00:00 of you uh joining from other time zones.
00:02 Welcome,
00:03 uh,
00:04 to the learning from the Evidence of Force Displacement.
00:06 This is a training session on social cohesion in forced displacement context.
00:10 Uh,
00:11 this learning program was organized by the,
00:13 uh,
00:14 UK government,
00:14 UNHCR World Bank,
00:16 building the Evidence of Force Displacement Research Program
00:19 in collaboration with the,
00:20 uh,
00:20 World Bank,
00:21 UNHCR Joint Data Center on Force Displacement.
00:24 My name is Paula Eliche.
00:26 I am an impact evaluation specialist in the Building
00:28 the Evidence Program and the World Bank FCV Group.
00:31 I will be moderating today's training session,
00:34 as I mentioned,
00:35 uh,
00:35 on social cohesion in forces placement context.
00:39 This,
00:39 this is the 7th session in a learning program,
00:42 uh,
00:42 including 8 modules.
00:45 Uh,
00:46 before,
00:46 um,
00:47 introducing today's,
00:48 uh,
00:48 speakers,
00:49 I'd like to cover some logistical aspects.
00:51 Uh,
00:51 this session,
00:52 as you can see,
00:53 is being recorded
00:54 and we'll post the recording publicly on our website,
00:57 uh,
00:57 following the session.
00:58 The conversations instead of discussions that you will have in the breakout rooms,
01:02 uh,
01:02 will not be,
01:02 uh,
01:03 recorded.
01:04 Um,
01:05 you are encouraged to keep your camera on,
01:06 uh,
01:07 throughout the session and kindly,
01:08 um,
01:09 be sure to be on mute when you're not speaking.
01:12 We're going to have 90 minutes for the session.
01:14 Um,
01:15 you can use the chat to ask questions
01:17 as well as raise your hand.
01:19 Uh,
01:19 we will also have a dedicated,
01:21 uh,
01:21 uh,
01:21 time for the Q&A,
01:22 uh,
01:23 in the end of the session.
01:24 Um,
01:25 in case,
01:26 uh,
01:26 you're not already renamed,
01:28 uh,
01:28 please do it,
01:29 uh,
01:29 by right clicking,
01:30 uh,
01:31 using the three dots that are next to your name,
01:33 indicating,
01:34 uh,
01:34 your name and,
01:35 um,
01:35 and your affiliation.
01:36 And,
01:37 uh,
01:37 feel free as well to start using the chat to introduce yourselves,
01:41 uh,
01:41 tell us,
01:41 uh,
01:42 where you work,
01:42 uh,
01:43 which country you're joining from.
01:45 So this covers uh the logistical aspects of the,
01:48 of the session.
01:50 Um,
01:51 I'm now pleased to introduce our speakers,
01:53 um,
01:56 And,
01:58 here,
01:58 yes,
01:59 thank you.
01:59 Yeah,
02:00 if you could go to the,
02:01 uh,
02:01 perfect.
02:02 Here we are.
02:03 Um,
02:04 so today's speakers we'll have first Eric,
02:06 uh,
02:07 we both,
02:07 uh presidential Compact professor of Political
02:10 Science at the University of Pennsylvania,
02:12 founder of the Development lab at the University of Pennsylvania,
02:15 and co-director of the PEN Development Research Initiative.
02:19 We will then have uh Guy Grossman,
02:21 a professor of political science at the University of
02:24 Pennsylvania and co-director of the Development Research Initiative,
02:28 uh,
02:28 still at UPEN.
02:29 And our third speaker um is Gina Kuzmido Bradley,
02:33 Regional economist for West and Central Africa at the UNHCR.
02:37 Um,
02:38 so that gets us ready to start,
02:40 and I'm pleased to hand the floor over to,
02:42 to you,
02:42 Eric.
02:44 OK,
02:44 thank you,
02:44 Paula,
02:44 and thanks to everyone who is here in attendance.
02:47 Um,
02:48 I just wanna give you a really brief overview of how we're gonna organize this.
02:51 So I'm gonna,
02:52 I'm gonna start off,
02:53 um,
02:53 sort of presenting a little bit about the,
02:55 the scope of the challenge that we face in this,
02:57 uh,
02:57 in this context,
02:59 um,
02:59 talk a little bit about how we think of social cohesion,
03:02 uh,
03:02 to provide,
03:03 uh,
03:04 try to provide some precision around what I think is oftentimes a vague concept.
03:07 Um,
03:08 and then talk a little bit about,
03:09 um,
03:09 some key findings from a,
03:11 a very broad review of the,
03:12 of the literature.
03:13 And then I'm gonna turn it over to Guy.
03:15 Guy is then gonna walk us through in,
03:16 in some detail,
03:17 uh,
03:17 uh,
03:17 the Uganda,
03:18 uh,
03:18 a case study of Uganda,
03:20 where inclusive government policies have really facilitated,
03:23 um,
03:24 relatively good outcomes with regards to social cohesion.
03:27 And he will then,
03:28 we'll,
03:29 we'll take a,
03:29 a quick,
03:30 um,
03:32 Zoom break where we'll all have a conversation.
03:34 About what inclusive policies might mean in the countries that you work in.
03:37 Paula,
03:38 uh,
03:38 I'm sorry,
03:38 um,
03:39 Gina will then come back and provide us some,
03:42 some discussion of the application of research into her work
03:47 in,
03:47 uh,
03:47 Central and,
03:48 and East Africa.
03:49 And Guy's gonna come back once more.
03:52 He's gonna talk a little bit about how
03:54 to sort of,
03:55 uh,
03:55 build rigorous evidence into the design of policies bearing on forced displaces.
