1 00:00:00,420 --> 00:00:03,630 So I'd like to give the floor to Robert. 2 00:00:03,930 --> 00:00:10,760 He's research director and associate professor at on campus, which is based in the anthropology department. 3 00:00:10,770 --> 00:00:18,750 But he's also the director of the very brand new Dphil in Migration Studies, which will start to run in the coming academic year, 4 00:00:19,110 --> 00:00:26,790 which is also interdisciplinary across development studies, anthropology and potentially in future, also other disciplines. 5 00:00:27,330 --> 00:00:31,500 And he's also a member of some kind of college. So thank you very much. 6 00:00:32,010 --> 00:00:34,950 Thank you for your invitation to speak to us. 7 00:00:34,950 --> 00:00:44,940 I mean, I think the seminar, this particular piece of research is part of a bigger project on the impacts of forced migration, 8 00:00:45,270 --> 00:00:55,290 on the impact of hosting refugees. Refugees Returning Home is a project that ran from about 2013 to 2016, 9 00:00:55,290 --> 00:01:03,900 and it was funded by different as part of the growth and labour market income program and is doing work with is about race. 10 00:01:04,740 --> 00:01:14,250 Now in order to to set the stage first of all, once you have every guest in one place you're talking about long term solution. 11 00:01:14,550 --> 00:01:16,170 There are three things that you can do with them. 12 00:01:16,650 --> 00:01:26,130 You can integrate them locally and for the most part, focus on one that you don't want to be is to say you can be the result of them. 13 00:01:26,160 --> 00:01:31,830 Economic policy can send them to a third country. And of course, that means depending on third conflicts, you know, 14 00:01:31,830 --> 00:01:37,290 the biggest resettlement program is a that is dates and obviously going to trial has reduced significantly. 15 00:01:37,500 --> 00:01:40,559 And the third option, which is where we put in primary law, 16 00:01:40,560 --> 00:01:46,080 because it would be the one preferred by everyone, is that you should do coverage on refugees back off. 17 00:01:46,080 --> 00:01:50,730 So driven by the issue and this is a one which we're going to explore. 18 00:01:51,720 --> 00:01:56,760 And when we started thinking of all of these, the first thing that came to mind was just look at the I mean, 19 00:01:56,910 --> 00:02:01,890 there's a lot of evidence on the return migration return after about what happens when people go back off. 20 00:02:02,460 --> 00:02:09,060 And for the most part, it's very good news. So migrants in general, they go back home, they have knowledge of new markets. 21 00:02:09,510 --> 00:02:13,890 They might have learning about new business strategies, techniques of production. 22 00:02:14,220 --> 00:02:17,310 They might gain some skills in their language. 23 00:02:17,970 --> 00:02:21,570 Now you have transnational curriculums because they have been living in another country. 24 00:02:22,680 --> 00:02:28,680 And most of these resources say that they're more likely to return or they have more likely to bring innovation. 25 00:02:29,150 --> 00:02:32,910 There's something going for economic data, topic zero support for democracy. 26 00:02:33,150 --> 00:02:41,100 All of these things then think is with the return of maybe so substantial evidence of these positive effects. 27 00:02:41,940 --> 00:02:45,630 Now in the displacement context then is different. 28 00:02:45,840 --> 00:02:52,950 So that that is that these are areas where some of the displacement bottlenecks is they made for one of the start. 29 00:02:52,950 --> 00:03:02,550 I mean a lot of these people when they are in your country, they have four sections of labour market access or mobility waiting camps. 30 00:03:02,820 --> 00:03:07,770 So the idea they're going to acquire some new skills I going to bring home is not there. 31 00:03:07,770 --> 00:03:14,459 So that possibility is not there. And return is often disorganised, it's often seldom so, sometimes just the three things. 32 00:03:14,460 --> 00:03:23,040 So that's just one of these aspects. Obviously they're affecting returning to countries are having affected by conflict and may not be prepared. 33 00:03:23,520 --> 00:03:31,020 So population increase resulting from preterm flows might lead to competition for spare resources, 34 00:03:31,320 --> 00:03:35,850 social support allowed and therefore to have incentives before. 35 00:03:35,850 --> 00:03:40,170 So people might also look at the risk. Going back home might cause these problems. 