Good afternoon to everyone from Copenhagen. Good morning or good evening, depending on where you are, and welcome to the 8th and last session of our Learning from the Evidence of Forced Displacement Training Program, training program organized by the UK government, UNHCR World Bank Building the Evidence on Forest Displacement Research Program in collaboration with the World Bank, UNHCR Joint Data Center on Forced Displacement. My name is Domenico Dabaso. I'm a senior economist at the Joint Data Center. And today, I'm joined by Kirtan Shutla, a senior economist at the World Bank, and Joan van der Goltz, who's also a senior economist at the World Bank. Uh, they will be leading our module today, which is a module which focuses on forced displacement and jobs, and in particular, they will be talking about labor market impacts on force of forced displacement in low and middle income countries and the cost effectiveness of job, jobs interventions. Uh, during the module, we, we will also hear from UNHCR colleagues who will tell us about their work and their experience in this, in this field. Before we get started, as usual, let me remind you of a few housekeeping rules. Uh, this meeting is being recorded, and the, the, the recording will be made available on the website of the building evidence on force displacement program together with all the accompanying material. Uh, please do feel free to keep your camera on throughout the sessions should you wish to do so, but we do, uh, kindly ask you to keep your mic mute throughout the session. Uh, the, the session will last 90 minutes. Feel free to use the chat to post your questions and also add comments and suggestions. If you'd like to ask a question, I think we can accommodate a few questions throughout the session, so raise your hand, and we will uh give you the floor. Uh, last, in case you'd like to do so, please feel free to rename yourself. Uh, you can do so by clicking on the three dots at the top right corner of your screen and add your name and an affiliation. You can also use the chat to introduce yourself to the other, the other members of the audience and to, and the speakers. Um, we did, uh, we'll leave the floor to Jan and and Kirsten, uh, for them to start leading this module, and I wish everybody an enjoyable session. Jan, Kirsten, over to you. Thank you so much, Domenico. Thank you so much. And good morning and good afternoon to everyone also from our side. We're very delighted to be here and share with you results of work we've been doing over the last, I think, 56 years, um, and also mainly as part of the Building the Evidence on Force Displacement um program. So very happy to be here. Um, uh, together with our UNHCR colleagues today. Um, and now, at classic, now the slides are moving. So we have a packed agenda for the training today. We want to talk with you about the jobs impacts of forced displacement for hosts, as well as for those forcibly displaced themselves. We want to talk about the impacts of interventions, facilitating refugee and IDP labor market inclusion, be that policies or program and project interventions. And lastly, we want to talk about the cost-effectiveness of these interventions, an aspect we often forget, unfortunately, to talk about. So we will start with the jobs impacts of forced displacement for hosts and refugees. And I will start introducing you to the impacts and what we know on a global level. And then Jan will take over from there to introduce the research work that we've been doing in 4 country case studies and what we found out, um, in these countries. So what do we know on the global level on how an inflow of refugees or IDPs impacts those living in host communities? Um, the literature on in economics on this question has really exponentially increased since the Syrian crisis. So today, we have many more studies to draw on, uh, to reply to this question. And together with Paolo Verma, we did a review um that tried to cover as many studies as possible. We covered 59 papers of 190 major discourse displacement crises to get an idea and compare across those contexts, uh, what we know. So we looked at the impacts on employment and wages, but we also included the impacts on prices, um, because as you know, an influx of refugees or IDPs is not only a shock to labor supply. So labor supply increases, but also it is a shock to consumer demand. So demand for goods and services changes. And what is more important is that overall, it's important to look at what that actually means for well-being. We've weighted the results by the journal's impact factor. So why did we do that? Because with the journal impact factor, we try to use that as a proxy for the quality of the results. So to additionally say we give more weight to those results that have been published in journals that are widely read and, and cited. So in line with the research on impacts of migration in general, we found much less impacts than we would have expected. With the exception of prices. So you will see that for prices in around 80% of the times, we do find an impact, but those impacts are more or less evenly divided between positive and negative impacts. And then we really see that it depends on the types of goods that we talk about, if they're tradable or not, what kind of region of the country we are in, etc. But we see much less impacts for employment and wages. Um, we see that for well-being, our results are, are around half of the time positive. But here, it is important to note that the results come mostly from low-income countries and only for certain indicators that we framed as the overall economic well-being of the household. We did not go into the psychological well-being. On the employment or wages, we see that in around 60 to 70% of the time, we don't have, um, we have positive or non-significant impacts, but we also have negative impacts and they're concentrated mostly with female workers with informal and low-skilled employment. But it's hard to say cause it really differs across context who's negatively impacted. And we've also seen that these negative impacts tend to disappear in the longer term. But as I was saying, the literature has increased, but there's still gaps in the literature. And it is hard to compare the results across studies, which is also why here we only talked about positive, negative, or non-significant, but not about the size of the impacts. And this is exactly the reason why with Jan, we undertook the study, we undertook on the four-country case studies that Jan will tell you more about to be able to actually compare results. But before we look more into the hosts in these four countries, let me zoom in on what we know about those forcibly displaced themselves on a global level. So we see that in most settings, refugees, where we have most evidence on, but also in, in part IDPs have worse labor market outcomes than hosts, um, due to the specific constraints they face. But it is also important to note that not all constraints are equally binding in each setting. And when we look closer at the constraints, we see a lack of skills because refugees did not go to the destination because they saw a match for their skills and often also lack of labor demand because they were pushed out by violence but not less, not necessarily drawn by, by labor demand. This also somehow affects hosts, but less. Then we see a number of constraints that also affect migrants, lack of language proficiency, but refugees have even less time than migrants usually to prepare or learn the language beforehand. Lack of social networks. We know that migrants are much more drawn by social networks that exist than refugees are. Um, also an uncertain or short time horizon because their legal status might be unsure because they don't know when they will be able to return. Um, we also see legal challenges that they face and discrimination. What is specific to those forcibly displaced in addition to these constraints are lack of assets. Lots of times they have to leave assets behind. They don't have time to sell them before they leave. Um, we also see lower levels of health, so um, forcibly displaced are usually negatively selected in terms of their health compared to migrants who are positively selected. And we have mental health issues, a higher prevalence of such issues. And we also have studies that show that the impact of forced displacement, the experience of conflict and forced displacement has on the risk appetite of this group, and that's also on their likelihood to become entrepreneurs, for example. So I'll leave it here and um hand um over to Jan to zoom in onto our study where we try to look at the impacts on those forcibly displaced and the host workers in four-country settings. Over to you, Jan. Thank you very much, Kirsten, and, uh, good morning, good afternoon also for me. Um, it's a great pleasure to be here. Um, very nice to be able to do this training. Um, so, let's illustrate a little bit, um, what Kirsten has been talking about with a, with a large case study that we did in, in 4 countries. So, Colombia, Jordan, 2 middle-income countries, one with a very open labor market policy in, in Colombia and Jordan that's been opening up a bit more gradually. And then Ethiopia and Uganda to low-income countries again with this balance uh between a very open labor market access policy in Uganda, um, and gradual opening up in Ethiopia. Um, it's a study that the two of us led together with Julie Bouquet, who was at KU Leuven, and, and Theodos Kebede, who is at FAO in Norway. Uh, next slide, please. Um, you know, Kirsten has already explained a little bit what, what our goal here was. The goal was to say, Um, look, when, when we have a finding from a single country, that's interesting and that's helpful. But the question is often, well, you know, now there's a crisis in another country, what does this tell me, right? Should I expect that the same thing that happened, um, there is also gonna be happening here. Um, and it's difficult to do that because we're we're comparing across contexts, but also, we're often comparing Um, studies that are done