 Okay, thanks Ines and in for excellent presentations. I'll try to keep up basically what I'm going to present so builds on What you have presented already. All right, so I'm going to talk about Inequality and human development. All right, and this is so it's empirical work that we've done with Carlos here and Vicente back in Barcelona, right? And so what we're doing is basically use this amazing data that these guys are putting together to try to reassess So the connection between the quality of human development, right? And the focus as the subtitle says is on the role of different parts of the income distribution. All right This is already a saw he why they're working paper in case you guys want to take a look. All right, and Yeah, I mean this is still open for for improvements But let me motivate briefly. So two main trends that we can relate to of course. So one is Inequality and and as he was suggesting so the keys in equality within countries, right? So on the rise you were suggesting that is sort of Stable or on the right but in in many countries is is what the data suggests that is on the rise All right, and that's a major concern, right? So when we talk about inequality is not between countries anymore is mostly within countries, right? And and so in line with with the project the idea is to see okay But what exactly is happening when we talk about inequality, right? And one one thing that I want to highlight here also already highlighted is is it this proportional concentration of income at the very top No, and this this has been Center of debate with key out or spaghetti and so on so discussing this concentration of income at the top Right that one thing and we connect this with the idea that development means more than pure economic growth No, and Ines was telling us how at the beginning we were sort of focusing on on economic growth And now it's we we started to to look beyond no education health and other development outcomes And Just to to bring this out elephant serpent grab I'm not gonna get into the the technicalities of the shape here, but this is sort of also how how Basically what what you were explaining also when we look at what has happened in the last decades. So how it's basically The very rich who are really taking the big part of the pipe not so This is globally not so The the global sort of poor have been on the rise a little bit because of the rise of the emerging countries, right? And you talked about for instance China and But then the middle sort of quick bottom in the USA Western Europe and this connects to political debates And those left behind and an electing Trump and that would be another sort of discussion if you are right And then the super rich which are are taking the big sort of share of income. All right and This is also from so I mean this is you can of course Easily download from from the internet and this is so cross-country variation in in this concentration of income at the top at the top We can see it looking at the top then. All right, and we see sort of The dispersion I mean the big variability across countries. I want to highlight Latin America of course Where we know inequality is really high. All right, and there has been a lot of discussion in this Congress about inequality in Colombia, but also when we talk about Top incomes right actually I did a little bit so you can play with this online, of course And I took US China the world and Colombia and you see Colombia is like Champions up there not so and this and I selected this because these are countries US is I mean It's of course one of the countries that we started So the data starting to show this this concentration anyways for for the Colombian audience Like that we hear in Bogota, right? But the same if we look at the if we look at the top one percent. All right, so again But in America red red, so the top one is taking on all of these countries more than 20 percent of the total income That's quite a lot and again Colombia's at the top like In the ranking the good Anyway, so the aim as a studies to having this motivation and this is data in mind is to Reassess this relationship between income inequality and human development as I said already And so what we do is to look at a large panel of countries so we take for the moment We take a cross-country approach. We look at close to 150 countries over the last decades 1990 to 2019 as and as I was saying so the idea is to explore the role of the Different parts of of the income distribution basically the concentration at the bottom the middle or the top. All right Some I had some literature review, but in this it's such an amazing work So I don't know what else I can add but just to go quickly So we know that inequality can have impact on economic growth and there is a mixed evidence here So we could be positive. I could probably add that when we look at so When we find a positive effect, this is usually because we're looking at the short run, right? That's sort of one distinction that we can add and when we when we find a negative effect This is usually the long run on this relates also to the two channels. So these negative channels They are rolling a more longer term, right? And that's that's an important distinction that I think we have to make I'm not gonna say much about the mechanisms. You could play this very well And you also said we also know that the this impact may depend on different characteristics So like the level of development barro 2000 that you mentioned but also the initial level of Inequality and here we know this has also been said of course is that some inequality is is good, right? So if we have a low level of inequality and increasing inequality may actually be good news It's when inequality is too high that that the impact