36 00:03:40,830 --> 00:03:46,710 But this is something that hasn't been quantified. So one of the things that we have knowledge to quantify often what you can eat is is true. 37 00:03:47,040 --> 00:03:50,550 How long does it take to have some home births? 38 00:03:53,230 --> 00:04:00,060 I know what to keep in mind is that Richter You can have a lot of people returning home every year. 39 00:04:00,510 --> 00:04:10,049 So this is just we collected the five year period. So you take, for instance, that we know 1990, 1994, about 8 million people return home. 40 00:04:10,050 --> 00:04:13,080 I forget how immediate refugees return home. 41 00:04:13,320 --> 00:04:17,820 That has been decreasing over time because protracted displacement has been increasing. 42 00:04:17,820 --> 00:04:26,240 But if you hear those questions about Syria and some of these conflicts, a lot of the discussion is about when can we send refugees back home? 43 00:04:27,150 --> 00:04:33,330 I and if you think about countries from countries Afghanistan do not into some big of Rwanda, 44 00:04:33,690 --> 00:04:37,410 Sudan and of course these countries deferring the population size. 45 00:04:37,830 --> 00:04:45,810 But at some point these countries receive over 350,000 people by refugees back in a single year. 46 00:04:48,660 --> 00:04:57,540 And the one thing that we got going in the past, we have explored the consequences of return for returnees, and most of the evidence is based on that. 47 00:04:57,540 --> 00:05:01,560 So if I had a refugee. Abroad and the personal returns home. 48 00:05:01,580 --> 00:05:06,410 Most of the evidence is about comparing that individual to the people who actually stay. 49 00:05:06,680 --> 00:05:10,450 But what happens to those communities of origin that are receiving the revenues? 50 00:05:10,800 --> 00:05:15,740 Thus let's explore and that is what we are going to be doing in the project. 51 00:05:16,730 --> 00:05:26,720 So we are going to look at the case of a brewery. It is a company that experienced large scale outflow of migration and large repatriation. 52 00:05:27,110 --> 00:05:33,860 We happen to be doing the data that we have collected in the country and we are going to focus on those state houses, 53 00:05:33,860 --> 00:05:37,740 those who never left the country. And they may be more technical. 54 00:05:37,760 --> 00:05:46,010 They will be able to use what I call features of the community of origin in order to to do our statistical analysis for litigation purposes. 55 00:05:48,800 --> 00:05:56,220 Now let me give you some background on the case study. So with all the experience, a major conflict in 1993. 56 00:05:57,570 --> 00:06:06,900 He has some of the same features of the Rwanda conflict but have different but essentially tensions between Hutus and Tutsis. 57 00:06:08,160 --> 00:06:14,190 And when that conflict happened in 1983, about 10% of the population of Washington nationally displaced. 58 00:06:14,190 --> 00:06:17,670 Many people were displaced internally and returned home after a while. 59 00:06:17,700 --> 00:06:27,390 But there was a large international displacement and the main destination was Tanzania that at the time was the main safe haven for refugees. 60 00:06:29,070 --> 00:06:34,540 And this is just to give you an idea. This is the number of the average for using Tanzania. 61 00:06:35,160 --> 00:06:40,300 One point is that they were about 150,000 refugees there already in 1992. 62 00:06:40,320 --> 00:06:47,760 Those are from a previous conflict in the 1970s. There's a spike when the conflict started, 1983. 63 00:06:47,760 --> 00:06:53,730 Then there's a return home. Then there's the actual increase in the number of refugees. 64 00:06:54,210 --> 00:06:57,960 And around the year 2000, there was a peace agreement signed. 65 00:06:58,440 --> 00:07:04,470 But it took about nine more years after the peace agreement for the refugees to go back home. 66 00:07:06,300 --> 00:07:12,750 I would use this figure like twice more because I'm going to make different points, but figures are going to change a little. 67 00:07:14,680 --> 00:07:21,690 Now, one thing to keep in mind is that once they were in Tanzania, they wouldn't have given land for agricultural activities. 68 00:07:22,350 --> 00:07:25,950 Many engaged initially in coastal employment. I love story a lot. 69 00:07:26,430 --> 00:07:30,360 What happened then was implication hosting this for four years in front of you. 70 00:07:30,780 --> 00:07:33,030 So we had the matter of that initial analysis. 