differently, and they use different methods, they use different types of data, they look at different outcomes. So we try to take out these factors. Try to look at four countries that are very different with methods that are very consistent. So we really try to use the same kind of data, look at the same kind of outcomes, and work, uh, in a way that, um, that's consistent across these, these 4 countries. Uh, at the same time, the goal was then to say, look, Uh, we can never compare settings 1 to 1. You can never say, OK, we saw that in, in Country A. We're also expecting to see it in Country B. So let's really understand why things happen. Let's look in detail at the labor markets and see what happened in the interaction between displaced workers and host workers. So that we can take some lessons that maybe are a bit more transferable. So we understand there was a mechanism here. I can now look at the country that I'm interested in and try to see whether I think that that mechanism could also be at play there. And then we did some work on, on attitudes and perceptions that Kirsten will tell you, uh, more about in a moment. So, the whole thing is, is based on a reanalysis of, uh, of a lot of publicly available data. It's also based on primary data collection, uh, from, um, three of these countries excepting Jordan. Next slide, please. So, let's start just with an, an, an overview of the main findings of the analysis we did. So, what you see here are effects on consumption and earnings. So, a key welfare proxy, right? Are people, are households consuming more? Do they have higher incomes or lower incomes? So, that's the top panel. Um, and then at the bottom, you see effects on employment rates. So, another thing that, of course, is always Um, very high up on, uh, policymakers' agendas is, uh, what's the effect on people being able to find a job. Um, and you see the results from all four countries. They're color-coded, so adverse effects are in this orange color, um, beneficial effects are in the green color, and no effect, uh, are the white boxes. Um, and so, what really struck us here is that in this consistent analysis where we look at, at different countries in the same way, we found a similar finding to what kind of the literature shows. Um, the, the impacts when we compare across these four countries, um, of hosting displaced workers tend to be mild. Uh, and in some cases, they're positive. So, if you look, for instance, at the top row, you see that in both of the low-income countries, despite all their differences, the estimated effect of hosting, um, displaced workers is actually positive on consumption. So, households in, uh, host communities see a small increase. It's not a huge effect, but, you know, it's a, an increase nonetheless, uh, in their consumption. Uh, similarly, in, when we look at the, the labor market outcomes, the employment rates, you see that there's no effect across these four countries when we look at the whole of the economy. So that's really the first message. Uh, there's, there's a lot of understandable worry, usually about what's gonna happen to jobs when, um, a community becomes a host community and, uh, refugees or other displaced persons arrive. Um, but the international experience says, On average, in the whole of the labor market, um, we can hope that the effects actually won't be as bad as, as, as people may think. But then there's a 2nd message, and the 2nd message is that There's change in the labor market, right? There are new workers coming, there are new consumers coming. We're going to talk more about that in a moment. Um, and so different groups in the labor market do see different effects. And sometimes people have adverse effects. So, for instance, if you look at Colombia, um, we estimate that the earnings of temporary workers went down in host communities. Uh, if you look at the bottom, um, there's also a decline in the employment rates of, of men in the labor market and of young workers in the labor market. They're small effects, but there are adverse effects. So there are people here, um, who, who lose out, um, from the arrival of, of displaced workers. However, conversely, there can be groups in the labor market that benefit. So, for instance, if, again, you look at the top, um, some impacts on consumption in Uganda and Ethiopia, you see that there are different groups of workers that benefit, rural workers, um, different types of farmers, whether they're oriented to the, to the market or they're more subsistence-oriented, uh, in the case of Ethiopia wage workers. And some of these effects are actually, uh, quite sizable. So, the second finding, um, We, uh, we have is that. The overall effect, we can expect to be mild or positive, but we need to pay attention to what happens to different groups of workers. There is going to be change in the labor market. For some people, that's gonna mean new challenges. For other people, it's gonna mean new opportunities. But so from the policy perspective, uh, we need to find out who is likely to be affected in these different ways and what kind of support, um, they might need. Now, um, one more point on this slide is to say that, you know, our goal was to look for patterns, who, who could be, who, who tends to be positively affected, who tends to be negatively affected. But it turns out that's quite difficult. The, the one finding that's quite consistent across these four countries is that there tend to be opportunities in agriculture. Um, and in some places, that's maybe quite easy to understand and markets that aren't always very highly integrated, right? The food, food is to some degree locally produced. It's not like, uh, goods just, just move, um, at a moment's notice between different places. And so if there are more consumers in the market, there can be more opportunities for food producers, uh, for food processors, etc. But that's really the one pattern. Beyond that, there's no consistent pattern that we found. For instance, it's not the case. That it's always, uh, vulnerable workers, for instance, who are negatively affected, can be the case, uh, but it's not consistently the case that they are the ones who, who have additional, um, competition. Um. So, the, the third message that, that I think we would like you to take away is context matters enormously, and the way we should use these lessons from, from research is really to think about our own context and ask, all right, what, what are the vulnerabilities here? What are the opportunities here? Uh, not a one on 1 to 1 translation of what happened in other, in other contexts, but really a way of thinking about what could happen in our context. Uh, next slide here. Uh, I'll keep the next slides relatively brief, but we can revisit them after the, the breakout groups. But so in the interest of time, just a few facts that I think are useful to, to keep in mind as you think about labor markets. Um, one, as Kirsten pointed out, Displaced workers tend to be at a disadvantage in the labor markets. So what you see in the top panel here is reliance on low-quality, uh, daily wage work, so hornaleros, right? So, workers that, that just wait every day to be hired, uh, for a wage, and they may get hired or they may not get hired. In most settings, much higher among the displaced workers. Um, what you see at the bottom, uh, asset, is the asset wealth of, of households. Um, so a measure of how, how well the household has done over a longer time. Again, displaced households, much, um, much less asset wealth on, in general, um, than among host households. Um, next slide, please. Another thing I think that's very worth, uh, keeping in mind as we think about the potential labor market impacts in the settings that we work on is that policy matters a lot for how refugees engage in the labor market, but it's not the only thing and it's, it doesn't fully determine outcomes. So even in the really restrictive policy environments, if you think, for instance, about, uh, you know, ADIS, which is a, is a difficult labor market to work in for refugees, um, refugees participate. Uh, it's, it's not going to be a level of participation that you might see in a, um, in a more open labor market. It's not going to be the level of participation among hosts, but there are workers that participate. But conversely, even in the very open labor markets, refugees tend to participate less than their hosts. Again, not always the case, you know, in Colombia, it's a fairly similar level of participation. But as something to keep in mind, there are going to be a significant number of refugees, uh, who rely on unearned income, whether it's remittances or whether it's, uh, some kind of assistance, who participate in the local markets. They may be food consumers, for instance, uh, but they don't participate in the labor market. Next slide, please. Then the next point, I think, to think about as, as we try to anticipate what the labor market impacts might be in the settings that we work on, is that the local structure of the labor market is incredibly important, and we have to be very realistic about it. And I'll try to motivate that with Two examples. What, so what you see here are two labor markets in Uganda. You see Kampala on the left-hand side. So the big city labor market, and then you see a Sinjiro district, uh, on the right-hand side is a district in the, the south of the country, a very rural area. Uh, and on top you see the kind of work that hosts do, um, And there are no surprises here, but it's incredibly important, I think, to be realistic and keep that in mind as we do our labor market analysis. So in Kampala, about 1/3 of workers in wage work. Um, about 1 in 6 in daily labor, and the rest self-employed. Almost all of them outside of agriculture. So, these are gonna be street vendors, these are gonna be people who, you know, drive a motorbike and either take, uh, take goods around or take a passenger around, etc. Um, You see on the right-hand side, what happens in the rural labor market. Again, no surprise, 50% of, uh, workers are self-employed farmers, uh, 1 in 4 self-employed in services or in other activities