have considered they would always be able to conceal their wealth by using sophisticated combinations of shell companies and trusts. Conversely, the richest evaders might have feared that governments would strengthen their monitoring of the wealthy in the aftermath of the financial crisis; or liquidity constraints may have prevented less wealthy individuals from using tax amnesties that require them to pay back taxes. In the end, whether richer evaders self-select into amnesties is an empirical issue. By contrasting the amnesty and random leak data we have access to, we can directly test for such self-selection. The results discussed below suggest it is quantitatively small; if anything, wealthier tax evaders seem to be slightly less likely to participate in an amnesty.
3 Patterns of Tax Evasion in Leaked and Amnesty Data
In this Section we study how the probability to have a hidden HSBC account, to own a shell company created by Mossack Fonseca, or to disclose hidden assets in a tax amnesty, varies with wealth. Because our three samples differ in size, these probabilities do not have the same absolute level, but in all cases they rise sharply with wealth. We start by describing how we rank households in the wealth distribution, before discussing the results.
3.1 How We Rank Tax Evaders in the Wealth Distribution
We construct the full distribution of household wealth in Norway, Denmark, and Sweden fol- lowing a common methodology. All wealth series, computations, and results are described in a detailed manner in Online Appendix A (for Scandinavia as whole), B (for computations and issues specific to Norway), C (Sweden), and D (Denmark); here we discuss the main method- ological principles and data sources.
We compute wealth at the micro level for the entire population by distributing 100% of the macroeconomic amount of household wealth at market value recorded in the national accounts, following international guidelines codified in Alvaredo et al. (2016). Although the national accounts are unlikely to be perfectly accurate, this method enables us to estimate wealth levels
16See Baer and Le Borge (2008) for an analysis of a theoretical and empirical analysis of tax amnesties. 9