04:00 Um,
04:01 and then we'll wind down and,
04:02 and have a few minutes for Q&A.
04:04 So that's,
04:04 that's how we've organized things.
04:05 Um,
04:06 again,
04:06 I wanna thank you all for coming.
04:07 Um,
04:08 just,
04:08 just to give you a little bit of sense,
04:09 I mean,
04:10 you all are the experts in this area.
04:11 So,
04:12 so this slide is maybe not even necessary,
04:14 but I think,
04:15 um,
04:15 it's worth reiterating that,
04:17 you know,
04:17 we're,
04:17 we're living in a world where
04:19 the challenges of forced displacement and refugees are,
04:23 are,
04:23 are very,
04:24 very large.
04:25 So,
04:25 um,
04:26 at the end of 2022,
04:27 we're talking about 108.4 million um forced displaces.
04:32 Um,
04:32 and
04:33 there's a lot of concentration on how,
04:35 on these folks moving across borders,
04:36 but of course,
04:37 they're not all moving across international borders.
04:40 Um,
04:40 a lot of the,
04:41 a lot of the challenges come from a relatively modest number of countries.
04:44 So we're talking about 87% of,
04:46 of refugees worldwide coming from these 10 countries.
04:51 And of course,
04:51 the implication is that the challenge of forced displacement and of
04:55 refugees is greatest in these countries and amongst their near neighbors.
04:59 But of course,
05:00 not,
05:00 not only so,
05:01 um,
05:01 so we have,
05:02 for instance,
05:03 a growing number of,
05:04 um,
05:04 Venezuelan refugees in
05:07 uh Peru and in Chile,
05:08 and in the United States.
05:09 And in fact,
05:09 my wife works on,
05:11 um,
05:11 refugee resettlement in the US and works with
05:14 All of these populations,
05:16 and,
05:16 um,
05:17 and working with uh resettling refugees in the,
05:20 in the US.
05:22 It is worth emphasizing,
05:23 and I,
05:24 I mean,
05:24 this is something that I learned over the course of this,
05:26 of this project.
05:27 So as a political scientist,
05:28 I tend to focus on,
05:30 and political scientists in general tend to focus on
05:32 the role of conflict in generating
05:34 um forced displacement.
05:36 And certainly,
05:36 there's an awful lot of conflict-induced forced migration.
05:40 You can see this at the,
05:41 the bottom here.
05:42 So we're talking about currently 28.3 million
05:45 um uh forced displaces as a result of conflict.
05:49 But
05:50 But
05:50 when we look over the medium term,
05:52 and we look now,
05:53 what we see is,
05:55 in fact,
05:55 there are more folks being displaced by,
05:58 um,
05:59 by disasters than by violence.
06:01 And,
06:02 you know,
06:02 one of,
06:02 one of my other projects is a,
06:04 is a project called Machine Learning for Peace,
06:05 and one of the things that we do is we,
06:07 you can think of this as a,
06:08 uh,
06:09 a Social cohesion,
06:10 almost real-time monitor.
06:12 We see many,
06:13 many,
06:13 many cases within countries where local reporting is really about displacements
06:17 and the,
06:18 the local,
06:19 um,
06:20 the local sort of conflicts that are oftentimes induced by,
06:23 um,
06:23 by these disasters,
06:24 oftentimes and increasingly
06:26 from climate-related displacements.
06:29 OK,
06:30 so this brings us to um
06:32 to the issue of social cohesion.
06:33 And here I've,
06:34 what we've given you here is a,
06:35 is a definition.
06:36 I'm just gonna read it,
06:37 and then I'm gonna explain why I think it's important.
06:40 So,
06:40 social cohesion,
06:41 we define this as a sense of shared purpose,
06:43 trust,
06:43 and willingness to cooperate
06:45 among members of a given group,
06:47 between members of different groups,
06:48 and between people
06:49 and the states.
06:51 And I guess the,
06:51 in the big picture,
06:52 like a lot,
06:53 an awful lot of the research on uh refugees and displaced populations
06:57 has focused on the characteristics of those individuals and those households.
07:02 And I think that what's distinctive about the focus on social
07:05 cohesion is that we're really talking about relationships among people.
07:08 We're talking about relationships
07:10 among
07:10 the displaced,
07:12 between the displaced and their host populations,
07:14 and between
07:15 uh the displaced and,
07:17 and hosting states.
07:19 And this,
07:19 I think,
07:20 um,
07:20 has implications for everything from how,
07:22 like,
07:23 if we think about social cohesion as being important,
07:25 um,
07:26 then it has implications for how we think
07:27 about policy interventions and how we collect data,
07:30 i.e. we're really interested in relationships among people.
07:33 Um,
07:34 social cohesion,
07:35 as the second bullet bullet point emphasizes,
07:38 is,
07:38 is a,
07:39 is a concept that really emerges out of a bunch
07:40 of different academic disciplines and areas of applied research.
07:44 And this is,
07:45 I think this is just a function of the fact that social cohesion is,
07:47 is impacted by a bunch of different kinds of relations,
07:51 economic relationships,
07:52 family relationships,
07:54 social networks,
07:55 all of these sorts of things come together and provide insights into
07:58 um the origins of,
08:00 of social cohesion and the conditions under which it can break down.
08:03 Um,
08:04 the dimensions of social cohesion,
08:06 norms of cooperation,
08:07 interpersonal trust,
08:08 collective action,
08:09 civic engagement,
08:10 these have big implications for all manner of,
08:13 of aspects of development.