like food processing, for instance, and very few in wage, employment and daily labor. So this matters, of course, incredibly for how refugees will be able to engage in the labor market. For instance, Wage employment is going to be rare. It's generally going to be rare in low-income countries, and it's going to be vanishingly rare in rural labor markets in, in low-income countries. So it's not something where refugees can hope to slot in, and we need to keep that in mind when we think about our support. By way of contrast, if most hosts work as self-employed farmers, Then for refugees, access to land is going to be very important. The question, can I find land? What kind of quality does the land have that I can find? If you think about an urban labor market, where most people are self-employed, uh, access to funding is going to be very important. Do I have the means to, you know, stock a little streetside shop? Do I have the means to buy a motorbike? Um, am I able to do this kind of job that's available in the labor market that I moved to? And then conversely, thinking back about the impact on hosts, this shows us where the competition is likely to come from. If you have refugees arriving in a rural labor market, um, and they have no access to land, they will not be able to compete with farmers. They will look to compete. Um, either with the self-employed or as you see here in Iinjuri district, they will look for employment as daily laborers, for instance, on the farms. So, it's going to create a certain pattern of opportunity, for instance, for farmers who want to hire laborers, but it's also going to create a certain pattern of competition, for instance, for local workers, uh, who previously were, were farm hands, right? So, the message here really is, let's look very realistically at the kind of jobs that are available in the local labor market. Let's not bring, um, any preconceptions or assumptions from higher-income labor markets to, to our work. Uh, next slide, please. Uh, I'll just touch on that very briefly in the interest of time. So, uh, in middle-income labor markets, what you see here is Jordan. The story is quite different. So you can find a labor market, um, like Jordan, where most employment for hosts is in wage work. And here, the question then really becomes about what's the degree of access to these kind of jobs for refugees? Um, are they able, are they allowed to work? Uh, are they able to work informally? Um, And the, the answer to that, the policy framework again creates patterns of competition. You can imagine that, for instance, a work permit program can raise competition for host workers who are formally employed, but it may decrease competition for those who are informally employed. So again, it's a question of who is affected in what way and how can we support, uh, groups of workers, both among hosts and refugees, um, who are affected, uh, in different ways. Next slide, please. Um, you know, I know we, we need to be mindful of time, so I just want to highlight the finding here though. Um, We, we often think about skills. It's something that, that comes quite naturally. It's, it's our own experience, you know, our, our skills have mattered a lot in our career. Um, we see it a lot in a lot of certainly higher-income labor markets that skills determine how far you can go, um, in, in your jobs. And skills certainly matter. However, when we look at lower-income labor markets, it's worth bearing in mind that the kind of work that people do, uh, doesn't tend to be quite as differentiated as it is in higher-income labor markets. Uh, a lot of jobs in agriculture, a lot of jobs in basic services. Again, you know, the, your hospitality, the tea shops, you know, the roadside, uh, vendors, the transport. So, The, the range of skills that are relevant in the labor market for most workers, except for the really high-skilled ones, is relatively narrow. And so the skill match is maybe in some cases a bit easier, right? You're a farmer, well, you know, you, you have a large labor market in front of you, uh, where your skills are going to be relevant. It's other things that become perhaps more important for the kind of match in the job that you find. It's about language, for instance, as Kirsten said, it can be about networks, uh, if you want to be a trader, you know, certainly incredibly important both to find customers who want to buy from you and to find suppliers, and it becomes about access to funding, it becomes about capital. And here what we, what we discussed a lot in the report, and you can see, uh, I think a lot of detail there is that the displaced really are at a disadvantage there because for most displaced workers, Displacement comes with a, a big loss of assets. You can try to bring something with you, but it's often far from the same of the position you were in before. And this can become a big obstacle, uh, in doing self-employed work. And it can be something that it is very hard to recover from because generally, saving, as we all know, in lower-income environments is very difficult. So, if you, if you start with very little, your household doesn't have much to, to build on in its job activities. Um, you are at a disadvantage in these labor markets where self-employment is so important. Next slide, please. All right. Um, we're going to move into our breakout discussions, and I just want to, to motivate that with, with this slide. Uh, so, in the report, we try to, try to provide some suggestions for how we can look at labor markets that we're gonna work in. Um, and we thought that for the breakout rooms, it would be nice to, to use that as a template and discuss a little bit the settings that you're familiar with. Um, so, without, I think, further, further ado, I'll, I'll take it over, uh, turn it over to Domenico, uh, to, to take us into the breakout exercise and, uh, we can then look at that slide together. Thank you. Thank you very much, Jan. And actually, just to let you know, we are perfectly on time. We are gonna have now a 10 minute, uh, breakout room discussion. Uh, Jan and Kirsten have already covered quite a bit of ground, and so it's a good time to sit down and reflect, uh, and listen from you about your experience in, with respect to these 3 items that have been put on the slide, but Meant to, you know, to guide a bit the, the conversation. So, but really, we'd like to hear from you in terms of what your experiences in terms of impacts, uh, similarities or differences across context, and uh how basically a refugee or forcibly displaced people more generally here in the, in the labor markets, uh, in, uh, that you are familiar with. Um, technical note, it's a very free space in the sense that we are not recording the vertical room. So please feel free to use the space for a, for a, you know, candid conversation uh among us. Uh, one request is that We, you were asked to uh nominate a note taker because the reporting back will uh happen through the chat in the interest of time. So the, so the chat will stay there, um, and so we can use that the material coming from the chat to inform the reminder of the session and also, uh, the, you know, the, the material that will come out of this, of this session more in general. So without further ado, uh, I'll ask our, um, colleague Natalia whether she can. Thank you very much. Um, I hope you had a good breakout, uh, group. Um, I certainly participated in an interesting one. I heard some interesting comments and some actually some, some interesting elements of the difference with respect to what has been presented, and which reminds us again of how important Context is in some policy settings are. Um, Jan, should I give the floor back to you while I invite all colleagues who are the note takers to, uh, you know, put in the chat what you've heard in the, in the, in your breakout room. Jan, over, over to you. Thank you so much. Thanks, Domenico, and I think it's actually Kirsten, but, but, you know, I'm sure I speak for everybody on the team that, uh, we wish we had a little bit more time in the breakout room. So, I'd be very happy to continue the discussion. Um, you know, I'm sure we'll, we'll have our emails, uh, somewhere and be great to, uh, to chat at some point. Thank you. Can I actually take the floor for a second to remind everybody to also use the chat to pose your questions to Jan and Kirsten or any further reflection even inside those that we hired on the, during the breakout rooms. Thank you. Over to you, Kirsten. Thank you so much, Dominica. And also to say from my side, I enjoyed the breakout room and also the, we had experiences from all over the world being shared and it reminds us of the complexity of the situations, but also some similarities that exist between those contexts and the, and factors that might matter. So we're moving on now. We kind of looked at the impacts on hosts and on those forcibly displaced, how that might interact with each other. But we're here to mainly also understand, so what can we do about it? How can we improve those outcomes? And so we're gonna turn now to the impacts of interventions. Um, So within um the jobs group, um, we did a literature review um of all the studies that are out there looking at different support types, uh, trying to address the specific challenges that refugees and IDPs faced and that we discussed previously. Knowing that most of the studies actually focused on refugees, it's one of the gaps in the literature and in our breakout room, we discussed differences between refugees and IDPs in this context. But, um, we divided it up in different types of interventions. We see that the repeated, uh, transfers, for example, that try to address the loss of assets and income and also the lack of social networks, there are quite a number of studies, um, and some of them also look at the potential employment impacts. And we see that here, the repeated transfers might actually sometimes potentially have a negative impact on employment. But only because they seem to allow refugees in this case, for which the studies were done to actually have the time and the bandwidth and the