71 00:07:33,540 --> 00:07:40,260 But what happened over time was that the Brazilian government, about five years after, after their arrival, say, well, look, 72 00:07:40,710 --> 00:07:48,660 you cannot leave camps limited to four kilometres around the camp and you cannot engage in economic activities outside the camp. 73 00:07:49,440 --> 00:07:52,679 And this means you go back to the story of return migration, 74 00:07:52,680 --> 00:07:57,120 and this means that they were not acquiring any skills that they were going to bring back home. 75 00:07:57,810 --> 00:08:07,050 I think after a few years, the government decided that it was time to close the camps and then they returned the refugees to Britain. 76 00:08:08,280 --> 00:08:17,490 And this happens here. So the peace agreements in the year 2000, around the year 2009, is when the period of return finishes. 77 00:08:19,380 --> 00:08:24,480 I got to explain in a minute, but essentially the data that we collect is for this medium. 78 00:08:24,930 --> 00:08:28,980 So we collect data for this period between 2009 and 2015. 79 00:08:29,520 --> 00:08:39,959 And then there's another outflow of refugees for Burundi at the moment using another conflict situation that is happening. 80 00:08:39,960 --> 00:08:45,630 I'm going to talk about that in a minute. But that is not going to be affecting that we are going to be discussing. 81 00:08:45,900 --> 00:08:51,120 So everything. But then again, what only is going to happen in this period, whether for years where back off. 82 00:08:54,380 --> 00:08:56,840 So what we did is we wanted to start it with. 83 00:08:56,990 --> 00:09:02,650 The one thing to keep in mind is that at the moment that we are starting this, we are thinking that the country is peaceful. 84 00:09:02,660 --> 00:09:08,420 So we are starting a company after. I know the term post-conflict might be a bit controversial among some of you, 85 00:09:08,420 --> 00:09:13,060 but for us a post-conflict society is of this process of return has finished. 86 00:09:13,100 --> 00:09:19,880 I would want to see how this people are settling. How are they doing compared to other people and how are the communities that are receiving them? 87 00:09:21,290 --> 00:09:23,270 What is happening in the communities that are receiving death? 88 00:09:25,440 --> 00:09:34,460 So we went to put all the we collected data in January and March 2001 and 2015, we collected data of 1500 households. 89 00:09:34,470 --> 00:09:36,610 So this is a follow up. 90 00:09:36,930 --> 00:09:44,040 We also interview 100 community leaders, one in each of the communities, and we are able to use all of that data in the analysis. 91 00:09:44,430 --> 00:09:50,090 And the REINTERVIEW rate is very high because this there's not that much mobility across the country. 92 00:09:50,100 --> 00:09:53,490 So we were able to find about over 90% of the houses. 93 00:09:55,140 --> 00:09:58,410 So this is one of them, just for reference. 94 00:09:58,980 --> 00:10:03,690 Bosnia is here. Rwanda and the DRC is on this side. 95 00:10:04,560 --> 00:10:07,110 Each of these dots is the one community that we visited. 96 00:10:07,470 --> 00:10:13,950 We interviewed 15 households in each of those communities, and we collected data for all the members of the House. 97 00:10:16,740 --> 00:10:28,400 As I mentioned, the president announced in April that he was running for a third term in office and this was another wave of conflict abroad. 98 00:10:29,220 --> 00:10:35,680 However, this announcement came in April 2015 and we finished the data collection in March 2015. 99 00:10:36,630 --> 00:10:43,850 So I sometimes agree that there's no commonality between those two things, but we left the country just before the announcement of the president. 100 00:10:43,860 --> 00:10:49,889 So in some sense, what we happen is that a country of ours and a country that is supposedly a 101 00:10:49,890 --> 00:10:53,490 country that have returned to peace and in which there's no more civil strife. 102 00:10:58,230 --> 00:11:02,280 I was a major that the Nazis were interested in those who never left the country. 103 00:11:02,280 --> 00:11:09,270 So we limit the support to those people and we have almost 754,000 that we got to observe. 104 00:11:09,310 --> 00:11:14,850 And that's where I think that was a mistake. Those leave from 87 different communities. 105 00:11:15,360 --> 00:11:23,130 I am for technical reasons, we have to exclude. We can go to the country, the capital of the country from the Nazis. 106 00:11:26,800 --> 00:11:31,180 So we're interested in different parameters. One is livestock. 107 00:11:31,630 --> 00:11:35,240 Livestock work is the main source of malaria. 