 Thank you very much. So I got the tough draw, in a sense, and also the humility of having my own country put in this category, which was a little bit of pull to swallow. So really, what are we doing here? We're doing a sort of a within-group exercise. So I'm looking at the not good or, as the title called it, uninspiring on the growth side prospects. And really, what I'm supposed to try and tease out is, well, how constraining is that for poverty? That's the issue on that. Is that the ball game? Is that over? And how would it not be over? Well, you know, it could not be over by the quality of expenditures changing or shifts in income sources that leave the same growth, but are party to a structural transformation. So there's some mechanisms that are worth thinking about here. And also in terms of what's constraining growth. So as everybody said, the whole point of this project was to give great attention to the data within each country. And my approach is somewhere in between the first two speakers. I'm not going to give you a lot of detail on each country. I'm going to use each country for a lesson, starting with a very deep, profound lesson from, from Corévoire. And it's a lesson about instability, political and social instability. Hopefully you can see the graph. But, and I didn't make the graph, I would like to take credit, but it's in the book. And it talks about military coups, a number of them, and there's uprisings and, and the data's an index of social unrest. And, and it's, it's pervasive. And, and completely shook up what we'll see is it completely shakes up the, the, the Corévoire and Malieu with devastating consequences for the poor. It's probably worth noting even now. So here it gets a little flatter and, and there's a stabilization time in 2003 onwards, but it doesn't seem to have been able to turn things around. So those are some of the lessons already. But it's not just about politics. So it's this interweaving of an interactions between the political Malieu and the economic Malieu. Because what was going on in this country at the time? It wasn't exactly, these are GDP per capita figures and cash crop incomes. And so you, you can see we start, it's on a strong upward positive trajectory, which is already a challenge for us. 1962 is where the graph starts through to the end of the 1970s. And then what happens? Well, the cocoa price collapses. Devastatingly. So also on this graph is the cocoa and coffee output per capita. And you can see it plummets and the two track each other very profoundly. And so that's part of the story and part of the political unrest. And there's a feedback between, between those two factors. I'll leave that slide. What are the consequences for the poor? This is the earliest period, 1988. So for those of you schooled in these, in these distribution functions, this is a picture of a disaster, a poverty map of a poverty disaster. Because what you see is the later time periods shifting up, which means greater incidence of poverty, a lowering of income right across the distribution really and huge increases in poverty. And particularly, let me just draw your attention to the fact that the worst case scenario is, is quite recent. Is a fairly recent scenario. I've got growth incidence curves too, but it makes the same point. But for those of you that do this, these are all below zero. So those are declines in real incomes for each percentile of the income distribution. So what do we get out of this country's experience? It comes back to the point that David Staffel was making about preconditions for development. But it challenges the notion of preconditions a little bit too. Because don't forget that in the earlier period up to the end of the 70s, this country was on the move and not doing too badly. And then it, it implodes and that somehow just couldn't cope with, with that. So one of the themes in my particular country studies, then revolves around issues of implosion versus a shock versus periodic crises. Because that's one of the themes that comes through my particular countries that don't, that aren't growing very well. So we go on now to discuss the country Madagascar, which didn't have exactly the same experience, doesn't have this massive implosion, but had systematic political shocks that, that really disrupted things. And then some economic shocks as well. And as a consequence, you can see, if you just look at the trend of this line, which is the per capita GDP, it's, it's very constant. It's not improving. And the red dots are the poverty, headcount poverty ratio. So it's at 60%. It's a very high poverty country in which real GDP is not going anywhere. And, but yet there's a go, the people are trying to do things. There's political disruptions. There's a political disruption here and there. And all the way along, it's an unstable milieu. And then in 2003, there's a rice crisis as well. So there's an economic disruption. And with that, there's a government that's trying to get on and do some things in a basic sense. And it's, it's interesting to see how these disruptions disrupt the attempt to do good things. So very high poverty rates. It's very interesting to note actually that the, that's the next slide that. So just looking at the trends, that's the national poverty. Again, you've seen that the rural poverty is, is here. And it goes up slightly. And it's higher, obviously, as in just about every, every country. But the urban poverty actually goes up higher, faster or for lower base, but rises faster. And the reason for that, and it validates the focus on prices to some extent, or one of the reasons anyway, for that phenomenon is, is this rice price crisis that, that hit. Anyway, one can see Madagascar disrupted. There is some So at the national level, there's, there's minor progress on the, on the head count poverty front. The urban rural differences are interesting. I've already, I've already teased them out a little bit. So these are the stunting rates. And what I was trying to, the point I was trying to make here is that the government was quite well intentioned on the non-money metric things. One of the reasons for looking at non-money metric aspects of poverty is not just to, not just because that's something you do, but because it tends to go better to other dimensions of policy and tell you about what else government is trying to do. And there's some minor improvements here. So that's a situation where there are these regular disruptions. Cameroon, I'll, I'll click through quite quickly as, as a country with promise, no particular crises, but somehow can't quite get it together to really go. Here's a long, very long run picture of Cameroonian GDP per capita. There's an oil boom here. And I guess the story that comes out of Cameroon is, is somehow that wasn't leveraged to, to put, to put Cameroon either on a very good growth trajectory or, and to, to strongly alleviate poverty. Although the, the survey data does, tells a fairly optimistic story about the, the drop