reverses, right? It also depends on the type of inequality, right? This is something that we have to remember and I mean we had a nice sort of discussion yesterday So whether it's market or structural inequality or inequality of opportunities as put by Ferrara yesterday and In a previous paper we show with with my culture with Vicente we show that so the two things happen at the same time You can actually capture the positive and the negative effect if you are able to disentangle the structural versus marketing equality, right? I think that's also interesting And yeah, so beyond growth we know that there is an impact on health and education Outcomes, but as you said the evidence here is more limited than there is more to be done All right, and then what what we've been sort of exploring recently is how inequality connects to human development We have already some evidence that high inequality lowers human development The idea of this work was to explore that in more depth and again looking at different measures of inequality So yeah, I think that the potential contribution is to to look not only an aggregate inequality indices Right like the genie which is as you said the traditional sort of way to go But also to look at differences along the distribution of income. All right, and To Just as we say not to the best of my knowledge. There is no paper already doing that So I think that's the contribution here I want to show you a little bit about the data, but again, I mean you already had sessions with the experts explaining the data So not much to add here When we look at the HDI so for human development We look at the HDI and you know that this is basically Income education and health. All right, and I just to show you that of course there is what I mean a lot of cross-country variation And also over time not this idea to explore this variation in terms of inequality We rely on on you guys on the on the wheat. All right, and as I said, I'm not gonna say much about this because It's already been explained Just to say that so what we do is again is to use different measures and basically for the moment We've been focusing on the genie to sort of try to Reproduce previous results and then look at the bottom 40 the top 10 and the top one and of course Implicit here is the middle. All right. So again along the income distribution I showed you grabs with that top 1% of the top 10% I can also show you maps with the gene index just to show you that I can spend time doing maps anyways And let me show you so the association between inequality and HDI. All right So if we do simple scatterplot, or we do simple sort of drug section or OLS Sort of or long-run associations and we find this sort of negative Association also if we look at the genie or also if we look at the top one top 10 This is positive because here we're looking at the bottom 40 So you have to understand it the other way around. All right So this is the idea that that the so looking at a global sample of countries over time You're gonna find this this negative association between Inequality and HDI. All right, but we're gonna explore this in more depth Of course using a regression analysis, right because that's why I study the econometrics and I teach econometrics So have to use econometrics So the the functional form is pretty simple So HDI country I time T and we regress that on on inequality measures We try to have some some luck here We have some controls and then so this is sort of pretty standard in the literature And this is what so trying to reproduce what what all the papers have done Changing of course so previous papers look at growth Here so what we do is look at HDI. No, but then we add to that adding so we add to that the distinction between different sort of Part of the of the distribution so for instance between the top and between the bottom on the top All right, so for so for the analysis we use our global panel five year intervals So sort of more long-run association and we control for a lot of variables. All right And let me guide you through the results. So this is the first sort of results So human development and inequality and using different indicators. So Basically and this has so this has so Contrifics the facts time fix effects and then we play with the with the controls, right? So this is sort of like The empirical strategy now As you see many cases you don't find much And this is probably the idea that there is mixed evidence and it's not easy depending on what you do But what what I can say so if you focus here So we find a positive and significant association between genie and income and this is so for some other Previous papers that said okay with you if you stick the facts in a panel You probably gonna find a positive association on for for some people. This is like well Inequality supposed to be bad so right so I think what is interesting here is that we we we reproduce that But then it disappears when we look at the concentration at the top is to say okay So maybe there is a positive effect of inequality for instance through savings or some of the mechanisms that in this Discussed but not when we look at the top so the top So the concentration at the top is not associated with with higher income. All right And I think that's already an interesting finding Second set of results this is then sort of if you want using the second equation here is sort of Adding the bottom 40 and the top 10. All right and here if you want so and we look at different So we look at the HDI we look at income we look at education and we look at health All right, and this is what we find so higher concentration of income at both tails All right, so at the expense of of the middle It's associated with a lower HDI. So I think that's also an interesting result is to