108 00:11:35,740 --> 00:11:44,340 So this is what they have to make sure. Well, in this case, we are going to be literally adding chickens and cows. 109 00:11:44,410 --> 00:11:51,670 So we have to create an index that's going to compare those foods, going to allow for a comparison of different type of animals. 110 00:11:52,360 --> 00:11:58,480 So we use something called tropical life units. We are able to use measures of subjective well-being. 111 00:11:58,600 --> 00:12:03,190 So how people are doing according to their own description. 112 00:12:04,020 --> 00:12:15,460 And we are going to then go and look at different factors such as long assessed food security, health and insecurity, etcetera. 113 00:12:18,150 --> 00:12:21,970 This is a risk measure. So so this is our alcohol free press. 114 00:12:22,580 --> 00:12:25,809 And the main thing to know from here is that what we want to know is how that 115 00:12:25,810 --> 00:12:31,110 share of refugees in this community is going to be affecting these outcomes. 116 00:12:31,130 --> 00:12:38,620 So for us, these are people who never left. So how would you bring these people back from California? 117 00:12:39,520 --> 00:12:47,050 Some or others from other countries around the region is going to affect everybody, of course, as well as economies. 118 00:12:47,060 --> 00:12:48,010 This is where we start. 119 00:12:48,080 --> 00:12:57,400 You can think about in the generic conflict context about, you know, this is going to have chronic impacts on the receiving community. 120 00:12:57,610 --> 00:13:01,000 Of course, it might lead to conflict and ruin. Do you think? 121 00:13:04,650 --> 00:13:09,510 We're going to show you the results for 2011 and 2050, so for both years. 122 00:13:10,020 --> 00:13:16,080 And just to let you know, the share of returnees in the population, bodies from Seattle to 62%. 123 00:13:16,500 --> 00:13:24,330 So that communities in which no one is returning, their communities in which two thirds of the residents are actually revenues. 124 00:13:27,450 --> 00:13:34,500 One of the big things here is, is there going to be any bias in the analysis? 125 00:13:34,950 --> 00:13:40,409 If you think about it, how does someone stay back from this 1992? 126 00:13:40,410 --> 00:13:45,330 Can someone stay in Tanzania? So may be that the only the best, the most successful are people who return. 127 00:13:45,540 --> 00:13:48,840 Or maybe they left the less really successful people returning. 128 00:13:49,410 --> 00:13:54,989 The answer to that part is no. So everyone had to leave Australia at that moment. 129 00:13:54,990 --> 00:14:01,890 I mean, maybe a few that would say yes. But in general, they have to leave the camps, so there's nothing about staying back home. 130 00:14:02,670 --> 00:14:09,390 The second point is you have to go back to your country or to your community of origin because you can't get land there. 131 00:14:09,510 --> 00:14:17,670 And this is why the big tensions, the peace agreement that led to the end of the conflict, so refugees can go back home and they can claim land. 132 00:14:18,000 --> 00:14:22,860 But obviously, once they go home, that land has been used by older people. 133 00:14:23,610 --> 00:14:27,929 There's the tension of, you know, you know, you have to share the land between the two of you. 134 00:14:27,930 --> 00:14:32,340 But it's not a place, I think the lands of everybody's returning back home. 135 00:14:32,730 --> 00:14:39,630 And there's this violence about I mean, this is all this evidence about exposure to conflict and violence being grounded. 136 00:14:40,530 --> 00:14:42,240 How about the point that we have? 137 00:14:42,330 --> 00:14:49,860 This is something well-established in this kind of forced migration literature, is if you come from a wealthy family with your family, 138 00:14:50,310 --> 00:14:56,130 the likelihood that you're going to flee the country in the face of violence is higher. 139 00:14:57,030 --> 00:15:01,620 So it means that the people that were in Tanzania was actually left the country 140 00:15:01,620 --> 00:15:05,669 during the conflict where the wealthier families and the wealthier communities, 141 00:15:05,670 --> 00:15:11,940 those communities with more outmigration were wealthier. 142 00:15:11,970 --> 00:15:15,930 If you're looking for out what if I were you, then you use one word coping mechanism. 143 00:15:16,320 --> 00:15:21,270 You might be internally displaced. You might use some other way to deal with violence. 