 Thank you very much for the invitation to fulfill this role. We've had three excellent presentations, I disagree with very little that's been said. What I'll try and do is sort of synthesise a little bit and maybe point out a couple of issues in terms of taking this agenda of work forward. Now though the session was called poverty and inequality in Africa, the focus has been very much inequality, and that's entirely right. We know much more about poverty, we know much less about inequality, and as Arun pointed out, inequality in Africa is higher on average than other parts of the world, and we need to understand this, and it's really important. And the point about the gross elasticity of poverty being so low in Africa is almost certainly linked to that high inequality. So it's a really important issue. Two of the presentations we had basically used international data and basically asked questions about what are the causes of high inequality. Andrea and Arun differently, but really addressed those sorts of questions. These questions are fundamentally important. What is the factor underlying high inequality in Africa? Kathleen's presentation focused much more on measurement, but also focused on some additional perspectives on inequality. That's also really important. All of these things are really important issues moving forward. Now the measurement issue is absolutely fundamental. The data quality, despite the best efforts of WIDD and other things, the quality of inequality data for Africa remains poor. That is the reality that we have to face. To add to it are the problems that Kathleen talked about, about surveys not being comparable. It's been a continual source of frustration to be in using things like PovConnet and World Development indicators. You can't judge whether data is comparable or not. That's a major disservice to the development community that you just can't understand which data are comparable and which not without looking into it much more carefully. Or rather, that's telling you that you need to check out much more carefully before just using data from an existing data source. Of course, as Kathleen says, inequality is often inadequately measured. The response to this I think is not to make up lots of new observations in the way of WIDD based on what are already weak data to start with. The response I think is to try and improve the quality of the underlying data. Now let's just think for a minute about the suitability of the household surveys we have for measuring inequality. The household surveys have been very much motivated by poverty measurement. The focus of the surveys is very much on measuring consumption and very much on the consumption items of poor households because the interest is on poverty. But rich households consume different things. For rich households actually we might be more interested in income than we are in consumption. That might be much more relevant thing to ask. Of course, rich households are the ones that are least likely to answer the questionnaire, the ones that are least likely to respond. And okay, we find replacement households and even rewite, you're still going to end up underestimating inequality. So on the surveys that we use to measure poverty, really a good source to try to measure inequality. What else might we be able to do? For example, can we use other sources to try to get at some of the top incomes? Kathleen talked about the extreme wealth. On the state of inequality in Africa, well, what can we say? Well, certainly that there are some very high inequality cases. That's clear, around seven outliers. Certainly the low poverty elasticity of growth, no question about that. And that there's a lot of inequality and increasing inequality between countries as well as within countries. Those things, I think, are clear. What is less clear is the trend in inequality. So with the international data, Andrea and Harun were sort of suggesting that maybe inequality might be falling, but actually I'm not sure how robust that actually is. And Kathleen, I think, cautions against drawing any conclusions about that. Everyone agrees that there's a huge diversity in inequality experiences, and that, I think, is the point we should agree on. There's a lot of diversity, there are increases, there are reductions, there are upward U shapes and inverted U shapes and everything. The focus on what are the causes of inequality in Africa I think is really important. Natural resource dependence almost comes as number one. It's a really important issue. And this is not just a matter of how well the natural resources are managed, but swann is often an example of a country which is well managed. It's natural resources. It's still among the seven top countries. Natural resource dependence seems to be associated with high inequality. Lack of structural transformation is almost certainly another part of the story. Maybe the limited progress or the slower progress in post-primary education and all kinds of other things that are there, we want to understand how those things influence the level of inequality. But we shouldn't just be interested in the level of inequality. We should be interested in the changes. We should be interested in the reductions in inequality. Where there's reductions in inequality, what caused that? And also, even before we get there, inequality falls. Is this a sustained change? Or is it just the information you have for the two patterns of time where you actually have data? If you had a bad harvest in one year and a good harvest in another year, inequality could come down, measured inequality could come down, simply because of that. It's not something