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Gabriel Zucman

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Gabriel Zucman (born 30 October 1986) is a French economist known for his research on tax havens and corporate tax havens from his 2015 book The Hidden Wealth of Nations: The Scourge of Tax Havens.[1][2][3] Zucman is also known for his work on the quantification of the financial scale of base erosion and profit shifting ("BEPS") tax avoidance techniques employed by multinationals in corporate tax havens,[4][5] through which he identified Ireland as the world's largest corporate tax haven in 2018.[6] Zucman showed that the leading corporate tax havens are all OECD–compliant, and that tax disputes between high–tax locations and havens are very rare. Zucman's papers are some of the most cited papers on research into tax havens and corporate tax havens.[7]

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  • The 2017 Stone Lecture on Wealth Inequality: Professor Gabriel Zucman
  • The Hidden Wealth of Nations
  • Inequality and Taxation in a Globalised World
  • Rising Inequality and the Changing Structure of Political Conflict
  • The Numbers Game: How's The Middle Class Doing?


- Okay everybody, welcome. I'm Janet Gornick, think you know that by now. It's really a pleasure to be here. I'm gonna just speak for just really a very few minutes to introduce you to the Stone Lecture series. And also to the speaker for today. So for those of you who were here yesterday at the welcome session I explained that the LIS Center was renamed and we expanded in September of this past year. Following a gift from two Boston based philanthropists Jim and Cathy Stone. Who were enormously generous and helped us to form the Stone Center. So the Stones are with us today. Jim and Cathy in the front row. Thank you and we're happy that they're with us today. (audience applauds) They've visited us a few times before. So before there was the Stone Center there were in fact, the Stones. And I met Jim in the spring of 2014 and he had a very long standing interest in inequality. And we had a long discussion about LIS and the LIS data. And income inequality and wealth inequality and they made a small gift to us to support the data construction in Luxembourg which is always a very much appreciated as those of you who were in the data business know it's not that easy to find funding for data infrastructure. And then after that, before we got to the larger business of the Stone Center Jim and with Cathy, they approached us and asked if we would build a lecture series focused specifically on wealth inequality and their particular interest or Jim's interest certainly is especially about the top of the wealth distribution. He's very concerned about the sequestering of wealth. The lack of intergenerational mobility that's due to sort of the hoarding of wealth. He's interested in taxation and many other issues. So we founded this lecture series with support from them and this is the inaugural Stone lecture and it will take place once a year. Here at now what later, now we have the Stone Center but it will take place here at the Graduate Center. So we had a rather informal selection committee which unfolded this way. It consisted of me and Jim. And I said how about Gabriel Zucman and he said great. And that's kinda what happened. And he said, "Do you think we'll get him?" And I said, "We'll see." So we sent him an email and voila. So, we would be interested in getting suggestions for next year but at this point, it was an informal process. But we were really delighted. Right around the time that we were thinking about the inaugural lecture, Gabriel's book The Hidden Wealth of Nations: The Scourge of Tax Havens had come out and was of course capturing a tremendous amount of attention including our own. So we're so pleased that he was able to come. And I'm also very thankful to ECINEQ for allowing us to place the Stone lecture in the middle of this already very crowded program. So they had put the keynotes together and they allowed us to, quite enthusiastically I might add to schedule this inaugural Stone lecture in the middle of the ECINEQ lecture so you all could hear that. So without further ado, there's a lot of... Gabriel has a very informative website and of course everybody can find biographies online. But let me just mention that he of course is an economist who is educated in France. An undergraduate, and then Master's and Ph.D. from the Paris School of Economics and received his PHD in July of 2013. And after doing a few other things in between he's now assistant professor of economics at UC Berkeley. I know a lot of you, as I said, will know his work. He's done a lot of very pioneering work. Especially with the, on his own and with many colleagues and with Thomas Piketty and Emmanuel Saez. And as I said again, I think the book that most of us know him for the work is the book The Hidden Wealth of Nations which has been translated into many languages. And received just extraordinarily good reviews in the popular press as well as in the academic press. And it has been translated and widely read and widely discussed. So on that note, I don't want to take any more time. Gabriel, welcome. What we're gonna do is he's gonna speak for about 40 minutes as this session is just one hour. And then we'll take questions from the audience and has asked that our volunteers of course can pass the microphones as they did yesterday. And Gabriel's preference is to collect maybe three questions before he answers. So welcome, welcome to New York. (audience applauds) - All right. Thank you very much Janet. Thanks to the organizers. Thanks to the Stone Center. Thanks for all of you for being here today. It's really a pleasure to present this research on tax evasion and inequality. This is research that we've been conducting recently with my co-authors Niels Johannesen and Annette Alstadsæter. Annette is a professor at the University of Oslo. Niels is a professor at the University of Copenhagen. And in that research we ask a very simple question. Which is, how big is tax evasion in rich developed countries and how is it distributed? And broadly speaking, I think it's an important question for a number of reasons. So of course, it matters for tax authorities. They have limited resources. They would like to know who's more likely to evade taxes. If people are more likely to, for instance evade taxes on tax credits. If fraud and self employment income is more likely or if sophisticated forms of tax evasion at the very top of the wealth distribution matter quantitatively. They would like to know so as to better target their enforcement effort. It's a question that matters for tax policy. Broadly speaking, tax evasion effects the cost of raising of taxes. It redistributes the tax burden so understanding how big it is that matters to study you know, this bread and butter political and mixed issues of who pays what in taxes in particular. And most importantly, it's a question that matters for the study of inequality. So, over the last 15 years scholars have increasingly been relying on tax data to study inequality and in particular, top income and wealth shares. Simon Kuznets was the first one to do that in the 1950s. He was the first economist to look at tabulated income tax returns in the US to combine those with national accounts data to estimate top income shares in the US. And what's striking is that basically from Kuznets in the 1950s to Thomas Piketty, Emmanuel Saez and Tony Atkinson in the late 1990s, early 2000 almost nobody picked up on Kuznet's agenda of using tax data to study trends in top income and wealth shares. Tony was you know, the main and very important exception but apart from him almost nobody did that for you know, all these decades in between Kuznets and the late 1990s. And the reason, one of the key reasons is that people felt that of course, tax data is great. We like tax data because they are better than survey data when it comes to capturing the top of the distribution. You have bigger sample sizes. But of course, there's a big issue which is tax evasion. The top marginal income tax rates that rich people face the tax evasion technologies they have access to. The tax enforcement methods that tax authorities implement. All of these have changed enormously over time. The top marginal income tax rate in the US from zero percent before 1913 to up to 90% in the post world war two decades for instance. The vary a lot across countries. And so it's not clear that we can learn a lot about the trends in income concentration and the cross country differences in income and wealth concentration just by looking at tax data. So that's a very important issue. And the problem is it's hard to study this well for the very simple reason that you don't have any good data set that's going to tell you here's the total amount of tax evasion, and here is who's doing tax evasion. The key data set that's used to study tax evasion today is randomized audit studies. Well the IRS for instance randomly audits a number of tax payers and then it checks whether these tax payers of duly reported whatever income they've earned and duly paid whatever taxes they are supposed to pay. The big problem is that these random audit studies they face two key challenges. First, you don't have sufficiently many very wealthy individuals who are sampled. And so it's hard to study tax evasion with people who stand 50 or 100 