 So the paper I'm going to present here is tentatively titled, Considering the Benefits of Hosting Refugees. Evidence from refugee camps influencing labor market activity and economic welfare in Rwanda. I should say this is a joint paper with Melissa and our colleague Ozgay Bill Gilley from Utrecht University. So before anything else, we should take a step back and say, why is this topic important? Motivating this study probably really isn't that necessary for the audience in this room. We all kind of know that displacement now is somewhat of a topic on high on the agenda. UNIX-ER annual update, it's highlighted that displacement continues to rise and remains at a modern day high, really, since record keeping began since World War II. So currently, we have about 66,000 million displaced individuals around the world. And about a third of them are refugees. Important and sometimes it's lost in the conversation is very important for us to kind of always keep note of the vast majority of these refugees moved to neighboring countries, never making it anywhere near, let's say, Western Europe and North America, even though in popular media, sometimes forget this. This typically somewhere between 84 and 89% depending on resources, say that refugees reside in low and middle-income countries and around 35% in fragile states. And beyond that, the third main point of why this topic is important in general is that it seems, at least depending again on your sources, that the length of displacement, the length of time in displacement is on the rise. So there's a need to consider not just the short-term effects of the refugee shock, but more importantly, the medium, longer-term effects that were some of the core development issues that we're all discussing. Following up on that, I think this map does a pretty good job of just kind of giving a geographic idea of where displacement by and large is taking place. So these are the top 10 countries of origin for refugees in the world today. This is just the statistics from the European Commission. And what we see is of the top 10, but seven of them, seven of them specifically, are located in their central or eastern Africa. So yeah, you get Congo, you have Sudan, you have Somalia, et cetera. So it's not just, you know, it's really important that this is clearly just countries of origin, but to think about those regions in general, given the fact that most refugees are staying in those regions, to really look at the effects of displacement on those refugees within those regions themselves. In this case, obviously we're on the falls within the region of. So with this paper in particular, what do we want to understand? Our main research questions are twofold. First of all, how do host communities adjust the market activity in the presence of refugees? And second, what are the consequences for the host communities in terms of that kind of goal? To do this, we use data from an original household and community survey collected in May of last year within refugee camps, three refugee camps in particular, and surrounding host communities at various distances through those places. To give you a quick preview of those results, on average, residing within 10 kilometers from refugee camp needs to increase wage employment for host community members. On average, residing within 10 kilometers from refugee camp needs to greater asset ownership for those same individuals. And females in particular, nearby camp, seem to be more likely to be self-employed. So this work really is speaking to a literature that isn't that long in the making and isn't that deep, but there are specific people including the likes of Isabelle here and Carlos that are very much trying to tackle this economic support migration type of issue and going a little deeper. Many of them are using this data set from Tanzania, from the Kagera region, but there are others as well. But in general, I guess, in this literature, what we can say is that there's a consensus, by and large, of the arrival of refugees, as the potential, at least, to breathe new life and dynamism into the local and regional economy. We can say that, yes, refugees come in, there are issues with supply and demand, there are issues with the local labor markets, there are adjustments, and there are lively activities that are created. There might be redistributive effects that need to be taken into account, but by and large, there's something happening once to see a population or a significant population move into America. The seminal paper by Chambers in 1986 really helped set the framework of how to look at some of these issues and frame the issue in a more nuanced way regarding unequal effects in the host community. So it's not just everyone may benefit or everyone may be hurt, but there are maybe specific parts or groups within that host community which might particularly benefit, make advantage of the benefits that are available. Whereas there might be others that are losers when refugee populations are distributed. Stemming from that paper, some of the papers, the more empirical papers looking at the specific objectives here or the outcomes that we're interested in here, specifically labor market and economic welfare. In terms of labor market, you have a few papers, one of them by Isabelle and her co-author Carlos, who find that locals face higher competition in general from refugees in certain sectors and are less likely to be involved in agricultural work or casual labor. And then another paper looking at Syrian refugees around the Turkish border from Tumen, you have this idea that NATO's informal employment declines with the presence of refugees while their formal employment rises. So again, you're seeing this kind of substitution effect once a population moves in with various skills. And then second, in terms of economic welfare, there hasn't been as much work I'd say in this area. Most of it has been on the labor market effects, but there are a few and by and large, we find that when a refugee population moves into an area that there are positive wealth effects, including particularly with regards to asset ownership and consumption. We'll just give you a little bit idea of the Rwandan context in particular. I'm not sure how many of you are aware of, everyone understands more or less the context of Rwandan and their genocide and their own issues of displacement, but Rwandan itself has been a country