and shares for each Scandinavian country that are directly comparable, and comparable to those estimated in the United States by Saez and Zucman (2016) and in a growing number of countries where a similar methodology is applied.17
One advantage of the Scandinavian context is that it is possible there to compute a particu- larly reliable estimate of the wealth distribution, for one simple reason. While in most countries one has to rely on indirect methods to estimate wealth inequality, in Scandinavia we directly observe the market value of most wealth components for the entire population. Scandinavian administrations collect individual-level wealth data from a large number of third parties—banks, mutual funds, central securities depositories, insurance companies, etc.—which report on the end-of-year market value of the wealth they manage on behalf of their clients. Non-financial assets are recorded using land and real estate registries. These data have been successfully used in various research contexts, for instance by Fagereng et al. (2018) to study how rates of return vary across the wealth distribution in Norway and by Jakobsen et al. (2018) to study how wealth taxation affects wealth accumulation in Denmark.
To ensure comparability across the three Scandinavian countries (and with other countries), we make a number of adjustments, closely following the literature (e.g., Jakobsen et al., 2018). We summarize these adjustments in Appendix Table A.3. First, whenever appraisal values for housing are below market values, we upgrade the recorded values using the ratio of observed market prices to appraisal values. Second, we account for funded pension wealth, which was not reported at the micro-level in 2007.18 Last, we impute non-corporate business assets and unlisted equities by capitalizing business income and dividends respectively.
One might be concerned that these imputations introduce noise correlated with being a tax evader, which could bias some of our estimates. We have tested this by recomputing key results using the raw wealth data (without adjustments), and found negligible differences.19 This result is not too surprising, since the largest form of wealth missed by the administrative data is pension wealth (and housing wealth in Norway, which is recorded for only a fraction of its market value), forms of wealth which only account for a small fraction of total wealth at the top of the distribution—the main focus of our analysis.
17See the series published on the World Inequality Database at WID.world (Alvaredo et al., 2018).
18Pension wealth has been reported at the individual level in Denmark data since 2012; see Jakobsen et al. (2018). In 2012 we observe that about 40% of Danish pension wealth belongs to wage-earners and 60% to retirees. We assume a similar breakdown in the other Scandinavian countries; we then allocate the pension wealth of workers proportionally to wage income (winsorized at the 99th percentile) and the pension wealth of retirees proportionally to the pension benefits paid out of pension funds. Saez and Zucman (2016) use the same imputation procedure in the United States.
19See Appendix Figure G.6 which shows that in the case of Norway, the probability to hide assets by wealth bin is virtually unchanged whether one ranks households by their taxable net wealth or our measure of wealth.
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As shown by Appendix Figure A.16, wealth is similarly distributed in Norway, Sweden, and Denmark. The top 1% owns about 20% of total non-hidden wealth, the top 0.1% around 9%, and the top 0.01% around 4-5%. These estimates are the best we can form on the basis of the information available to the tax and statistical authorities; they disregard hidden assets. Taxable income is also similarly distributed, and the 3 countries share many macro features (in terms of average income and wealth, wealth composition, etc.; see Appendix Figure A.1 to A.17 for extensive comparisons). Thus for our main analysis, we combine Denmark, Norway, and Sweden into a single Scandinavian “country” as follows. We collapse each country’s population- wide data into small bins (of as few as 10 tax units at the top), compute average, minimum, and maximum wealth in each bin, using current market exchange rates to convert local currencies into US$,20 and interpolate the distribution of wealth within each bin using generalized Pareto interpolation methods (Blanchet et al., 2017). This makes it possible to study the distribution of wealth and tax evasion in Scandinavia as a whole, in a dataset virtually identical to the one that would exist if the population-wide files of the three countries could be appended (which is not currently possible). Admittedly, Norway, Sweden, and Denmark differ in some dimensions; e.g., Norway has less private wealth (maybe because it has more public wealth). But the gradients in the probability to hide assets are similar within each country; pooling them together simply allows us to reduce standard errors.
3.2 Tax Evasion in Leaks
The HSBC leak, the Panama Papers, and the amnesty data all paint the same picture: the probability of hiding assets offshore appears to rise sharply, continuously, and significantly with wealth, including within the very top groups of the wealth distribution.
Starting with HSBC, the top panel of Figure 2 shows that the fraction of Scandinavians who hide asset in that Swiss bank is negligible up to the top 1% threshold, and then rises to almost 1% for the 0.01% richest households, who own more than $44.5 million in net wealth at the end of 2006. Remember that HSBC Switzerland is just one bank in one tax haven, a bank that managed around 2% of the wealth held offshore globally at the time of the leak, so the high
20In the context of our study that focuses on top-end wealth, using market exchange rates seems preferable to using PPP exchange rates, because rich Scandinavians all have access to the same basket of goods and global assets. In Appendix A, we report detailed results on Scandinavian income and wealth using both market and PPP-adjusted exchange rates. PPP-adjusted rates slightly reduce the weight of Norway (where the price level is relatively high) in the Scandinavian aggregate but does not significantly affect any of the main results of the paper. All dollar figures given in this paper are at current-year prices and using current-year market exchange rates (for instance, $44.5 million is the threshold to be part of the top 0.01% of the Scandinavian wealth distribution in 2006, using 2006 prices and exchange rates to convert Scandinavian currencies into US$).
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absolute level of the probabilities is notable. The gradient is notable too: households in the top 0.01% are 13 times more likely to hide assets at HSBC than households in the bottom half of the top 1%, i.e., in between percentile 99 ($2 million in net wealth) and 99.5 ($3 million). The differences in the probabilities across wealth group are statistically significant. The first column of Table 1 reports bootstrapped standard errors for these probabilities and the second column shows pairwise comparisons across wealth bins. The probabilities to hide assets at HSBC differ from each other at the 5% level.21 As shown by Appendix Figures E.4 and E.4b, the gradients look the same in the three Scandinavian countries separately.
A remark is in order here. For the purpose of ranking HSBC customers in the wealth distribution, we added the hidden HSBC wealth to non-hidden wealth.22 This mechanically moves HSBC evaders up the wealth ladder. However, this re-ranking does not drive the gradient reported in the top panel of Figure 2. In Appendix Figure E.2, we re-produce this figure, but ranking households by their wealth excluding that held at HSBC; the patterns are similar.23
Households who evaded taxes through HSBC hid a strikingly large fraction of their total wealth in that Swiss bank. The bottom panel of Figure 2 shows the ratio of the wealth held at HSBC over total observable wealth in the sample of HSBC account-holders with available account values—the intensive margin of evasion, in contrast to the extensive margin studied in the top panel. HSBC customers owned around 40% of their wealth there, with no trend across the wealth distribution.
21 The only exception is for the very top bin—the top 0.01%—where the small sample size does not allow us to reject the null hypothesis that the probability to evade taxes is the same as in the rest of the top 0.1%. Appendix Table E.7 reports a version of Table 1 where the top 0.01% is lumped together with the next 0.04%, i.e., the top 0.1% is split in two equal-size groups, P99.9–99.95 (tax units with between $9.1 million and $14.6 million in net wealth) and P99.95–100 (tax units with more than $14.6 million). The probabilities to own an HSBC account are statistically different in these two groups at the 10% level.
22The amount hidden at HSBC is observable for 300 households out of 520. As discussed in Appendix E, the main explanation for the gap is that a number of accounts initially held by households directly in their own name were over time transferred to shell corporations, following which the identity of the beneficial owner remains observable in the files leaked by Falciani, but not the account details. As shown in Appendix Figure E.1, excluding accounts with no known values does not change the gradient reported in the top panel of Figure 2.
23Including hidden wealth when ranking households seems preferable, because doing so delivers the best estimate of the amount of wealth the HBSC evaders actually own given observable data. Johns and Slemrod (2010) follow a similar procedure in the United States. Note that if HSBC account-holders hide assets in other banks too, then we under-estimate their true wealth. In the extreme case where all offshore wealth belongs to the HSBC sample (i.e., these are the same households who have unreported accounts at HSBC, UBS, Credit Suisse, etc.), then many HSBC account-holders ranked below the top 0.01% actually belong to the top 0.01% and the gradient in the probability to hide assets abroad would be even steeper than implied by the HSBC data shown on Figure 2. Conversely, if all the non-HSBC offshore wealth belongs to other tax evaders (i.e., HSBC account holders do not hide assets elsewhere), then we over-estimate the rank of HSBC account-holders in the true Scandinavian wealth distribution. Our computations that add observable hidden wealth to non-hidden assets to rank households attempt to reach a middle ground between these two polar cases. With the data at our disposal, we cannot tell whether tax evaders tend to have accounts in multiple or just one bank.
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The Panama Papers confirm that the use of offshore financial institutions steeply rises with wealth. As shown in the top panel of Figure 3, the probability to own a Mossack Fonseca offshore shell company reaches 1.2% in the top 0.01% of the (Norwegian plus Swedish) wealth distribution, against less than 0.2% for all groups below the top 0.01%. The difference between the top 0.01% and all other groups is highly significant (Table 1, col. 5). The use of tax havens appears more concentrated in the Panama Papers than in the HSBC leak: in both Norway and Sweden, as shown by Appendix Figure F.1, one finds very few households who own Mossack Fonseca shell companies in the bottom 99.9% of the wealth distribution. One interpretation of this finding is that wealth concealment using shell corporations is a more sophisticated form of tax avoidance than owning offshore bank accounts. The two techniques are often combined, but the wealthiest tax evaders might be more likely to combine offshore accounts with shell companies, while less wealthy tax evaders may be relatively more likely to own offshore accounts in their own names.
3.3 Tax Evasion Among Amnesty Participants
Turning to amnesty participants, the bottom panel of Figure 3 shows that the probability to disclose previously hidden offshore wealth also rises sharply with wealth. There are three additional findings. First, and most importantly, the amnesty data reveal widespread evasion among the rich. Strikingly, 14% of all top 0.01% Norwegian and Swedish households have disclosed assets in a tax amnesty between 2009 and 2015. Thus, we know that at least 14% of Scandinavians’ richest households were evading taxes on the eve of the financial crisis of 2008-09.
Second, by contrasting the probabilities to appear in the HSBC leak to the probability to voluntarily disclose hidden assets, we can study whether self-selection into amnesties correlates with wealth. We find that the poorest evaders are slightly more likely to participate in an amnesty. Households between the 95th and the 99.5th percentile—i.e., with net wealth between about $1 and $3 million—are relatively over-represented in the amnesty sample. For that group, the odds of using the amnesty are 32.8 higher than the odds of evading taxes at HSBC. For the top 0.1%, the odds ratio drops to 20.4. Overall, however, the self-selection is not massive. As can be seen by comparing the top panel of Figure 2 to the bottom panel of Figure 3, the gradients in the probability to hide assets at HSBC vs. report hidden wealth in an amnesty are remarkably similar. As a result, our key estimates would be almost unchanged should we only use the amnesty data and disregard the leaked data altogether. This finding suggests that amnesty data—that are available to many tax authorities throughout the world—could be
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leveraged to study tax evasion and its distribution more extensively than they have so far.24 Third, as reported in cols. 9 and 10 of Table 1, we find that amnesty participants used to hide close to a third of their wealth on average, with no trend across the distribution. The fraction of wealth hidden is lower than in the HSBC sample (where it reaches 40%), consistent with the notion that the most aggressive tax evaders are less likely to self-select into amnesties. Finally, we pool HSBC evaders and amnesty participants, excluding the small overlap between the two samples. As reported in cols. 11 and 12 of Table 1, 14.8% of the top 0.01% richest Norwegians and Swedish households revealed hiding wealth or were caught in the HSBC leak, a probability statistically greater than that of the the next 0.04% (11.8%), which is itself greater
than than of the next 0.05%, and so on.
4 The Size and Distribution of Offshore Tax Evasion
The samples analyzed above are drawn from the universe of individuals who use tax havens. In this Section we combine these samples with macro statistics on the stock of wealth held in tax havens to estimate how much tax is evaded offshore by each group of the wealth distribution. We proceed in five steps:
1. Using central bank macro data, we estimate the total amount of wealth held by Scandi- navians in tax havens.
2. We make an assumption about what fraction of this wealth is hidden vs. properly declared.
3. We assume that hidden wealth is distributed in the same was as in our micro samples.
4. We apply a rate of return to the wealth hidden.
5. Using a tax simulator, we estimate the amount of evaded tax on hidden wealth in each
bin of the wealth distribution.
We discuss each of these steps in turn, before presenting robustness tests based on changing one, several, or all of these assumptions at the same time.
4.1 The Macro Stock of Offshore Wealth
First, the available evidence suggests that Scandinavians held in total around 1.6% of their wealth (the equivalent of 4.2% of their GDP) in tax havens in 2007. This estimate includes household wealth only, whether hidden or duly reported to tax authorities; it disregards cor- porate assets, such as assets owned by mutual funds operating in Luxembourg. As shown by
24Data from U.S. state amnesties were analyzed by Mikesell (1986), Fisher et al. (1989), and Crane and Nourzad (1990). These studies did not address the effect of tax evasion on U.S. income or wealth inequality.
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Alstadsæter, Johannesen and Zucman (2018, Figure 5), Scandinavian countries appear to have one of the world’s smallest stock of household offshore assets: significantly less than the United States (the equivalent of 7.3% of GDP), Continental European countries like France, Germany, and the U.K. (around 16% of GDP), or Greece (36% of GDP). Although quantifying the macro stock of wealth held offshore by Scandinavians involves a margin of error, our result is likely to be robust: we obtain similar results using two different methodologies, presented in Table 2.
Bottom-up estimate. Our first strategy is a bottom-up approach that scales up the wealth held by Scandinavians at HSBC Switzerland. We know that this bank managed $118.4 billion in wealth in 2007. Based on a systematic investigation of the international statistics and the anomalies therein, Zucman (2013) estimates that households held $5.6 trillion in tax havens globally at the time of the leak, i.e., 47.5 times the wealth held at HSBC. We apply this 47.5 multiplicative factor to the amount of wealth owned at HSBC by customers who were taxable in Scandinavia, could be matched to a tax return, and for whom we are able to observe account values, namely $1,013 million. By this estimate, Scandinavians owned $48 billion in tax havens globally in 2007, 1.5% of their total wealth. This method has two potential drawbacks. First, because it disregards the HSBC accounts that could not be matched to any individual income tax return and those where no balance information is available, it might under-estimate the total amount of offshore assets owned by Scandinavians. Second, if HSBC was the “go-to” place for Scandinavians to park their wealth, the 47.5 multiplicative factor we use would be too high.
Top-down estimate. Our second strategy is a top-down approach that does not rely on the HSBC data. It is this top-down approach that we retain for our benchmark estimates. Starting from the $5.6 trillion in global offshore wealth, we allocate this total across countries by using macro statistics disclosed by tax havens on who owns deposits in their banks. The Swiss central bank has published a breakdown of the bank deposits owned in Switzerland by country of the owner since the 1970s; a number of prominent tax havens—including Luxembourg, the Channel Islands, and Hong Kong—have started publishing similar, retrospective information through the Bank for International Settlements in 2016. In a companion paper (Alstadsæter, Johannesen and Zucman, 2018) we use this new information to allocate the global amount of offshore wealth to each of the world’s countries, and thoroughly discuss the data and methodology involved. By this estimate, Scandinavians owned 1.6% of their wealth in tax havens in 2007.
It is notable that our two methods deliver consistent results, despite the fact that they rely on independent data. This result confirms that Scandinavians did not have an idiosyncratic
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preference for HSBC. The amnesty data also clearly show that the wealth hidden at HSBC was only a small fraction of that concealed in total by Scandinavians. Among the 8,233 Norwegian and Swedish households who disclosed previously hidden assets in a tax amnesty over the 2007– 2015 period, only about 50 disclosed an HSBC Switzerland account. More than 99% of amnesty participants hid assets in other offshore banks.25
If anything, our estimate of Scandinavians’ offshore wealth is likely to be conservative. Both our bottom-up and top-down approaches rely on Zucman’s (2013) estimate that $5.6 trillion was held by households in tax havens globally in 2007, which is at the low-end of the scale of available estimates. The OECD calculates that households owned a total of $5 to $7 trillion offshore in 2007 (Owens, 2007); based on interviews with wealth managers, the Boston Consulting Group (2008) finds $7.3 trillion that same year; Cap Gemini and Merrill Lynch (2002) have a $8.5 trillion estimate for 2002; Palan, Murphy, and Chavagneux (2010) write that “the global rich held in 2007 approximately $12 trillion of their wealth in tax havens;” and Henry (2012) finds $21 to $32 trillion as of 2010. One limitation of Zucman’s (2013) methodology is that it only captures financial wealth, disregarding valuables, works of art, real estate, and other non-financial assets.
In the second step of our estimation procedure, we take into account that not all offshore wealth evades taxes. Consistent with the evidence from the HSBC leak and several other concurring sources (US Senate, 2008, 2014; Roussille, 2015; Johannesen and Zucman, 2014), we assume that 10% of the macro stock of Scandinavians’ offshore wealth was duly declared to tax authorities in 2006, and 90% hidden.
4.2 The Distribution of Offshore Wealth
In a third step, we distribute the macro amount of offshore wealth owned by Scandinavians across wealth groups. To do this allocation, we assume that Scandinavia’s offshore wealth is distributed like in the HSBC and the amnesty samples. That is, we assume that 77% of it belongs to the top 0.1% richest households, 52% belongs to the 0.01%, etc., which are the fractions observed in these two micro datasets (top panel of Figure 4).
It is striking to note that offshore wealth is very similarly distributed in the HSBC and
25Because the wealth disclosed by amnesty participants tends to be smaller than that held by tax evaders at HSBC, in terms of amounts, HSBC accounts for a bit more than 1% of the total assets disclosed during the amnesty (about 1.2%). Note that 1.2% is less than what we estimate was the share of Scandinavians’ offshore wealth held at HSBC (2.0%). This suggests that we may under-estimate the total offshore wealth of Scandinavians. Another interpretation is that HSBC customers were less likely to self-select into the amnesty. Nothing, however, prevented them from using it, since Scandinavian tax authorities only received the HSBC list in 2015, following the “Swiss leaks” scandal—hence before 2015, HSBC evaders had not been prosecuted for hiding assets in that bank and were free to use the amnesty.
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amnesty samples. All available evidence suggests that in 2007, the offshore wealth of Scandi- navians was extremely concentrated. Admittedly, Swiss banks had hundreds of thousands of customers at the time of the Falciani leak, but the wealth held by bottom 99.9% evaders does not account for much compared to that owned by the top 0.1%. While the top 0.01% owns only about 5% of all non-hidden wealth, it owns about half of all hidden wealth. Consistent with our finding that self-selection into amnesties is slightly negatively correlated with wealth, the concentration of offshore wealth appears slightly lower in the amnesty sample. The differences, however, are small and not statistically significant. To allocate Scandinavia’s macro stock of offshore wealth, we thus simply take the arithmetic average of the HSBC and amnesty distri- butions (e.g., we assume that 51.6% of Scandinavia’s offshore wealth belongs to the top 0.01%, which is the arithmetic average of 55.3%—observed in the HSBC sample—and 47.8%—observed in the amnesty sample; see Appendix Table J.1).
4.3 Taxes Evaded on Offshore Assets
Fourth, we apply a rate of return to the wealth hidden. Based on the observed composition of offshore wealth and the returns on global securities markets and deposits in 2006, we apply a 4.5% taxable rate of return to the wealth hidden.26
The last step involves computing how much tax each group of the wealth distribution evades offshore. Using a detailed tax simulator that allows us to estimate the average marginal tax on capital income and wealth by wealth group in Norway, Sweden, and Denmark, we compute the amount of taxes evaded on the hidden wealth itself (when a wealth tax exists, which was the case in Norway and Sweden in 2006) and the dividends, interest, and capital gains it generates. We apply these empirical marginal tax rates to the amounts of income and wealth hidden by each wealth group. This procedure is reliable, because there is very little heterogeneity in the marginal tax rates on financial capital faced by individual taxpayers at the top of the distribution, as marginal tax rates in Sweden and Norway are the same for interest, dividends, and capital gains.27 For instance, we find that the average marginal tax rate on capital income for the top 0.01% richest Scandinavians was 49% in 2006 (taking into account both income
26The average interest rate paid by Swiss banks on their term deposits was 4.3% in 2006; the US Federal fund rate was in range of 4.3% to 5.25%; the total nominal return (dividends reinvested) was 13.4% for the the S&P500 and 20.65% for the MSCI world (see Appendix Table J.4). Contrary to a widespread view, most of the wealth held offshore if invested in global financial markets, so returns on offshore accounts are no lower than returns earned in domestic financial institutions. As shown in Zucman (2013), about 75% of the world’s offshore wealth was invested in global securities (equities, bonds, and mutual funds) before the financial crisis; the rest was held in bank deposits.
27In Denmark, share income is taxed at a lower rate, 42% vs. 48% for interest at the top. 17