million dollars using random data. You're simply not going to have sufficiently many rich people in the sample. And the second and more important reason is that even if your average people who are randomly audited tax authorities do not detect well the sophisticated forms of tax evasion that take place at the top of the wealth distribution. It's very hard for instance. Think of someone who's, let's say hiding assets in Panama. And the IRS randomly audits that person. What is the probability that the IRS is going to find out? Zero, you know the IRS is not going to ask all the banks, all around the world and all providers of offshore services about whether that person is hiding wealth here or there. And so in practice, random audits are good at detecting certain relatively easy to detect forms of tax evasion. But they need to be supplemented by other data sources if you want to capture evasion by the wealthy. Now until recently, there was no such data but what has happened is that in recent years new data have become available that make it possible to study precisely this. And this new data, they come from massive leaks of data from financial institutions located in offshore tax havens. So what we're going to do in this research is to analyze this leaked data. And our two main leaks. The first one, the most important one is from HSBC Switzerland. So the Swiss subsidiary of the banking giant HSBC. In 2007, an employee of HSBC Switzerland stole the whole file of all the clients of that Swiss bank with more than 30,000 clients. And in 2008, the French Tax Authority obtained it. Then it shared this list with foreign country tax authorities when Christine Lagarde, the current managing director of the IMF was first minister in France and so this list became known as the Lagarde list. And so the US, the IRS has it. Tax authorities in Scandinavian countries have it. And so what we've been doing is that we've been working with tax authorities in three countries. In Sweden, in Norway, and in Denmark to study okay, who all the Scandinavian depositors who were hiding assets at HSBC Switzerland. How wealthy are they? And we can study that question because in Scandinavia the tax and statistical administrations they collect very good data on individual wealth. That makes it possible to compute wealth at the individual level and to rank people in the wealth distribution. So, we use that. So these are if you want, kinda random samples of rich people who have been found hiding assets and doing tax evasion. And so that's going to make it possible to study how concentrated that form of tax evasion is. And then what we do is that we combine that this distributional information with estimates of the macro economic amount of wealth that's hidden in tax havens to derive some estimates of how much tax evasion takes place in total through tax havens, and who does it. We use a second leak which is the Panama Papers. That corroborates what we see in the HSBC list. And I'm going to talk a bit more about that. And so we combine these leaks with macro estimates and with random audit data to study the size and distribution of total tax evasion. And so here is the key result. So that's a graph that ranks households by their net worth. So total assets, financial and non-financial net of debts in Scandinavia. So 10 million households. And then in each bend of the wealth distribution what we computed, a simple statistic which is the following how much taxes people evade as a fraction of the taxes that they are supposed to pay. And on average, for Scandinavian economies as a rule tax evasion is just small. The average is close to, is around 3%. It's not a big surprise you know in modern developed economies it's just very hard to evade taxes. Most people earn wages or pension income or investment income through domestic banks. And thus, it's almost impossible to evade taxes on those forms of income because employers and domestic banks that provide information to the tax authorities that is, what we call third party reporting that makes tax evasion impossible. In these Scandinavian countries the amount of self employment generally speaking, as countries develop the share of self employment and total economic activity falls and so economically, tax evasion becomes harder and harder for the majority of the population. So that's how the average, what the graph shows is that when you move up to the very, very top of the wealth distribution and here we are really zooming into the very top bends of the wealth distribution. Then tax evasion rises a lot. In the smallest sub group that we can see here. The top zero, .01% richest households. The 1,000 Scandinavian households with more than $50 million in net wealth. What we find is that the tax evasion here the rate of tax evasion here is 30%. They evade 30% of their true tax liability. And to see substantial rates of tax evasion you really need to go you know, to the very top. That is, if you look at people who have $2 million of $5 million or $10 million you don't see super high rates of tax evasion. It's really at the very top end of the wealth distribution. So let me stress on the onset that the study of tax evasion you know, is not a perfect science. And obviously there are lots of uncertainties and I'm going, in the rest of presentation try to explain what all the different sources of uncertainty and of course how we obtained those results. I think the general level and pattern is robust. But as we're going to see there are of course, some margins of error. Okay so let me start with the first step of the analysis which is okay, what did we learn from these leaks, the HSBC leaks the Panama Papers that have come out recently. Let me start with the leak from HSBC Switzerland. So HSBC Switzerland, Swiss subsidiary of HSBC is the private banking arm of HSBC. HSBC, we all know HSBC as the bank that advertises in all the world's airports. That's one of their ads, you know before the leak. Security, security, security. So presumably, your account was super safe at HSBC and your financial data except that there was this big leak. You know, Hervé Falciani this system engineer stole the whole file of the 30,000 clients in 2007. So, in many ways for our purposes, it's a perfect leak. It's the perfect leak because HSBC was a big player in the market of offshore wealth management in Switzerland in 2007. It managed about 120 billion dollars on behalf if its clients. Which is about 5% of all the wealth managed by Swiss banks on behalf of foreigners. And you have to keep in mind there are more than 200 Swiss banks. Okay so a market share of 5% is pretty big. HSBC was probably in the top 10 even maybe in the top five biggest Swiss banks at the time of the leak. Along with UBS and Credit Swiss in particular. What we know is that HSBC had clients from all over the world in just the same proportion as other Swiss banks. Okay, so it seems to be represented. There is no indication that it was catering to any countries in particular. Or to particularly wealthy tax payers. Again, you know it was advertising in all the world's airports so maybe it's even possible that its competitors actually had an even wealthier you know, customer base. So now first result, what we do is very simple. We compute in each bend of the wealth distribution what the fraction of Scandinavian households would have a hidden HSBC account. And I forgot to mention a critically important piece of information. Which is that the HSBC leak is particularly nice because it gives you a very simple way to assess whether there is tax evasion on it. So having bank accounts abroad is perfectly legal. As long as you report those accounts and the earnings that they generate on your tax return. So what we can do is, we can check. Once we've matched the names on the HSBC list to the tax returns we can check with all the accounts were duly reported. What we found was that in 90-95 percent of the cases depending on the country the accounts were not reported. Okay, so in 5-10 percent the accounts were duly reported. That's consistent with a whole bunch of information which shows that at the time of the leak in 2007 more than 90% of all the wealth in Switzerland was indeed evading taxes. There's been a couple of reports for instance with the US Senate on tax evasion by US citizens through HSBC Switzerland and Credit Swiss. They found exactly the same proportion. 90-95 percent of the accounts were undeclared. Credit Swiss had to pay a fine of more than two billion dollars. And UBS close to one billion dollars. So HSBC is not an isolated case. Now we can compute the number and the fraction of the population who hides assets by wealth bend. And surprisingly, if you are in the bottom 90% or even 99% of the wealth distribution well, you don't hide assets in Switzerland. Okay, so zero percent. Now, when you move up the wealth distribution the probability rises steeply within the top one percent and then within the top .1% to one percent in the top .01% of the wealth distribution. So you have one percent of the wealthiest Scandinavian households who are evading taxes in just that particular bank. It's just one bank, HSBC and one tax haven which as far as we can know manages 5% of all the wealth in Switzerland. 