capacity financially to look for better, less dangerous jobs. So where employment was reduced, also the number of refugees reporting being in, in, in dangerous, dirty, difficult jobs also decreased. And transfers have some number of additional other benefits that might also indirectly have a positive impact on jobs outcomes like in uh benefiting mental health through the security they provide and also having potential positive impacts on the next generation in terms of health and education spending. Um, we also have evidence, but less on the one-off transfers that can potentially increase, um, uh, entrepreneurial or self-employment activities. Um, but there, we definitely need more studies. Um, same thing on the vocational business and other skills training and recognition of skills. And there is where we are also a bit more cautious in general as Jan. Saying, given the context that we're in, refugees might benefit from them if there is a skill mismatch, but we're never sure if it's actually, this is actually the binding constraint or if the binding constraint is more on the capital side and on the network side, and on the language side. So the evidence we have on language training is mostly from high-income settings, but it's more positive. We still need more studies, but also using studies we have for migrants in general, we see that language training is important, particularly also for social networks and for the quality of jobs that refugees and IDPs and particularly refugees who don't speak the language can actually make and uh take up. Healthcare and psychological support is where the evidence is green, green, green. So we see very positive impacts even from short-term interventions, uh, low-cost interventions, we see a lot of positive impacts, um, that then can also potentially have a positive impact on, uh, labor market outcomes of the target group. If we look at job search assistants, the evidence and the studies we have is a bit more mixed, and it will be interesting to later hear from UNHCR an example where the matching is not just happening in one labor market where we're, but we're actually a Geographical matching is happening. So refugees are moved geographically and helped to move to the, where the opportunities are, which are often not in the remote areas where they arrive, um, at first, um, across the border. Evidence on wage subsidies and especially on subsidized public sector employment are less good in the context of forced displacement and particularly on the subsidized public sector employment, good positive short-term impacts, but the expected long-term impacts, positive long, long-term impacts on employment have not been found by the studies. We also need more studies on access to markets and value chain interventions. There's also, we are missing evidence. Where again, and this is the last type of support I want to talk about, and where we have more evidence is on the improving the legal framework and informing about rights. But on the other parts where we are missing the evidence, the nice thing to see and we've included uh, a recent publication and the references at the end of this PowerPoint. Who lists them all is that we have a lot of new RCT results that will soon be published. So we have a lot of RCTs in the pipeline and it will be very interesting to see this rigorous evaluative evidence and then to see if, if the other interventions might be more promising or what do we actually learn of how they need to be tweaked to fit the needs of this specific target group. But coming back to the, to the legal um framework and the information about rights, we have a lot of evidence, particularly from high-income settings about what happens when the legal uh restrictions are actually being taken away. And we see a lot of positive impacts on labor market outcomes. But the question is how does that translate in labor markets where there is not so much formal employment? What does actually happen there? And this is something that we looked at in our study, um, as well on the four country country cases. And where we looked at Jordan and Colombia, both countries that have kind of opened up the labor markets, um, for refugees. And we see that in both contexts, we find less impacts than we would have expected. So we see very little effect on host workers' earnings and employments, but we also see a change in which workers face competition. So for Jordan, we see that there's small effects of the early days of the Jordan Compact on jobs outcomes for hosts in these early days. We see some positive impacts and some adverse impacts. We see that um wage earnings potentially increased, um, but we have a slight drop in formal employment. Um, but what is very important to note, as I said, there's no evidence of any adverse aggregate effects on employment or on unemployment, and not on overall earnings. When we looked at Colombia, um, on the 2nd longer residence permit that was established for Venezuelans in Colombia, we confirmed also results from a study, studies on the 1st round of these residence permits because we found, again, very um Small or no effects on the, on kind of, of the work permit itself on the workers. But where we did find large effects is on the refugees themselves and their earnings. And these effects are tremendous, between 25% and 33% increase in earnings, and we see a lot of shift also in the labor market. So we see that refugees, Venezuelans, uh, in need of international protection in Colombia have actually been restrained by their legal status. The last thing I want to say looking at, at um these policies is that perceptions matter in all of this. Perceptions of the host allow certain policies to be implemented or not, and they will also frame how, how hosts actually perceive. Uh, perceive these policies and interventions. And what we saw here, we did a listing experiment in two countries in Uganda and Ethiopia as part of the survey data we collected. And what we saw here is that the actual competition matters when uh when hosts are prompted with a potential competition from refugees, their perception tends to be much more negative than if they're not prompted. So in general and overall settings, we did not find a bias, but where they are, were prompted about labor market competition, we see the worry shining up. And we also see that this is the case even in contexts where, like Abyss, where very few refugees actually participate in the labor market. And so we see that the worry about competition plays a much larger role or plays a large role as well as the actual competition. So policymakers really need to take that into account. So let me close with some thoughts of the study results that Jan presented um on what we think that they mean for, for policy. So we see that hosting displaced workers can make winners and losers. We've, we've seen that, but that economy-wide aggregate effects, they're very small or zero, and that also means that there's room to focus on those that lose out and that they can be compensated. Um, we also see that there are opportunities. Yan was pointing out, there are people who actually win, and usually the policy does not focus on these opportunities. There's an increase of people who demand certain goods and services. There might also be investments made by the international community, by the governments themselves. So there's opportunities here and policies should try and seize them. We also see that there are these distributional impacts because of who loses and who wins, and there needs to be an open policy discussion about How and why this is shaped and the way it is shaped. Often it is pretended that by not allowing refugees to work, we prevent impacts for everyone while this is not true. And we see impacts even in these cases, but on different groups than if we open up the labor market. We also see that hosts move towards opportunity. We've seen this, um, in Jordan slightly where hosts seem to move to sectors that are close to refugees. We've seen it in other sectors. And we've also particularly seen it in the agricultural. Sector because of the opportunities the food sector provides for hosts and for refugees. And this is something where policies can also support, um, help people move geographically, but also help them move between sectors, between occupations. What is also important, and I think we've stressed it quite a lot now, is, is that it's really the characteristics of the host labor market that matter. We cannot come to a setting without conducting an analysis first, understanding the context, and also adapting to our policies to the type of labor market and to the characteristics of hosts and of those forcibly displaced. We've also discussed about the fact that refugees and IDPs are likely to face substantial capital constraints because they cannot bring their assets with them. They might have lost them through conflict and through their journey, might not have been able to sell them or access them anymore. So this limits their ability to establish self-employed activities. And in a lot of settings we work in, these are the main type of activities that exist because there is little wage employment available. And skill and skill matches, as Jan was stressing, might play a role, but we need to really assess if there's, this is the binding constraint, or if it is much more about capital, language networks, other points. Yeah. We've also seen with the work permits, as I said, we have little impacts on hosts, but huge impacts potentially for the refugees themselves. But we've also seen that it might be less about them actually moving to formal sector jobs, especially where there are little of these jobs, but more about actually having them on the same footage as host workers in the sense of a signaling effect. That they're actually allowed to work and that they have to be treated the same way even if they work in the informal sector. And this is where we can think also about, about complementary policies that can, can promote this, um, and help them. And what is also important to see is that all the impacts that we've detailed, they've happened