taxes and wealth taxes expressed as a fraction of taxable capital income). This is the rate that we apply to the hidden income of the top 0.01% (i.e., to 4.5% of their estimated hidden wealth). We do not attempt to take into account any tax evasion that might have occurred on the principal—some of the wealth held offshore is probably accumulated out of untaxed earnings, but we are not able to quantify that form of evasion with the data at our disposal. We also disregard tax evasion on inter-generational transmissions of hidden assets.
4.4 How Offshore Tax Evasion Varies With Wealth
The bottom panel of Figure 4 reports our estimates of how much tax each group of the wealth distribution evades offshore, as a fraction of their true tax liability. We find large rates of evasion at the top of the wealth distribution: in our benchmark scenario, the top 0.01% evades 25% of its true tax liability through tax havens.
What drives the high evasion rates we estimate at the top? It is not the macro stock of wealth hidden by Scandinavians offshore—a mere 1.4% of total household wealth (90% of 1.6%), significantly less than what is found for Continental European countries, the United States, let alone Latin American or African countries. It is the concentration of offshore wealth revealed by the leaked and amnesty data. As we saw in Section 3, top 0.01% households are much more likely to hide assets, and, conditional on doing so, hide a lot (about 40% of their total wealth in the HSBC sample). This explains why offshore tax evasion is orders of magnitude higher in the top 0.01% (25% of taxes owed) than in the overall population (a mere 0.6%). A second factor drives the sharp gradient displayed in the bottom panel of Figure 4: at the very top, the vast majority of income derives from wealth. So when a top 0.01% taxpayer hides 40% of her wealth, she hides close to 40% of her income (or even more, if the taxable return on hidden assets is higher than on domestic wealth) and evades close to (possibly more than) 40% of her taxes.28 For a less wealthy evader who hides 40% of his assets, the taxes evaded offshore will account for a smaller fraction of his tax bill, because a large fraction of taxes owed arise from
28The 4.5% return we assume in our benchmark scenario is slightly higher than the realized taxable return observed on non-hidden wealth (about 3.5% for the top 1% richest Scandinavians). The observed return on non- hidden wealth is a lower bound for the return on offshore assets, for two reasons. First, the portfolio composition differs: the non-hidden wealth of top 1% Scandinavians includes a large fraction (around 50%) of closely-held equities, which tend to have lower taxable returns than listed securities. Second, there are incentives to realize low returns on non-hidden wealth so as to avoid taxes, for instance by investing in non-dividend paying equities or by retaining earnings within closely-held firms. A case in point is Norway, where following the introduction of a new tax, dividend distributions collapsed in 2006 and retained earnings surged, leading to low realized rates of return (Alstadsæter et al., 2016). There are no such incentives to avoid taxes for offshore investments that evade taxes altogether.
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labor income.29
One might wonder how the presence of a wealth tax in Sweden and Norway affects our
results. In an accounting sense, it does not: when computing the ratio of taxes evaded to taxes owed, wealth taxes enter both the numerator and denominator; absent such taxes, rich Scandinavians would still evade a similarly high fraction of their tax liability (albeit a smaller amount in absolute terms). From an economic perspective, however, wealth taxes might have a causal effect on tax evasion. To analyze this issue, it is useful to consider the overall tax rate on capital income in Scandinavia. With a 4.5% rate of return, a wealth tax of 1.2% (as in Sweden) is equivalent to a tax on capital income at a rate of 27%, a wealth tax of 0.9% (as in Norway) to a tax on capital income of 20%.30 All included, the marginal tax rate on capital income reaches 57% in Sweden and 48% in Norway, slightly higher than Denmark (42% on share income) where no wealth tax applies. These marginal rates are high, but not extraordinarily so. For instance, a wealthy New York City resident faces a 56% marginal tax rate on interest income and 36% on dividends and capital gains in 2016. In effect, Norway and Sweden offset part of their wealth taxes with flat rates on investment incomes, while other rich countries usually tax at least part of capital income progressively.31
The skewed distribution of offshore wealth also implies that top wealth shares increase substantially when accounting for unreported assets. As reported in Appendix Figure B.3, including offshore wealth increases the top 0.1% Norwegian wealth share significantly: from 8.4% to 9.8% on average over the 2000–2009 period. For the top 0.01%—a group that includes about 300 Norwegian households in 2010—reported wealth increases by about 25% (Appendix
29To reconcile the estimates of the rates of evasion shown in the bottom panel of Figure 4 with the patterns of evasion in the micro-data studied in Section 3, consider the following simplified computation. As reported in Figure 2, about 1% of top 0.01% richest Scandinavians hid assets at HSBC Switzerland, and they held there about 40% of their wealth. Assuming that HSBC Switzerland accounts for 2% of all offshore tax evasion (and that HSBC customers do not hide assets in other offshore banks, and vice versa), this implies that 50% of top 0.01% Scandinavians hid assets abroad and that the top 0.01% concealed 20% of its total wealth offshore. The fraction of taxes eschewed is slightly larger than 20% in our benchmark scenario, because the return we assume on hidden wealth is slightly higher than on non-hidden wealth.
30More precisely, in Sweden the marginal wealth tax rate was 1.5%, and in Norway 1.1.% but in both cases it applied to only a fraction of wealth (e.g., 80% for equities in both countries). So the marginal tax rate on listed equity wealth was 1.2% in Sweden and 0.88% in Norway; see Appendix Table J.7b for detailed computations. The Swedish wealth tax was abolished in 2007.
31The evidence reported in Table 2 shows that Denmark—where wealth taxation was abolished in 1997 and the overall marginal tax rate on capital is slightly lower—seems to hide a smaller fraction of its wealth than Norway and Sweden. However, given the uncertainties involved, we caution against drawing strong conclusions from this difference. In our view, tax evasion is better analyzed at the level of Scandinavia as a whole; at the micro level, small sample sizes do not allow us to detect any statistically significant differences across countries. We leave to future research the task of investigating the causal effect of wealth taxation on capital flight using micro-data and within-country variation. For cross-country comparisons of marginal and average tax rates in Scandinavia, see Appendix Figures J.1, J.2, and J.3.
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Figure B.4). That is, these households own about 20% of their wealth in tax havens. These results highlight the need to move beyond tax records to capture income and wealth at the very top, even in countries where tax compliance is generally high.32
4.5 Robustness Tests and Sensitivity Analysis
Because our estimates of offshore tax evasion are obtained by transparently combining macro stocks of hidden assets with observed distributions and assumed taxable rates of returns, it is straightforward to asses how changing one, several, or all of our assumptions at the same time affects the results. We consider a large number of robustness tests in the Online Appendix, based on varying the macro stock of Scandinavians’ offshore wealth (variants a, b, c, d, e in Appendix Tables J.1, J.2, J.3), the fraction of offshore wealth that is hidden from the tax authorities (Appendix Table J.1), the distribution of offshore assets (cols. 9, 10, and 11 in Appendix Tables J.1, J.2, J.3), and/or the rate of return on hidden wealth (Appendix J.2 and J.4). In all cases, offshore tax evasion turns out to be large at the top—much larger than the evasion detected in random audits. For all plausible scenarios, it is in a range of 20% to 30%.
In the bottom panel of Figure 4, we consider two extreme scenarios. In the low-end scenario, we assume that Scandinavians own no offshore assets outside of Switzerland. The Swiss central bank publishes direct, official data on the stock of wealth owned by foreigners in its banks, with a country-by-country breakdown.33 We only include these directly observable assets, and exclude any wealth held by Scandinavians in Luxembourg, Singapore, or any other tax haven, which is less directly observable. This reduces the offshore wealth of Scandinavians by about half. The top 0.01%, however, still evades 12% of its tax bill, which is—as we shall see below— three times higher than the amount of evasion detected at the top in random audits. Note that we know as a fact that Scandinavians hid a sizable amount of wealth in Luxembourg, Jersey, and similar havens in 2006—if only because around half of the wealth disclosed in the Norwegian tax amnesty was held outside of Switzerland. So our low-end scenario is maybe better interpreted as reflecting a world where about half of Scandinavians’ global offshore wealth is duly declared to tax authorities. Conversely, we report a high-end scenario, where we assume that Scandinavians own the same fraction of their wealth offshore as the world as a whole. This scenario is informative of how offshore evasion might look like in Continental European
32in Alstadsæter, Johannesen and Zucman (2018) we investigate the implications of hidden wealth for in- equality in ten countries, which account for close to half of world GDP, assuming that offshore wealth is as concentrated in the other countries as in Scandinavia. The results show that inequality increases even more than in Norway (as other countries typically own a higher fraction of their wealth offshore than Norway).
33See Zucman (2013, Section III; 2015, chapter 1) for a detailed analysis of this unique, high-quality dataset. 20