that has taken in quite a few refugees over the years. Today there are about 75,000 Congolese refugees in particular in the country, and the vast majority are in a protracted situation, meaning they've been living there for more than five years in one to five camps. We today will specifically be looking at three camps and I'll talk about them in a moment. Officially, and this is important for the premise of this whole entire study, is that Rwandan government has not imposed restrictions on Congolese refugees regarding their rights to work, their access to education, and their freedom of movement. So in principle, the Rwandan or the Congolese population is able to leave the camp, they're able to find work, they're able to access land if possible, they're able to access education. In practice though, the local integration of Congolese refugees still remains quite a big obstacle and especially in host communities has been a persistent challenge. And by and large, this is one of the main reasons for this. One, the limited nature of access to land, Rwanda is a highly, densely populated country and the land is somewhat limited, so for a Congolese refugee to come in and try to buy land is somewhat difficult, and at the same time, the restricted nature of just the local labor market. It's difficult for a Congolese refugee to find formal wage employment. So by and large, a lot of times, some of these populations have been there since the early, the mid to late 90s. They've remained dependent on humanity and within refugees. So as I mentioned, the three refugee camps that we are looking at here are Gehembe, Igheme and Giziba. The year establishment is there, so just give you an idea of how long they've been open. Basically, Gehembe was open in 97, Giziba in 96. It's important to note that 2012 has a little asterisk against it because Igheme originally was open in 1995 for the Burundian refugee population at that time. In 2009, that camp was decommissioned due to the Burundian population returning at that moment, but then the Wanda government decided to reopen the camp due to a new influx of Congolese refugees who were fighting in the North and South Tidway area around that time. In terms of the population, so you can see that the total population of these camps ranges from about 14,000 to about 19,000 individuals, so it's nothing to sneeze at. More importantly, in terms of the relative population of the local host communities, it ranges from about 9% to 19%. Again, these aren't huge numbers, but at the same time, they're not minimal either, so relatively they're a significant increase in population. In terms of our research design, so here's a nice little map just to give you an idea, geographic idea, where these camps are located within the country, so this is a map of the one that the administrative cell level, and so we specifically surveyed within each of those three camps, Yehanbae in the North, Yehanbae in the South, and Yeeva in the West, as the little yellow cell in the middle of those concentric circles. In the orange areas, we randomly surveyed households, so that's within 10 kilometers of that camp that we surveyed there, and then we also randomly surveyed in house, or randomly surveyed households in communities beyond 20 kilometers. So in a sense, what we're trying to do here is create this counterfactual scenario where we can compare households within 10 kilometers of the camp versus households outside 20 kilometers. As you mentioned, that 10 kilometer, 20 kilometer decision, it kind of stemmed from, well stemmed from the literature, stemmed from discussions with other researchers who were very much aware of this context, and also just some practical issues. I mean, basically when we talked to people about where refugees were interacting with local communities, they always said, you know, with local markets, and through the fact that there isn't much public transportation in this context, a lot of people get around just like food, or possibly by bicycle, it seems like most of the interaction would be happening within a 10 kilometer area in those local markets, whereas it was less likely, much less likely for refugees to be interacting with hosting these outside 20 kilometers. So following up on that, our empirical approach, generally as I said, is pretty straightforward. We're just going to report winner probability estimates of the main variable of interest, which is camp proximity. Again, this is just going to be a variable for whether the household is located within 10 kilometers, or whether the household is located beyond 20 kilometers from each camp. Plus, we want to look a little bit or dig into some of these heterogeneous effects. So we include interaction terms to identify some heterogeneous effects on even effects based on gender. We also look at camp-specific effects. And I don't think we're going to have time to think of camp-specific effects in this presentation, but it's in the paper if you're hearing. And then beyond just these baseline estimates, we also include a bevy of robustness checks, due to the potential for selection bias. I'm sure many of you have already been considering. So one thing is that there could have been, once these camps were established, there could have been local Rwandans who moved into these areas in anticipation of a booming local economy. To try to mitigate that, we limit our sample to only those people who were either born in the community that we're surveying or moved into that community prior to the establishment of the nearest community. In a sense, we're mitigating that positive self-selection. Secondly, you can imagine that these camps didn't just fall down from the sky. They were placed in certain areas for specific reasons, might affect our outcomes. In all our discussions with government officials, for example, to try to get at this why, why back in the early 90s, early to mid-90s were these camps located in this specific region. The main answer they got was, there was land available. Yes, why was there land available? It was just there was land available and that was the main thing. So thinking a little bit further about why much of the land available in the country that has such a high population density and has such a high restriction to the land access, we started thinking, okay, maybe it's because that land was in for a while, or maybe it was just less desirable than other areas that might