 I am very happy to be here to present one of my PhD students' PhD thesis work. This work is co-written with Christophe Axol, Kim Lerer and William Sate, and we work on the internal migration decision of educated youth in Ghana. So we heard a lot of international migration, but internal migration is a relevant question for the development economy, and it's a real phenomenon. The world bank is estimated to 11% of the world population who lived in their birth country but outside of their birth region. So we consider it as internal migration, and in Africa it's over 12% of the population, of the African population. So it's quite a relevant phenomenon. And in this work we are wondering what are the characteristics of educated youth who migrate between regions in Ghana. Then we ask what part of the economic opportunity to play in the internal migration decision in Ghana, and if income or unemployment differences between regions would drive the internal migration. So if we look on the literature, there is some paper about consequences of internal migration in Ghana. Some of them are looking for the consequences for the migrants, and some of them are looking for the household, but both are finding that migration raised the well-being, the well-being of migrants or the well-being of the household stayed at origin. And if we look in particular on internal migration and labor markets, there are some fewer papers. The one, the key paper, Theoretical or Lewis in 1954, and a recent one. And some recent empirical papers focus on China, on the internal migration in China, and there is a lack in the literature on internal migration in Africa and in Ghana. We found one interesting paper from Tegai, but he's focusing on the Volta region. So it's a paper who finds that income difference between migrants and non-migrants are a factor of internal migration, but in our paper we will look in the world of Ghana. So this is a difference. And we will try to fill the gap in the literature on internal migration and labor markets in Ghana. We will bring an overview of use-internal migration, use-educated, and another contribution is to adapt the choice model to internal migration, who has never been done. And we bring another contribution with our database we collected in Ghana several years ago. So our main database is the one we collected in 2000. So it's a panel survey and we are using the two first waves in 2010 and 2012. We are following some students of senior high school and we interview around 3,000 youth to understand what are the drivers of the migration choice. And here we consider as a migration a person who is currently living in a region with different than them the birth region and the SHS region, the senior high school region. So here you have some descriptive statistics. We can see in general that there are more male in our sample and there is like over 20% of the population who studied who has migrated after the senior high school. So it's quite important and a majority of them are born in rural area. We are using an additional database, the Ghana Living Standards Survey from Statistics Ghana and the World Bank. We are using the fifth waves conducted in 2005. We are using this additional database to have information about average income and average unemployment rate by region. So we calculated this ratio and then we are using this ratio to estimate the driver of the migration. I don't know if you can look, but on this graph, on this graphic we can see the two main regions were attractive. So it's Ashanti, the first region here, and Greater Aqours with quite obvious because it's a capital. And the other eight regions are more thunder of migrants than welcomeers. In this graphic we can see the positive relationship between income, the average income by region and migration rates. Some quite driven by Greater Aqours, but even if we don't take into account Greater Aqours, the relationship is still some positive. The model we are using is a McFadden choice model to understand how the migrants are choosing one region compared to another one. And we adapted this model to the migration issues. Then we are looking both the original characteristics and the individual characteristics. I will not enter into the detail of this model, but just an overview of the assumption. So we assume that a rational individual assesses the characteristics of each region with his own criteria, then he will choose the region that maximizes utility. And we estimated this model with a mixed logit. So the UIG here is the probability to choose one region compared to another one. And the ratio is the ratio of income or the ratio of unemployment between each region of Ghana. So we have created this ratio for each region and we are comparing the difference between each region between unemployment and income. Maybe it's too little, I don't know. But these are the main results. So the first part of the table is the ratio. So these are the income ratio. The two first columns are the ratio of birth region compared to destination region. And the second one is AHS region compared to the destination region. The two other columns are the same thing but for a restricted sample of educated youth Ghanaian. So the two first columns are the whole sample and the two other columns are the restricted sample. And the other part of the table is the specific characteristic, so individual and AHS senior high school characteristic for each region. So we are comparing the probability to choose the AHS region to the probability to choose the central region and we are doing that for each region. So I show here just the AHS region but we have the same result for each region. And what we found here is the income ratio, the difference between the income in origin region is higher, the probability of migrates will decrease. So people are attracted by the income and the higher income in the other region. If we look the individual characteristics, we can see that being born in a rural region has a negative effect to the probability of migrating to Ashantian greater aqua but this born rural person will more migrate in Volta which is a poorer region. And about the sex, being a man has the same positive effect almost on every region. And we can see that the older youth has a positive effect for just three regions. So all these results are compared to migrating to the region central. If we look on the senior high school characteristic, we show here that the network of migrants has a negative impact on the probability to migrate in Ashantian greater aqua and the distance between the AHS and aqua has a positive effect on migrating in Ashantian but a negative one on the probability to migrate in eastern. In the second table, we estimated the income and unemployment ratio. So we can compare the effect of differences in income and differences in employment between the region and it's just another form of presentation but I present here just the result for the whole sample and the difference between AHS region and destination region. And we can see here that the negative effect for the income ratio is still persisting but we can compare the effect of unemployment ratio and we can see that the income differences have a higher effect than the unemployment ratio. So people are more attracted by the differences in income than the differences in unemployment ratio between the different regions in Ghana. So to conclude, how results show that the women and the rural born youth have less access to internal migration in Ghana. The young educated Ghanaian migrates inside of their country hoping for better income than where they were living and income differences are more taken into consideration by use than unemployment differences between region and Ghana. In terms of policy advice, these results can show that we need to develop rural regions and increase women's opportunity and the rural regions have to offer attractive incomes to young educated Ghanaian inside of their region. Thank you.