2% of all the wealth hidden in all the world's tax havens. That's example number one. It's kinda, if you want the extensive margin of tax evasion. You know, who's more likely to conduct that type of tax evasion. What about the intensive margin that is conditional on hiding assets? How much do you hide. Here, there's no trend. There is, across the world distribution condition on hiding assets at HSBC on average, tax evaders were hiding 40% of their total net worth in their hidden HSBC account. So few people do tax evasion in general well, except at the top. When they do it, they do it big. They hide 40% in just one Swiss account. What about the Panama Papers. So the Panama Papers is likely different in the sense that it is not a leak from a bank. It's a leak from a company, Mossack Fonseca. That creates shell corporations on behalf of customers and just like the HSBC leak we can match the names in the Panama Papers to tax returns. It is, there are a number of limitations compared to the HSBC leak. The main limitation is that although in the HSBC leak we could know whether tax evasion is involved. There was a clear test. For the Panama Papers, it's less clear. There are legal uses of shell corporations so tax authorities are still investigating whether there is tax evasion or not. So I'm not saying this is 100% tax evasion. What this graph shows however is that the use of tax havens by that metric, is even more concentrated than what we could see in the HSBC leak. That there's here, when you look at the top .01% of the wealth distribution in Scandinavian they are six times more likely so these are people with more than 40-50 million dollars in net worth. They are six times more likely to appear in the Panama Papers than people who only have in between 10 and 40 million dollars. And below eight million dollars in net worth there's almost nobody in the Panama Papers. Okay so that's, you know the use of tax havens is extremely concentrated. What about now, a third type of evidence? A third type of evidence comes from tax amnesties. So after the financial crisis a number of countries have implemented tax amnesties where they say well, if you were hiding assets you can use amnesty, you can come clean and we will reduce penalties. In Sweden and Norway we have access to a really large sample of people who have used tax amnesties. More than 8,000 households in these two countries have use tax amnesties since 2009. And we can do away with this exercise who are they and how do they rank in the wealth distribution. It's very similar to what you see in the HSBC leak with this gradient within the top 1%. Notice here, just the 92 so you have 40% of the riches Scandinavian households who in between 2009 and 2015 just basically said, oops yes we were doing tax evasion okay? So that's just by their own admission. And just want this specific data set. Now interesting differences with the HSBC leak in the sense that here you know, people that have in between one and three million dollars in net worth they're relatively over represented in the amnesty samples relatively to the HSBC sample. What this suggests is that there is some self selection into amnesties. Tax amnesties are less good generally speaking because they are not random. People choose or not to participate in tax amnesty and on a priori grounds and self selection could go either way. Poor, relatively poor tax evaders might be more likely to self select. For instance, if they've inherited an account and they just want to get rid of it and they're not really actively engaging in tax evasion. Wealthier people may be more likely to self select if they feel that now the tax authority is going to investigate, you know to put more resources into investigating really rich people. What we find empirically is that there is some self selection. It's mostly relatively poor tax evaders who are more likely to use tax amnesty than wealthier tax evaders. In any case, the HSBC data and the tax amnesty data are very consistent in that they both show how concentrated the wealth in tax havens is. So that's what this graph shows. This graph shows that the top .01% of the wealth distribution in both the amnesty data set and in the HSBC data set owns about 50% of all the wealth that was hidden. If you added these two groups you have the top .1% richest households. They own about 80% of all the wealth hidden in tax havens. So of course, dozens of thousands of people at the time of the HSBC leak had, hundreds of thousands of people had hidden accounts in Switzerland. But what matters quantitatively is tax evasion at the very top end. That is the top .1% accounts for 80% of the wealth hidden. Contrast this now with the distribution of non-hidden wealth. Otherwise you know, real estate financial assets held through domestic banks and so on. The top .01% in Scandinavia owns about 5% of recorded wealth. 50% of un-recorded wealth. So now if you want to think about the implications that this has for inequality it's all going to depend on how big the macro stock of wealth in tax havens is. So what do we know about that? I've done some work in previous research about this issue. Now what we see in the macro economic statistics is that Scandinavian countries they are not, they don't have a ton of wealth in tax havens. They are not, generally speaking the kings of tax evasion. If you rank countries by their share of world GDP and you compare that to their share of the wealth hidden in Switzerland you see that in Scandinavian countries they are way below the 45 degree line. They have less wealth in Switzerland than what you would expect just based on their share of world GDP. Countries that have more include you know, Venezuela, Saudi Arabia Spain, France unfortunately. Italy, and so on. So they don't have so much wealth in tax havens. By my estimate, they have about 2.5% of their total household wealth hidden in tax havens. Much less than the global level of about 4%. Now what are the implications? If in total, these countries hide 2.5% of their wealth in tax havens and 80% of this belongs to the top .1% you see that this means that the top .1% owns you know, 2% of total wealth in tax havens. And so that's going to increase the top .1% wealth share from about 8%, that's what you see in the very high quality statistics that exist currently about wealth inequality in Scandinavia. To about 10%. Okay what this shows is that the decline in wealth concentration that has you know, happened over the course of the 20th century is actually less pronounced in actual facts than what you see based on uncorrected tax data. And similarly, the rise in wealth inequality as we see in this case has been stronger than what you see using uncorrected tax date. That's even more spectacular when you look at a .01%. Here what we find is basically taking into account offshore wealth we are back to the levels of wealth concentration of the early 20th century of the 1930s. Something that you don't see using uncorrected tax data which is much less clearly. What you also see is that for the top .01% they hide, by our estimates 25% of their true wealth. So to move from their reported wealth to their true wealth you need to multiply their reported wealth by a third. All right, let me briefly discuss what all of this implies for tax evasion. So if the top .01% hides 25% of its wealth that's going to imply more or less that you know, it evades about 25% of its tax liability. For the top .01% what almost all of their income close to 100% of their income derives from wealth and so if you hide a quarter then that's going to be one quarter of your tax liability that you're not going to pay. Now, here is one attempt at quantifying the margins of error and the uncertainty around these estimates. The main uncertainty is not really about the concentration of hidden wealth which you see both in the HSBC leak and in the Panama Papers leak in the amnesty sample. The main source of uncertainty is how big the macro stock of wealth in tax havens is. It turns out that there's one true piece of information in all of this. Which is Switzerland for the very simple reason that the Swiss Central Bank just publishes that information. Every month, that's disclosed and published on the website of the Swiss Central Bank. Just the amount of wealth that foreigners own through Swiss Banks. So, this lower bound scenario here corresponds to tax evasion by rich people if Scandinavians only have offshore wealth in Switzerland. They have nothing in Luxembourg and the Cayman Islands in Jersey and so on. Okay, so that's a really extremely low bound scenario. The higher estimate, which is not even an upper bound corresponds to an estimate where Scandinavian countries as a whole, hide abroad as much wealth as the world average. So 4% instead of 2.5% okay? Now if you want to have a complete picture of tax evasion there's not a need for tax evasion through offshore intermediaries. No doubt, many other forms of tax evasion. How can we study those? We can look at random audits. In Denmark in particular, you really have existent randomized audit data where close to 1% of the population is randomly audited every year. So very big sample sizes. And they do, in the hub they devote a lot of resources into really trying to identify whether all income has been duly reported using the vast amounts of data that the Danish Tax Authority collects. In particular, about wealth. And so what you see in this random audit study is that you don't see a lot of tax evasion. 