say, okay So it's so concentration at the extremes what seems to be lowering Human development. All right And when we look at income education and health we see that sort of the tracking is Education so particularly with education. All right, and now this sort of supports some of the of the Still early findings on on educational outcomes How am I doing on time? Okay, all right good For health here, we don't find much. All right Now what we do is so we can based on the literature is to say, okay, let's look at let's look at levels of development So let's Compare for instance high income countries with low and middle income countries And again, we look at HDI income health education and health and then HDI income education and health here. All right And again bottom 40 and top 10. All right, oh here bottom 40 and top one We play to with the concentration of income either at the 10% or at the 1% Now so for low and middle income countries, so we're gonna start here We find that the concentration of income at the top and bottom So again at the expense of the middle is negatively correlated with education. All right So it seems that in in low and middle income countries again the story is about education Now when we look at high income countries We find that the constant talk at that high concentration of income at the top All right is significantly associated with lower health and we found this as interesting because you mentioned that when when They look at health outcomes. They don't they don't find much. So here we find in something and and It sort of supports. So this is what we're trying to do now So there is outside economic that is literature that that sort of discusses this right now So inequality especially when it's like so I see what my neighbor has and all this So this this may impact health outcomes. All right, and we find this this for high income countries So we think that it might be a story there. All right Now so another exercise that we did here is to say, okay So if part of the story is concentration of income at the top, there is a story about Institutional quality, right? So we thought okay. This is this Concentration of income or institutional quality. You also mentioned that there is an association between these two so basically what we did was to to use data on sort of So proxy for institutional quality and we built two sort of measures So one for political institutions and another one for socio-economic conflict All right and see what happens when we control for institutions and we will split countries by by the quality of institutions So looking at countries with low quality institutions. So you we know that if this is usually countries with low level of development They're all controlling for institutions. We find that so sort of basically Part of the story is is institutional quality, but the results are still there. All right, so it may be that part of the effect Works through institutions. All right But again, it's not all the story. All right So this this will be if you want the sort of regressions So basically if you if you compare this with with the previous table so the coefficient goes down So again, it seems that one mechanism could be Lower institutional quality, but the results still there for for inequality or for in this case The top 1% so you mean that it's not only lower institutional quality is something else Which relates to concentration of income at the top. All right, and I think this is where we have to explore more. All right But again, you see for instance for the top 1% we still have a negative coefficient and in this case so for HDI also for income although not significant and for Education So we did more robustness checks than this is so in case as of if you if you are interested in the econometrics behind But I'm not gonna spend much time here So we use alternative series of human development for instance a augmented or the hybrid, right? And so for our period of analysis, which is the 1990 2019 our main results hold. All right, the other thing that we did was sort of Using alternative ways of introducing the role of the middle income groups Not so remember that the story here is is that this concentration at the extremes All right, so we did so following some previous papers also the topic we for instance use the genie plastic The third quartile or the middle 50, right sort of to capture the idea of the middle class or the median voter that Arinez was mentioning. All right So yeah, I'm gonna conclude with this. So basically we reassess this inequality development relationship To take from from my presentation. So concentration of income At the top sorry At the expense of the middle if you are is associated with lower HDI especially for human capital accumulation and In developing countries and health in high income countries. All right And of course, there are policy implications of this that we can if you want we can discuss. All right For their work, we want to do this at the national level different contexts and police frameworks And maybe come back with results next time we see each other. All right I still have one minute, right? And I'm gonna be allowed. I'm gonna save my last minute to do a little bit of propaganda Decade to my mind. So this is that conference on on development And I just got a book out which is called our elusive quest for prosperity And in this book idea, I do I thought it's a short book on on the history of economic thought trying to in a in a very easy way trying to do So go through the ideas on what it means To be prosperous or for us development how to understand it and sort of in an historical perspective If any of you is interested in There it is. All right, it's in English but also in Spanish if you want to to read in Spanish. Thank you