 Well, thank you very much Marcella and I must say that when your friend the other Marcella told me you guys were going to this project I said, well, yeah, maybe after seeing the output and this is the second time I see that thing This is really extremely important and I'm sure you mentioned at the beginning This is the first step of a wider agenda trying to understand some of the cross-country variation in this shape How this could be changed by policy other determinants of this equilibrium just some Isolated notes perhaps for for further conversation And we can talk about this later. I haven't followed this detail in all of Latin America But in my kind of don't write down and let I I'll take notes for you later In my country, there is a lot of people who have some life arrangements that implied participation in some things called social movements And these are people who are in working age and they get their salaries through sort of state programs administered by what would be the labor unions of the Informal and unemployed first. I was wondering how these people appear in your sample And then I also and I have been born a lot, which is the political dynamics We had that because there is a game in which for various labor market regulations state intervention Political dynamics. It's much more productive to To stay so so there is a matter of understanding the determinants some will be Productivity related some will be the structure of the economy related some will be Regulations in the labor market and in other markets and then the other side that I'm sure you guys are going to that is Sort of the other extreme. I remember the joke of the other Marcella yesterday People who look at firms and people who look at people in some sense also Distribution of human capital of the population supposedly gets much here and wondering how much how that much works And what is the priority for those of us that like myself now that work with people more than with firms? Okay, if I increase the human capital, so all these kids eventually will get to a good job But then you show me that there is no good job until you had really Higher up in Latin America and these kids will never make it if it is a supply side phenomenon of the organization of firm So I think this is probably you know one of the crucial things we have to unravel to see what are the next policy steps Thank you very much. So thanks very much, Mariano I mean these is these are precisely the I think the large questions to which this facts speak to if I were to answer your Your to your list, I would be very boring and basically repeat it Maybe with a different ordering in terms of what I think are other priorities to start with as As the income distribution showed us I of course Emphasize the fact that we have this low long and and dance That's the populated tail, but the first thing that jumps to your view to your eyes I'm sure is the fact that the distribution is very much shifted to the left And I think that has to be traced to the distribution of productivity Captured by few human kept by human talent. So if you start there My first inclination would be to to put that high in the in the list I think in terms of the determinants part of what's going on is if you take the underlying productivity distribution That is to say what are our capabilities to to produce value? That translates into income for people and when we say what are our I'm thinking about people What are the capabilities of these people? We have a very much shifted to the left Distribution and that is the first issue to solve So if you did if you just took that and we had no institutions and is or rather institutions were identical to the other countries With with higher incomes you would buy construction already start finding that the people who are with lower capabilities End up organizing in lower productivity firms and that does those lower productivity firms are going to be smaller And you would have smaller firms so that would be sort of your basic macro model without distortions But then if on top of that you start laying out The institutions then you're going to have more more answers and if I'm going to Give you a second priority for the case of Latin America. I would precisely point at one of the things you mentioned the labor market I think one of the main barriers for this building up of the smaller businesses smaller But still organized and able to grow in in all my previous work I think me and other people would have shown is that if we have a deficit in terms of productivity It is not so much a deficit of our ability to form enterprises or to be entrepreneurs But rather an ability to have those businesses grow and so that's I think that's that's Very high a very high priority and one of the main barriers is definitely how costly it is to Organize in terms of of labor and I'm sure in the next panel Santiago will lay out some of the alternatives That he and other people have been thinking about for for labor productivity then a third issue I think is definitely the tax systems Latin America is characterized by tax systems that rely mostly on businesses to produce their income Very high corporate income tax rates Very high fraction of the collection coming from businesses and so just creating businesses that Pay those taxes Thus are formalized thus are able to also grab some size without you know having to be under the radar Is another challenge and I think that's that's also a crucial issue And I think there's going to be necessarily a tension between the question of redistribution Colombia today is in the midst of discussing a tax reform part of the discussion is are we going to? tax dividends more strongly is that on top of taxing the corporate income Highly Those I think those controversies are absolutely crucial for or or very closely related to the set of facts that I am laying out here And I will be happy to take questions Marcella, thank you, nano So I had one very specific question and and like a more general comment The specific question is on the measurement of productivity for the different factors of average productivity So for for labor you're doing this very nice adjustment of human