144 00:15:21,280 --> 00:15:29,910 But if you confront what you find, you need. So that means that the analysis when we see return, obviously you are going to have a lot more of these. 145 00:15:30,310 --> 00:15:37,440 You have everyone was forced to return home to have more returnees in those communities in which more people left essentially Rwanda, 146 00:15:37,440 --> 00:15:42,240 hot water them in the wealthier communities. And that's going to have implications for the result. 147 00:15:43,800 --> 00:15:52,340 The way to go around that is to find some reason for which people are going to defer in their chances. 148 00:15:52,350 --> 00:15:57,030 Communities are going to be further in their chances or having more or less refugees. 149 00:15:57,150 --> 00:16:00,690 Okay. And that's why we use geographical factors for that. 150 00:16:00,700 --> 00:16:06,000 So this means if you have two countries equally affected by violence, you get African factors. 151 00:16:06,060 --> 00:16:08,070 And then how far east and south, 152 00:16:08,070 --> 00:16:17,190 the distance to the border altitude of the place that you're looking at is going to have a big effect on whether you have displacement or not. 153 00:16:17,250 --> 00:16:22,430 One thing is in Burundi, all this displacement was by food, so people were walking to Tanzania. 154 00:16:22,440 --> 00:16:26,150 So this does play a key role. The graphic that features people. 155 00:16:26,160 --> 00:16:30,210 So we use this graphic of features in order to identify our more. 156 00:16:32,220 --> 00:16:33,510 I'm not going to talk. 157 00:16:33,510 --> 00:16:43,450 Most of this is just to say that this geographical features actually seem to be strongly correlated with the level of displacements. 158 00:16:43,770 --> 00:16:44,820 I again in community. 159 00:16:47,260 --> 00:16:54,510 Now one thing you can argue is for this the graphical features are also potentially related to the same factors that you're trying to explain. 160 00:16:54,870 --> 00:17:02,370 So they might be related to how much life do you have that these features might be related to how much land that you have. 161 00:17:02,640 --> 00:17:06,000 It might be related to the class labour, how much of the you have. 162 00:17:06,420 --> 00:17:14,970 So geographical features might be related to those factors. And one thing that we have is we have that information for the pre conflict period. 163 00:17:15,270 --> 00:17:24,509 So from before the conflict, we know for those households that exist that have been how much livestock they have them and how much land they had, 164 00:17:24,510 --> 00:17:36,030 then we can see if factors related to proximity to the border or that meaning know differences in the in the in the in the stroke 165 00:17:36,120 --> 00:17:44,310 of the place in their biography are related to free water rights or free water on how much of the patients these households have, 166 00:17:44,550 --> 00:17:52,190 whether they had finished primary school. We do that analysis and we find that these factors are not currently revealed, 167 00:17:52,290 --> 00:17:57,120 very confident that by using these significant factors we are not bias in the results. 168 00:17:59,310 --> 00:18:03,390 Now I'm going to show you the results. I want to start with livestock. 169 00:18:03,660 --> 00:18:09,870 One thing about the results is that the numbers of data that I going to show you another to explain what they have. 170 00:18:10,200 --> 00:18:14,520 I have the paper here with the actual interpretation of the estimates. 171 00:18:15,480 --> 00:18:21,000 Just to let you know what they mean. But this is the estimate for our livestock. 172 00:18:21,000 --> 00:18:25,680 And well, then so this is essentially for the year 2011. 173 00:18:25,740 --> 00:18:29,970 It is a confusion that we are looking at the year for the year 2015. 174 00:18:30,090 --> 00:18:35,970 And this is combined for a two year period. Now, we are talking about the meaning of the confusion there. 175 00:18:36,420 --> 00:18:41,780 What you can see is that the confusion is double the size in 2015. 176 00:18:42,080 --> 00:18:49,300 Okay. So that means that things such as life properties move back or from term is getting basically worse over time. 177 00:18:49,320 --> 00:18:52,379 So these households, same households are worse off. 178 00:18:52,380 --> 00:18:58,020 Doesn't things with more attorneys are worse in terms than in 2011. 179 00:18:59,730 --> 00:19:04,020 The interpretation of that particular one four. 180 00:19:04,260 --> 00:19:10,710 So based on this confusion right here is that if you increase the chair of returnees by one percentage points, 181 00:19:11,490 --> 00:19:16,650 you are going to have a reduction in traffic at a lot of stock units of 0.01. 