which can necessarily be extrapolated. Kathleen's inequality of opportunities and Chico and others have worked a lot on this. I think that's a really key factor. And this idea that children are managing to get higher levels of education at their parents and starting to do different jobs from what their parents are doing, I think it's really important. But is this still telling us that inequality of opportunity is falling? Don't we need to know about what's happening among poor households and among richer households? Is this catch-up happening equally everywhere in the distribution or not? And finally, just in terms of some future issues, the point about understanding what data is robust and comparable remains important. Understanding the cause of high inequality and changes in inequality I think is really important. Non-monetary inequality. We talk about poverty being multi-dimensional. Inequality we should also think of as being multi-dimensional as well. Non-monetary inequality is also very important. Now, that's less clear how to do because a lot of our non-monetary measures are often zero-one measures. But there may be ways of doing it, and even with DHS data and asset quintals and so on, we can start to understand some patterns of non-monetary inequality. The inequality of opportunity agenda I think is a really important one and one that's worth taking forward. Thank you very much. Thanks Andy for a clear, comprehensive and brief discussion. Excellent. So this now allows us still to have about 10 minutes or so for questions. Let me start with Professor Eric Thor back here and then I'll take the two at the back. I'll take them in groups of three. Thank you very much for three excellent presentation. My first question is for Catherine and the surveys, whether they're consumption surveys or income surveys, typically do not take into account the imputed value of public benefits received by households. If this were the case, my guess is that it would increase inequality in the sense that some of the non-poor households may receive a larger share of the benefits. So that's another way of looking at inequality. Secondly, when you looked at service deliveries or the quality of education and you had evidence on Uganda, I noticed that it stopped in 1990 and a number of your other graphs also stopped around 1990. And I find it surprising the other day I was trying to get recent evidence on service deliveries in Africa recently and it's extremely difficult to get this kind of information. And it seems to me that maybe the World Bank and AERC might work on doing this. Finally, I do have a question for Harun. You did not mention the structural transformation particularly in terms of what is happening between agriculture and other sectors. And we all know that prior to 2000, the structural transformation in Africa tended to be flawed in the sense that workers moving out of agriculture would end up in jobs that were even less productive in the informal sector. More recent evidence, I've looked at 14 countries, seems to indicate that structural transformation, even though these workers out of agriculture did not go into manufacturing, was much more successful. They would take jobs that were more productive and this is one of the reasons for the high macro growth in Africa. So it seems to me that you might want to say something about this structural transformation. Thank you, Eric. I had two people at the back, the gentleman at the very back and then the second one there. And then we'll do a second round after that. Thank you so much. My question is to Andrea Cornier, but also maybe to all the panellists. The best situation I think everyone would agree on that is that if we have growth which is pro-poor, growth which is accompanied by the reduction of inequalities, but in real life usually it doesn't happen. If not for Africa then for the whole world, usually the growth is accompanied by some increase in inequalities. The case in point is China. You take people out of poverty because of growth but also there is an increase in inequalities so it's like the price to pay for growth. And judging by the data that were shown today in Africa, some fast-growing economies like Mauritius, Botswana, Ghana, maybe South Africa, they also experience the rise in inequalities. So the question is what is the general framework to make a judgment whether it's acceptable and to what extent it's acceptable. There is a UNDP inequality adjusted human development index. What is your attitude to that and what is the framework? How we can discuss it? To what extent this increase in inequality is acceptable as a price for growth? Thank you. Thank you. I've been remiss in not asking people to introduce themselves. So if the next ones could, this is the gentleman there, could introduce yourself and be brief, please, with your question. Yes. Hello. Thank you. My name is Daniel Waldensström, Uppsala, University of Sweden. So I was wondering a little bit about the role of institutions. It was kind of mentioned, but perhaps I would have thought that the role of institutions would have been emphasised a little bit more, especially when it comes to the role of manufacturing and perhaps why we don't see more of that. There are papers showing, for example, papers by Ray Fiesman in Colombia that countries with a high degree of protection of property rights also receive disproportionality much after FDI flows. So overall, the role of institutions, property rights, governance, I think, is more among the deeper drivers of development rather than the more mediating or intermediate drivers such as the manufacturing outcome as such. So that would be interesting