 What we are able to do in this report is the first systematic assessment of globalization in terms of economic inequality. And what we show here, one of the main results is that despite high growth in emerging countries, and this growth actually is very often used to argue for a reduction in global inequality, well we see an increase in global inequality and this increase can be very much expressed in one single line, which is that the top 1% captured twice as much global growth, so that is all new rupees, yuan, euros, dollars, the new dollars generated and all the new money, all the new cash generated since 1980, well the top 1% captured twice as much growth as the bottom 50% combined. There is a snapshot in 2016 where you see the share of national income captured by the 10% richest in each country. In Europe the top 10% captured 37% of national income and the Middle East 61%, and then you have a diversity of positions, so India is close to the top, 55%, China 41%, USA Canada 47%. So this is the picture today, where do we come from? So let's look at the evolution since 1980, so again we look at the top 10% income share. We look at India, in yellow, USA, Canada, so North America in blue, Russia in purple, China in red, Europe in green and we see these diverging trajectories since 1980. So low level of inequality at the beginning of the period, high level of inequality at the end, but the trajectory is really varied, so if you look at for instance Russia, so most equal country in 1990 during the Soviet period, and then in just five years it became actually the most unequal country in this subset, so a very brutal shift out of the Soviet economy. Now if you look at China and India for instance, you see in both cases a rising inequality, but much more moderate in China, especially at the end of the period. I will come back on that, and then if you compare USA, Canada and Europe, you also see a very similar inequality level in 1980, and a very, very different position at the end of the period. If we take a step back and put these relatively short term or mid term evolutions in a broader historical perspective, well we see that all these countries went through from 1950 broadly to the early 1980s in a low inequality phase. We're back in a rising inequality phase, so there was a decreasing phase back to a rising phase. Well here I'm adding three more regions to the graph, so I'm adding the Middle East at the top, here Brazil also at the top, Sub-Saharan Africa at the top, which are arguably regions which never went through this compression phase of inequality, whether a communist regime, Soviet regime, highly regulated economy regime, or mixed economy regime in the US or Europe. These regions arguably always had a very high level of inequality, unfortunately we don't have at the moment enough data for the longer historical period, but you see that they seem to set what we could call a high inequality frontier in the sense that levels of inequality in these regions is so high that it is actually high to go even higher in terms at least as defined by the top 10% income share, and some countries seem to be back to this extreme levels of inequality. So now that we've looked at these different building bricks of our global distribution of income, let's look at all world individuals. So let's break the boundaries of countries, let's just look at individuals just with their income levels. And here we sort world citizens from the poorest on the left to the richest on the right, so we have 100 group of individuals here. And so this is a population scale, so we attribute to each group of equal population size, so here you have 10% of the world population, here 10%, 10%. So they represent 10% of the excess, 10% of the excess, 10% of the excess, so they are scaled by population. What we do on the y-axis is that we plot the real income growth rates over the period, and this is our global elephant curve. So basically you see at the bottom among the poorest group here of the global income distribution, the rise of emerging countries with a total growth rate over the period, so from 1980 to 2016, over 100%. In the middle of the distribution or second half, you see growth rate that are much lower, so below 50%. So these are the squeezed bottom 90% in the US and in Western Europe, and actually we look at the case of the US in more detail. In the US, the bottom 50% actually grew at close to 0% of the period, so it can go actually much lower than 50%. And then if you go to the top of the global distribution, you see very high income growth rates over 200% for the very top groups. Now one may raise an important question, which is does it really matter to have very high income growth rates here? In fact, by definition, the top 1% is just a very small group of people. Perhaps they have very high income growth rate at the individual level, but this doesn't matter much from a macroeconomic perspective. Perhaps it's just a small share of the cake that they captured. So we try to answer this question with this graph, which is the same data. The only difference is that we represent here individuals on a different scale. So it's still the poorest on the left, the richest on the right. The difference here is that we give each group of a given population size a length that is proportional to the total share of growth that it captured over the period. So look at the top 1%. So everyone on the left of 99, they represented just one dot. Here they would be right here, just one dot. Here they represent 27% of the axis because they captured 27% of total growth over the period. So here we scale by the share of growth captured. Now let's look at the bottom 50%. Half of the world population captured only 12% of total growth over the period. So that's two times more for the top 1% than for the bottom 50%. So answer to the question I raised before, does it really matter? Yeah, in terms of macroeconomic growth, it is a substantial amount of growth captured, of income growth captured by the top 1%. So in fact, squeezing half of the world population on the left-hand side of this graph is not necessarily the best way to represent the importance in terms of population of this group. So we prefer to adopt a mixed representation. So in this graph, I'm mixing the two previous graphs. We're giving some space for the bottom 50% to be able to really see here the importance in terms of population size. But we're also stretching the top 1% to show the importance in terms of the share of growth it captured. So this is one of the benchmark, the key result of this report, our so-called global elephant curve of inequality and growth. This elephant curve of inequality and growth, in fact, comes from two curves. The addition of two, so to say, cobra curves. So here is the same curve, but just for US, Canada, and Western Europe. The poorest on the left, the richest on the right, we see here that growth rate moved from 0 to a bit more than 400%. Most of the income distribution, so 80% of the population grows below 50%, 30%, 40%. And then when you go up to the top, you see very important growth rates over 40% for the very top groups. So this is Western Europe and US, Canada. Same graph, but for China and India. So the first big difference here is what you see on the y-axis. So we don't stop at 400% anymore, but 4,000% growth rate that we're much higher. But more or less it's the same general pattern. We still have a cobra, so to say, with very extreme growth rate at the top and much lower growth rate at the bottom, even though these matter a lot at the bottom. You see that growth rate were between 100% and 800% for the bottom 80% of the population. I'll come back on that. But our global effort is actually the combination of these two cobras. So when you combine that kind of curve for low income region and this curve for high income region then this is when you get the elephant. And here this elephant is just for China, India, USA, Canada and Western Europe. It's a bit different than the one that I presented before. Why? Because growth was higher in China and India than in other emerging countries. So when we add other emerging countries, this value here that's around 250% is reduced and this is when you have this final result here that I presented before.