in the national head count ratio. What one of the very interesting features of, of Cameroon is that the strong differences across regions and differences across urban and rural spaces in terms of the performance. So actually urban Cameroon is doing quite well. And there's a lot in, of discussion in the relevant chapter about the growth in services as a contribution to, to GDP. And that's a very urban based thing. And so the urban head count drops dramatically. The rural head count does not. And the national aggregate is, is some uneasy compromise of the two. And so generally Cameroon just doesn't balance that very well. There's a discussion about bad use of oil resources for seemingly good things, like infrastructure investment, but bad choices. And then that, that just implodes. It actually makes things very difficult for one. And, and so we see some urban benefits, but we don't see rural poverty. We see rural poverty increasing. And then there's a very telling point as well. The, the, the chapter uses non-money metric measures to make a very, very positive, a very compelling point about the, the bad use of, of resources that the government had available to it at one point by showing on non-money metric measures that the main cities actually have, have improved strongly on those measures, but the rest of the country hasn't. Thank you. So the Kenyan case is, is, is not a, doesn't have a political, is not a political disaster case of the 2008 elections are tricky. They come very late in the particular story that we're telling here. The, the, the strength of the Kenyan chapter is to put on the table for us of a long run trajectory in which the country is going through an almost classic Lewis, Fae Reines type of growth path where, where there's movement out of the agricultural sector to, to the cities, but it's not particularly quick. It's a very slow process taking place over time. The slide perhaps, but, but it's not inconsequential. So over the long run, this is a, this is a early, a slide giving you early economic history in a sense. Well, not early in the long, in the real sense of that word, but 1914 to 1976. And you can see that the long run process of development, particularly in the, in the independent era, well, so in the independent era, poverty has declined markedly through this transformation of people moving to urban areas through, through wages, increasing non farm agricultural activities in rural areas, et cetera. And so poverty has come down quite dramatically as a sort of an income using sense index to, to a value there of 20. But it's then very constant. And I guess the story in the chapter is that it does, we don't see huge improvements on that since then. And really, it's given that the chapter was anchored in the sort of long run development dynamics. It's a fascinating story that was in the Latin American session yesterday about the role of the labor market and how it can transform or not transform. And it's not as though it's not dynamic. It's not as though there's nothing going on in the Kenyan labor market. There clearly is. But for example, there's a big shift from the formal, from out of agriculture into the urban areas, but into informal urban activities, which have pretty low wage and therefore don't have dramatic impacts on poverty reduction. Let me go to this slide, which shows you exactly that. I'll focus on this. So here we have real average earnings growth. And you can see that, that it's strongly positive over here, but through the 2000s is very, very sluggish. And the reason for that, I take it, we have Ana in the room and he's the author. So we can validate my statement. But if you look at the growth of the informal sector employment, it's much stronger than formal sector employment growth. And so this is the mechanism that comes up. So it's not so much an employment problem. You don't see much unemployment because the informal sector and agriculture still absorb like a shock absorber. But then the poverty story depends upon what's actually going on in those sectors. So we see a very sluggish poverty performance in Kenya. You'll have to believe me because of time constraints. So South Africa in a minute, I plot some densities here for you. And one can see this is this is 1993, the start of the post-apartheid period. And you can see real income improvements at the bottom of the distribution over the post-apartheid period. This is a poverty line. And what we see in South Africa is some mild but pretty unspectacular declines in poverty in the country. And work that we've done myself, Harun Barat, a number of us, Ingrid Willard, show that this is due entirely to the state's social grant program. And that's worth thinking about in a low growth climate. So Africa is not a no growth climate. It's between 2% and 3% long run average over the post-apartheid period. But an exceptional use of expenditures in the budget to target conditional cash transfers within that environment. And that is what made a difference on the poverty front. The labor market did not. The labor market is a bit of a Kenyan story except in South Africa we do have unemployment and a large unemployment problem. So the labor market didn't didn't do very much. Also on the state side, on the non-money metric poverty side, we can tell a story that's much more positive than the money metric story of increased improved access to water, electricity, sanitation and housing, huge improvements actually over the post-apartheid period. And the multidimensional poverty exercises we've done show big improvements on money, non-money metric methods. We then look at the price, we do do some price exercises and they are quite useful, I think. Because it's fine to use these assets and to use non-money metric indices to show that there are more taps, there's more access to water, et cetera. It's fine, but it depends upon the milieu. If people are paying for these services, well then the prices of them are very, very important in mediating between does it look like people have stuff and do they really have stuff and can they really use it. And so some of the price exercises we have done look at the prices weighted by their weight in the consumption patterns of different parts of the distribution and this little quadrant here is a quadrant of prices that are particularly relevant to the poor rather than the rich. And the fact that it's above this red line means they rise higher than the consumer price index. So these are prices that are really relevant to the poor that go up faster than the CPI. And it's quite telling. Housing and electricity is the winner, which is a very bad thing for the poor in South Africa given that we've actually in terms of the surveys rolled out housing and electricity. Thank you. I'm getting frantic zeros from the chair. Food and meat. Anyway, the story was that if you account for price changes, that modest poverty decrease is even more modest. I think I better leave my ruminations because I've used my time. Thank you.