capital Through the use of micro data But there's no equivalent adjustment for capital For things such as intangible capital and equality of capital So of course, that's not easy to do and the kind of data that you have May not borrow itself to that, but I think in terms of the interpretation of the results the apparent realization that Capital is being Rewarded in all regions above its Productivity I need has to be I think need has to be you know passed through At least the the the questioning that that that adjustment is not happening in a world where we know that intangible capital Has become increasingly important. So that's that's the specific question and then the more general comment. It's just that One one running theme of the whole session is is the importance of Understanding the differences for the discussion of reduction of inequality Between the countries where these has been a traditional discussion the low and middle income countries and the things that have been brought to the Center of the debate now that this has become also a concern in in the richer countries So the the most prominent issues there of the increase of the sorry the decrease of the labor share The increase of market concentration the increase of huge fortunes the Simply need to be taken with a lot of caution when informality so prevalent as As it is in our countries and Andres showed a version of why that is so important in this Wait, the things that you're showing that are so extremely different In terms of between the low and middle income countries and the richer countries and all the other discussions that have gone around Okay, let so there are like five questions there so Let me begin by saying that there's the issue of Of You know personal firms Is roughly taking into account here with these golden's methodology Do you remember the methodology the point is they take out from the whole Income mixed That is not enough. Let's say this this is not doing the deal. So let me go back So this data set the first the first time we think about this data set Was because we were thinking about the composing Changes in the income distribution Like like the total genie is Factor each factor share multiplied by the genie of the ownership of the factor And this was the plan but We need a lot of time to build To have the whole distribution of ownership of all the factors. So but basically The message here is look in for the whole sample These changes in factor shares may be explaining an increase in inequality in high-income countries But not in low-income come In low-income countries as a whole because we will have to take a look at it at each country To see but what we see is that you have a lot of noise But at the end of the day they end up basically in the same place they began Then well, you know the other paper we have the same set of our first we have a paper relating the resource boom with income distribution and what we find there is that There's there's During the boom the dodge. This is mechanism Increased the demand for on-skill labor So so this helped to reduce inequality during these years If we are right We should see At the iteration or let's say an increase in inequality again now the capital So there's a beautiful paper. I don't remember the author, but it's it's an econometric guy and it's I don't know from one year ago Or something and he claims that The increasing in the physical capital share is basically due to two untangibles It it may be the case And if you talk to Or the galore. He's going to tell you here you have entrepreneurial To entrepreneurial activities with which is actually labor income Fair enough We cannot for the moment. We don't know how to deal with that The weak answer I can give you is this is quite standard. We are just Doing what the other people are doing but with more fine-tuning I'm sorry. This is not a nice question answer, but okay If Okay, thank you very much. Ah, sorry. Sorry Marcella. Thank you nano. I Wanted to ask why are you packing together low-income and middle-income countries when we've looked at how a Capital shares and labor shell shares evolving work with Marcella's lava. We see a lot of variants across countries Yes, so it's strange No Good point at the point. We are building the data set and We have to show you something in 20 minutes. So this is this is the answer Of course for the paper, it would be nice to have different sets of countries and to analyze Heterogenities within groups Santiago thank you nano my question is what is the composition of the data set? Perhaps I'm wrong, but what I saw is basically all the aggregate facts are driven mostly for for high High-income countries so the composition is quite balanced, but high-income countries make up a Higher part of the total income and this is explaining part of the story We had we made the same few years with waiting for population Things change, but not that much Yes, but my concern is if maybe because there's an under-representation of these developing countries Then perhaps the the facts that you're saying are not are basically due to selection and not because this is a basically An established fact No, I see I see I see so so you see if you're talking about number of countries in each group is quite balanced The point is the size of the countries And and again, this is the standard. This is how people measure the global trending in labor-income share, but again, it's it goes basically in the same direction as Marcella's point Thank you nano for your presentation and my question regards the natural resource a Measurement and like what does it includes I understand maybe the minerals and in the oil and oil and gas But maybe have you thought about including maybe carbon reduction as Means of capital okay, that that's a very good point. So there's not only minerals It's also forest. So it's the data the the World Bank is providing a nice data set But so you're asking about externalities. So you destruction of value and I think there's something but but it's quite imperfect So these data cities is not going to be good to analyze the other things you have in mind Bad when we think about ways to work with that. Okay. Thank you very much