 So, we had three very interesting presentations, and now it's time for questions, discussions, comments, suggestions. We take a few and then the panel will reply. Alright, so as a natural resource and environmental economist, listening through all three presentations is like my environment part of my brain just keeps going up. So, I will start with ethnic inequality. If you observe global use, you realize that, for example, in many developing countries, the nomadic people are usually at the north of the country where they have the poorest quality land. So, they live in less favorable agricultural land and that in itself is inequality, right? So, to fix that structurally, how would you account for those geographical people are poor just because of where they are placed and in the US to the same thing with the Native Americans, right? They are also found on poor agricultural lands. So, basically, agriculture will not be the thing they can do. So, basically, national policies to address inequality on the ethnic part may have to look at how to improve geographical things, maybe improving infrastructure in those areas, I don't know, because those areas lack water and stuff like that. Also, the Human Development Indicator Index. I find that very exciting, like the whole presentation, all three of you, was very exciting. But I think the idea of the assumption of a long and healthy life life is a very strong assumption to include in the Human Development Indicator. My research has shown that developing countries are disproportionately affected by environmentally related issues. For example, health risks that are associated with water pollution, air pollution, force for users like charcoal and firewood. We see a lot of mortality from there. The World Bank actually estimated that about 24 percent of global debt can be linked to the environment. So, basically, we can have, let's say a country is supposed to have a life expectancy for 65 years, but the quality of that life expectancy reduces which in turn affect the Human Development Indicator. So, how do you intend to account for the quality of life expectancy in that given the disproportionate effect from the environment? And also, my issue again was that when you were presenting, you talked about the fact that we might need social safety net to reduce poverty for old people, right? But when we look at developing countries, that still come back to the point that a lot of people live in poverty because of where they live. I grew up in Ghana, right? You have poor quality water, no toilet facility and all of that. So, even if you have a safety net, the government distributes like $500 a month. You still have things from your environment that literally cuts down the money because you have a physical money, but the experience money you get is low because infrastructure in where you live is less developed. And most people, most old people in developing countries live in the villages. So, they don't experience the infrastructure development in the urban centers. So, basically, there is something to consider as well. Yeah, those are my questions. Thanks. And also, thank you for having a LNOB session in a quality conference because actually, we do get a lot of opposition between the two. And I don't think that's true. So, it was great to have the session. A clarification question for Martha, if you look at plus 80 in some of your graphs, I was just wondering what is the relevance of that threshold for developing countries, actually, when we see that they are... I was actually looking at the numbers and it's ridiculously low for Africa, for instance, and I don't know how that would look for it if you increment it. And for Hereto, thank you so much. It was very interesting for us because we have been thinking a lot about these issues. And I have two questions. One is more... Have you tried to look at how this correlates with, let's say, municipal level poverty rates? Because you do have a lot of spatial mapping of poverty. And it would be interesting to have a look at the two. But also, what does this tell us? What would an HDI, I don't know, municipal level indicator tell us? And how would you then link it to policymaking? Because you said that the HDI is used to classify countries. Now, how does this then impact the action? And on inequality, because you said that you were looking into expanding it to inequality. Is it the HDI corrected by inequality? Or are they specific inequality indicators? And in that case, would you be looking at inequality within, let's say, municipal boundaries or what type of indicator? Thanks. Yeah, thank you for a fabulous session. I'll just follow up on where Anna was talking about, the local level municipal. There are a lot of census data available for download from EPUMS. And so one of the things one could do a little bit is, and you've got provincial poverty things. So one could think about some of the local area estimation things on the census data to generate more local level indicators. That was just a thought on the first paper. Wonderful paper. I was thinking about the equivalent scales a little bit. Because you use the OECD and OECD adjusted or something, right? Which are that doesn't exhaust the scope of equivalent scales, but yet they make a difference. They're not that far apart that they make a difference. So I was interested in that because other equivalent scales would be much more different to that, like a per capita, for example. And then you