countries, where macro stocks of offshore assets are larger than in Scandinavia. Offshore tax evasion for the top 0.01% then rises to 40% of taxes owed.
5 Beyond Offshore Tax Evasion: Distributional Tax Gaps
Offshore evasion is just one form of evasion, and it is not too surprising that it is concentrated among the rich. In this Section, we contrast and combine offshore tax evasion with the evasion detected in random audits. The interesting and non-obvious result of our research is that tax evasion at the top (25% of taxes owed) is large relative to the forms of tax evasion detected in random audits, the current gold standard in the literature (less than 5% throughout the distribution). This suggests that to have a good measure of tax evasion, combining different data sources is critical.
5.1 Random Audit Data
The random audit data we use come from the stratified random audits conducted by the Danish Tax Authority (SKAT). The first wave of this program, for the tax year 2006, was studied by Kleven et al. (2011). Here we analyze the three subsequent waves, which were conducted for the tax years 2008, 2010, and 2012. In each wave, SKAT randomly selects a sample of self-employed individuals and a sample of individuals who are not self-employed—mostly wage-earners and retirees. The sampling rate is higher for the self-employed, who are relatively more numerous at the top of the distribution and more likely to evade taxes; in both groups taxpayers with complex tax returns are over-sampled. Our final sample pools tax years 2008, 2010, and 2012 and includes 18,985 randomly audited taxpayers (of which 6,223 are self-employed and the remaining 12,762 are not).34 Detailed summary statistics are presented in Appendix H.
The Danish random audits are widely considered to be of high quality, because the tax authority can draw on a particularly comprehensive set of information: returns provided by employers, banks, credit card companies, and other financial institutions; supporting documen- tation requested from the taxpayers themselves; and detailed wealth data. This enables SKAT to detect a wide range of errors, from mistakes in the claiming of deductions (e.g., for alimony or commuting expenses) to mis-reporting of income that is not declared by a third party (e.g., tax- able fringe benefits) and unreported labor market activity (which SKAT can infer by comparing reported income to the change in wealth). Every line item on the tax return is examined.
34Overall, 0.15% of the entire adult Danish population is randomly audited each year in the context of this program. The empirical sampling rate is 3.5 times higher for taxpayers in the top 1% of the distribution (0.53%); our sample includes 663 taxpayers in the top 1% of the wealth distribution. See Appendix Table H.2.
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By construction, the rates of evasion measured in the random audits exclude offshore evasion, for the following reason. Examiners are not well equipped to detect evasion through offshore intermediaries in the context of random audits. In the rare cases when an examiner might suspect such type of evasion, the case is transferred to a specialized unit within SKAT with the skills to conduct a specific investigation. Whatever is found at the end of this long process is not included in the result of the random audit study, as this would delay the publication of the results for too long. Moreover, despite the richness of the information available to SKAT, the random audits are likely to miss some forms of evasion throughout the distribution, especially when no information trail exists.
5.2 Patterns of Tax Evasion in Random Audits
Random audits find modest rates of tax evasion, albeit with a lot of heterogeneity across income sources. In total, 11.5% of all taxpayers are found making mistakes. As shown by the top panel of Figure 5, this probability rises sharply with wealth, to more than 35% for the 0.5% richest households. This trend reflects the facts that the probability to earn self-employment income rises a lot with wealth (to close to 50% in the top 0.5%), and that the error rate is much higher among the self-employed (around 60%, with no trend across the wealth distribution) than among wage-earners and retirees (around 10%, with no trend either); see Appendix Figure H.4. Conditional on evading, around 10–20% of income is misreported, with a declining trend across wealth bins. These fractions are modest, and hence the overall tax gap is small: 2.2% of personal taxes owed are found to be dodged in total. This number rises a little bit from the 90th to the 99th percentile, but in no wealth group does evaded tax exceeds 5% of taxes owed.35
In the United States, the IRS estimates that a larger fraction of taxes is evaded, about 11% (Johns and Slemrod, 2001).36 There are two reasons for this difference. First, the IRS blows up the tax evasion its random audits uncover by a factor of about three, contrary to SKAT which does not correct the results found in its random audit program. The multiplication done by the IRS rests on weak foundations. Second, the self-employment sector—where the bulk of detected tax evasion takes place—accounts for roughly twice as much of total economic activity in the
35These figures include all mistakes found during the audit, whether deemed voluntary or not. In Appendix H, we report similar statistics where we exclude the errors that examiners deem non-deliberate. The fraction of households found evading taxes is reduced by a factor of 10 (1.28% of audited taxpayers are found deliberately evading taxes, a fraction rising to 5.4% in the top 1%; see Appendix Figure H.5), but the average amount of income misreported increases by a factor of 5 (Appendix Figure H.6), so that taxes deliberately evaded account for about half of all unpaid taxes. The distributional patterns are similar (Appendix Figure H.7).
36As shown by Appendix Figure H.3, although the level of evasion is different, its distribution across wealth (or income in the case of the United States) groups is similar, with an increase in the top 10%.
22