2.3% on average. You don't see very clear patterns in tax evasion. Maybe you know, bit of an increase at the very top around you know, 4% but it's not very statistically different than what you see in other parts of the wealth distribution. So does it mean that the random audits just are useless, just don't detect anything? That's not the case, they do detect a lot of mistakes of you know, forms of tax evasion on tax returns. If you look at the extensive margin these random audits, they find for instance in the top 5% these top 5% tax payers in 40% of the cases the tax authority finds some mistake some forms of tax evasion. But it's just that the forms of tax evasion that are detected in random audits they are not big. They are you know, these are relatively small amounts. And in particular, for the reason that I mentioned at the very beginning that the tax authorities just don't have the resources in the context of the random audit programs to detect really sophisticated forms of tax evasion. So basically what they detect is fraud on self employment income or tax credits and things like that. All right. So, let me talk a little bit about how we can explain these findings. The basic, despite the uncertainty I think there's one thing that's really clear. That there is a steep gradient in evasion within the very top groups in Scandinavian. So, the traditional model that economists have to study questions of tax evasion that is the Illegal Sandmo model. Basically the Becker Crime model applied to tax evasion where tax evasion depends on marginal tax rates under-probability to be caught and the penalties paid, condition on being caught. This model is not going to be very helpful in understanding why tax evasion arises when you move from 10 to 50 to 100 million dollars. Why, because you know people at these wealth levels they all face the same marginal tax rates. And very, very wealthy people if anything, they are much more likely to be non-randomly audited by tax authorities than less wealthy individuals. So according to the Becker model they should evade less. What we find is that they evade more. We think that to understand that you need to shift the focus from the demand side of tax evasion to the supply side. So you need to think about what institutions like HSBC do, or UBS. What they do is they cater to very wealthy individuals and they sell them some financial services many of which are legitimate and legal. Some of which sometimes are just conducive of tax evasion. The way to do that is that they organize events galas, concerts, you know sponsor concerts you know, golf events. And for those events, they don't invite me. They don't invite you. So who do they invite? You know, that's the question that we try to think in this very simple model. So we're going to try to model the supply of tax evasion services. Historically thinking about Swiss Banks. Swiss Banks, you know there was a cartel agreement that regulated the fees that the banks could charge and so we modeled that as a monopoly. We also have a competitive model that doesn't make much difference to the quantity of results. You have appropriation of mass one with some density of wealth f(y). You have a monopoly of providers of tax evasion services. The banks that charge dicta per dollar of wealth that they're help hiding. We're going to shut down the demand side of the model by saying, based on infinitely elastic demand for tax evasion price data. And so what the cartel does is it just optimizes on the number of clients that it's going to serve. And when the Swiss banks serve the top S percent of the distribution they manage k(s) in wealth and they earn dicta times k(s) in revenue. Okay so the very simple idea of the model is that what these providers of tax evasion services do is they internalize the cost of being caught. They have revenue, which if you have a bigger customer base you have more revenue. So you want to serve probably lots of tax evasion services. And you have costs. One of the costs is that with some probability you're going to be found facilitating tax evasion. If you have too many customers for instance then the probability that there's a leak increases. Because you need to employ more people and you know, the way that you have some too ethical employee that's going to blow the whistle rises okay, and so what we say is that the probability to get caught is proportional to the number of clients served. And let's name that times S. And if the bank is caught then it pays a fine, phi times k(s). The k(s) is the amount of wealth they manage. And so what's optimal for the bank to do is to provide, if wealth is Pareto distribution there is a very simple solution to the cartel's problem that is the following. The supply of tax evasion services takes this very simple form and what's very important, the most important thing to notice in that equation is just that the supply of tax evasion services is going to be a declining function of inequality. So when wealth is super concentrated the inverted Pareto law in coefficient b is high and so everything here that equals S is going to be small. So if you have just a few billionaires who own most of the world's wealth that's going to be the customer, the potential customer base of the Swiss Banks. If wealth is more equally distributed then the banks are going to supply more tax evasion services. The second important thing to notice is that it's kind of a message of hope. Is that the supply of tax evasion services is going to depend on the probability for the bank to be caught and the fine in case it is caught. And so if the fines are very high let's say, if a bank caught facilitating tax evasion is put out of business, which corresponds to an infinite fine that model you're going to have a zero supply. So that's a message of hope because it means that it's not so complicated to fight against tax evasion. You just make sanctions really big for the providers, for the facilitators of tax evasion. And so let me finish very quickly with the following. Does this mean, what happens? What would happen if indeed the tax authorities and countries fill out this strategy. They increased fines for banks. Does that imply that wealthy people would pay much more in taxes? Well, that's going to depend on whether they legally avoid more. On the interplay between tax evasion and tax avoidance, you could imagine that if they can't evade, now they are going to find legal ways to just pay very little taxes and so it's hopeless to collect more revenue from the very wealthy. And so the way that we study this question is by looking at this big sample of Norwegians who use the tax amnesty since 2009. And they used to hide a lot of wealth. They decide to come clean. Question, do they start avoiding more? And so we have a very simple event study design. Where we follow over time the evolution of reported wealth reported income and taxes paid by this sample of people who use a tax amnesty. And what do we see? So we see that after using the tax amnesty the amount of wealth that the former tax evaders report boom, rises by 60%. Okay? After the tax amnesty, the amount of income that they report, taxable income boom, rises by 20%. In both cases, it rises just in line with what you would expect based on the amount of wealth that they were hiding and they disclosed during the amnesty. What about taxes? Let's say they arise by more than 30%. The result here is that four years after the amnesty this sample of tax evaders they still pay 30% more in taxes. Okay, so at least in that context and I'm not saying that these amnesties are necessarily a great idea and that doesn't take into account the effect of amnesties on non-evaders and complicated dynamic effects. But in that particular setting the treatments are under treated and the people who use the tax amnesty is strong and persistent. They pay much more taxes four years after using the tax amnesty. So my conclusion is this. In rich economies with little self employment tax evasion is small on aggregate but it's high at the top with a strong gradient within the top 1%. This can be explained by a simple model where the suppliers of tax evasion services internalize the costs of being caught. And both the model and the evidence suggest that collecting more revenue from the wealthy might be possible under current law. And that's the last slide. This is Scandinavia, I don't have the time. Maybe during the questions we can talk about what we learned or don't learn about the US or the rest of the world. The point is that the data that we use in that research is available in many, many countries. And so, these methods that were developed and these data sources that we use could be applied to the US, to other countries to construct kind of similar distribution or tax gaps. And the ultimate goal of all of this is to correct global inequality statistics which right now, don't take tax evasion into account at all and the hope is that ultimately they will take into account plausible estimates of the amount of tax evasion. Thank you very much. - [Man] Thank you. It seems like you have to assume for this to be a correction that auditing is somehow a priori, is not as effective only for the high wealth. If it's because what you do, is you supplement it with a particular you know, data set on a particular form of evasion that's only prevalent in very high wealth groups. But if auditing only a priory was equally ineffective across the distribution, most say 30%. And then you adjust supplement at the high wealth end with particular forms for high wealth of evasion then it's not really a correction is it? It's more of a, it could lead to more biased estimates of