 comments, questions, suggestions, so let me number one, two, three, four, five, six, so let's start with one. One of your findings has been that high growth is not necessary for inclusiveness, but presumably it is inclusiveness in the presence of growth, which is an interesting phenomenon. If you don't have much growth, then I suppose the digital atom in other words is not only growth but also inclusiveness, but not to have one or the other is not a particularly interesting case for examination in any event. Thank you. There is a remarkable contrast between Senegal and Tanzania in terms of inclusiveness. Is there any particular lesson we can learn from Senegal as to how they achieve that inclusiveness? Second one, in the Tanzanian case, the rest outside city, growth is much higher than the city itself. I'm wondering there is some inconsistency with the incidence curve. Is this because of the bias you were mentioning? Because the data suggests that the growth outside the city is much lower. So most probably it may be the other way around. Thank you. I'd like to make two points. One is that it seems to me that you're using the measurement of growth in terms of money to determine the questions you're asking. But I'm wondering whether in fact what you are measuring is the participation in the money economy. Because as you go farther away from the cities in Africa, people are less and less inclined to use money. They are more inclined to live off the land with their agricultural produce, etc., etc. So although they might not be actually showing high rate of money usage, they are in quite a good state of well-being, for instance. So that's one point. Is it really correct to just measure growth in monetary terms and relate it to all the phenomenon that you're doing? You haven't considered so many other factors. What impact does this growth have on the environment, on the sustainability of the production of agricultural produce or whatever else, and things like that? The other aspect is the case of Tanzania. Now it seems to me that your measurements are after the Ujama policy was abandoned. Now the very nature of the Ujama policy under Julius Nerere was a good, equalized distribution of, shall we say, growth for simplistic terms. And the whole social structure was organized in such a way that this was an attempt was made to bring this about. For example, the head boss of an institution in Tanzania would probably earn almost the same as a lower level worker. And all he could hope for was some privileges which a lower level worker didn't get, privileges which were given to him by the government in terms of a motor car, maybe, and things like that. But essentially the difference between the lower income and the high income person under Ujama was very small, actually. And I have come across highly educated Africans who said they supported Ujama and so on, but I wondered whether they really meant it because it meant, in fact, that they lived at very much lower economic levels than they would have done in Kenya, for example, unless of course they took bribes and they augmented their income with bribery. So therefore you had this situation where the policy was attempting very much at equalizing growth increments to the whole population. But after Ujama it has become a capitalistic system and I don't know what has been the consequence and the result of that. And these are just some comments. Can I come to the presenters and then to respond, I will go back to pick some more. Okay, thank you very much for your questions. In fact, we considered the first question about whether the high growth that we observe may actually lead to increasedness. I think that was the question. In fact, what we are doing here is that we know that when we are talking about growth increases, we may consider several other factors that may actually come into play. But here we only focus on expenditure and we know that this may be limitations of the way in which we can assess the impact of growth on income, for instance. So here, for instance, we are not using income. That will be the best way to measure the increase for growth. But here we only focus on expenditure so that we cannot really say whether the high growth that we observe in Tanzania, for instance, have been really increasing, have been really increasing. We respect to all dimensions. We only say that it has not been increasing in Tanzania with respect to the expenditure dimension. That's what we are saying. And so we regard in Senegal. We know that in Senegal, it may be about political stability or something like that. Because we see that in Senegal, actually, everything works pretty well because the growth rate of expenditure was much similar across the same type of expenditure or across a place of residence, which is not the case in Tanzania. But if we take the case of Senegal, actually, it has experienced political stability and so on. But in Tanzania, I may say that it was not exactly as in Senegal. So maybe political economy may be an argument or an explanation for this difference that we have seen between Senegal and Tanzania. Of course, there might be other reasons, but we didn't really look into the detail of the causes of the difference between the two countries. And regarding the bias that may be introduced by migration from the rest of the country to the capital city, in fact, we look into the news to check whether there have been some massive migration of poor workers, for instance, from the rural areas to the capital city in those countries where we did not find any evidence of this kind of huge migration toward the city. So that's why we consider that even if our resolve may be biased by this kind of issue, it may not be so much significant, but we continue to investigate this issue further. Now the last question was about, no, it was comments, actually. So we welcome the comments, and I think, even if my colleague wants to add something to this question, otherwise we can proceed. So let's take another round of questions. One quick comment I had was that it might be interesting to look at this growth incidence curve at the sub-regional level, which can be easily done with surveys. And then you can relate that to the structure of regional domestic product or whatever. Right now you are comparing just only a few observations. By doing that, you may be able to draw stronger