 I'm George Vizier from the Paris School of Economics. I will be presenting this study with my colleague, Clara Champagne, from the NSIS in Israel. And this morning, we're going to present you the results of a study that we have been conducting in the project, Increasing Growth, run by the think tank, in partnership with the Paris School of Economics. So, just motivation for this study. In fact, we have seen that over the past decade, Africa has witnessed stable and high economic growth. But in the meantime, there is a very weak decline in poverty. So, these two facts contrast with what we can see in other regions of the world, like China and India, where the significant economic growth there has been followed by a massive reduction in poverty. So, from this point, there have been a lot of reasons that have been put forward in order to explain this proposal, among which the lack of increasing growth. And here, we're not going to deal with the explanation of this proposal, but rather with the identification of relevant policies that may be conducive to increasing growth. And so, that's why we studied the incidence of growth in three countries, namely Cameroon, Senegal and Tanzania, which have different growth performance. And we try to identify just some relationship between growth performance and growth inclusiveness. So, let me give you a quick view of the literature. So, what we are dealing with here is a part of the distribution or incidence of growth. And actually, the concept of increasing growth is a result of a significant rethinking of the relationship between growth inequality and poverty. So, we know the older view about the Kuznet hypothesis, which are finally being consistent with empirical evidence. For instance, if we consider the relationship between growth and poverty reduction in Asia. And then, from this fact, emerged a new concept about pro-poor growth, which is pioneered by Ravalion and his co-authors. And now, in fact, currently, we have a new concept which has emerged, which is the subject of this conference actually, which is increasing growth. And this view advocates the fact that we should focus on all groups of the society instead of just the poor if we want to deal with the incidence of growth. So, there have been several definitions of increasing growth. And also, but actually we have a few measurements, Abito and Makinli, which propose for the first, the elasticity of growth with respect to poverty as a measure of increasing growth. And Makinli, which suggests an index of increasing growth in his 2010 article. And we also have another issue about increasing growth, which is the comparison across time and countries. And with that respect, we have the work by Bouguillon, his article 2011, which deals with this issue. So, our contribution to that literature will be twofold. First one, we are going to extend the definition and measurement of increasing growth proposing the literature to specific dimensions such as a place of residence, gender, generation and level of education. And secondly, we are going to provide an insight into increasing growth policy at the macro level. So, in terms of definition and measurement, what we retain in this study is the one, the definition proposed by Claisenin, which states that growth is inclusive if it benefits to all parts and all groups in the society. And then we consider the fact that increasing growth may have several dimensions. We may think of increasing growth in terms of the distribution of expenditure or income, but actually if you want to talk about a real policy, you may be interested in a specific dimension along which growth might be inclusive, such as a generation, place of residence, or level of education, or even gender. Here we take a qualitative measurement of increasing growth, so we consider growth to be inclusive when we have the growth incidence curve, which is downward sloping actually, and the reverse hold when the growth incidence curve is upward sloping. So here, the main dimension of increasing growth that we consider here is expenditure distribution through the center of the distribution, and we add a specific dimension which is the place of residence where we split the country between those households living in the capital city and those living outside the city. So our data is drawn from two sources. We have macroeconomic data and also micro data from nationally representative households survey from Cameroon Stalingrad in Tanzania. And also our measurement of expenditure actually, first I want to emphasize that we would like to use data on income, but in fact those data are not always available and those who are available are not actually reliable in terms of statistics. And so we focus on expenditure, and here we compute the adult equivalence real annual household expenditure in dollar PPP in order to ensure cross-country comparison. And we are using the 4.0 adult equivalence scale because it accounts for both gender and age in its definition. So our methodology relies on the one proposed by Chen and Raovalio about the way in which we can compute or we can draw the growth incidence curve and we extend this definition to the specific dimension that I was talking about here, place of residence. So we extend the definition of the measurement of increasing growth to this new dimension. So here just to give you some summary statistics about the three countries we see here that Cameroon and Tanzania have experienced relatively stable growth unlike Senegal and growth was much higher in Tanzania during the period of our study than in the other countries. So in terms of GDP structure what we can see here that in Cameroon manufacture is much more important than in the other three countries whereas in Senegal what we have actually here we do not give the detail but they will come in another table and in Senegal what we have is tourism, construction and fishing