evasion. Unless you have the a priori assumption that we're mainly missing evasion by the high wealth groups. - Okay, let me actually answer that question immediately. So, it's totally true you know, that what we do is we take the random audit data. We take them as is and then we supplement those using the leaks. And it's true, it's possible that the random audits not only miss some forms of tax evasion at the top end by our estimates they do miss regularly a lot of tax evasion at the top. But also here, okay. That's possible. Is it likely that they underestimate by effect of 10? Tax evasion in those wealth bends here I mean, that's not the viewpoint of either tax authorities or people who've used these audit data so far. For the very simple reason that most people here in those wealth bends, they just can't evade taxes. Okay, if all the income that you get is weighed income, or pension income or interest in dividends earned in domestic banks it's just impossible to evade taxes. And the tax authorities at least the Danish Tax Authorities that we've been working with a lot they're pretty confident that they do a good job here. That yes, there's tax evasion in self employment income and they do find a lot. They find that half, you know 45% of the self employed in Denmark evade taxes. That's reflected in those numbers here. They do find a lot of evading in self employed income but some supplemental income is so small and aggregate that it doesn't mean that there's a lot of tax evasion. So, I take your point that maybe there's a bit more tax evasion here. Maybe it's not 1% here, maybe it's 4%. But what we find is that for the very very top bend, it's 30%. And I don't think it's likely that they are forms of tax evasion that are indicated here that could move those dots up to 30%. - [Man] One question about taxes rules are different in different countries and people may choose where to have their fiscal residence. So, they will disappear from the distribution and perhaps you may have in your tax records those very rich, which left the distribution. We may think of soccer players, singers, and so on. So they may have some bias in the distribution. - Yes, that's also a great question. So it's true that... One way to avoid taxes, sometimes to evade taxes that's popular at the very top end of the distribution is to change our country of residency. For the US it doesn't work because they are citizenship based taxation. So wherever you live in the world you're supposed to pay taxes to the IRS. But the US is the exception. Other countries, if you move away from Denmark then you are not taxed anymore in Denmark. It's very important and all the data that I've showed we've excluded non-residents. So we see quite a fair number of Scandinavian nationals in particular in the HSBC list that we can match to some of these sets of data. But they say, they claim to be non-residents and so we remove them from our estimates. Which I think is probably you know a bit too extreme in the sense that one form of tax evasion that sometimes happens at the top of the distribution is to you know, falsely claiming that you are a non-resident. Okay, but we've taken their word here. We can't detect that form of tax evasion with the data we have. And so we've removed all non-residents so all the series that I showed only include resident, taxable individuals. - [Man] Thank you. I think that you concluded that all what you presented is valid if there is a low degree of self employment. If you are in Italy, which is my own country the average income declared by small enterprises artisans, shop keepers and so on and so forth is lower than what an unskilled laborer earns. And so last part of the tax evasion occurs in the, I want to say bottom 50% of the distribution, 50, 60, 70 percent. So only people working for the formal sector or pensioners, or they pay... And then of course there are some big cats that are evading. Now, what the tax office argues that they were unable to catch all the tax evaders. This would be people with the low/medium level of income. And so if you collect the distribution that ID would give us an average which is lower than the one which we estimate on the basis of the surveys. So, just to emphasize that. Norway is one country and Italy is another. So the nature of the correction could be the opposite of the one that you were hinting at the end of the discussion. Is that correct? - So the pattern of tax evasion that's found in random audit data here in Scandinavia. You know we've not discovered that it's been studied quite a lot by many people before us. The only difference compared to the literature you know, on random audits is that we rank people by wealth instead of taxable income. But if you look at studies in the US. You know, the National Resource Program the NRP, the random audit studies that the IRS conducts. You know, a number of people have studied these random audits and they find a distribution of evasion that's relatively similar. That is slightly rising at the top of the income distribution. So that's what you find both in Scandinavian and in the US NRP. Again, these random audit studies have a lot of limitations that we've discussed. I think tax evasion by self employed people you know, it's important. New countries like Greece, like Italy and developing countries in general. Let me show you just a graph that may be helpful. So that's the graph that compares the US with Denmark with similar pattern in tax evasion in random audits. Now, here is a graph that shows the share of supplemental income in GDP in OECD countries. Denmark, which is the country that I've been using for the random audits you know, is here at 5%. If self employment is only 5% that puts the big limitation even if all the self employed evade and evade 100% of their income that's not going to imply big rates of tax evasion overall. Now this is Denmark. In Greece, in Poland, and Turkey self employment is 25% of GDP. In that case, the graph here that I showed is likely to be different. That is absolutely true. Now this dot, would be maybe even higher in Greece than in Scandinavia, that's one possibility. Those dots here would also be higher. So I don't want to claim that this pattern here is a universal law. That's absolutely not my point. In Scandinavia, that's what we find. In countries which have a very low share of self employment this is likely to be close to the truth. Because just these people here, they can't evade a lot. And tax evasion is only possible here at the top. Okay, one more question. Yes? - [Man] I'm curious about your opinions on the implications of rewards for tax whistle blowers. As I'm sure you know, the IRS promises 15-30 percent of taxes collected if it's greater than two million which is a big payoff, like $300,000. Hiding serious money requires the cooperation of a lot of people. Some of whom are poorly paid. So does this alter the supply of tax evasion services to people of different nationalities? Does it have an impact on your estimates overall? - That's a great question. Yes, it's true that the main way that authorities try to put pressure on the providers of wealth concealment services is by you know, agitating the risk of whistle blowing and paying huge sums to whistle blowers. So for instance, the IRS paid $104 million to a former UBS banker who revealed tax evasion by Americans at UBS Switzerland. That's a lot of money. That's of course a big, he also went to jail so you know. (audience laughs) Not to tell you consistent incentives but just the money incentives for whistle blowers. Yeah, they're pretty high. That's for sure. Now, is it really enough? I'm not sure, I think that there are two problems. One problem is that if the fines that are imposed on banks like UBS and so on are too small then you know, it's not going to be enough to you know. They make a cost benefit analysis and if whenever they're caught they have to pay $900 million or $800 million which is what UBS had to pay. This just pales in comparison to their profits. HSBC was found. Was found facilitating money laundering by Mexican drug cartels. Which is really, with huge sums involved. Which is a very serious offense. And we know they got to keep their banking charter in the US they had to pay $2 billion in fines to the US. But that same year in 2013, they made more than $20 billion in profits. Okay so it's not clear that the fines are high enough. And the second problem and I think the deeper problem is that there is a view, it was in the banks and certainly may be within amongst some regulators that big banks are just too big to indict. That is, it's not a good idea to take the risk to put a big bank like HSBC or UBS out of business. Because it would topple financial stability. It would destabilize the world market. And so what we've seen is that there's no big bank that's been put out of business. Nothing like what happened at the time of Enron for instance. The regulators just don't take those risks. Now if the banks internalize that that they're too big to indict even if you have whistle blowers that might not be enough for them to curb the supply of tax evasion services. Another strategy for them is just to move these evasion services to smaller divisions and to improve their internal systems and so on. So my view is that whistle blowing is not enough of a threat. What's critical is to find a way to impose relative sanctions for the facilitators of tax evasion. Thank you. (audience applauding)