have something to do with it. Kind of pulling on that thread and going beyond that, we're thinking about an instrument that might be able to proxy for agricultural conditions. We're here using a measure for long-term precipitation. Precipitation's right. This measure is based on data from NOAA. It is highly granular, so it's at the half degree by half degree, looking at long-term precipitation from 1984 to 1994, so for establishing those camps. And yeah, we use that as an instrument to try to understand a little bit about that selection in terms of the camp location. And then you might be thinking of, what about the exclusion criteria and that precipitation might have to do with your outcomes? Well, we also checked it against the 1991 census and we find and show you in the techniques, but we find NOAA's physical significant relationship between our outcomes. And then finally, we also take the 2012 census data and try to create an analogous of an analysis as we possibly can. So it's kind of similar of a setup of this within 10 kilometer versus outside 20 kilometer measurement to see what we find there and see if basically our results, using our data, for example, are robust. In terms of the outcome variables that we're really interested in, again, two main ideas that we really wanna get at here is labor market activity and economic welfare. In terms of labor market activity, we specifically look at primary daily activity and three specific categories of it that are mutually exclusive. So first wage employment, self-employment in business or self-employment in farming or livestock production. And then beyond that, you can imagine that many people, it's something our sample is about 75%, and official statistics is actually similar, that most people in this country are involved in farming or livestock production in one way or another. So we went a step further and said, okay, if those people are involved in farming or livestock production as a primary daily activity, what about secondary activities? Possibly, if a male-headed household is working on the farm and the female-headed household could be involved in a local shop or a local trading or something that could help supplement their weekly or monthly. And then in terms of economic welfare, we focus specifically on asset ownership. We generate an ownership index based on a long list of leisure items that I can also show you in the appendix if you're interested using multiple correspondent analysis. And we also look at a subjective measure of the current economic situation. Generally, this is just based on a five-point market scale where one is the most negative based with the household head of finding the situation very difficult, verse five, where they're finding it very difficult. So just to jump right into the scripted statistics of these outcomes, broken up or broken down by the distance to camp within 10 kilometers or outside 20 kilometers. Focusing first on primary daily activity, we find that there is a difference in terms of wage employment for those individuals. It's almost individuals, I should say wage-employed individuals residing within 10 kilometers of the camp are almost double to be involved in or double the likelihood of being involved in wage employment compared to those individuals wage employment outside 20 kilometers. They're also slightly higher to be self-employed in business. It's only a significant 10% level though. And obviously the difference is made up by those people outside 20 kilometers being more likely to be involved in farming or livestock farming. In terms of secondary activity, we find a difference in terms of self-employment in business. It's small, but it's significant. And then in terms of economic welfare, again, we find a positive and significant difference in terms of asset ownership as well as security. I won't go into different covariates that we include in our models, but I'll just highlight a few that I think probably are the most people think of when they think they can include models of these types. But one thing that we need to take into consideration is the distance to markets that this house will have. So obviously they're interacting with refugees, how far away they are to those markets is important. Also the distance to the local city, the nearest city. So obviously a household that's close to the secondary city with a more robust local economy is going to have an effect here. And then just in general community population. You can see that households outside of 20 kilometers are actually further away from the nearest market. Households outside of 20 kilometers are closer to the bigger cities, so the capital, Tagali, or secondary city, and the population is similar. So in terms of baseline results for primary daily activity, jumping right into the main results and main findings, here we find that residing within 10 kilometers of a camp versus residing outside of 20 kilometers, households are an individual, a wage employment individual, is 14% more likely to be involved in wage employment, about 7% more likely to be involved in employment. And we break this down by gender. So the way to read this is, that's why it's a female male here. It's females within 10 kilometers versus females outside of 20 kilometers. Both females and males within 10 kilometers are more likely to be involved in wage employment, whereas in terms of self-employment, only females within 10 kilometers of a camp that are more likely to be involved in self-employment. As for secondary activity, we find no results, no significant results when it comes to wage employment, based on distance, but here again with self-employment, we find something happening here with gender dynamic with females in particular, that females are 9% more likely to be involved in self-employment business as a secondary. That's based on people who are primary daily activity, farming, farming elastic. You can say that of these households that principally are involved in farming elastic production, some of these females are taking advantage of the fact of the increased population, potentially trading. In terms of economic welfare, we find a positive, specifically significant result in terms of asset ownership. So it's tough to interpret, because it's based on an index, but you can just say it's positive and significant, and we see across both email-headed households and mail-headed households where we go holds, and