182 00:19:17,490 --> 00:19:21,000 If you translate that in 20 words, like more about one chicken, 183 00:19:21,000 --> 00:19:27,390 less per household but able household member, and that's about a 5% reduction regards to the average. 184 00:19:29,070 --> 00:19:34,799 Now other point is how do people perceive themselves as they perceive themselves 185 00:19:34,800 --> 00:19:39,360 to be worse off or better off after they have more police in the community? 186 00:19:39,960 --> 00:19:44,250 I hear interestingly, contrary to the actual estimates that we have, 187 00:19:44,640 --> 00:19:50,460 when we look at subjective well-being, there's a strong impact on the first round in 2011, 188 00:19:50,970 --> 00:19:57,600 but that in fact is a lot more difficult reaching so far as more in terms of 15 and is not statistically significant. 189 00:19:58,080 --> 00:20:01,410 So in terms of livestock, fairness seems to be getting worse. 190 00:20:01,890 --> 00:20:08,520 There's a how do you feel about it? On the subject of wellbeing, it seems that in fact perhaps people have been getting used to it. 191 00:20:08,820 --> 00:20:20,440 The fact is actually a smaller. Another thing that you gave us is while it may be the case that, you know, as I show you, 192 00:20:20,440 --> 00:20:24,740 you remember from that first chart, some of these people returning in 1996. 193 00:20:24,980 --> 00:20:29,420 Some of these people return in 2006. So they have returned in many different periods. 194 00:20:29,780 --> 00:20:37,130 So maybe it is not just any returnees is just a recent rhythm is the ones that are having a big effect. 195 00:20:37,610 --> 00:20:40,850 And we can do that. So because in the data, we know when people return. 196 00:20:41,180 --> 00:20:44,780 So we can create a variable which is about the recent returnees. 197 00:20:44,780 --> 00:20:49,340 Yeah, I've seen what happens when they're done. 198 00:20:49,550 --> 00:20:56,150 Done. I don't want the return of this operations. But just to tell you that these hopefully are much larger than the previous ones. 199 00:20:56,670 --> 00:21:03,860 And that means that the fact it's much stronger for those communities that are hosting recent returnees, 200 00:21:04,190 --> 00:21:09,080 meaning those communities that have received large controls during the last ten years. 201 00:21:09,980 --> 00:21:14,150 So the effect is more stronger for those communities. That's true for the actual effect. 202 00:21:14,450 --> 00:21:20,500 That's true for the subjective well-being measure. 203 00:21:20,510 --> 00:21:27,560 It is for both cases. It is. It is the case that those communities have received a lot are suffering far more. 204 00:21:31,740 --> 00:21:36,060 Another important body of work for us was land. 205 00:21:36,210 --> 00:21:44,490 So what is happening around? As I mentioned, people will go back and once they come back, they had a right for that to their land. 206 00:21:44,820 --> 00:21:50,190 But most people, when they get back home, somebody have their land some place and family members have sold their land. 207 00:21:50,550 --> 00:21:53,820 So obviously the government were very happy that they had to so much else. 208 00:21:54,090 --> 00:21:57,150 So this people are happy away from their 15 years. 209 00:21:57,750 --> 00:22:03,000 So there was this commissions that were put in place in order to solve this dispute. 210 00:22:03,360 --> 00:22:06,840 And about 90% of the solutions of these problems was. 211 00:22:07,120 --> 00:22:08,280 Now they have to share the land. 212 00:22:09,180 --> 00:22:17,790 So one question is what happens to the access of this or the access to ease people who did immigrate when the revenues came back, 213 00:22:17,790 --> 00:22:29,010 when they have a large influence. And the result is that before is negative and is also gets worse over time, I guess to interpret that. 214 00:22:29,100 --> 00:22:34,259 So a one percentage point in the chair of refugees in the population is low income to leave 215 00:22:34,260 --> 00:22:40,020 to a policy to five hectares reduction in landholdings for a stay here stay households. 216 00:22:40,410 --> 00:22:50,060 That's about 4.44% reduction relative to the main source of the grazing land for those communities that actually have a lower return is is 217 00:22:50,070 --> 00:22:59,490 something that we respect that for whatever I do that look at the conflict convexity might be something that down the line can lead to conflict. 