Gabriel Zucman was born in Paris, France in 1986. From 2005 to 2010, he attended the École normale supérieure de Cachan, one of France's prestigious Grandes Écoles.[8] Hereafter, he first earned his M.Sc. in economic policy analysis in 2008 and a PhD in economics in 2013, both from the Paris School of Economics, for which he received the French Economic Association's award for best PhD dissertation in 2014. After finishing his studies, Zucman worked for a year as a postdoctoral scholar at the University of California at Berkeley (UC Berkeley) before accepting a position as assistant professor of economics at the London School of Economics (LSE) and the same position at UC Berkeley, being currently on leave from LSE. Moreover, Zucman has worked as Co-Director of the World Wealth and Income Database (WID), a database aiming at the provision of access to extensive data series on the world distribution of income and wealth, since 2015.[9]

Besides his research and teaching activities, Zucman has refereed for several economic journals, including the Quarterly Journal of Economics, the Review of Economic Studies, Econometrica, and the Journal of Political Economy. He also co–founded and acts as editor–in–chief for Regards croisés sur l'économie, a review aimed at exposing the French general public to academic research in economics.[10]


In August 2014 in Capital is Back, Zucman and French economist Thomas Piketty investigate the evolution of aggregate wealth–to–income ratios in the top eight developed economies, reaching back as far as 1700 in the case of the U.S., U.K., Germany, and France, and find that wealth–income ratios have risen from about 200–300% in 1970 to 400–600% in 2010, levels unknown since the 18th and 19th centuries. Most of the change can be explained by the long-run recovery of asset prices, the slowdown of productivity, and population growth.[11] Zucman has co-written several papers with Thomas Piketty.