told us how the single person household was crucial, actually. So it seems as though these household dynamics are quite important. And I was wondering whether it wouldn't be worthwhile pushing that a little bit. And maybe your equivalent scales give you some sort of framework, at least some sense of what's important there. And then, of course, you're using the relative poverty line. And I was wondering about any sensitivity test for some sort of deprivation approach. To certain developing countries, that would be quite important, I think. Thank you very much. Anyone else? Thank you. I mean, first of all, thank you very much for some very interesting presentations. Some of it is extremely exciting in terms of thinking about what's going to happen and so on. And it's obviously great to see that the Human Development Report Office actually managed to survive. And that's great that this kind of work is now inserted into it, that's for sure. One thing that I'm kind of particularly pondering about, I was wondering whether you might want to comment on that. And it relates a little bit to what has already been said by Murray. Some work that has been ongoing has been trying to establish to which extent when we are estimating poverty, we are getting it wrong when we are using censuses and households, surveys and so on that are, by definition, outdated when we are doing our analysis and whether that actually matters. And the work we have so far been able to come up with is that it actually suggests that it does matter a lot because basically when you try to use the satellite images and so on and then try to make estimates of poverty, then it shows up that it has actually significantly changed as compared to when you use the census data. And I was kind of wondering, and that maybe adds, it's a little bit along the lines of what we're sort of asking, why do you jump straight into the HDR, I mean, sorry, Human Development Index? I mean, why not, for example, start with a poverty where you have quite a developed kind of set of estimations and so on? And you would actually then also be able to get kind of into an area which is sitting very crucially in relation to the SDG-1. So I'm just sort of thinking about this and I'm not having a very clear, but these are some thoughts that come to mind. And if I may just sort of add that I think it's extremely fascinating to be thinking about these tools because, I mean, from some of my own experience, I mean, we've been trying to take what are established as poor areas at a very low disaggregated level in individual countries and then actually trying to understand, are they actually going to be harder hit by climate change as compared to richer areas? And I just want to make one statement. That's still an active area of research. We still don't know. I mean, that doesn't mean that the poor areas are not in areas which are today worse off. I mean, that is completely agreed, but it's not an established fact yet that those areas will be the ones that will be warmer, et cetera, et cetera, when we look into the future. That's still an open question. And what that tells me is that, I mean, trying to get that right is extremely important for policy, right? Because you want to somehow with the evidence to be ahead of the policymaking process. So if you can be ahead of that process, then you might actually be able to be very effective when you as a researcher come up to the policymaker while we established this three years ago and then you can start feeding it in. So I don't know whether this makes sense, but I hope it. Well, I have also a few questions, quick question, first to Rachel. I was wondering, I mean, probably you have followed the question about the referendum of the new constitution in Chile, no? And one of the hot topics that probably produced the result of rejection of the constitution was precisely this multinational definition of the country, that generated rejection on the non-indigenous population. And yeah, so it's like, to what's your opinion? So to what extent these kind of multinational definitions of the state is a good idea, could help to integrate the, or better improve the living conditions of in this case, indigenous people, or on the opposite, could create more divisive lines within a country, and maybe at the end could be have a negative effect. Maybe depends on the proportion of the indigenous population over the total, maybe it's very different, no? Chile from Bolivia in that case, because it's a small minority, but yeah, what that your opinion. And the second one, because I think you mentioned at the moment that some programs were not very effective, in terms of reducing horizontal inequalities. I was remembering one case a long time ago, or that can produce negative effects in some cases. It's the case of Malaysia. And I remember being, I was there, and since I'm also very interested in these ethnic things, I bought in the library two books, almost randomly about ethnicity, and it could be, they were both on ethnicity in Malaysia, and it looked like they were talking about two different countries. Why? One was written by a Chinese person, and the other one by Malaysian. And of course, one uses the perspective of this new economic policies, how the problem is called, is an affirmative action program that is improving the living conditions of the majority, but disadvantaged population. And on the other hand, the view of someone that became my ethnicity, because we have a