08:16 Um,
08:16 and it's everything from,
08:18 from very,
08:19 you know,
08:20 micro micro things like the management of borewells,
08:23 or the nature of exchanges in markets,
08:27 all the way to the health and,
08:29 and sort of capacity of a,
08:31 of a national democracy.
08:33 So this is something really,
08:34 really big,
08:34 and it requires a,
08:35 a sort of a reframing of the lens from just the individual
08:39 to the relationships between individuals and,
08:41 and the broader society.
08:44 Um,
08:44 so it,
08:45 it is,
08:45 it is that definition that sort of informs,
08:48 um,
08:48 a,
08:48 a large project that we did,
08:50 um,
08:51 with the bank
08:52 in partnership with FCDO and,
08:54 and UNHCR.
08:56 And of course,
08:56 these are,
08:57 these are organizations that are,
08:58 that are focused on building out how humanitarian
09:01 relief and development investments can reduce
09:03 inequalities and promote social cohesions and,
09:06 in context of,
09:07 of,
09:08 um,
09:09 large movements,
09:09 um,
09:10 of,
09:10 of the displaced.
09:12 And just to give you a little bit of background,
09:14 um,
09:15 about 2 years ago,
09:16 folks from the World Bank came to me and a few other
09:18 academics with the idea of we really need to learn what,
09:21 sort of what the frontier of knowledge is.
09:23 This process resulted in a,
09:25 in a request for proposals.
09:26 We got a lot of proposals,
09:28 and we
09:29 selected out of that,
09:31 uh,
09:31 sort of a competitive process,
09:32 generated 26 papers
09:34 on lots of different countries,
09:35 which is what you can see in this map,
09:37 um,
09:37 a global report that tried to syn synthesize.
09:40 all of that.
09:41 And I would say we,
09:42 you know,
09:42 the,
09:43 the evidence that we are drawing on is not just that extensive effort.
09:46 It's also a,
09:47 a,
09:48 a booming,
09:49 um,
09:50 area of,
09:50 of sort of academic research.
09:53 So we're bringing all of that in as we,
09:54 as we try to summarize the state of knowledge.
09:58 And here's the big picture.
09:59 Um,
10:00 let me just,
10:01 let me just,
10:01 you know,
10:02 I'm gonna walk you through these three key findings in a little bit of detail.
10:06 Um,
10:06 but the first big one is that displaced
10:08 people and migrants often elicit negative attitudes from,
10:11 from host citizens.
10:13 Um,
10:13 this is something that we see from many,
10:14 many,
10:14 many settings,
10:15 but it is not always the case.
10:17 Um,
10:18 and the factors that affect the responses are complex.
10:21 Now,
10:21 oftentimes,
10:22 when academics say things like responses are complex,
10:24 it sounds like anything goes.
10:26 And I would say we're not in In a situation where we,
10:28 like,
10:28 we have a lot of systematic knowledge here,
10:30 i.e.,
10:31 if,
10:31 um,
10:32 if you have a lot of
10:34 uh interactions in informal,
10:36 uh,
10:37 unskilled labor markets
10:39 between hosts
10:40 and
10:41 the displaced,
10:42 you're more likely to get,
10:43 um,
10:44 sort of
10:45 biased or discriminatory interactions.
10:47 OK.
10:48 So,
10:48 um,
10:48 the factors are complex.
10:50 That's not to say that anything goes.
10:51 It's,
10:52 we,
10:52 we,
10:52 we,
10:52 we've learned a lot about the kinds of things that condition negative responses.
10:56 We have,
10:58 we have
10:59 case study,
10:59 I would say,
11:00 examples of when,
11:02 um,
11:03 the arrival of refugees have negative economic consequences on
11:07 displaced,
11:08 uh,
11:08 on host populations.
11:10 Um,
11:11 but,
11:12 uh,
11:12 as I'll talk about in a minute,
11:14 those findings are relatively narrow and short term.
11:18 That there are oftentimes positive impacts of the arrival of refugees.
11:23 Um,
11:24 and one of the things that we're trying to figure out is what exactly are
11:27 the conditions under which you get the
11:28 positive or the negative versus the negative.
11:30 Over the medium to long term,
11:31 I just want to emphasize that we tend to see
11:34 the res the negative effects washing away and disappearing.
11:38 Um,
11:39 and then the third key point,
11:40 and this is what Guy is really gonna talk a bunch about,
11:42 is that we have a,
11:43 a growing body of evidence
11:45 that,
11:45 that governments can,
11:46 governments
11:47 and multilateral institutions
11:50 and bilateral donors can make a positive impact here that There are policy tools
11:55 that can promote
11:56 um inclusivity.
11:58 And interestingly,
11:59 one of the things that is showing up again and again is that in many cases,
12:03 there are not political costs to providing
12:05 those more,
12:06 um,
12:07 those more inclusive policies.
12:09 And these,
12:10 these things make for better outcomes for refugees,
12:12 and oftentimes they facilitate better outcome for host citizens as well.
12:16 OK,
12:17 so turning to the,
12:18 to the first bullet point on the previous slide,
12:20 um,
12:21 so it's undoubtedly the case that we see that migrant,
12:24 that when you see the,
12:25 the arrival of a large number of migrants,
12:27 this can increase everything from anti-immigrant violence
12:30 to support for right-wing polic uh,
12:31 uh,
12:32 parties and policies.
12:34 And these findings are pretty broad.
12:36 Um,
12:36 there's the,
12:37 probably the,
12:38 the tightest evidence comes from,
12:40 um,
12:41 high-income countries,
12:42 especially Western Europe,
12:43 I would say.
12:43 Say,
12:44 but this,
12:44 I think is just a function of the fact that that's where the data is the best.