Much of Zucman's research is on issues of economic inequality and, most importantly, tax havens. In 2015 in his book,The Hidden Wealth of Nations, Zucman uses the systematic anomalies in international investment positions to show that the net foreign asset positions of rich countries are generally underestimated because they don't capture most of the assets held by households in offshore tax havens. Based on his calculations, he finds about 8% of the global financial wealth of households, or $7.6 trillion, to be held in tax havens, three–quarters of which go undeclared.[12]

In 2017–18, Zucman has been focused on the scale of multinational tax avoidance by base erosion and profit shifting ("BEPS") tools in the largest corporate tax havens. Zucman believes Ireland, recognised as a major corporate tax haven, is still materially underestimated by Orbis–database studies due to technical factors (even though these studies rank Ireland as the 5th largest global corporate Conduit OFC).[13] Research published by Zucman, Tørsløv and Wier in June 2018, showed that Ireland is the largest corporate tax haven in the world, even larger than the entire Caribbean corporate tax haven system.[4][5][6] This research also showed that tax disputes between high–tax jurisdictions and corporate tax havens are extremely rare, and that tax disputes really only occur between high–tax jurisdictions.[14]

Along with James R. Hines Jr. and Dhammika Dharmapala, Gabriel Zucman is noted as a leader in the study of tax havens,[15] and his papers are amongst the most cited research on tax havens.[7] As of October 2018, Zucman ranks 1st out of "19,829 economists whose first publication of any kind is 10 or fewer years ago", on the IDEAS/RePEc St Louis Reserve database of papers by global economists.[16]

Much of Zucman's other research deals with the effect of the G20's crackdown on tax havens and corporate tax havens, cross–border taxation and multinational profit shifting, the long–term relationship between wealth and inheritance, and the trajectory of wealth inequality in the United States. Zucman is frequently quoted in the leading global news media.[17][5][18]

Zucman tax havens

Zucman-Tørsløv-Wier 2018 list

The only tax havens from the Zucman–Tørsløv–Wier list that have ever appeared on an OECD list of tax havens, are some Caribbean locations, namely The British Virgin Islands (but not the Cayman Islands).[19] Nine of the top ten locations from the Zucman–Tørsløv–Wier list, match the top ten on the James R. Hines 2010 list (assuming that Zucman's "Caribbean" is mostly two locations, The Cayman Islands and The British Virgin Islands; Zucman lists Bermuda separately).