to hear more about. Thank you. So I'm not sure we'll have time for a second round, so let me take the lady here who had indicated that she wanted to ask a question now as well, and then we'll go to the panel. Thank you, and thank you for very interesting presentations. My name is Tru Shadwin. I work at CEDA, the Swedish International Development Corporation Agency. My question is very much related to the first question on the patterns of the structured transformation that we're seeing, a movement from agriculture more into services sector than to manufacturing. And I also wanted to just make references to what was discussed this morning in the panel of thinking new and of finding solutions that are suitable in Africa. And I'm thinking my question is, could it be that we underestimate the productivity of the services sector so hence we underestimate the possibility, to the potential of the services sector to play the role that the manufacturing sector has historically played in growing economies and reducing poverty and inequality. Thanks. Thanks. So with that, let's go back to the panel, to comment on the questions that were addressed specifically to each speaker, but also feel free to address more general ones if you like. Let's go in the same order perhaps. Thank you for your comment, Eric. It is correct that our consumption-based inequality measures don't account for the use of publicly provided services like health education, even sanitation. And in my experience, I think intuitively, it would definitely lead to greater inequality, particularly on the spatial dimension, because we know that these services are concentrated in urban areas which already have an advantage. I have to think more about how we can potentially incorporate that into some measurement, because sometimes we have that information in household surveys, and if we can potentially put a price tag on it, we might be able to see how much it affects it. So as I just mentioned, we sometimes have information on to what extent households are using publicly provided services from our household questionnaires, but it's often not very detailed. The World Bank does have an effort to a program called the Service Delivery Indicators Program, which is operating in several countries, more on the quality of the supply side of publicly provided services, so issues like teacher absenteeism, whether or not health workers are giving good information and showing up on time. But it hasn't really linked up to the household survey side, so that's something for us to explore. I'll make one comment not related to my presentation, but a topic close to heart on the last comment from the lady from CEDA. I think one thing that one area on a measurement, on a data side, where we really haven't, I think, figured out what to do is how to unpack the service sector, because I think in most countries in Africa, a huge part of the service sector are very small micro enterprises, and it's quite different than what maybe we think of from a Western perspective on what the service sector is and could be. So I would hope that in another 10 years' time, when there's another wider UNU conference, that we could talk about not the service sector, but type A, type B, type C in Africa and what it means. Thank you. Thanks very much. So in fact, that's right. The first and the last question were both about structural transformation and the extent to which we may have underestimated the role of services. So there's a couple of comments. First, there is a wider project that's just been launched. John Page is not here. He's in the other... It's not the title, but the title of the project that I've warped is growth without smokestacks, which is an attempt to understand whether we can get growth in Africa without manufacturing as its core, as its lifeblood. I think there is a data issue. Certainly from the employment numbers, and say from Kenya and Jogunais here, shows that despite massive growth in financial services, the employment effects are relatively small when you compare it, say, to the urban informal sector type employment. So as an inequality-reducing channel, rather than productivity gains, I think you may get slightly different results. But I agree that there is a really important question about whether you can do development outside of the Roderick view of development, right? So can you get growth in development and inequality and all the good stuff without manufacturing being front and centre? And that, by implication, is the role of services. But just to quickly emphasise what Kathleen has said, I think the data issue... We keep on talking about it, but really it's about things like statistical capacity, the political economy of access, resource allocation. I'll just leave you with one final point in our meeting yesterday. The largest economy in Africa, in Nigeria, cannot give us unit record labour force survey data. And these are researchers who have access to the statistician general and so on, but we cannot get unit record data to count the numbers of people working in Africa's largest economy. Sorry, finally about institutions. I think the two are linked. So you'll find that you need... Chico has done some great thinking around the role of infrastructure and the pausty of infrastructure and why it undermines manufacturing competitiveness. But in addition to that, in order to improve manufacturing competitiveness, property rights, governance, also important. OK, now, first one on the data issue. I think that we really strive. The founder of the World Income and Equality Database of WIDA, which has been updated and so on and so forth. For Africa, there are still some