United States than in Denmark, 11% of factor-cost GDP vs. 6%. As shown by Appendix Figure H.10, Denmark is not unusual in having a low share of self-employment: the other Scandinavian countries have similarly low shares, as do most of the world’s high-income countries, e.g., Japan (4%) and France (6%). In countries such as Greece and Italy, the self-employed generate a higher fraction of output (about 20%-25%); tax evasion is likely to be much higher there than in Denmark. Looking forward, Scandinavia is likely to be more representative of the overall rich world than a country like Greece, since self-employment typically falls as countries develop.
The key lesson from random audit studies is that in developed economies, total tax evasion is limited, because the majority of the population is not able to evade. Most individuals earn only three forms of income in their lifetime—wages, pensions, and investment income in domestic financial institutions—which, due to third-party reporting, are difficult to hide (Kleven et al., 2011). Whenever tax evasion is possible, however, it tends to be high.
5.3 Combining Offshore Evasion with Random Audits
The bottom panel of Figure 5 shows the tax gap by wealth group, for domestic evasion (as estimated from the random audit data) and offshore evasion separately. For most of the population—up to the 99.5th percentile—only detected domestic evasion matters and estimated evaded taxes are small. It is only for the top 0.05%, where wealth concealment seems widespread, that evasion becomes large.
Adding both, we find that 2.8% of total taxes go unpaid and that tax evasion appears to rise sharply with wealth (Figure 6). We stress, however, that because random audits are unlikely to uncover all forms of tax evasion, there is uncertainty in the slope of the evasion gradient. Our main finding is that at the top, offshore evasion is large compared to the evasion detected in audits. Combining random audits, leaks, amnesties, and macroeconomic statistics makes it possible to obtain a more comprehensive picture of tax evasion than was available until now. But more research is needed to improve the measurement of tax evasion in all segments of the distribution.37
One implication of our results is that the personal tax rate effectively paid by the wealthiest Scandinavians is substantially lower than implied by the tax law. Appendix Figure J.4 computes effective tax rates across the wealth distribution, taking into account payroll taxes, individual
37Moreover, Figure 5 only includes evasion on payroll, personal income, and net wealth taxes. It excludes evasion on the VAT, the corporate tax, real estate taxes, and excise duties. These forms of tax evasion are significant (see Skatteverket, 2014, for Sweden), but are harder to allocate across the wealth distribution—a task we leave to future research.
23