Missing Profits of Nations. Appendix: Table 2: Shifted Profits: Country–by–Country Estimates (2015)[4]
Tax Haven
Rank by
Profit Shifted
Profits ($bn)
Of Which:
Local ($bn)
Of Which:
Foreign ($bn)
Shifted ($bn)
Tax Rate (%)
Corp. Tax
Gain/Loss (%)
Belgium 10 80 48 32 -13 19% 16%
Ireland*† 1 174 58 116 -106 4% 58%
Luxembourg* 6 91 40 51 -47 3% 50%
Malta 11 14 1 13 -12 5% 90%
Netherlands*† 5 195 106 89 -57 10% 32%
Caribbean*‡Δ 2 102 4 98 -97 2% 100%
Bermuda*‡ 9 25 1 25 -24 0% n.a
Singapore*† 3 120 30 90 -70 8% 41%
Puerto Rico 7 53 10 43 -42 3% 79%
Hong Kong*‡ 8 95 45 50 -39 18% 33%
Switzerland*† 4 95 35 60 -58 21% 20%
All Others 12 -51

(*) Identified as one of the largest 10 tax havens by James R. Hines Jr. in 2010 (the Hines 2010 List).[20]
(†) Identified as one of the 5 Conduits (Ireland, Singapore, Switzerland, the Netherlands, and the United Kingdom), by CORPNET in 2017.[21]
(‡) Identified as one of the largest 5 Sinks (British Virgin Islands, Luxemburg, Hong Kong, Jersey, Bermuda), by CORPNET in 2017.[21]
(Δ) Identified on the first, and the largest, OECD 2000 list of 35 tax havens (the OECD list only contained Trinidad & Tobago by 2017); only some Caribbean territories were listed by the OECD in 2000.[19]


  • Zucman, Gabriel (2015). The Hidden Wealth of Nations: The Scourge of Tax Havens. University of Chicago Press. ISBN 978-0226245423.

See also


  1. ^ Sunstein, Cass R. (January 14th, 2016). Parking the Big Money. The New York Times Book Review.
  2. ^ Houlder, Vanessa (October 2nd, 2015). ‘The Hidden Wealth of Nations: The Scourge of Tax Havens’, by Gabriel Zucman. Financial Times.
  3. ^ Drucker, Jesse (September 21st, 2015). If You See a Little Piketty in This Tax-Haven Book, That's Fine. Bloomberg Businessweek.
  4. ^ a b c Gabriel Zucman; Thomas Tørsløv; Ludvig Wier (8 June 2018). "The Missing Profits of Nations" (PDF). National Bureau of Economic Research.
  5. ^ a b c "Zucman:Corporations Push Profits Into Corporate Tax Havens as Countries Struggle in Pursuit, Gabrial Zucman Study Says". Wall Street Journal. 10 June 2018. Such profit shifting leads to a total annual revenue loss of $200 billion globally
  6. ^ a b "Ireland is the world's biggest corporate 'tax haven', say academics". Irish Times. 13 June 2018. New Gabriel Zucman study claims State shelters more multinational profits than the entire Caribbean
  7. ^ a b "IDEAS/RePEc Database". Tax Havens by Most Cited
  8. ^ Curriculum vitae of Gabriel Zucman.
  9. ^ The WID is managed jointly by Facundo Alvaredo, Tony Atkinson, Thomas Piketty, Emmanuel Saez, and Gabriel Zucman; see the website.
  10. ^ Curriculum vitae of Gabriel Zucman.
  11. ^ Thomas Piketty; Gabriel Zucman (August 2014). Capital is Back: Wealth–Income Ratios in Rich Countries 1700–2010. Quarterly Journal of Economics, 129 (3). p. 1255-1310.
  12. ^ Gabriel Zucman (August 2013). The Missing Wealth of Nations: Are Europe and the U.S. net Debtors or net Creditors?. The Quarterly Journal of Economics, 128 (3). p. 1321-1364.
  13. ^ Gabriel Zucman; Thomas Tørsløv; Ludvig Wier (November 2017). "Why high-tax locations let tax havens flourish" (PDF).
  14. ^ Gabriel Zucman; Thomas Torslov; Ludvig Wier (June 2018). "The Policy Failure of High–Tax Countries" (PDF). National Bureau of Economic Research, Working Papers. pp. 44–49.
  15. ^ Vincent Bouvatier; Gunther Capelle-Blancard; Anne-Laure Delatte (July 2017). "Banks in Tax Havens: First Evidence based on Country–by–Country Reporting" (PDF). EU Commission. p. 50. Figure D: Tax Haven Literature Review: A Typology
  16. ^ "Top Young Economists, as of October 2018". Federal Reserve of St. Louis. The rankings: Top 200 Economists (10 years or less) Taken from a pool of 19829 economists whose first publication of any kind is 10 or fewer years ago. These rankings consider only the youngest economists registered with RePEc. Young is defined by the year of the first publication in any form. Note that the shorter the time span considered, the more likely the ranking is going to be spurious.
  17. ^ Gabriel Zucman (8 November 2017). "The desperate inequality behind global tax dodging". The Guardian.
  18. ^ Gabriel Zucman (4 August 2017). "Gabriel Zucman on tax evasion and inequality". Financial Times.
  19. ^ a b "Towards Global Tax Co-operation" (PDF). OECD. April 2000. p. 17. TAX HAVENS: 1.Andorra 2.Anguilla 3.Antigua and Barbuda 4.Aruba 5.Bahamas 6.Bahrain 7.Barbados 8.Belize 9.British Virgin Islands 10.Cook Islands 11.Dominica 12.Gibraltar 13.Grenada 14.Guernsey 15.Isle of Man 16.Jersey 17.Liberia 18.Liechtenstein 19.Maldives 20.Marshall Islands 21.Monaco 22.Montserrat 23.Nauru 24.Net Antilles 25.Niue 26.Panama 27.Samoa 28.Seychelles 29.St. Lucia 30.St. Kitts & Nevis 31.St. Vincent and the Grenadines 32.Tonga 33.Turks & Caicos 34.U.S. Virgin Islands 35.Vanuatu
  20. ^ James R. Hines Jr. (2010). "Treasure Islands". Journal of Economic Perspectives. 4 (24): 103-125. Table 1: 52 Tax Havens
  21. ^ a b Javier Garcia-Bernardo; Jan Fichtner; Frank W. Takes; Eelke M. Heemskerk (24 July 2017). "Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network". Scientific Reports, Nature Publishing Group. 7 (6246).

External links

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