218 00:23:02,760 --> 00:23:07,530 There's also the question of food security. 219 00:23:07,620 --> 00:23:16,050 So what happens to the food security of these communities that are receiving a large number of refugees? 220 00:23:18,030 --> 00:23:25,890 It is the fact it's negative. The good news is that becomes insignificant in the second in the second period. 221 00:23:27,150 --> 00:23:31,950 But essentially, this a one percentage point increase in the share of returnees in the community 222 00:23:31,950 --> 00:23:36,299 leads to a one percentage point increase in the likelihood of experiencing full, 223 00:23:36,300 --> 00:23:41,430 difficult food difficulties or on daily basis. So one percentage point higher come. 224 00:23:41,430 --> 00:23:51,150 But often if they are on this list of one percentage points higher, a likelihood of food difficulties and we just have almost a 1 to 1 relationship. 225 00:23:51,540 --> 00:23:58,030 But as I said before, that the relationship is only for the year 2011, for the year 2015. 226 00:23:58,050 --> 00:24:02,670 Even if these households actually have less land and they are less like livestock. 227 00:24:03,060 --> 00:24:06,660 Food difficulties don't seem to be a problem anymore. 228 00:24:09,840 --> 00:24:13,830 One factor that we also look at is health and crime. 229 00:24:14,530 --> 00:24:19,860 The aspect is important because there were a series of studies done at the time 230 00:24:21,240 --> 00:24:26,130 during that and I forget what percentage of the all stories or those studies. 231 00:24:26,640 --> 00:24:29,940 This was a community that was very poor in terms of health. 232 00:24:30,390 --> 00:24:34,890 So the likelihood of the incidence of malaria, for instance, was very high. 233 00:24:35,520 --> 00:24:39,630 These people are returning home. So are they bringing some of these things back home? 234 00:24:39,990 --> 00:24:45,180 What are the implications of this? We don't see any significant impact. 235 00:24:45,190 --> 00:24:52,560 So even if these Burundian communities abroad were suffering serious, serious health problems, 236 00:24:52,800 --> 00:24:57,990 it doesn't seem that that translated into food or health outcomes for the local community. 237 00:24:58,440 --> 00:25:05,790 Something else that we did with health, because we have children, we have small children under five years of age in the first round. 238 00:25:06,150 --> 00:25:09,870 So we can see them when they are, let's say, five and when they are ten. 239 00:25:10,350 --> 00:25:15,149 Five years later, we follow those children as we see those children in communities with more the 240 00:25:15,150 --> 00:25:19,570 means were more effective because of have their height and weight or anything. 241 00:25:19,600 --> 00:25:24,600 Doesn't seem to be the case. Crime is an important one. 242 00:25:24,610 --> 00:25:27,960 So is this inflow of refugees leading to more crime? 243 00:25:28,570 --> 00:25:30,450 So no previous studies. 244 00:25:30,450 --> 00:25:41,970 We show how labour market opportunities are limited for these are refugees, but it doesn't seem to be the case that they are affected by crack. 245 00:25:43,320 --> 00:25:52,530 Something else that we did was to explore what was the response of these households to the presence of refugees. 246 00:25:52,890 --> 00:25:57,660 You can think about if you live in one community and suddenly the population 247 00:25:57,660 --> 00:26:01,890 of the community doubled because their revenues moved to another community. 248 00:26:02,130 --> 00:26:08,040 So they could be the longer stays we call them, who would be moving across community. 249 00:26:08,580 --> 00:26:15,420 Or it might be the case that if there's a inflow of refugees into returnees, into your community, 250 00:26:15,720 --> 00:26:22,320 maybe instead of just working the land, you change occupations to do something else, you can shift to a different occupation. 251 00:26:22,710 --> 00:26:27,120 So we explore this positive potential possibilities, and there was no response. 252 00:26:27,120 --> 00:26:28,260 There was no mobility. 253 00:26:28,830 --> 00:26:36,060 And this is interesting because we already has very medium mobility across regions, among other reasons, because land is a scarce everywhere. 254 00:26:36,420 --> 00:26:40,380 So if this country a community and they got to caravan with them. 255 00:26:40,770 --> 00:26:45,180 It's not like you can just go to the next community and have fun somewhere else. 256 00:26:46,050 --> 00:26:49,650 It's roughly the same thing across occupations. It's a very simple economy. 