um in a context of usually government and international community investment. So it is important for this investment to happen, to seize opportunities, um, and, um, also to kind of cushion any potential negative effects of these inflows. So I'll leave it here with a kind of more theoretical discussion and with a few evidence from our case studies and hand over now to our colleagues from UNHCR who will present to us, uh, two case studies from Mexico and from Uganda of their work, um, in terms of interventions they've done. Over to you. Starting with Mexico. Thank you very much, Jan and Kirsten. Um, in the meantime, I, of course, I invite all of you to have a look at the, at the chat because there's so much coming from the breaker rooms in terms of, uh, you know, reflection on skills, in terms of access to formal or informal jobs, in terms also the opportunity of comparing certain countries with others because of, as we heard, the context matters and policies frameworks matters a lot. Um, Let me steal 30 seconds to also signal that there are a couple of comments about data and, you know, the lack of data, or sometimes also the fact that, you know, we, we're dealing with a fragile populations for fragile people. So we have to be careful in the way we collect data. And of course, as a member of the Joint Data Center, I'm very glad to, to hear and to, to, to see these reflections in the chat. Um, but now, as, as Kirsten said, we've invited two UNHCR colleagues to join us and give the, give us their, uh, reflection from the field. So I see that the slide on Uganda is up. So Damali, Damali Zalongo from UNHCR in Uganda, the floor is yours. Thank you. Thank you very much. Um, so, uh, I, I'll, I'll, I'll quickly, uh, take you through the context in Uganda. Um, and as you can see, we have approximately 1.5 million refugees, and out of those we have uh. It's a population of about 40% that are able to, uh, participate in the labor market. And, um, the policy in Uganda is quite enabling for the refugee employment because they are allowed to work, they're allowed to move, and they also have the right to access, uh, education, which eventually leads them to skilling and ability to, uh, enter into the labor market. Um. Uh, from the studies that have been done by the World Bank, 29% of the refugees in Uganda are actively working compared to 64%, uh, of the host community. And, uh, this is attributed really to some of the structural issues and, uh, de facto barriers. Uh, the fact that Uganda has experienced a slowdown, um, in economic growth, uh, for quite some time, that means that, um, there's been, uh, uh, um, Uh, there's been quite, um, Uh, less, uh, uh, uh. Attachment and efforts towards Uh, productivity growth and human capital, and there's been much more, uh, on factor accumulation, which is mostly labor. Um, but also I have to highlight the fact that, um, a higher number of refugees earn less than nationals with similar skill set, and many of these accept employment opportunities, uh, below their skill level, education, and pre-displacement occupation. Um, uh. There's also non-recognition of refugee qualification from places of displacement, especially for, uh, formal sectors like in education and, um, and, uh, health, where we do have refugees who have qualifications, um, as, as nurses or as doctors and, and teachers, but, uh, they have to, uh, go through processes to be able to, um, enter into the formal, uh, employment or labor market. Um, so, uh, some of the interventions that have been made to enable refugees access the labor market have been really, uh, efforts, uh, concerted efforts by a number of actors, um, in the refugee response from both the development and the humanitarian, including the government. And one of the examples I give here is an apprenticeship program that Uh, enabled refugees to enter into the formal, uh, sector because there were opportunities there, uh, around the country, and this program was running, um, was being run by the Ministry of Labor together with the Uganda Hotel Owners Association. So, um, uh, together with the ILO and UNHCR was the entity that is in charge of all hotels around the country was engaged. Um, there was an opportunity to take on refugees into, uh, these opportunities and, um, alongside, uh, a higher number of, uh, host communities. Uh, uh, and this was mainly in the urban setting. Uh, on the other hand, in the rural setting, the efforts have been mainly towards, uh, business and entrepreneurship training. Uh, to enable refugees, um, access or be able to start up businesses, uh, self-employed because the opportunities for formal employment are quite limited in the settings that are in, in the rural areas. Um, and, and there we saw examples of, uh, trainings that are being done together with vocational training institutes, um, and an initial seed funding that has been provided for refugees to be able to, uh, Uh, uh, produce, uh, particular products and linked to markets. However, some of the obstacles to the success of this, uh, um, intervention have been the fact that, uh, the, the remoteness of the locations where the refugees are is already an impediment for them to. Be able to successfully start businesses, uh, because then their services for business, uh, development are less. Um, uh, the ability for them to register businesses is, is limited because, uh, the service providers are not there. There are many other region, um, and sustainability of, of, of, of their businesses is also low, um. That would even be lower, uh, given the fact that even the survival rates of businesses in Uganda is already low. So we have to, uh, rethink, uh, as has been said before, some of the, um, um, opportunities, um. Uh, that don't, uh, require a lot of, uh, interventions, especially from the development or humanitarian entities, but can engage refugees, um, uh, independently and sustainably for them to be able to, uh, ablely, uh, operate in the labor market. There's been less, uh, impact, I think, uh, especially on the host community because there's less competition really in In the sectors that the refugees have been trained in, for example, the hotel, uh, sector, there's less competition there, but also the, uh, the, the, the, the sectors that the businesses are in are informal, so everybody's trying to survive in there, but there's not much impact in terms of negativity, um, for the host community. Um, I think that's, that's it from the Ugandan side. Over to you. Thank you very much, Emily. And by the way, I see that some, uh, one of our colleagues in the chat, uh, she, she posted, uh, some links related to what you were saying. So thank you very much to Bethelle. Um, and now we, we move from, from Uganda to, to Mexico. Uh, so Africa Sanchez, uh, also a colleague from UNHCR, the floor is yours. Thank you. So, we're going to talk a little bit about the inclusion and sustainable integration of refugee and asylum seekers in Mexico. Uh, since 2016, UNHCR has been implementing a relocation job placement, a local integration program. Uh, next slide, please. Um, we have This is an individualized integration program that provides an opportunity or support to integrate through formal labor market. The program includes transfer to 10 reception cities located in the center in the northern part of the country, where is a vast labor marketer. um, and there is a um higher capacity. Of absorption from the health and education system. The program also supports refugees and asylum seekers in the search and access to housing, as well as psychosocial support through the first year of integration. Uh, college support and accompany people through home visits and phone calls through the whole process of integration. And alongside, obviously, refugees and asylum seekers, we er build on the integration objectives, er where do you want to work, how do you want to live, if you have children, er, access to school, if you want to certify a skill or do vocational training. So these objectives are built together. Um, another important fact is the program is based on access to the labor market, which also allows to present an advocate and the retribution or contribution of refugees to the formal economy of the host country. For example, we have the 30,000 refugees, is this, these are the data to half of the year, um. Contribute to the economy with $8 million US dollars in tax contribution. This is far more of the budget of the local comma, the access to the The asylum system in Mexico, for example. And this has gave us an opportunity to construct alliances with the private sector, with local governments, uh, when we see a specific, uh, contribution to the economy. Uh, open relocation, we can establish that the gross salary earned by participants is around 200 $340 per month. And we, when we analyze the base list and the current tax miscellaneous as well as the calculation of participant contribution to the social protection system. Uh, we have this number, each participant contributes with $32 US dollars in income taxes, $24 US dollars in value-added tax, and $8 US dollars to the Mexican Social Security Institute. These are numbers that matters because they allow us to present a clear contribution of refugees to societies. Also, we know that refugees contribute on so different levels, but this has gave us an opportunity with the private sector. The context in Mexico is that we have a vast industrial corridor, er, many vacancies to be filled, so there is no competition with the local er citizens. This is the main factor that gave us an opportunity to work with the private sector. It has been 7 years, obviously, so this has been quite a work. We have work training with companies to present the documents that refugees have, the recognition of these documents, so we can guarantee the same conditions that Mexican citizens have when access job opportunities. We also worker companies give you the opportunity to start even without experience, er they have their own training process, er, but we also support vocational training and skill certification er for refugees to er improve the opportunities to access the