12:47 In general,
12:48 I would say that this is,
12:49 this is something
12:50 that is fairly general.
12:51 And a recent meta-analysis finds that a 1% increase in the share of immigrants
12:56 in a European locality
12:58 is associated with a 0.57% increase in the vote share of anti-immigrant
13:03 parties.
13:03 Now,
13:03 that's not,
13:04 obviously,
13:04 that's not a gigantic effect,
13:06 but that is an effect.
13:07 So I think we need to be aware that this is a real thing.
13:10 Um,
13:10 and And at the local level,
13:12 it can be substantively important.
13:14 But it's also worth
13:15 um recognizing that these attitudes towards
13:18 migrants and refugees are really heterogeneous.
13:20 They're heterogeneous within countries and
13:22 they're heterogeneous across countries.
13:24 Um,
13:25 so,
13:25 for instance,
13:26 um,
13:26 this,
13:27 this 2016 paper
13:29 by Bn et al.
13:30 shows that,
13:31 um,
13:31 amongst Western European respondents and surveys,
13:34 there's clearly a bias against,
13:36 um,
13:37 Muslim refugees.
13:38 So there,
13:39 there's some,
13:39 there's some religious aspect to this,
13:41 but it's really,
13:42 um,
13:44 um,
13:44 there are a number of,
13:45 I think,
13:46 relatively clear,
13:48 um,
13:49 findings at this point
13:50 on the kinds of factors that condition the negativity of the response.
13:54 And knowing those things ex ante can have,
13:56 uh,
13:56 you know,
13:56 can,
13:57 can help drive
13:58 the formulation of,
13:59 of policies.
14:00 Um,
14:00 and in fact,
14:02 Axwei and Jin,
14:03 and this is a paper that appeared in the,
14:04 in the volume.
14:05 That we put together with the bank show that on average,
14:08 the volume of refugees
14:10 um has no impact on attitudes towards,
14:13 um,
14:13 uh,
14:14 refugee populations and immigrants in across low and middle income countries.
14:18 So they do this for a large,
14:19 large,
14:20 large number of countries.
14:21 And on average,
14:22 they just don't find that much.
14:23 So I,
14:24 I think,
14:24 um,
14:25 you know,
14:25 that's really important because
14:27 what we see is that the number of
14:28 people experiencing displacement in OECD and non-OECD countries,
14:33 like,
14:33 There's a lot of research on the OECD cases because there's a lot of data.
14:37 The non-OECD cases is where a lot of the displacement
14:41 is happening and where many of the displaced are going.
14:44 And um it is in that set of cases
14:46 where we find on average that we don't
14:48 have a really strong negative impact on attitudes.
14:53 OK.
14:54 Second,
14:55 uh,
14:55 2nd major
14:57 takeaway from the evidence,
14:58 I would say,
14:59 is that the economic consequences of forced displacement
15:02 are,
15:02 are really varied and context-specific.
15:05 I want to emphasize again that this doesn't mean that we,
15:07 that anything goes,
15:09 like,
15:09 I think we have a relatively clean set
15:11 of findings at this point that are consistent with
15:13 basic microeconomic models of how local labor markets work.
15:17 Um,
15:17 so for instance,
15:18 we can point to particular cases like the impact of Syrian refugees in Turkey,
15:23 where there are some negative impacts on employment among native,
15:28 uh,
15:28 Turkish workers.
15:30 But these,
15:30 these negative findings are very concentrated.
15:33 We're talking about
15:34 workers in the informal sector,
15:35 less educated workers,
15:37 young workers,
15:38 workers in construction,
15:40 and part-time and self-employed.
15:42 Women.
15:42 So that's a,
15:43 that's a lot of different kinds of workers,
15:45 right?
15:45 But um it's not all Turkish workers.
15:47 This is not,
15:48 uh,
15:48 this is not,
15:49 uh,
15:50 job displacement
15:52 on the order of,
15:53 uh,
15:54 you know,
15:54 everyone across the economy.
15:56 And it is,
15:57 and I would say that for every case,
15:58 like,
15:59 like the evidence from Turkey,
16:01 um,
16:01 we can point to other evidence such as that in
16:03 the Roger et al piece showing that Venezuelan refugees improved.
16:07 Actually associated with an increase in employment.
16:09 And you might say,
16:10 well,
16:10 why would you get that in one case and not the other case?
16:12 And I think the key here is what is the,
16:14 what is the,
16:15 what is the nature of the skills and level of education of the displaced
16:19 relative to the host population?
16:21 That is one of the things that's gonna
16:22 have implications for the extent of labor market competition
16:26 and impacts on,
16:28 on sort of the employment effects for,
16:30 for hosts.
16:31 Um,
16:32 unsurprisingly,
16:33 we can see some short-term increases in,
16:35 in some prices.
16:36 So housing expenditures,
16:38 um,
16:38 have gone up for Jordanians as a result of,
16:40 of,
16:41 uh,
16:41 millions of,
16:42 of refugees.
16:43 I want to emphasize here that
16:45 this doesn't,
16:45 um,
16:46 this,
16:47 this is reflected in increased incomes
16:49 for owners and,
16:51 and those who,
16:52 who do the renting,
16:53 right?
16:54 So that can also incentivize the building of more housing.
16:58 Right?
16:58 So,
16:59 if you have owners that are making more money via rent,
17:02 then increased rents might increase the supply of
17:04 housing over the medium and long term.
17:06 And this is just a a specific way of emphasizing again,
17:09 that any short-term negative effects
17:11 oftentimes seem to peter out over the medium term.