income taxes, and wealth taxes (when they exist), at all levels of government. Absent tax evasion, the top 0.1% richest Scandinavians would pay about 45% of their income in taxes. In practice, the rate effectively paid reaches 35% for the top 0.01%. This rate remains a bit higher than the rate paid by the bottom 95%. But tax evasion erodes the progressivity of the tax system, and, accordingly to our estimates, makes it regressive at the top.
6 Explaining Tax Evasion Among the Rich
How can we explain the high rates of evasion we find at the top? The canonical Allingham and Sandmo (1972) model predicts that the very rich should evade little, because they are likely to be (non-randomly) audited by the tax authority. Yet our results show the opposite: in all our leaked and amnesty micro samples, tax evasion rises with wealth at the top; top 0.01% households are much more likely to hide assets abroad than households in the bottom of the top 1%. A simple model with a fixed cost of hiding wealth cannot realistically generate this pattern, because it only costs a few hundred dollars to create a shell company (see Findley, Nielson, and Sharman, 2012), and even less to open an offshore bank account.38
To explain our findings, it is important to consider the supply of tax evasion services instead of its demand only as in the literature so far. There is an industry that sells wealth concealment services, and this industry primarily targets very wealthy customers. Think of a representative Swiss bank.39 It derives revenue by levying fees on the wealth it helps concealing and faces penalties in case it is caught helping tax evaders. The more clients the bank serves the more revenue it makes, but the higher the probability it is caught breaking the law (e.g., because the probability that a leak occurs rises). Internalizing this cost, a rational bank will target very wealthy individuals, who are few in number but own a large fraction of world wealth (because of the multiplicative and cumulative processes that govern wealth accumulation). In practice, private wealth management banks typically select customers by requiring them to have
38Purely informational explanations cannot fully account for our results either. At the time of the HSBC leak, there was almost no information exchange between offshore banks and foreign tax authorities, making tax evasion easy. This lack of third-party reporting is probably an important explanation for the high rates of tax evasion we obtain at the top of the distribution. However, it was as easy to hide assets for households with $2 million in net wealth as for households with $50 million, yet households with $50 million were much more likely to do so. Although both types of households could have felt very confident in the evasion strategy used (i.e., could have felt they had a low probability of being caught), only the very wealthy evaded. The lack of third-party reporting thus does not seem enough to explain the gradient we obtain.
39Swiss banks supplied the vast majority of cross-border wealth management services until the 1980s, before financial liberalization in the U.K. and the emergence of new offshore centers. They historically had a cartel agreement, the Convention IV of the Swiss Bankers Association, which strictly regulated fees; see Zucman (2015, chapter 1). In the Appendix, we also consider a model with competition in the market for wealth concealment; the key intuitions of the model with a single provider of tax evasion services carry over.
24

a minimum amount of assets (e.g., $10 million, or $20 million), in effect setting an infinite price for less wealthy individuals, while advertising their services to potential high-net-worth clients through by-invitation only events (see, e.g., Harrington, 2016). In the Appendix, we provide a model along these lines that can rationalize why tax evasion is sizable at the top in equilibrium, as observed in our data. The model yields a number of additional insights.
The most important insight is that government policies have a critical role to play to reduce tax evasion. Increasing penalties for tax evaders has not proved to be a very practical way to curb tax cheating so far. There are limits to the penalties that can be applied to persons conducting such crimes; and if the penalties set by law are too high, judges might require a stronger burden of proof from prosecutors, potentially leading to fewer convictions. Large sanctions against the suppliers of tax evasion services (instead of tax evaders themselves) could help overcome this problem. If policy-makers were willing to systematically put out of business the financial institutions found facilitating evasion, then the supply of evasion services would shrink, and tax evasion at the top could be reduced dramatically. In turn, a lower equilibrium level of tax evasion would make it possible, everything else equal, to increase effective tax rates on the rich and hence ultimately may contribute to reducing inequality.40 While there is a view that taxing the rich is not possible in a globalized world (e.g., Landier and Plantin, 2017), with proper enforcement, progressive taxation might be more sustainable than previously thought.
This insight also shows that tax enforcement and financial regulation policies are intertwined. It is easier to close small financial institutions than systematically important ones. Since 2009, 80 Swiss banks have admitted helping U.S. persons to evade taxes; 16 others have been under criminal investigation by the Department of Justice. But the U.S. government has been able to shut down only three relatively small institutions (Wegelin, Neue Zu ̈rcher Bank, and Bank Frey). By contrast, in 2014, Credit Suisse was able too keep its U.S. banking licence despite pleading guilty of a criminal conspiracy to defraud the IRS; in 2012, U.S. authorities similarly decided against indicting HSBC despite evidence that the bank had enabled Mexican drug cartels to move money through its American subsidiaries.41 If big financial institutions become “too big to indict” (because regulators fear that this would destabilize financial markets), tax
40Of course, should government be successful at reducing tax evasion, other behavioral margins might be affected. For instance, because they have access to many opportunities for legal avoidance, the rich may simply start avoiding more whenever they are compelled to evade less. In Alstadsæter, Johannesen and Zucman (2018b), we study how the participants in the Norwegian tax amnesty changed their avoidance decisions after disclosing their previously hidden assets. We find no substitution between illegal tax evasion and legal tax avoidance: the taxes paid by amnesty participants rise 30% at the time of disclosure; the rise is sustained over time; and the use of the key avoidance techniques documented in the Norwegian context does not seem to increase.
41Instead, HSBC was fined $1.92 billion, in a year when its pretax profits reached $22.6 billion. 25