activity which are much more dominant in this country and in Tanzania the agricultural sector is still important related to the other two countries. And so here just some statistics about the expenditure variable what we can see here is that overall there is an increase in average expenditure in the three countries which actually we will see with respect to the distribution of expenditure or with respect to the place of residence what happened and I will leave the floor to my colleague Lera Champagne to present the rest of this. So at first let's look at the growth incidence curve to observe growth inclusiveness along the expenditure dimension. So on the x-axis are the centiles and on the y-axis we calculated the yearly percentage change in household expenditures. For growth to be inclusive the spending of the lower centiles have to increase more than the spending of the upper ones. As we can see in the case of Cameroon the lower centiles experience more growth than the upmost especially for the second time period from 2001 to 2006. So therefore we can conclude that growth has been inclusive in Cameroon for both time periods. On the other hand in Senegal growth has been almost homogeneous along the expenditure distribution. We even have a smaller growth for the lower centiles during the second time period displayed here the upper dashed line. That means we have no just moderate growth inclusiveness in Senegal. And the situation is even more extreme in Tanzania. We only have in Tanzania the data for one time period which is more recent than our data for the other two countries. But we can observe that in Tanzania the poorest centiles had a decrease in expenditures whereas the upper ones experienced up to 6% growth per year. Therefore we conclude that growth has not at all been inclusive in Tanzania. Now let's move to the area dimension. When we compare the average expenditure level in the capital with the rest of the country the expenditure of far higher in the capital so for growth to be inclusive they have to increase more in the rest of the country than in the capital. And now you can see on the x-axis the two regions capital and rest of the country for two time periods for Cameroon and Senegal and one time period for Tanzania. And again on the y-axis are the yearly percentage change in the average household expenditure. In the first time period we observe an increase in the gap between the capital and the rest of the country. For Cameroon the expenditure in the capital grew 2.5% faster than in the rest of the country during this period and in Senegal the expenditure grew 0.5% faster than in the rest of the country. But for the most recent time period we can recall the fact that for all three countries growth has been inclusive. In particular we observe that the growth has been far more important in the capital than in the rest of the country the cases of Cameroon and Tanzania. In Cameroon the expenditures in the rest of the country grew 5% while they grew only less than 1% in the capital and in Tanzania the expenditure grew more than 2.5% in the rest of the country against 0.5% in the capital. Therefore for this time period growth has been inclusive along presses of residents in these countries. One may argue that our results are biased by migrations because in fact poor people might move from the rest of the country to the capital between surveys created an increase in the expenditure in the rest of the country independent of growth. But this phenomenon cannot explain the increase in the gap in the first time period, the increase in favor of the capital. And this is particularly relevant in Cameroon where growth has been stable over both time periods. This table gives an overview of our results. The first line shows the characteristics of the GDP in terms of importance of growth, stability of growth and composition of the GDP. And the second line shows our finding on the inclusiveness of growth for the three countries. For example, growth has been inclusive in Cameroon both along the expenditure distribution and places of residence for the second period. And by linking the results we can draw three conclusions. Firstly, the inclusiveness of growth does not depend on the magnitude of growth. In fact Cameroon experienced low GDP growth but at the same time strong inclusiveness along the expenditure distribution. Secondly, the two countries with stable GDP growth namely Cameroon and Tanzania experienced inclusive growth of places of residence. And finally, the three countries have different GDP composition and they do not experience growth inclusiveness along the same dimension. So to conclude, high growth is not necessary for inclusiveness according to our results. And moreover, two relevant questions emerge. Is there a relationship between growth stability and inclusiveness across places of residence as we observed in both Cameroon and Tanzania? And does the dimension along which growth is inclusive depend on the structure of the GDP? If this is the case then policymakers wanting to promote inclusiveness have to take GDP composition into consideration. We've targeted several objectives to further develop our project. Our result may be dependent on our qualitative measure of inclusive growth. So we want to build a quantitative measure for the inclusiveness. Second, we want to study the effects of growth on the level of expenditure of the population but we need to know how this increase in expenditure can be linked to the social well-being of the individual. And for studying this we will rely on the work of Bourguignon. We also want to add additional dimensions for this study such as generations, gender and level of education. And for this we need to extend the analysis to the individual level. And finally, in order to identify more robust stylist facts we need to replicate this analysis for other countries. Thank you for your attention.