17:15 OK,
17:15 we see the same sort of things when it comes to wages,
17:17 consumption,
17:18 and poverty.
17:19 We,
17:19 so,
17:20 among,
17:20 for instance,
17:21 Colombian workers who are most exposed
17:24 to low-skill
17:26 competition from Venezuelan refugees,
17:28 we see reduced wages,
17:30 OK.
17:31 But in In a case like Peru,
17:32 where we think that it is relatively better off and better educated,
17:36 um,
17:37 Venezuelan refugees who are arriving,
17:38 i.e.,
17:39 they can make it farther to Peru,
17:41 not just to neighboring Colombia.
17:42 We see,
17:43 we see that we don't get the same kinds of competitive effect on,
17:47 on reduced wages.
17:49 Um,
17:49 and we can find similar kinds of,
17:51 of findings from a lot of different,
17:53 a lot of different places.
17:54 Uh,
17:54 we point here to this review piece.
17:56 This is the Journal of Development Economics.
17:58 Um,
17:59 the most recent,
18:00 uh,
18:01 World Bank annual development report
18:04 does also a great job of reviewing the literature.
18:06 And again,
18:07 I just want to emphasize the key takeaway being that in the short term,
18:09 there might be some negative effects.
18:11 Over the medium and long term,
18:12 those negative effects tend to disappear.
18:14 And there is a growing body of evidence that there can be positive effects.
18:19 Um,
18:19 the,
18:20 the oftentimes,
18:21 the,
18:21 the economic effect of refugees and,
18:24 and displacement
18:25 sort of is conflated with a set of cultural concerns.
18:29 And I guess here I just want to emphasize that these are,
18:31 these can be,
18:32 you know,
18:32 it's worth distinguishing,
18:34 distinguishing these things,
18:35 especially for folks that are responsible for
18:37 formulating policies on the ground.
18:39 So the economic concerns
18:41 are,
18:41 are the typical ones one gets that refugees and migrants are
18:45 depressing wages.
18:46 Competing for jobs,
18:47 that they're draining the welfare state,
18:49 not just the welfare state,
18:50 but for instance,
18:51 um,
18:51 that they're getting benefits from UNHCR,
18:53 um,
18:54 when,
18:54 when host populations are not.
18:57 Concerns that refugees and migrants are overwhelming public services.
19:00 I would also emphasize that in some cases,
19:02 Guy and I are doing some work now in Uganda,
19:04 where there's actual
19:05 concerns about competition for local resources,
19:08 things like firewood.
19:09 These are sort of very typical economic concerns.
19:12 These are
19:13 Different than these sort of very symbolic concerns
19:15 about ways of life and status competition,
19:18 and um issues of
19:20 um different notions about the status of women in families,
19:23 about child marriage,
19:25 about all sorts of,
19:27 about,
19:27 you know,
19:27 uh,
19:28 perceptions or misperceptions,
19:30 on cleanliness.
19:31 These things bear on
19:33 a different set of issues than the economic ones
19:36 that I,
19:37 that we just presented on,
19:38 or that I just presented on.
19:41 Third and finally,
19:42 and I'm,
19:42 this is gonna sort of be the beginning of me passing this over to Guy,
19:46 we have a growing body of evidence
19:48 that,
19:48 that inclusive policies on the part of host governments
19:53 can produce better outcomes.
19:55 OK.
19:55 And,
19:56 and,
19:57 I mean,
19:57 there's really no need for me to walk through this first paper.
19:59 Guy's gonna walk through this in more detail,
20:01 but basically,
20:01 they show that
20:03 areas where you have more refugees.
20:06 have better services.
20:08 And the reason they have better services is because the,
20:11 the Ugandan government has pursued a set of policies
20:13 to provide better services to communities that are hosting a lot of refugees.
20:18 The implication of that is that you have school and health and health utilization,
20:23 and all other sorts of outcomes improving
20:25 in cases,
20:26 um,
20:27 in,
20:27 in,
20:28 in these communities.
20:29 OK.
20:29 And this is
20:30 This is part of what is sort of helped ease
20:34 the potential competition
20:36 between refugees and host
20:38 over,
20:38 over,
20:39 over local services and,
20:40 and local resources.
20:42 I do want to emphasize that in the,
20:44 in the volume,
20:44 we also have a,
20:45 a pace by Ellie Muard,
20:47 which looks at the long-term impacts of these kinds of policies
20:50 in the context of
20:52 uh more than a million Greek Orthod.
20:54 Orthodox refugees from the 1920s back to Greece.
20:58 And she,
20:58 and she shows
21:00 not just that you get these relatively nice
21:03 economic outcomes,
21:04 but you also get um much more social integration
21:08 as a result of these kinds of policies that allowing for the ownership of land,
21:11 allowing for work,
21:12 these kinds of things really have not just short-term implications,
21:15 but very positive long-term implications for social cohesion.
21:19 Um,
21:19 and,
21:20 and finally,
21:21 I just want to emphasize that
21:23 the Axo and Jin piece that I,
21:24 that I mentioned earlier.
21:26 Um,
21:27 shows that on average,
21:28 these more inclusive policies are not associated
21:31 with more negative attitudes towards refugees.
21:34 OK.
21:34 So,
21:35 so it's not the case that if the government provides more to refugees,
21:37 that this is necessarily gonna elicit a negative response,
21:41 um,
21:41 from host citizens.
21:43 OK.
21:43 And,
21:44 and so this is,
21:44 this is sort of a hopeful place to,
21:47 to sort of leave the literature and move forward into the question of
21:51 How might one go about improving social cohesion
21:54 in
21:55 conditions where there are lots of forced displaces.