evasion might flourish. But if financial regulation ensures no bank is so big that it cannot be shut down, then tax evasion could be curbed.42
Our model can also explain some of the key observed trends in top-end evasion. In our model, the size and distribution of tax evasion are endogenous to the wealth distribution. The higher inequality, the lower the number of people who evade. The intuition for that result is simple: when inequality is high, relatively few individuals own the bulk of wealth; they generate a lot of revenue for the bank and are unlikely to be detected. Moving down the distribution would mean reaching a big mass of the population that would generate only relatively little additional revenue but would increase the risk of detection a lot; it is not worth it.
This inequality effect could explain why on top of ultra-rich households, we also observe a number of moderately wealthy, old evaders in the HSBC leak and the amnesty data. In the 1950s and 1960s, following the destructions of World War II, nationalizations in Europe, and a number of other anti-capital policies, wealth inequality was at a historically low level. Swiss banks may have chosen to serve a broader segment of the population back then. Conversely, the number of clients of Swiss banks seems to have declined over the last ten years; as shown by Appendix Figure E.6, it has been divided by 3 at HSBC Switzerland over the 2006–2014 period.43 Part of the fall probably owes to improvement in the information available to the tax authorities, to technological change making leaks easier, and to increases in the rewards offered to whistleblowers (see Johannesen and Stolper, 2017). But one other contributing factor might be the rise in global wealth concentration (Alvaredo et al., 2018b). Indeed, while the number of HSBC clients fell, the average account value increased 80%, from $3.7 million in 2006 to $6.6 million in 2014; the offshore wealth managed by Swiss banks has also increased significantly since 2000 (Zucman, 2015). As the world becomes more unequal, offshore banks might choose to serve fewer but wealthier clients—making tax evasion even more concentrated at the top. Looking forward, we hope to study this issue using data from new leaks and tax amnesties throughout the world.
42In recent years, governments have compelled tax haven financial institutions to provide bank information to foreign countries’ tax authorities (Johannesen and Zucman, 2014; Zucman, 2015; Johannesen et al., 2018). Information reporting coupled with large sanctions for the providers of tax evasion services could prove effective in reducing top-end evasion in the years ahead. But our analysis suggests that information reporting alone is unlikely to be enough if offshore financial institutions have insufficient incentives to report truthfully.
43In the specific case of HSBC, part of this fall probably owes to the Falciani leak.

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29

Table 1: HSBC evaders, Panama papers individuals, & amnesty participants, by wealth group
Wealth group
P0-90 0.00 35.08
A A A A A A A A
0.00 (0.00) 0.01 (0.00) 0.01 (0.00) 0.04 (0.01) 0.04 (0.01) 0.16 (0.06) 0.17 (0.07) 1.19 (0.39)
0.03 (0.00)
36.52 (1.86) 25.32 (2.06) 27.42 (1.26) 31.02 (1.95) 30.89 (1.52) 31.26 (2.79) 32.84 (2.92) 26.30 (4.51)
C
0.03 (0.00) 0.26 (0.01) 0.80 (0.02) 2.89 (0.09) 4.49 (0.12) 8.51 (0.45) 11.76 (0.59) 14.83 (1.29)
P90-95
(0.00) 0.01 (0.00) 0.03 (0.00) 0.07 (0.01) 0.19 (0.02)
(9.21) 38.27 (4.45) 39.34 (3.51) 42.32 (5.91) 46.51 (3.77) 36.19 (5.85) 36.63 (9.24) 38.60 (9.34) 10,617,167
A 0.25 (0.01)
A AB B B ABC BC AB
P95-99
A 0.78 (0.02)
P99-99.5
B 2.83 (0.09)
P99.5-99.9
B 4.31 (0.12)
P99.9-99.95
0.38 A (0.08)
B 8.16 (0.45) B 11.49 (0.58) 13.77 (1.25)
P99.95-99.99
0.66 A (0.12)
A A
P99.99-100
0.94 A (0.30) 10,617,167
Number of households Number of tax evaders
520
300
7,547,170 165
7,547,170 8,233
7,547,170 1,375
7,547,170 8,571
[1] [2] Extensive margin
[3] [4] Intensive margin
[5] [6] Extensive margin
[7] [8] Extensive margin
[9] [10] Intensive margin
[11] [12] Extensive margin
% of all Test households
% of evaders’ wealth
Test
% of all households
Test
% of all households
Test
% of evaders’ wealth
Test
% of all Test households
HSBC
Panama Papers
Amnesty
HSBC + Amnesty
Notes: Cols. 1, 5, 7, and 11 show the fraction of all households who evaded taxes at HSBC Switzerland, who are in the Panama papers, or who used a tax amnesty to voluntarily disclose hidden wealth, by wealth group. For HSBC, our sample pools Norwegian, Swedish, and Danish households; therefore wealth groups are defined relative to Scandinavia as a whole (Norway, Sweden, plus Denmark). For the Panama papers, amnesty participants, and HSBC plus amnesty columns, our sample pools Norwegian and Swedish households; therefore wealth groups are defined relative to Norway plus Sweden. Col. 3 shows the wealth hidden at HSBC Switzerland as a fraction of each evader’s wealth (including that hidden at HSBC); the sample includes all HSBC evaders for whom HSBC account values are available. Col. 9 shows the same statistic for the sample of Norwegian amnesty participants. All values are expressed in percentage points. Bootstrapped standard errors are reported in parenthesis. Cols. 2, 4, 6, 6, 8, 10, and 12 show the results of pairwise tests for the equality of the group means displayed in cols. 1, 3, 5, 7, 9, and 11. Wealth groups sharing a common letter are not significantly different at the 5% level.

Table 2: Offshore wealth at HSBC, in all Swiss banks, and in all tax havens (2007)
A. Wealth held offshore ($ billion)
At HSBC Switzerland Private Bank
In all Swiss banks
In all the world’s tax havens (benchmark estimate)
105.0 2,670 5,620 5,620
21.5 12.8 51.0 28.4 54.2 26.2
0.32 0.20 4.2 4.4 14.1 8.4 17.3 10.7
– Bottom-up estimate
B. Wealth held offshore (% of household wealth)
In all Swiss banks
In all the world’s tax havens (benchmark estimate)
1.5% 3.3% 3.3%
0.7% 0.9% 1.6% 1.9% 1.7% 1.8%
0.6% 0.4% 1.9% 0.8% 2.4% 1.0%
– Bottom-up estimate
Notes: This Table reports estimates of (i) the wealth managed by HSBC Private Bank Switzerland, (ii) the offshore wealth managed by all Swiss banks, and (iii) the offshore wealth held in all the world’s tax havens. Offshore wealth is defined as bank deposits and portfolio securities managed by domestic banks on behalf of non-resident households. All the data are for the middle of 2007, the time of the Falciani leak. For HSBC, the column “world” is the official total published by HSBC (2015); totals for Scandinavia, Sweden, Norway, and Denmark only include the accounts that could be matched to an individual taxable in Scandinavia; they exclude all unmatched accounts, non-resident account-holders, and remove the double-counting of joint accounts; see Appendix E. The offshore wealth in all Swiss banks is constructed from official statistics published by the Swiss central bank; see Zucman (2013, 2015), and Appendix I. The wealth held in all the world’s tax havens is estimated by averaging the end-2006 and end-2007 estimate of Zucman (2013); see text for a description of the benchmark and bottom-up allocation of this total to Scandinavia. Panel B divides the amounts reported in Panel A by household wealth totals constructed by averaging end-2006 and end-2007 values; see Appendix A.
World
Scandinavia Sweden 1.01 0.49
Norway Denmark

Share of HSBC wealth
0 .02 .04 .06 .08 .1
Denmar Norway
Figure 1: Country distribution of wealth at HSBC vs. in all Swiss banks
Sweden
Russia
HSBC wealth vs. wealth in all Swiss banks
Belgiu Canada
India
Egypt Mexico
Greece Argent
Spain
UAE
USA Israel
Brazil
German
Saudi
Turkey
0 .02 .04 .06 .08 .1 Share of wealth in all Swiss banks
Data source: ICIJ and SNB.
Notes: This figure shows the country distribution of the wealth managed by HSBC Private Bank Switzerland in 2007 and the country distribution of the
Note: In the full sample excluding tax havens (134 countries), a regression of the share of HSBC
wealth on the share of Swiss deposits has slope b= 0.90 (se = 0.04) and R-square of 0.75.
foreign wealth managed by all Swiss bank in 2003-2004 (the last years before the introduction of the European Saving Tax Directive which greatly increased
the use of shell corporations by European owners of Swiss accounts; see Appendix E.2). The black line is the 45 degree line. In the full sample excluding tax havens (134 countries), a regression of the share of HSBC wealth on the share of Swiss deposits has slope b = 0.90 (se = 0.04) and R-square of 0.75. Source: Appendix Table E.8.
UK Venezu
Italy