foreign origin, we are not considered citizens in this country, even if we are here for several generations. And the case of improving some things sometimes implies worsening other, maybe in this case improving one ethnic minority. The majority implies generating maybe some alienation of other groups that even if they are affluent groups, they still can be discriminated in many states. And probably maybe this would relate also with Marta. I was thinking also some trade-offs when you look at, you think in terms of age, and probably it's because a big part of what resource to find is in some countries having weak social protection for the elderly. But I was thinking also in some cases, it could be that improving the social protection of the elderly since has to be funded in some way could be increasing the burden for the young generations. And usually at both extremes is where to find highest poverty, because you have higher poverty among children that typically is because they live in households, relatively young households with nothing, et cetera. So to what extent do you think there is also, maybe it's more in rich countries where the social protection is bigger and the proportion of the older population is bigger that increasing the social protection of one group implies maybe increasing the burden for the younger generation. So now we are open around, maybe we go this order. Thank you. I don't think we have a lot of time, so I'm gonna try to, and I speak slowly, so things, I can answer more things in the coffee, but it's very important to maybe to come back to the origin of the human development index. So we know it's a very imperfect index, so we try to use some complementary things. But the idea is that it's like the entry point is the door of the house of human development. And therefore this allow us to start thinking about this question and then develop the tools to answer those questions. And I think this is what is in a way inspiring our work. So why human development index and not starting with poverty? Because it gives us the opportunity to capture the attention of people and if we can get it right, if we can provide something that we know is not perfect, has problems, but helps us to go one step ahead, then I think it would allow us to open a door that we think it's very important to open. So there are many ways in which this can be used and I'm not gonna go into details, but I think the key topic is that the world is changing fast and we have a lot of information about that at a geophysical level. So there are models, there are observations, there are models that give us information about what is expected to happen in the future and we are really lagging behind, measuring what is happening with social variables at a distributed level. So even for the SDGs, for very basic indicators, we are lagging behind. So this is a way of generating a new generation of data that we know is not perfect, but that would allow us to start saying thing and looking at the interactions with the geophysical variables. So that is what is inspiring us and we are planning to use more census data because in some cases it allow us to give very good training data for these models, but also to be able to address what happens with countries that haven't had a good census in decades. So we can generate data for that. And what's next? Many types of inequalities, just territorial inequality, just looking at these syndicators is straightforward to jump into that. But also we can do inequalities for different variables, income inequality, we can capture it through this type of analysis and certainly poverty. So I take advantage of what you need to say in October 17th, we are going to be launching a new report on multi-dimensional poverty. So we plan to cover also those aspects, but for us this is just the entry point. Okay, so I don't know your names, I'm sorry, but your question, Angela, thank you, Angela. So yes, I think you pointed to the importance of infrastructure particularly, and that has been an omission from my presentation, my fault, infrastructure and services to different things that are very important. My omission I think is due to the fact that this is one report in a series that has focused on different aspects of inequality in the past. And in this case, we were asked to work on population aging and older people, and this was new. So what I have emphasized in the presentation, what's more new, which is some pension systems, for example, and social protection. But in the report, we do refer a lot to services especially and infrastructure. I've mentioned that older persons face spatial and social barriers that preclude their participation and a way to overcome these spatial barriers is obviously through the right infrastructure and services. So it's addressed, and I'm sorry, I didn't mention it. One thing though, let's talk about social protection, and I repeat what Ocampus said yesterday. No social safety, and that's pretty social protection. It's a different thing. Then there was a question about the 80 plus, numerical relevance. Obviously the percentage of people who are 80 and older is still small in developing countries. The proportion is growing, but let's go again to the relative versus absolute. The absolute number of people who are 80 and over in developing countries is very large. And again, it's going to be growing. So I think it's relevant to pinpoint. This is not the main finding in our report. It's just one that