21:58 And I'm just gonna very quickly,
22:00 this is a,
22:00 this is 5 points that came out of our summary of the,
22:04 of the World Bank volume.
22:06 I'll just go over this very quickly before turning things over to Guy.
22:09 And,
22:09 and basically what we saw as we looked across these 26 papers,
22:13 is that um
22:16 We have to think about the impact of displacement on social cohesion
22:20 amongst the displaced,
22:22 right?
22:22 And we have to think about the impact
22:24 on attitudes and behaviors of host communities.
22:27 OK,
22:28 so,
22:28 so this is,
22:29 um,
22:29 we have two populations that we're concerned with here,
22:32 not just the displaced.
22:34 Um,
22:34 and we,
22:34 you see over and over again,
22:36 and again,
22:36 I want to emphasize that this isn't wishy-washy,
22:39 everything goes in different contexts matter.
22:42 We have a pretty
22:43 decent and growing understanding about the,
22:45 the pre-existing socioeconomic conditions and attitudes
22:48 in host communities
22:50 that,
22:50 that moderate the impact of displacement on social cohesion.
22:55 OK.
22:56 Fourth,
22:57 the presence of displaced populations in host communities
23:00 drives socioeconomic socioeconomic conditions of some host groups,
23:04 and thereby impact social cohesion.
23:06 So to the extent that governments can can invest in local communities,
23:10 this is going to have implications
23:12 for um not just
23:14 the displaced,
23:15 but also for host communities,
23:17 and ultimately for,
23:18 for social cohesion.
23:19 And the last point here is that policy interventions
23:22 designed to influence the economic conditions and refugees.
23:25 Um,
23:25 and,
23:25 and,
23:26 and hosts
23:27 are both gonna be impacting social cohesion.
23:29 So I think the tendency is to think
23:31 of these policies as impacting the direct recipients,
23:34 i.e. the refugee,
23:35 but these things oftentimes they're gonna have
23:37 spillovers between the refugee and the host communities
23:39 in ways that are important for social cohesion.
23:42 So with that,
23:42 I'm gonna,
23:43 I'm gonna say thanks again,
23:44 and I'm gonna hand things over to Guy.
23:46 And Guy,
23:47 I'm gonna,
23:48 Guy,
23:48 do you want me to leave the slides,
23:49 or do you wanna put your own slides up?
23:56 Guy,
23:56 you're muted.
24:07 Guy,
24:07 you're muted.
24:08 Oh,
24:09 am I still muted?
24:11 No,
24:11 you're good now.
24:12 No,
24:12 no,
24:12 I'm good.
24:13 OK,
24:13 let me just share my screen.
24:17 Can you see my screen?
24:20 Are we good now?
24:23 Uh,
24:24 I can't see it yet,
24:25 but I think it's
24:26 coming,
24:27 coming.
24:28 OK.
24:29 Yeah,
24:30 I'm good now.
24:31 Can you see my screen?
24:33 Yes,
24:33 guy,
24:33 we can.
24:34 Thank you.
24:35 OK,
24:36 thanks.
24:36 So
24:37 Eric,
24:37 thanks so much for,
24:39 uh,
24:39 you know,
24:39 setting the,
24:40 the
24:41 Uh,
24:42 you know,
24:43 setting the scene for the discussion
24:46 about,
24:46 uh,
24:46 how to improve social cohesion.
24:48 Um,
24:49 and before we go into,
24:51 uh,
24:52 different types of,
24:53 uh,
24:53 different types of,
24:54 uh,
24:55 uh,
24:56 policies,
24:57 uh,
24:57 and types of intervention,
24:58 I also wanna kind of,
25:00 uh,
25:00 you know,
25:00 I think it's,
25:01 it's good to start with,
25:02 uh,
25:03 just
25:03 laying down some fundamental,
25:06 uh,
25:06 uh,
25:07 tension or interpersonal,
25:08 intertemporal tension that,
25:10 that all
25:11 Uh,
25:13 uh,
25:13 countries that host refugees,
25:15 uh,
25:16 might face,
25:16 and this is the idea
25:18 that we know that in the kind of longer term,
25:20 uh,
25:21 hosting refugees carries quite a few benefits,
25:24 uh,
25:24 if you look at like the,
25:25 the fiscal,
25:26 uh,
25:26 benefits of like,
25:28 uh,
25:28 the cost of hosting versus the,
25:30 the net,
25:30 uh,
25:31 uh,
25:31 positive,
25:32 the.
25:32 The,
25:32 the,
25:32 the,
25:33 uh,
25:33 the net benefit to the economy,
25:35 uh,
25:35 in the long run,
25:36 uh,
25:36 refugees,
25:37 um,
25:38 uh,
25:38 a net positive,
25:39 and this has been shown in,
25:40 in a large number of studies,
25:41 but in the shorter term,
25:43 uh,
25:43 in the immediate term,
25:44 obviously there's,
25:45 there's quite a bit of cost
25:46 to,
25:47 to the host community.
25:48 Eric mentioned them.