formal labor market. We work with relocation because the main point of entering Mexico have the certain cities, and they, they don't offer as many opportunities. We have, uh, analyzed the context, economically, security, and socially, and these relocation cities offer opportunities to access the labor market. Education, er health system with er saturate the, the system, er, which also supports er er the work with communities. When you don't have competition that makes it a little bit easier, the, the process of integration. I think we will leave it here. Uh, this is, we have been implementing for 7 years, as I say, we work with uh companies, allied companies, as we call it. We have over 500 companies, um, over this, over these years, so I will leave it here. Thank you. Thank you very much, Africa. Thank you very much again, Mali, for uh bringing this uh field experience to, to us. Uh, I give again the floor to Jan and Kirsten for the last part of their module that is on cost effectiveness of job support. Uh, over to Kirsten, I believe. Thank you so much, Domenico. Thank you. And we're now moving into the last part of the training today. So we've now heard about at the beginning, the impacts on hosts and on those forcibly displaced and the labor market outcomes. We've now heard about what we can do in terms of policy. and in terms of potential interventions to improve those outcomes. And now heard about two examples from UNHCR from Uganda, as well as from Mexico as to what these interventions can look like and uh what potential impacts they might have. And now we're moving over to the last part on the cost-effectiveness of job support in context of conflict and of forced displacement. And this is based on work we've done in the last years as part of the Building the Evidence on forced displacement. And why have we done this work? Because we see that through impact evaluations and also through the RCTs that are now in the pipeline, we've really to build it, started to build some knowledge about what works in supporting jobs in context of conflict, but also, of course, displacement. Um, There's still a way to go, but definitely we have some evidence already as we presented and new RCTs coming. But we rarely pay attention to the cost of the supports. Um, so, um, we rarely include the cost effectiveness in RCT so far, and also the other literature that's out there does not really look at costs. While we Expect cost to be different in the context, of course, displacement. We expect the target group to be different, to have different needs, but also the surroundings to be different, especially where with IDPs we are in context of conflict, um, and, and the whole setting and framework conditions are different. And so why is it important, particularly in the settings? It's because there's such a huge need. So we put some numbers here on ***, where we see that in this, in this fragile context, um, we have a lot of support for jobs and youth entering the labor market, but if you see it in the terms of the numbers who are actually entering the labor market each year, it is a very small percentage that's actually covered by the support. And the same is true also for refugees. For example, if we look at the number of refugees that are hosted in low and middle-income countries, um, we see that support is not effi uh sufficient, so we don't only need to think about the potential impact of our support, but also about the costs, and this is what our study was all about. What did we do for this study? We collected data together with Oxford Policy Management from project documents and key informant interviews. In 6 countries. Where we covered forced displacement and non-forced displacement settings, as well as conflict and non-conflict and low and middle-income countries. And we covered FCDO, UNHCR, and World Bank projects. And we looked at all types of individual-level job support. So we did not look at the policy level here or on broader types of interventions, and then group them into stylized job support approaches. Yeah, and we already knew it was gonna be hard uh to measure cost, but we're surprised that it was even harder to expect it given how the reporting on projects is usually done regarding cost per outputs and per outcomes. Often, the data was not available. Even after we've kind of interacted with, with task team leaders and others in the organization. And also, even if there is more evidence on impacts, it's still not there for all interventions. So this is why then our sample diminished on what we're actually able to say about cost efficiency and cost-effectiveness. Um, so I'll hand over to Jan now to present you some results of what we found. Thanks very much, Kirsten. And so, this first slide just gives you some numbers on what different types of job support typically cost per beneficiary. So, you have the whole range there on the table, um, from the kind of support that we give to individual workers. So, capital support, these are usually cash grants or maybe they're packages for farmers, um, you know, the usual seed fertilizer tool kind of packages. Uh, job matching, um, more common in middle-income countries, of course, value chain support. So these are things like linking farmers, um, to, to food processing, for instance, or helping them access, um, markets where they can get a better return. Uh, labor intensive public works, of course, you know, very, very common modality of support, uh, especially in the kind of settings that, that we work on in low and middle-income countries, and then training. Um, why do we think this is relevant? Again, it's about the challenge of scale. Uh, we've all seen it, the needs are enormous, um, our budgets are limited, and we think this is a handy tool, uh, for somebody who's planning a project to understand how far can I get with that? How many people can I reach? Can I have an impact that's really going to make a difference in the big picture, um, for a, for a sizable group of, of beneficiaries. And so, just to point out a couple of uh features that we found in the data here. One is that the kind of capital support projects that try to help people essentially be self-employed, whether in farming or, uh, in urban services, tend to spend a lot less than the projects that are oriented toward training. And so it's just, just a fact to keep in mind, you know, it doesn't mean that one or the other is better, um, but it, it does matter for the reach of, of these projects. Um, a second point to highlight is that You know, sometimes we think it's strategic to work through firms, to give firms some kind of support, for instance, if they hire displaced workers, um, or to give them, you know, support to expand so that they can hire more workers. And it can be exactly the right choice, um, but these kind of projects do spend a lot. So, the typical beneficiary firm, Um, supporting one firm, one typical beneficiary firm costs about 75 times what it typically costs to support an individual worker. So, it just needs to get us thinking about how far can we get through this way. Do we think that giving that kind of support is going to then indirectly reach a lot of workers? It's going to create a lot of jobs or improve a lot of, um, a lot of existing jobs. Next slide, please. So that's just cost per beneficiary, what we sometimes, sometimes call cost, um, efficiency, but let's look at cost-effectiveness. So that is looking at the, the outcomes that these kind of interventions have generated, and then looking at how much was spent for each job created. Or how much was spent per dollar of additional income. You know, sometimes projects report one, sometimes they, they report the other. So this is really about how much does it cost you, uh, to get to the impact you're looking for. Now, one really important caveat here is that one job is not necessarily like another job. So you see right away in the top table, that public works spend by far the least per job. But that's because of the kind of job they create, right? So when you report the jobs you've created in public works, It usually means maybe, you know, somewhere between 2060, 80 days of manual labor, right, that pays something like the minimum wage, um, in, in the country that you work in. So, it's a fairly, um, basic level of job support, and that is why it is so, uh, so cost-effective. Um, comparing across the other important types of support, you see that training and capital support roughly spend similar amounts, um, Per job they create, and you can typically expect to break even maybe within 5 years with this kind of project. Now, here, the really important footnote is that, as Kirsten just explained, the impact evaluation evidence tells us that in many settings, It's more likely that you create a new job or a new kind of income generating activity through capital support than through training because the training, you always depend on whether there's demand actually for these kind of workers. Whereas with the capital support, um, there's kind of a broader road to self-employment that people can travel. So, If you create a new job through the, the project, uh, you undertake, it costs roughly the same, but keep in mind the evidence from impact evaluation and really ask, is there a credible path for the people who are trained to then also find employment. Um, the other thing to highlight here is that, um, Productivity support. So this is usually in agriculture, sometimes it's in food processing and related activities, is very, very favorable in terms of cost-effectiveness. So these are projects that tend to break even, uh, rather rapidly as you can see here. Uh, sometimes even within, within a year if, um, If they operate that quickly. Um, so, some encouraging evidence certainly for these kind of activities where there's a credible path. So in our context, where refugees can have access to land, um, or where there's a real chance for hosts to expand their, their activities in the food sector. Next slide, please. And here's just another look at support that we give through businesses and we've already said that generally we spend more per