I happen to highlight here. But it's important, I think, to highlight that these are people who are in need of special attention because a very blatant deficiency when it comes to aging and older persons is long-term care. And these are the populations that are most affected by the lack of formal long-term care programs, for example, as an example. From Murray, the equivalent scales, yes, you picked on the... So I think if I know correctly, the three main equivalent scales, you start the square root scale, which is not only OECD, it's increasingly used everywhere. This OECD modified scale, which the OECD is no longer using anymore. And then the per capita scale, which I skipped in purpose because I think the World Bank is still using it in many cases. I think it's less accurate than realistic to assume that no matter the size of the households, the costs are proportional to the number of people in the households. But if you wanna know, yes, the estimates differ even more if you use the per capita equivalent scale. So, yes, it's true. And then I think there was a question related to that on the living arrangements. Yes, we're going to prepare another report on that because we realize that that's a separate problem and we are going to elaborate. And then on the relative poverty line versus the absolute poverty, I don't know if it was Finn or you, but we were going to compare globally people. So for developed countries, the absolute poverty line as used around the world is not very relevant. The numbers would have been very small. That's why we use a relative poverty line. We look at absolute poverty too. The findings are a little bit different when it comes to absolute poverty. The older persons are maybe less disadvantaged, but there there's also the fact that the poorer die earlier. So there's a selection effect that happens by which the people who are poorest may have disappeared by the time they reach the age of 70. That's just one factor. Finn, I don't think there was a rest for me. And then Carlos on the trade offs, right? Oh, okay. I was anticipating. Empirically, because that's a question that we thought maybe as there is no evidence of this happening. There is no evidence of expenditure on young people or children being reduced because more resources have to be devoted to older persons. There is none. And I think it's because we often think, I think it was to where Rachel was saying, we think of like this is not like a limited box and there's an equation that is made to see what you spend. There's all these politics involved and there's all these constituencies that will defend educational expenditure. And it's unlikely that countries will reduce educational expenditure just because they can't afford it because I know there's lots of older people now. I think that two are decided through separate processes. So there's no evidence of this happening anywhere. Thanks for the question. So first for Angela's question. I mean, I think it raises first a great point that we need to think also about the source of the ethnic inequality. So is it, do we see ethnic inequality because of active discrimination and exclusion and repression and that's certainly a case in many places or is it coming more out of just, it happens to be that certain groups live in areas that are more remote and they have less access to services and markets. And I think that's certainly something that needs to be figured, taken into account when you think about what sort of policy would work. And certainly a part of the story is bringing state services to remote populations. That's certainly a part of the story in a lot of countries. So in point, very well taken. And then I guess the other question for me, Carlos, and I should have highlighted in the presentation that I mean, I have some work on group-based inequality and we've been hearing all about Carlos's work on the weed and on inequality generally, but he also works a lot on group-based inequality. And so we have several sets of work at wider on group-based inequality. But on the questions, I mean, I guess I don't know of Chile really, really well. I mean, I'm sympathetic in one sense to the value of inclusion when you've had historic exclusion, that I think there's some real symbolic value to signaling inclusion on the basis on which people have been excluded. On the other hand, I think it's really concerning the implications of sort of incentivizing ethnic identification and distributional conflict along ethnic lines. I think that's a real challenge. And maybe that's not so much a question with the Constitution. So I suppose with the Constitution, I would favor more the inclusion approach, but when you think about other policies, I think this risk of incentivizing ethnic distributional debate is really problematic. On Malaysia, we have a world expert on Malaysia in the audience. I would refer the specific questions about Malaysia to him, but certainly I think as the Malaysia case illustrates, I mean, any kind of discussion about this stuff gets very polarizing very quickly and it really incentivizes that polarization to be along ethnic lines, which is why the ethnically targeted policies get so tricky. But on the other hand, it's when you have ethnic inequality because of legacies of discrimination, then it's hard to get around addressing them directly. So that's a messy answer to a good question. Okay, thank you very much. So we ran out of time. So that's a big applause for the presenters.