we find no result when it comes to that subjective measure. Moving on to the robustness check, so as I mentioned, we first took a limited sample to try to mitigate this idea that people could be moving into these areas after the refugee population arrived. And here, if we just look at the baseline figures that were to show you, compared to the limited sample, the results by large hold, so it doesn't seem like there is any positive selection happening or affecting our results. In terms of asset ownership, similar. The actual estimate reduces slightly, but qualitatively, there's no difference in terms of the two. Moving to the instrumental variable approach, again, using a long-term trend in precipitation. Hoping first on the first stage, we see that there's a negative relationship between precipitation for the long term over the last 10 years, compared to being located near a camp. So it seems like our premise, this idea that camps were located in places where potentially agricultural conditions were worse off, makes sense. And then once you apply the instrument to the second stage, the estimate jumps up quite high, but again, it's still qualitatively positive and significant. And then using the same setup for asset ownership, we find that this is a fiscal significance drops to a 10% level, but again, marginally significant. And then finally, using the 2012 census data, we find pretty much the same results. It kind of gives us a little bit more support to what we're finding with our own specific sample. Then we find a positive relationship when it comes to wage employment, both for females and households. We again find a positive relationship in terms of respect to camp proximity or self-employment as well. If you remember in the baseline results, this was only for females. Here we find it for both females and males. So there's a slight difference there, but again, it's pretty much supporting what we found. And then finally, I should mention that we also conducted focus group discussions to try to provide a little bit more nuance to some of the airborne estimates and provide a little bit more interpretation. I'm just gonna have a couple of minutes. We're gonna highlight a few. The first kind of speaks to this general effect and one participant, one responded in the host community outside of the MBA camps that since the refugees arrived here, economic activities have increased, many houses were built and selling activities were multiplied. There are different market centers which were created because of the camp. So in general, it just speaks to this idea that really something was happening at the local level once the refugee population began. Even further, talking to a refugee in Kaziba camp in particular, we mentioned when we first arrived, there were no businesses, but after our arrival, there are so many types of businesses, schools, no health centers. When we arrived, that's when everything started, life came, jobs were great. And it's just kind of supporting this idea that really the refugee population moving in is having an effect on us. And then finally, we don't touch it too much in the study anymore. We did an original version, but just trying to break it down into kind of the winners and the losers in the local population that there are uneven effects in different groups. One responded, host community responded outside the MBA camp that what we are aware of is that the wealthy people in this community take products to refugees camp because refugees are hungry and they have money. Products are bought here at a low cost and taken there for sale. Wealthy people in this community are the ones who take products. There. So again, it's not that everyone, for example, may be benefiting, it's that there are certain sections of society, groups of society that are really able to take advantage of the fact of these refugee population coming in. They might be just better located within the local economy, they might be more wealthy, et cetera. So yeah, we should just keep that in mind when we're talking about the average of that. So just to summarize overall, residing within 10 kilometers of refugee camp makes them more likely than individuals engaged in wage employment compared to farming or livestock production. Likewise, households nearby camp have greater asset ownership in comparison to those living beyond 20 kilometers. Specifically, we find that females and males both are more likely to be wage employed relative to the same gender counterparts to their way. Whereas females in particular are nearby camp, are more likely to be self employed both as primary and secondary activities. This really speaks to this kind of gender dynamic at play here that we've been wanting to take a little further into. And then you'll finally just to kind of talk a little bit about why we might be finding some of these things and what the implications they have. And in general, this is speaking to the literature as well. It's something that Isabelle has found in her own work and others as well. But refugees compete with native workforce for the native workforce for informal agricultural activities and potentially pushing natives into formal labor activities like wage employment or self employment business and formal and informal. But beyond that, the presence of the refugee population just more generally presents market opportunities, especially at the margin in terms of small scale trading, commerce, construction, even in working for a local NGO that moved in that certain members of the host population are able to take advantage of. And then finally, in terms of policy implications, in light of the refugee presence and despite their minimal formal integration, it appears to be, there does appear to be a local shift away from subsistence-based agricultural activities. And this is in line actually with the Rwandan government's vision 2020 plan. So that's something actually that they can kind of say that this is a helpful thing. And then following up on that, final notes, we might say, okay, considering these development-oriented facts or this narrative at play, it might be high time for policy makers or international organizations or you do it to a certain extent to really be considering these benefits that the refugee population might be bringing to the host. And in the sense that we can try to set policy and minimize the potential harm. And I'll leave it there. Thank you.