business, significantly more than we spend per individual, um, Beneficiary as, as is intuitive. Now, the cost per job created through these type of projects in the, the projects that we could review was about $14,000. Now, that's a very large number, right? So, so I think the message that we take away from that is in these kind of projects, we need to think very carefully about two things. One is the quality of jobs that are created through them. Maybe it's the case that, you know, you support businesses, they create jobs that are unusually good. Often, people are looking for, you know, steady wage employment that pay good wages, and it's something that's just hard to find, right? Let's say in a low-income environment where most people are self-employed. So, we need to think about the quality of these jobs. It's gonna be easier to break even with this kind of project if the quality is high. Um, the other thing is, What's the growth path? You know, so 14,000 is a lot, but maybe our support sets the business on a path where it keeps expanding in the future and it keeps hiring workers. And then again, you know, it's probably going to be much easier to break, to break even with this kind of project. But, Still, you know, for me, this was a striking number, and I think, uh, what I took away is that in the future, when we discuss this kind of job support, we really need to investigate our assumptions, you know, is it realistic that we can reach, um, the kind of outcomes that would, would warrant this kind of investment in job support. Uh, next slide, please. And I think this is you, Kirsten, right? All right, I'll hand over. Thank you. Thank you, Jan. And then Moving over, so Jan has presented the overall results and what we see. When we now zoom in on the context of conflict context, fragility conflicts generally, and forced displacement context more particularly, what we see is that they both favor simplicity in the capital and access to finance. Interventions. And this is why we see that the spending per beneficiary is lower for capital support than training across, um, contexts in generally, but even more so in the context of force displacement and, and, um, FCV. Um, because at the same time, we see that in forced displacement settings, It drives complexity in training projects and matching because we see that the training projects try to address often multiple challenges that refugees and IDPs face. They add to potential technical training projects. They add language skills. Sometimes they then, um, Also add um aspects of the legal framework. They help refugees get a work permit, for example, or there's also more psychosocial support that is added. So all of that then drives up costs. So what We overall see is that in the context of conflict, fragility, and forced displacement, this gap between what uh capital support and access to finance costs and what training costs kind of, uh, kind of widens. So what are the implications of everything we've uh presented so far? Is that, um, What Jan has already said, we have to assess ex ante when we are planning the cost-effectiveness of the interventions that we have. And it's important to consider and to be very clear about the assumptions that we're making and if they're sensible on the potential jobs and incomes that might be created through the interventions. And also what the productivity of the jobs will be, their quality. Also, what the potential externalities and additional benefits might be, especially if you're working with firms, if we're in value chain interventions, for example. But also if the jobs are are really additional, and if they will be sustainable or not. So this is not only to differentiate between public works and let's say a value chain or, or a firm uh level intervention, but also within other types of interventions. And we need to closely scrutinize the case for job support through training, as I think we've, we've said several times today to really see if, um, if the lack of skills is the binding constraints. We also think it's important to zoom in and to see if uh combining interventions is really needed and how many interventions need to be combined. We see particularly in these more complex situations, also enforced displacement. As I said earlier, that because beneficiaries face these different challenges, we tend to combine interventions, but this also increases costs. So we need to better understand and open this black box of combined integrated interventions to understand which ones are really needed, uh, and which ones are driving costs more than others. Um, as we've said, is in capital support to business activities, it's important to consider the merits and cost implications of working with firms of different size and capacity because then also the costs tend to increase, but also the potential impacts if, but we have to be realistic about what we might be able to achieve. And also because we had such a hard time pulling the data together for this, and I think it's important we learn further about these issues is that when we do our own monitoring and uh and evaluation and our interventions, that we really keep a clear track of cost per beneficiary and cost per outcome to then be really able to assess, so what was the cost efficiency, what was the cost effectiveness of these interventions, and to be able to compare. Now zooming in again on, on FCV and forced displacement contexts, we see that in FCV the macroeconomic instability, the insecurity, and the low capacity increase implementation costs. And we see that it is important to keep Keep objectives simple, and that we need to use approaches that have been tried and tested in such contexts. Um, and, yeah, because unforeseen things might happen. Things are already pretty complex, so we need to make sure our approaches do not add to that complexity. Um, also, we've seen that we might be cautious about large investments for firms because it is very hard in this contexts to do a cost, um, to do a, a due diligence process with firms. In the forced displacement context, I want to stress as my last point that the restrictions on labor market access also have an impact on cost effectiveness of our measures. They impact what types of interventions we can actually implement, and they also limit the impacts that these interventions can have. So it is therefore important also from a cost efficiency and effectiveness point of view to work on the legal framework where we can to promote cost savings and interventions. So I'll leave it here and hand over to Domenico. Thank you very much, Kirsten. Thank you very much, Jan. Uh, I've seen in the slides, there are the references and again, uh, just a quick reminder that all these, uh, references and materials will be posted online on the Building the Evidence on Force displacement page. Uh, this ends our session for today. So, Jan, Kirsten, thank you very much and let me extend uh again my, our gratitude to the Mali and Africa. Uh, as I said at the beginning, this is our, the last session also of our training program. So I would like to invite my colleague and friend Paula Eliche from the Building the Evidence on Force Displacement Program for a close to her closing remark. And thank you. Over to you, Paula. Thank you, Domenico, and yes, we, we had to be friends to, to come through this uh um 8 modules uh session. So in the end of it, we became friends. Um, so I'd like to conclude by uh mentioning we have a feedback form. Uh, we'd love to hear from you, uh, feedback about this today's session. And, uh, in general, and my colleague posted that in the chat. Um, we also have a website where we're posting today's recording, the presentation, and all the background materials. So that's also, that link is also in the chat. And we also have a website for the training program in general, so, uh, that is also available and is posted uh to the chat. Um So, uh, as, uh, as you've heard by now, um, this was the 8th and last module, uh, in our learning series, um, that we started in the end of September. Uh, so we hope that everyone that participated took, uh, uh, found this helpful, um, and also enjoyable at the same time. And, um, we also hope that for those of you preparing to the Global refugee forum, these, uh, these insights and evidence, um, were helpful. Um, Um, we will, uh, take this, uh, live sessions and turn them into an e-learning experience as well that will be ready in the beginning of next year. Um, and other similar programs may also be available in the future, so we welcome any feedback you have, comments, suggestions, uh, you now know us, so feel free to reach out to, to any of us, uh, myself or, or, or Domenico. Um, I would like to thank Domenico for the partnership in organizing this training program and then also from both of us, uh, we would like to thank everyone who has made this training possible. Thanks to the management of the Building the Evidence on uh Forces Placement Program and also to the management of the Joint Data Center of Owed Forces Placement and to our parent institutions, World Bank and uh UNHCR. And of course to um uh donors and to our respective donors. We're also grateful to all the instructors who have led the development and delivery of these 8 modules and to all the guest speakers who have participated in the various sessions. Our special thanks go as well to uh Dini Jalal who has led all the communication efforts, uh, for the program. Uh, Natalia Dimovska, who has supported all the technical logistics and beyond, and America Grau Vicente, who has curated our website, uh, Agnes Gaga and Katherine Perkins as well for constant support in, uh, in various domains. Um, and finally, to all of you that have attended these modules, uh, Um, for your active participation and, uh, your interest in our work. We encourage you to stay in touch, um, with any of us, as I mentioned, uh, you now know us. Um, and I'll conclude there and wish everyone a lovely evening and great rest of, uh, your day depending on where you join from. Goodbye. Thank you. Thank you. Bye-bye. Goodbye, everyone. Thank you so much. Thank you. Bye-bye. Bye.