257 00:26:50,010 --> 00:26:55,800 Think about economies. We see our times that with this migration, people are changing the jobs that they were doing before. 258 00:26:56,250 --> 00:27:08,240 This is not the case and growth. Now let me give you the so-called solutions from our story. 259 00:27:08,810 --> 00:27:17,960 I mean, the general wanted to be, but we wanted to talk about what's up at this party of evidence about what happens when you have. 260 00:27:18,590 --> 00:27:26,300 But I think you have occasion for people to go back home. We know especially of what happens to refugees, how they compare with our people. 261 00:27:26,600 --> 00:27:31,970 What we don't know, what happens to those communities that are actually receiving the the refugees, 262 00:27:32,870 --> 00:27:39,400 the findings of the paper actually find some voice, some aspects. 263 00:27:39,830 --> 00:27:43,850 Those communities receiving a lot of refugees have less livestock. 264 00:27:44,630 --> 00:27:48,260 They have they are worse economic conditions, selective economic conditions. 265 00:27:49,160 --> 00:27:59,240 This could be to a large degree, driven by the lack of access from the land agreements that they were on and the the resource regarding food security. 266 00:27:59,870 --> 00:28:06,439 Now, one positive side of the story, if you want to call it positive, is that this food security aspect and in fact, 267 00:28:06,440 --> 00:28:10,480 this objective was begun so this upper years for the second branch of the service. 268 00:28:10,580 --> 00:28:13,760 At the beginning it was very big. Money disappears. 269 00:28:14,150 --> 00:28:17,270 The livestock and land access aspect is remains. 270 00:28:17,280 --> 00:28:23,960 Contact, in fact, gets worse over time. So it seems that households are adjusting in some way to this. 271 00:28:25,160 --> 00:28:31,969 Now, one thing I want to end with this is to talk about what this is applicable to our situation. 272 00:28:31,970 --> 00:28:35,990 So problem is a very specific caseload. 273 00:28:36,350 --> 00:28:41,620 So is this that I'm telling you about applicable to other cases I have read previous? 274 00:28:42,080 --> 00:28:50,540 In order for this to be true in my places, first of all, you need refugees who do not have access to a labour market or to chronic opportunities. 275 00:28:50,780 --> 00:28:55,790 So essentially they're not getting any skills or creating any financial capital when they are abroad. 276 00:28:55,790 --> 00:28:58,130 So basically that they're not bringing those skills back. 277 00:28:58,370 --> 00:29:05,330 And in fact, you could argue that losing skills while they're abroad, if they're not, they probably got the active duty. 278 00:29:06,980 --> 00:29:12,180 Obviously, some kind of a country with scarce natural resources. 279 00:29:12,180 --> 00:29:16,509 So if you come back to a country that has a lot of resources, 280 00:29:16,510 --> 00:29:23,750 so you make the case that you have these qualities of life just for security because you have a lower level of access. 281 00:29:25,430 --> 00:29:34,799 And third, you need essentially that the reason that the refugees are returning is that the host country in some way I mean, 282 00:29:34,800 --> 00:29:37,830 force it might be a strong way, but the whole country is pushing them. 283 00:29:37,850 --> 00:29:40,940 So in this case, it's apparently voluntary return. 284 00:29:40,940 --> 00:29:47,720 So they're not planning for after sense of return home. They will have preferred to stay in the in the in the country. 285 00:29:48,170 --> 00:29:52,670 So you can have these three things. We have look at the case stories. 286 00:29:52,670 --> 00:29:54,350 You can think about different case stories. 287 00:29:54,680 --> 00:30:02,839 I mean, Somalia, Kenya, Somalia can be one of which people are limited in their communities and they can do terrifically. 288 00:30:02,840 --> 00:30:11,300 Many of them are poor, if not forced, because of a push to their home on their return to a country which there's not much available. 289 00:30:12,350 --> 00:30:16,280 Maybe Afghanistan has some of the similar features that this case. 290 00:30:17,210 --> 00:30:21,320 So this is very specific to this particular set of situations. 291 00:30:21,650 --> 00:30:27,090 And in this particular set of situations, refugee return is going to have negative consequences. 292 00:30:27,110 --> 00:30:30,380 You can think about it from the political stability context. 293 00:30:30,560 --> 00:30:33,230 It may also have implications for political stability.