25:49 Uh,
25:49 in,
25:49 in his,
25:50 uh,
25:50 in his,
25:51 uh,
25:51 uh,
25:52 presentation,
25:52 this could be pressure on,
25:53 on social services like health and education,
25:56 so congestion of services
25:58 could be pressure on,
25:58 on housing,
25:59 it could be like short-term,
26:01 uh,
26:01 inflation,
26:02 um,
26:03 and so when we,
26:04 when we think about the fact that the,
26:05 and,
26:06 and a lot of our discussion is
26:07 about this relationship between host communities and,
26:09 and refugees,
26:10 part of the tensions that we
26:12 We face some,
26:13 some of the hostility,
26:14 uh,
26:15 uh,
26:15 might be because of,
26:17 uh,
26:17 the fact that we are,
26:18 we're focusing,
26:19 uh,
26:19 so intently on,
26:20 on the short term,
26:22 uh,
26:23 and,
26:23 and,
26:23 and we know that,
26:24 uh,
26:25 you know,
26:25 rising,
26:26 uh,
26:26 uh,
26:26 commodity prices,
26:27 rising rent,
26:29 uh,
26:29 competition on,
26:30 on natural resources,
26:31 competition on the labor market
26:33 can increase prejudice,
26:34 they can increase hostility,
26:36 and at time they can also generate some violence and so the question
26:39 then becomes
26:40 what,
26:41 what can we do?
26:42 So,
26:42 I'm gonna walk you through 4
26:45 types of interventions that we have identified as uh
26:48 promising to
26:50 improve social cohesion,
26:52 um,
26:53 and we're gonna separate between uh 22 kind of
26:58 uh metatypes.
26:59 Uh,
26:59 the first two,
27:01 intervention that we're gonna be discussing are ones.
27:04 Um,
27:04 that we can put under,
27:06 uh,
27:06 the rubric of inclusive,
27:08 uh,
27:08 uh,
27:09 hosting,
27:10 uh,
27:10 policies,
27:11 uh,
27:11 and this will,
27:12 uh,
27:12 pertain,
27:13 uh,
27:14 both
27:15 to,
27:15 uh,
27:16 policies
27:17 that ensure
27:18 that the,
27:19 the benefits or the,
27:20 the aid that,
27:21 uh,
27:21 uh,
27:21 goes to hosting refugees is shared widely also with the local population.
27:26 And
27:26 uh another set of,
27:27 of policies that we will,
27:29 uh,
27:29 we will,
27:30 uh,
27:30 put under the rubric of inclusive,
27:32 inclusive refugee policies
27:34 speak more
27:35 to
27:36 the policies that you can put in place
27:38 to support the uh economic integration of displaced people,
27:42 and we're gonna
27:43 show that
27:44 as Eric hinted before that they,
27:46 they don't only have
27:47 uh benefits
27:48 to,
27:49 uh,
27:50 to
27:51 the econ economic standing of refugees,
27:53 but they also improve
27:54 the relationship between
27:56 uh uh refugees and,
27:58 and the local population.
28:00 Uh,
28:01 and so,
28:02 uh,
28:02 both the,
28:03 the,
28:03 the,
28:03 the,
28:03 the first,
28:04 uh,
28:05 uh,
28:05 uh,
28:05 type of policies and the second type of policies
28:07 we're gonna put them under,
28:09 uh,
28:09 this rubric of inclusive refugee policies.
28:11 I will just mention that these are,
28:12 these are policies
28:14 that,
28:14 uh,
28:15 uh,
28:15 uh,
28:15 uh,
28:17 almo almost by definition entail the cooperation and the support of the
28:21 host countries,
28:23 uh,
28:23 governments.
28:24 Uh,
28:24 but then we're also going to turn to,
28:25 to two other,
28:26 uh,
28:27 types of interventions that,
28:28 uh,
28:29 don't necessarily entail,
28:31 uh,
28:31 the active,
28:32 uh,
28:33 endorsement,
28:34 uh,
28:34 or engagement of the,
28:37 of the,
28:38 uh,
28:40 host,
28:40 uh,
28:41 states.
28:41 Uh,
28:42 this could be interventions that could be undertaken also by
28:45 Other actors like,
28:46 you know,
28:47 international and local NGOs,
28:48 uh,
28:49 the first,
28:50 uh,
28:50 uh,
28:50 set of interventions are going to be
28:52 about changing psychological disposition,
28:55 uh,
28:55 for example,
28:56 through perspective-taking,
28:57 um,
28:58 and,
28:59 and other,
28:59 and other,
29:00 and other psychological,
29:02 uh,
29:02 uh,
29:03 and uh,
29:03 well,
29:04 I will talk about other,
29:04 other types of psychological interventions.
29:07 Uh,
29:07 and then,
29:07 and the last,
29:08 uh,
29:08 uh,
29:09 type of,
29:09 of intervention that will be discussed about increasing contact
29:13 and when we talk about increasing contact,
29:14 we'll be talking
29:15 about both increasing the,
29:16 increasing physical contact,
29:18 uh,
29:19 but also,
29:19 uh,
29:20 when that is hard to do,
29:21 uh,
29:22 especially to do at scale,
29:23 we'll be talking also,
29:24 uh,
29:24 briefly
29:25 about,
29:26 uh,
29:26 uh,
29:27 what,
29:27 what in the literature is,
29:28 is sometimes referred to as parasocial contact,
29:31 which,
29:31 uh,
29:32 uh,
29:32 uh,
29:33 interventions,
29:33 for example,
29:34 in,
29:34 in,
29:34 in,
29:35 in,
29:35 in,
29:36 In,
29:36 in media,
29:37 uh,
29:38 that,
29:38 uh,
29:38 so sometimes we,
29:39 we,
29:39 we put them under the,
29:41 uh,
29:41 the term of,
29:41 uh,
29:42 edutainment
29:43 where
29:44 through,
29:44 uh,
29:45 uh,
29:45 entertainment programming,
29:47 you can,
29:47 you can embed messages,
29:49 uh,
29:49 that might be able to
29:51 reduce some of the tensions and contribute to social cohesion.