comparability problems like Kathleen mentioned. But the World Bank is still, I think, working on this I2D2 database, which I don't know what it means. But basically they take the microdata for 300... The World Bank is working on this I2D2 database in which they take the single surveys and they try to make a standard statistical assumption for processing this data. So that might reduce the estimation bias. And we have been looking as part of this project to...we have written a paper on the seven sins of inequality measurement in which we mentioned that. Now, this I2D2 data are available only at least to us for, I don't know, 20 or 30 services have been processed. And fortunately, the numbers they came out in 80% or 90% of the cases were very similar to the one which we used. So while we should strive as much as possible to improve the databases, I think we should also rely on theory. And I think that the story is about structural transformation I don't think is in doubt. Why? Because, well, because there's been China's buying a lot of iron ore and petrol and so on and so forth. So these clearly have an equalizing effect. The fact that agriculture has risen in a few countries, unfortunately, not in all countries, this is also out of the doubt. The fact that the human capital and secondary education has risen less than what it has, this is clearly has an equalizing effect. The fact that the population growth goes on at 3% a year, this will have a very strong disequalizing effect. The fact that urbanization has proceeded the way it has with the following manufacturing is not only due to institution, it's due to trade liberalization. I mean, Africa is deindustrialized when the tariff rate has been falling. So this has to do with macroeconomic policy. So that is, there are a number of things which one has to take into account is not strictly related to data to tell the story. And that they seem to be more or less seems to me with all the questions because Francois Bourguignon told me for African Latin America on inequality you cannot say anything. I disagree with him. Now, on Vladimir's, they say, well, when you have growth you always have inequality. Well, I mean, first of all in Africa you have 70% of the population in agriculture and two models. There is the Lewis model, it moves people out of agriculture, they go to a higher productivity sector and then inequality will rise, national inequality will rise. But then there is another model which is called the Runnisfay model, which means you increase yields and incomes in agriculture. And so you reduce the urban rural income gap and then basically start moving people. So this is what happening in Ethiopia. And so I think that in a way there are one or two in Africa which show that it's not unavoidable. I mean, and if you take the Southeast Asian tigers, I mean Taiwan, Singapore, and so on and so forth, and Hong Kong, I mean, they grew very fast with flat inequality. So I think I know that the majority of the cases inequality like China and the Soviet Union and Russia, sorry, they brought that, but it's not God given. Thank you. So let me just say one minute of a few words of conclusion because I'm cognizant of the fact that it's coffee break time. In listening to the, oh, first of all, let me just clarify on I2D2 since Andrea mentioned it and both Kathleen and I worked on I2D2 for a while. And it would have been IIDD, so it's I2D2 and it's International Income Distribution Database. But there are so many IDDs already that we thought we'd use as Harun correctly guessed, a Star Wars analogy, and called it I2D2 in reference to the cute little robot R2D2 that you may remember. But I don't want to end on that note. I do want to end on a grander note, and that is to say that 10 years ago when a number of us were involved in writing this little world development report on equity and development, I had a bit of an exchange with Paul Collier and Stefan Durkin. I think Stefan is around later today, who were telling me, look, for Africa, forget inequality. It's all about growth. And maybe they were right then, maybe they weren't, but I think what this panel highlights today and the fact that there are so many of you here participating is that actually if that was ever right, it's probably no longer right. The relationship between growth and poverty reduction in Africa is created by inequality as it is elsewhere. And there's a lot of need for greater understanding. I think the panelists here have made a huge contribution in beginning to move us along the path towards a better understanding of inequality in Africa. But I cannot help as someone who's also looked at this question in Latin America a lot to feel that in this region there's more work to be done still. We're probably earlier in the process. I think, for example, of Nora Lustig and Luis Felipe Lopez Calva's book, as well as Andrea's other book on inequality in Latin America, which he says is much better. But there is more of a consensus and a little more clarity. Africa, because of the bifurcation, because of the data challenges, because of the differences across the region, presents a much greater analytical challenge. But because of the reasons that I mentioned at the beginning, and others have highlighted as well, to do with the importance, the centrality of Africa for any development goal going forward, including the SDGs that are about to sign. It's fundamental that we make efforts, both on the data and analytical dimensions that have been discussed, so that in the 35th anniversary of wider, we know even more than these panelists have regaled with today. With that, let me thank them very much for their support.