conclusions about the relationship between inclusiveness and growth rate, and the proper growth and regional GDP structure. Thank you. Number five. Thanks very much. Thanks very much for a very interesting paper too. Two quick questions. Can you just repeat your opening statement about the decline of poverty in Africa? It seemed to be much larger than what you were suggesting afterwards, but it went very quickly. The second thing, can you say, and I wouldn't have thought that one of your extensions would be to replicate this analysis for other countries. I think for me what's much more interesting is to figure out what happened in those countries, but particularly, I think it's Cameroon. Sorry, I just lost the Cameroon where you see this reversal and an incredible increase in pro-povertyness, if you like. One wants to know why that happened, whether that's sustainable, so that's not an eye-draw question. But I would be much more interested to find more about the details, and perhaps you can answer that question in the case of Cameroon. Thank you. Number six. Thank you. I had a question on the migration issue as well, but you addressed that, so I'll try a different one. I was a bit surprised because in the introduction you were talking about basically urban areas and rural areas, as far as I understood. But in your analysis, you only look at the capital city and rest of the country, so just a question whether you try to do robustness checks, let's say, with secondary cities and rural areas, or just urban municipal and rural areas, to see whether that makes a difference in your results. Thank you. Number seven here, please. And then eight here first, please. I think that the gentleman is ready. So my question is not well. Please welcome. So I think that the second question already raised the point. And it could be consistent. On one side you have, I forgot whether it was Cameroon or Tanzania, that basically the aggregate growth incidence curve is regressive. At the same time you have that rural incomes, which are normally poorer than urban incomes, they rise much faster. Now, the total inequality in consumption or income or whatever you want is basically basically decomposed as the urban rural consumption gap plus the genie within rural plus the genie within urban. So on the one side you showed us that the rural urban gap fell, which means it should be more equalizing. But then you showed us a growth incidence curve, which is regressive. And that may be explainable if within rural and within urban distribution of consumption there wasn't. But on the face of it, the information you provide us all suggests that the growth incidence curve for Tanzania is not like this, but it's like this. So you have to explain why the growth incidence curve is regressive and at the same time the urban rural gap is falling. But not the least. So I just would like that you comment a bit this major policies. What are the differences you really found? Because in your paper you also, you know, you compared what kind of monetary, fiscal and infrastructural policies these countries have had. It would be interesting to know, for example in case of Tanzania, I guess they have somehow anyhow worked and growth has been there. And then a structure of industries, for example. It would be in the future good to speak about sustainable growth. For example, tobacco industries producing or tobacco growing is very much affecting natural forests. So there are implications for growth. So in the future it might be good also to look into those ones a bit, as you also mentioned. Thank you. Okay, thank you. We have to stop here. We have five comments and questions. Can you do that in two minutes? I'll be very happy. We need to move on to the next section. Okay, one suggestion was to maybe look at the relationship between local production and the increasing effort of growth along the place of residence. Actually we did not have the data on local production so we could not look into that matter. But we do agree that it is a relevant question. So if we happen to have the data, we will look at this issue. Okay. And the reason why growth has been inclusive in Cameroon, Actually we did not investigate this issue. I think it may be interesting to see exactly why we have increasing growth in Cameroon. Actually it was a surprising result for us as well because we were expecting the reverse. But the reverse happened in Tanzania actually where growth is much higher than in Cameroon. So yes, we agree that it might be interesting to do much more detail analysis on Cameroon. Fortunately we have micro data on Cameroon so we may look into the detail of this issue. About the rural business check, in fact the composition or even the geographical limitation of rural and urban area evolves over a period. So that's what we want to avoid by using the capital city with respect to the rest of the country. So we did not check the business of our result with respect to the rural and urban composition. Because we know that it may be very really biased only due to the change in the scope of the rural area or the urban area. But actually we agree that it's a relevant question that we will address in the rest of the study. So there is a question about how we can explain the non-increasingness of growth in Tanzania. And the fact that growth has increased more in the rural area in Tanzania with respect to the capital. I think that it's a point that we need to investigate more. I do not want to give a right away an answer here. And the comments about the impact of environmental damage and so on. I think that it is an issue that we have to work on but we do not have the data right now to see how those environmental damage could affect the increase of growth specifically in rural areas. I think that this is an issue. Thank you very much. Shall we give them another round of applause? Do you have some comments on discussions? Can I see by hand any comments, questions to Mario and the paper? Thank you. Generally we accept that poor people produce larger families than rich people. Even in the developing world I would say. And so I'm just wondering to what extent your various formulas introduced this whole in a way problem. Because while you have a poor growth that very often is just divided by the greater number of individuals among the poor. And so they apparently seem to be at the same low