 Thank you very much. So those among you who know me, they know that I've been working on Rwanda for more than 10 years, despite my young age. They also know that I usually work on very specific topics using fancy econometrics and today I will be doing something completely different and I have to give credit to my new colleagues for that. Two years ago I switched universities. I moved from Leuven to Antwerp and there I met colleagues who were also working on Rwanda and they were much less positive about the recent Rwandan success story. They actually had an opinion about the success story and at this point I have to mention that these new colleagues were mostly working with qualitative methods and they were not economists but political scientists and anthropologists and so these interactions with these new colleagues led me to write a paper which is atypical for me, which actually has a broad perspective and in which econometrics is not central to the story or to the argument. So one thing about writing a paper with a broad perspective targeted to a broad audience is that it becomes a very long paper so you can find it online. It counts 70 pages. In 15 minutes I can really not talk about everything in the paper so I will give some snapshots of what I did and some highlights. So I assume that you all know that Rwanda experienced quite rapid growth rates. So in 2005 they actually reached GDP per capita levels similar to the pre-war periods and now GDP per capita stands at 50% higher. They also managed to achieve poverty reduction and inequality reduction especially in the five last years or between the two latest nationwide service, 2005 and 2010. And so this led observers to some excitement. Paul Collier said that Rwanda pulled off a rare hat-trick of rapid growth, sharp poverty reduction and reduced inequality and called this deeply impressive. There's also many studies analyzing the determinants of this economic growth and poverty reduction pointing to the importance of increased use of fertilizer on farm employment, social protection schemes for the poorest and the demographic transition. Others also point to the aspect of governance, arguing that Rwanda manages to keep the worst forms of corruption in check and still others say that the improvements have something to do with post-war catch-up. Now there's also many, many, many studies looking at specific sectors to capture in this success story such as the coffee sector, land market changes, health and education sector and the fertility transition. And I could list many, many more studies because studies on Rwanda have multiplied trying to keep up with the list of policy measures which is growing rapidly which I put here on the timeline. It's not complete and in the paper you find a discussion of each and every important policy measure. I don't have time for this here. But what I do want to discuss in this presentation is some of the questions that remain. Does the recent poverty and inequality reduction represent a true reversal of a trend? How can the data be reconciled with contrasting findings from qualitative fieldwork? Can economic growth continue to outpace population growth? Can development be sustained if the country continues to score very low on voice and accountability? I will mainly focus on the first two questions. But the latter two questions cannot be left untouched. It would be like speaking about recovery of the euro zone without mentioning the euro. So I will briefly say something at the end and in the paper you find a more lengthy discussion. Does the recent poverty and inequality reduction represent a true reversal of a trend? What are the alternative explanations? That the agricultural season in 2010 was better than in 2005, which is also true. That the post-war base was very low and so we observed post-war catch-up. And some of my colleagues and I will explain this better later say that it's a reflection of the cosmetic upgrading of rural life. So to assess whether there's a true reversal in a trend, I looked at five waves of Rwandan DHS data. And of course these data treat with health and education indicators and these are less prone to measurement error or rainfall fluctuations. So here's a snapshot of the indicators we look at. So for 1992, the first wave which is prior to the violent conflicts, 2000, 2005, 2007, 2010, we look at housing, durable assets, health and education. And so we see when these indicators deteriorate, indicated in red here, in which periods they actually improve. And at what point in time they reach their pre-war level or exceed the pre-war level. We also look beyond averages, looking at disparities in these indicators between the lowest and highest wealth quintile. We look when these disparities increase, when they decrease and when inequality, at least according to this measure, falls below the pre-war level of inequality. So more details in the paper but here I would say that the DHS data indicates that there are improvements in health and education and in general there's a pattern of convergence across wealth quintiles. So this is in line with poverty and inequality decline recorded in the nationwide service using consumption data and so data on expenditures. But then my colleagues would say, but what you observe as a result of social engineering, these are cosmetic changes. And they would refer to for instance, a system of fines used for the implementation of measures improving well-being. For instance, parents who refuse to send children to school or fines 10,000 francs. Walking barefooted also costs 10,200 francs, consulting a traditional healer without authorization as well. So my colleague in Antwerp who is an anthropologist, he writes, while these measures are designed to make significant portions of rural dwellers look less poor, they are likely to be