Figure 2: Tax evasion at HSBC: intensive vs. extensive margin
1.0% 0.8% 0.6% 0.4% 0.2% 0.0%
P90-P95 [0.6 – 0.9]
P95-P99 [0.9 – 2.0]
P99-P99.5 [2.0 – 3.0]
P99.5-P99.9 [3.0 – 9.1]
P99.9-P99.95 P99.95-P99.99 [9.1 – 14.6] [14.6 – 44.5]
Top 0.01% [> 44.5]
Probability to own an unreported HSBC account, by wealth group
(HSBC leak)
Net wealth group [millions of US$]
50% 40% 30% 20% 10%
0%
Average wealth hidden at HSBC, by wealth group
(% of total wealth (including held at HSBC))
P90-P95 [0.6 – 0.9]
P95-P99 [0.9 – 2.0]
P99-P99.5 [2.0 – 3.0]
P99.5-P99.9 [3.0 – 9.1]
P99.9-P99.95 P99.95-P99.99 [9.1 – 14.6] [14.6 – 44.5]
Top 0.01% [> 44.5]
Net wealth group [millions of US$]
Notes: The top panel shows the fraction of households in Scandinavia (Norway, Sweden and Denmark) who had an unreported bank account at HSBC Switzerland in 2006, by bins of 2006 Scandinavian wealth. The sample includes 520 Scandinavian households who could be matched to a tax return; see text. The bottom panel shows the ratio of the wealth held at HSBC over total observable wealth, in the sub-sample of 300 matched HSBC account-holders for whom account values are available. Source: Appendix Tables E.2 and E.6.

Figure 3: Probability to be in the Panama Papers or use an amnesty
1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0%
P90-P95 [0.6 – 0.8]
P95-P99 [0.8 – 1.8]
P99-P99.5 [1.8 – 2.7]
P99.5-P99.9 [2.7 – 8.1]
P99.9-P99.95 P99.95-P99.99 [8.1 – 13.3] [13.3 – 41.4]
Top 0.01% [> 41.4]
Probability to appear in the “Panama Papers”, by wealth group
(Shareholders of shell companies created by Mossack Fonseca)
Net wealth group [millions of US$]
14% 12% 10%
8% 6% 4% 2% 0%
P90-P95 [0.6 – 0.8]
P95-P99 [0.8 – 1.8]
P99-P99.5 [1.8 – 2.7]
P99.5-P99.9 [2.7 – 8.1]
P99.9-P99.95 P99.95-P99.99 [8.1 – 13.3] [13.3 – 41.4]
Top 0.01% [> 41.4]
Probability to voluntarily disclose hidden wealth, by wealth group
(Swedish and Norwegian tax amnesties)
Net wealth group [millions of US$]
Notes: The top panel shows the fraction of households in Norway and Sweden who are identified in the Panama Papers as beneficial owners of shell companies created by the Panamanian law firm Mossack Fonseca, by bins of 2006 wealth. The bottom panel shows the fraction of households in Norway and Sweden who declared hidden wealth in a tax amnesty over the period 2007 to 2015, by bins of 2006 wealth. In both cases, the wealth bins are defined relative to the pooled Norwegian plus Swedish population. Source: Appendix Tables G.2. and F.1.

Figure 4: The distribution of offshore wealth and offshore tax evasion
60% 50% 40% 30% 20% 10%
0%
Recorded wealth
P50-P90 P90-P99
Position in the wealth distribution
Distribution of wealth: recorded vs. hidden
Hidden wealth disclosed in amnesty
P0-50
P99-P99.9
Hidden wealth held at HSBC
P99.9-99.99 P.99.99-P100
50%
40%
30%
20%
10%
0%
Offshore tax evasion, by wealth group
High scenario
Lower-bound scenario
Position in the wealth distribution
Notes: The top panel shows the distribution of wealth in Scandinavia (Norway, Sweden, Denmark) excluding offshore wealth, and the distribution of wealth held at HSBC and disclosed by amnesty participants. The bottom panel distributes the macro stock of offshore across wealth groups and computes the implied amount of taxes evaded. See text for a description of the benchmark, higher, and lower-bound scenarios. 95% confidence intervals based on bootstrapped standard errors. Source: Appendix Tables A.2, J.1, J.3, J.3b and J.3c.
P90-95
P95-99
P99-99.5
P99.5-99.9
P99.9-P99.95
P99.95-P99.99
P99.99-P100
% of total taxes owed that are not paid
% of total (recorded or hidden) wealth

Figure 5: Tax evasion detected in random audits
40%
30%
20%
10%
0%
Tax evasion found in stratified random audits
Position in the wealth distribution
Fraction of income undeclared,
Fraction of households evading taxes
conditional on evading
Taxes evaded, % of taxes owed
30% 25% 20% 15% 10%
5% 0%
Tax evasion other than offshore (random audits)
Position in the wealth distribution
Offshore evasion (leaks and tax amnesties)
Notes: The top panel shows the probability to be found evading taxes in random audits, by wealth groups, and the ratio of income undeclared to true income, conditional on evading taxes. Tax evasion includes all mistakes found by the examiner, whether deemed deliberate or not. The bottom panel shows the fraction of taxes owed which are evaded as detected in random audits. The last dot shows the average for P99.5–100 (as due to insufficient sample sizes, we cannot estimate how detected tax evasion varies within the top 0.5%). We also report our benchmark estimate of taxes evaded offshore from Fig. 4. Source: Appendix H.3., H.4, and J.6.
P99-99.5 P99.5-99.9 P99.9-P99.95 P99.95-P99.99 P99.99-P100
P99-99.5 P99.5-100
P0-10 P10-20 P20-30 P30-40 P40-50 P50-60 P60-70 P70-80 P80-90 P90-95 P95-99
P0-10 P10-20 P20-30 P30-40 P40-50 P50-60 P60-70 P70-80 P80-90 P90-95 P95-99
% of taxes owed that are not paid

P99-99.5 P99.5-99.9 P99.9-P99.95 P99.95-P99.99 P99.99-P100
P0-10 P10-20 P20-30 P30-40 P40-50 P50-60 P60-70 P70-80 P80-90 P90-95 P95-99
% of taxes owed
30%
20%
10%
0%
Taxes evaded, % of taxes owed
Figure 6: Taxes evaded as a % of taxes owed, by wealth group
(stratified random audits + leaks)
Average: 2.8%
Position in the wealth distribution
Notes: This figure combines random audits with micro-samples of households hiding assets abroad and macro estimates of the stock of wealth held in tax havens to estimate the size of tax evasion across the wealth distribution in 2006. Each dot is equal to the average ratio of taxes evaded to total taxes owed in the corresponding wealth bin. P0-10 denotes the bottom decile of the Scandinavian wealth distribution, and P99.99-P100 the top 0.01% (households with more than $45 million in net wealth in 2006). 95% confidence intervals based on bootstrapped standard errors. Source: Appendix Table J.5.

gabriel-zucman.eu/files/AJZ2017.pdf

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