level because they have to share the growth among more people. So somehow it seems to me that this tendency for favoring growth among poor should be accompanied by population growth control of some form or another. And environmental protection for sustainable growth and stability. And I can go on but those are the two important things. Thank you. Any other comments, questions? Great. I'm wondering we speak about poor but you know there are very vulnerable groups. You know this gender issue, children, youth and handicapped. So when we only speak about poor as one group it's a bit dangerous. Thank you for this interesting paper. If I understand correctly I would need to absorb it a little more. Because the standard way growth is poor is if the reduction of poverty due to declining inequality is bigger than zero. I think is what you said. I don't use that definition because then you have the problem of how you measure inequality. I see. Because it's distributional changes in the poverty gap that's all right there. Okay. Because otherwise the normal approach would be to use the bourguignon's decomposition. We should take a change in poverty and this is partly due to growth and partly due to changes in inequality plus an interaction time. So that already tells you a little bit how much growth is poor or not poor. But if I understand correctly you are now looking at the poverty gap which gives you more information because it tells you also the intensity not only the frequency of poverty. So the value added is that you not only tells us how much but how deep. Is that correct? Yes. The household sizes are taken into account here because this is per capita income. So you would have the income from the household and then you would have the number of people so you divide. What I'm dealing with is that's on the paper but I didn't want to bore you with this here but this is income poverty. So it's very restricted. Unidimensional approach to poverty. There are many more. But that only claims that when it comes to poverty we could actually have an operational definition of propuners. I'm not saying it's the best one or the only one but at least it's one that I can measure. That's the idea. And commenting on your comments that's precisely what I think that this can give. Because what it looks is that the distributional changes in the poverty gap. That gives you an idea very much of if changes in the distribution actually made something for the poor. Obviously you need growth. I mean in Honduras with these poverty lines if I made only distribution. So if you look at the per capita income was below the poverty line for the country. It depends on the poverty line. But it was a clerk poverty lines. And then I wouldn't be pushing for a distribution without growth where everybody then becomes poor. But I think it's a good indication at least to say if you want to focus on the poor then at least we could have some target in terms of distribution or at least some evaluation of how it is progressing. Obviously then the next question is okay with what policies and I'm not getting into that. Okay. Any more? Shall we give him another round of applause? Thank you very much. Yes very interesting and it's nice to see this technical action challenge because they are mostly there for technical convenience. The scale invariance and translation and variance and so on. And one could think that perhaps an approach in that case if we don't know what kind of invariance we should impose on an index would be to look at a range of indices and to see if there is some agreement with these indices. Some of them would be scale invariance. Some of them would be a translation of variance. Perhaps intermediate indices. But isn't there a difficulty with this kind of approach when we look at growth? Is it possible to, what are the kind of growth pattern which would deliver simultaneously includes this net for all kind of indices? Is it possible to have a growth pattern like that? Or is there some logical contradiction in wanting to try to have a growth pattern which would be inclusive for all kind of intermediates? A pattern in what? Of growth. Is it logically consistent to try to have growth which would be inclusive for all kind of inequality indices? Whether there are scale invariance, translation invariance and so on. Or is there a difficulty there? What do you think? It's just an opinion. I need your opinion. Society is found at different levels of... At least my hearing is a little defective. Thank you. My question is an opinion. I need your opinion. Different societies found at different levels of development. For countries, countries in the north are highly developed and countries in the south are less developed and in Africa much less developed. What is the relevance and the importance of poor growth or inclusive growth for these countries which found at different levels of development? For which level of countries this development strategy is more important from your opinion? Thank you. I don't know if it's a question or a comment. Obviously, looking at changes in the distribution, you are right that if you look at relative indices like the Gini, what you're looking at is whether who is growing faster than who or the relative growth of the different groups. I think it would be interesting to distinguish between whether a distribution of a given income in one year is unequal, which it is, in every year it is unequal, or whether the changes have been in equality reducing or not. In this sense, I think it makes sense to talk of inclusiveness even if the reach or the non-poor are absorbing much more in absolute terms. Also from a policy perspective, not only policy but practical perspective, you could really not operationalize and go, from now on everybody earns the same. So that's why I think it keeps making a lot of sense to think of how the change it is. Does the change improve the distribution in comparison to the last time? That may make sense to call inclusive or in equality reducing. Can I stick to answer before I go too many more? I can handle only so many at a time. Your question was on whether it is possible to prescribe logically some pattern of growth which would be compatible with one's notion of inclusiveness. Is that right? In essence, if you open the meaning of inclusiveness to a broad set of indicators like that, are you going to remain