showAllTranscripts

duration

PT1H20M45S

scene7File

worldbank/20231115-Module8-Jobs

scene7Domain

https://worldbank.scene7.com/

scene7FileAvs

worldbank/20231115-Module8-Jobs-AVS

title

20231115 Module8 Jobs

description

20231115 Module8 Jobs

showTimestampAndTranscript

yes

sec-spacing

section-none

sec-spacing-bottom

section-none

sec-swoosh

sec-swoosh-type16

style

default, transparent-white-components, heading-center, add-style, bg-primary-blue-70-gradient, bg-dynamic-height

col-xs-12

col-sm-12

col-md-3

col-lg-3

col-xs-12

col-sm-12

col-md-7

col-lg-7

add-style
lp-body-content

The 8th session of the Learning from the Evidence on Forced Displacement training program focuses on forced displacement and jobs. The module instructors present the global state of knowledge on the jobs impacts of forced displacement, examine new evidence for selected low- and middle-income countries, and summarize the impact of policies limiting or enabling labor market participation of refugees and present new evidence on the impact of work permits.

Speakers:

Jan von der Goltz - Senior Economist, World Bank

Kirsten Schuettler - Senior Consultant, World Bank

Line Astrom - Senior Livelihoods and Economic Inclusion Officer, UNHCR

Africa Coromoto Sanchez Briceno - Associate Durable Solutions Officer, Mexico City, Mexico

lp-heading-top-medium

lp-heading-bottom-medium

col-xs-12

col-sm-12

col-md-2

col-lg-2

sec-spacing

section-none

sec-spacing-bottom

section-padding-between

style

default, video-transcript

everything

https://webapi.worldbank.org/aemsite/everything/search

true

{"facets":[],"orderby":"contentDate desc","select":"*","searchFields":"*","search":"*","filter":"contentType eq 'Video'","top":20,"skip":0}

See Rest of Series

yes

sec-spacing

section-none

sec-spacing-bottom

section-padding-between

style

default, bg-neutrals-15-gradient, remove-border, lp-mini-card-primary

Video Module 8: Forced Displacement and Jobs

RELATED

See Rest of Series