and feel as poor or even poorer than before. I think it's quite sensible that if you're fined for consulting a traditional healer that you may go to a health center to give birth. And this is what we observe in the data but at the same time we also see real progress, maternal mortality rates are declining. We can also illustrate this contrast between public and hidden transcripts by looking at fertility. So in 2007 there was a three children campaign conveying the message that three is the ideal number of children. And suddenly we see in the DHS a huge drop in the ideal number of children reported by households. But this is also matched by an actual decrease in fertility. So I would reply to my colleagues, while some changes may be cosmetic, there is also evidence for real improvements in quality of life measures. But then if there are really real improvements, how can the data be reconciled with these contrasting findings from qualitative field work at a local level? There are very experienced researchers in Oanda who go to the fields, who do focus group interviews, who collect life stories and they are extremely critical about the land consolidation policy, crop specialization and imidu gudu, saying that these policies have increased rural poverty and this contrasts a lot with recent figures from nationwide service on rural growth and poverty reduction. So when I talk about this with my colleague, my next door colleague, Phillip Ranjans, who is a political scientist, he says yes, but the quantitative data are wrong. The statistical department is extremely political, so they manipulate the data. And Andy McKay, who is sitting here in the audience, was involved with the implementation and design of the EICV data. He knows what I'm talking about because at the moment that the EICV data came out, Phillip Ranjans called in to come to Antwerp and explain how exactly it is possible that these data show an improvement and he had to explain how actually income and expenditures were measured. And I think Andy succeeded in convincing me that the data are not wrong, but I'm not sure about Phillip, even until this point. So I actually would like to conjecture that it is possible that both the quantitative and the qualitative research is correct and it's possible that they contradict because even if there is progress in some indicators that we can measure objectively with data, it's still possible that people feel more poor because of coercive measures and especially the rapid social transformation which leads to winners and losers. So this led me to a study of mobility and happiness using a small panel data set of Rwanda, using informational households which were interviewed in 2002 and 2008 in the former provinces of Gikongoro and Yitarama. And so we look at income mobility of these households between 2002 and 2008. We find that it's extremely high. We also look at self-reported social categories. We look at social mobility, so self-reported mobility across social categories. And we look at the self-reported reasons for mobility and we also look at happiness. Kenya Rwanda is as difficult to pronounce as Finnish, I'm afraid. So I will read the question in English. Have you recently been feeling reasonably happy all things considered? So we find that this happiness question does not relate to income levels. It relates to land holdings. It is strongly correlated with changes in land ownership and it's also strongly correlated with relative income changes. So even those reporting to be unhappy actually experienced an absolute income change in our data. They made progress but relative to others, less so. So there may be a mismatch between subjective measures of well-being and static measures of material welfare. That's no surprise. But maybe this mismatch is especially severe in the running context in which there are rapid transformative changes that lead to winners and losers and affected traditional land-based livelihoods. So to conclude, I'm going to say something on these transformative changes. Just one or two minutes. You got two and a half. Two and a half, great. So I will drink a bit of water then in these 30 seconds I've left. So Vision 2020 Nwanda states that one of the main objectives is to transform agriculture into a productive, high-value, market-oriented sector with forward linkages to other sectors. This is a very, very sensible policy in a society that's almost entirely agricultural based and has one of the highest, probably the highest population density in Sub-Saharan Africa. At the same time, it actually triggers policies that peasants find difficult to adapt to, such as land consolidation and monocropping. Now, what makes it even more difficult to adapt to these transformative changes is the rapid pace of these changes, but the pace will not slow down. Because even now that fertility has gone down, violence will count more than 20 million in 2050, and population density will rise above 800 inhabitants per square kilometer, which is three times as high as on the eve of the genocide. So subsistence-based agriculture is a dead-end street. Transformative changes are necessary and will bring about grievances because they imply winners and losers. Now, grievances may be higher if these changes are accompanied by coercive measures and if their design and implementation is top-down. This brings us to the Achilles heel of the Robin's success story, voids and accountability, in which there was no progress. And so, although the authoritarian approach is instrumentally bringing about transformative changes, which are necessary and without much overt process, there is a danger that these positive achievements will be undone and certainly if relative winners and losers, and so grievances align with a group identity. Thank you, and I'm squeezing directions for future research.