with anything? Can we agree on this working definition of inclusiveness or at least non-exclusiveness which is that your chosen measure of inequality ought not to change over time. Now that's a fairly undemanding requirement and I do not see that it is logically particularly exceptional. You're saying that a given pattern of growth is one which is non-exclusionary if it ensures that inequality however defined has remained roughly unchanged over time. Now the larger question of the precise pattern which will ensure this will depend upon the sort of inequality measure that you favor and that's what my discussion has been about. I have argued against the use of either purely relative or purely absolute measures and argued instead for an intermediate index. You can have different levels of intermediateness which reflect your own values. I'll come to that in a moment. But if we are agreed on that then the only question left to answer is to verify whether your chosen and reasonably well justified measure of inequality has remained roughly stationary over time. That's the best I can do in a hurry because I'm not sure that I've otherwise understood your question but this is in response to your question as I have understood it. The other question was on allowing for the possibility that you have different countries at different levels of development which in the context of the money metric that we are employing would simply translate itself into different levels of mean income. So that's what you have in mind. And my whole point is precisely this. When you use a relative measure of inequality, those levels become irrelevant. But when you use an absolute measure that become wholly relevant and perhaps much more so than they ought to be. Which again is the reason why one goes in for an intermediate measure to ensure that levels do matter but not overwhelmingly. Your question about changes being what matter rather than simply taking snapshot images. As a matter of fact that particular concern is already actually incorporated in the way in which you define your intermediate measure. Because you see the standard scale and translation invariance requirements are predicated on an answer to the question of what happens when the size of the pie increases. How is the addition actually apportioned? If the addition is apportioned in the same way in which the present distribution is apportioned then according to a relative measure inequality remains unchanged. But if the addition is equally divided in absolute amounts among the contenders for that then inequality in an absolute view remains unchanged. Now what an intermediate measure of inequality effectively does and this was a very good insight of yours is to ask the following question. Let us say that an intermediate measure of inequality is one which seeks invariance in the value of the inequality measure and the certain part of it of the increment of the change is distributed in the same proportion which now obtains and a certain part in equal amounts. The Critschia index for example is entirely based on an answer to this question so it answers this question with respect to every incremental dollar of growth that happens. So if you want to be a proper centress then you can say one half of the incremental income ought to be distributed along the lines in which it is distributed now and one half in terms of an equal division of the proceeds of growth. Then you use that income as a reference point and repeat the same exercise for the next incremental rupee and so on and if you're able to visualize that what you will obtain is a locus of points of invariance which describe a parabola. This is a non-linear locus with a little more time that would be much more transparently obvious but you also have linear paths which have been employed in the literature. So yes your insight is a very good one and the short answer to your question is that it is indeed increments or changes which are taken into account in answering that question. Hello Nadia Von Jacoby from University of Pavia. Thank you very much, very interesting presentation. I had a very brief question which was really just to ask you if you could write the name of the index that you proposed as an intermediate index that you found. It's much easier to write it than to say it because it's a word without a vowel. And once, what was a bit confused or what first name was not seriously problematic? Yeah, I'm just wondering in view of the three options that you've been mentioning in terms of distributing the income, the increased income. I'm just wondering how in practice this can be done actually because some of the increased income is given to communal advantages like better water supply, sewage and so on, roads whatever and the other part might go in the form of actual money in hand to the families. Now how easy is it to implement the middle way concept that you are proposing? Well that's not a hard question to answer because you see what I'm dealing with is a money metric measure of inequality. I'm performing this entire exercise on the assumption that it makes sense to use a metric such as income or consumption, expenditure or wealth as a legitimate dimension in which to work out inequalities. So all of my analysis is subject to that assumption. Now of course the straightforward answer to that question is this is an extremely inadequate measure but given the fact that you're dealing with an inadequate metric already in any event all I'm saying is that there is a case for dealing with that metric more rather than less reasonably. That's the simple message of my paper. But yes, I sympathize with your problem. There's nothing very much one can do about it. I think with that if there's none other we come to the end of the session. Shall we give a round of applause to Sir Ghanani? I don't have time to summarize all the presentations but I think the key message I get from George's presentation is that high growth is not necessary for inclusiveness. And then from the second presenter we know that growth is necessary but not sufficient to reduce poverty. Finally we've been exposed to a centralized measure of inequality rather than absolute or relative. I want us to give a round of applause to ourselves and then we go for lunch at the restaurant Marine. Shall we clap for ourselves? Thank you very much. Excellent presentation. Thank you.