29:54 Uh,
29:54 I would just say that like cross-cutting
29:56 these four different types of intervention,
29:58 uh,
29:58 we can think about another tool,
30:00 um,
30:00 uh,
30:01 that uh,
30:01 is,
30:02 is near and dear to,
30:03 to,
30:04 to many in the development,
30:05 uh,
30:05 community,
30:05 which is community-driven development,
30:08 which,
30:08 uh,
30:09 is,
30:09 is a tool in which can cross-cut these different types of interventions.
30:13 So,
30:13 for example,
30:14 Uh,
30:14 you can,
30:15 you can embed,
30:16 uh,
30:17 within,
30:17 uh,
30:18 community-driven,
30:19 uh,
30:19 development.
30:19 You can embed
30:21 things like,
30:21 uh,
30:22 perspective-taking,
30:23 you can embed things like,
30:24 um,
30:25 uh,
30:25 positive,
30:26 uh,
30:27 contact.
30:28 OK,
30:28 so what I'm gonna do now is just,
30:30 uh,
30:30 take you
30:31 through the case of Uganda which is a nice example
30:35 of how to think about inclusive refugee policies.
30:40 Um,
30:40 I'm gonna start by,
30:41 by mentioning that Uganda
30:42 is the largest refugee hosting country in,
30:46 in Africa and the 4th largest in the world,
30:48 uh.
30:49 Even though it has,
30:50 uh,
30:51 you know,
30:51 it's smaller in both size and population
30:53 than some of its neighboring countries like,
30:55 you know,
30:56 Kenya
30:56 and,
30:57 and Ethiopia,
30:57 so Ethiopia is 3 times,
30:59 uh,
31:00 uh,
31:01 uh,
31:01 uh,
31:02 the,
31:02 the number of,
31:03 of,
31:03 of citizens like around 120 compared to Uganda,
31:06 like 40,
31:07 uh,
31:08 it still hosts half of the number of refugees,
31:10 so Uganda is also,
31:11 uh,
31:12 a smaller in both population and size than,
31:14 than Kenya
31:15 and it hosts 3 times the number of refugees,
31:17 and this is in.
31:18 because Uganda has
31:19 a relatively
31:20 um
31:21 uh open border
31:23 uh uh policy for refugees
31:26 and in part because it,
31:27 it makes
31:28 the acquiring of refugee status
31:30 relatively
31:31 uh,
31:32 uh,
31:32 uh,
31:33 more simple than some of its neighboring countries,
31:36 uh,
31:36 for example,
31:37 uh,
31:38 um,
31:38 uh,
31:39 um,
31:39 by,
31:40 uh,
31:41 by having a category of,
31:43 uh,
31:43 refugees,
31:44 uh,
31:45 uh,
31:45 that,
31:46 um,
31:47 Uh,
31:48 so,
31:48 so,
31:49 so if some of the neighboring countries can receive a status of,
31:51 of refugee prima facie,
31:53 right?
31:53 If you come from Burundi,
31:54 if you come from South Sudan,
31:55 if you come from,
31:56 uh,
31:56 uh,
31:57 Somalia,
31:57 and if you come from,
31:58 uh,
31:59 from the DRC.
32:00 OK,
32:01 I want to talk about two policies that the Ugandan government has adopted in,
32:06 in
32:07 the
32:08 mid 2000s,
32:10 um,
32:11 and they speak to two aspects of what we can
32:15 think of as inclusive refugee policies.
32:18 One,
32:19 That refers more to how resource allocations get spent
32:23 and the other one
32:24 to the rights of uh refugees
32:26 and the ability to
32:28 uh integrate uh uh politically and,
32:30 and socially.
32:32 So let's talk first about the,
32:33 the first set of,
32:34 of policies
32:35 which are more about like resource allocation.
32:37 So,
32:38 uh,
32:38 in 2004,
32:39 Uganda passes the uh development assistance for refugee,
32:43 uh,
32:43 hosting areas,
32:44 uh,
32:44 regulation.
32:46 Um,
32:47 and,
32:47 and it has two major components that I,
32:49 I,
32:49 I wish to highlight.
32:50 The first one
32:51 is
32:52 the 70/30 principle that for every $100 that
32:57 come in as part of
32:59 a burden sharing agreement,
33:00 aid that comes to support Uganda's hosting refugees as part of
33:04 various burden sharing agreements,
33:05 $70 from each $100 will go to
33:09 uh uh support hosting refugees.
33:11 But $30 will be going to
33:14 uh
33:15 supporting the host communities
33:16 that are nearby refugee centers.
33:18 So this
33:19 is uh uh designed to ensure that the,
33:22 that the
33:23 burden of hosting refugees,
33:24 the cost of hosting refugees doesn't just fall disproportionately
33:28 on nearby communities,
33:29 but there's a recognition.
33:31 That because
33:32 uh they carry a lot of the burden in the terms of competition
33:35 over services and competition over natural
33:37 resources and maybe labor market competition,
33:39 they get compensated,
33:41 uh,
33:41 through aid allocation.
33:43 The second part of,
33:44 of,
33:45 of,
33:45 of,
33:46 uh,
33:46 of these policies,
33:47 the second aspect which is notable for our discussion
33:50 is this idea
33:51 that
33:52 aid allocation that go to host refugees
33:55 don't operate
33:56 as uh,
33:57 uh,
33:57 in,
33:57 in a parallel universe,
33:59 but they're integrated into the development programs or
34:01 the development plans of national ministries and local.
34:04 Government,
34:05 so
34:05 it's not as if
34:06 there's an investment in building a new school or a new clinic
34:10 that is,
34:11 is kind of operating as a,
34:13 as a parallel world in a different economy,
34:15 but,
34:15 but they're always going to be part of the development programs
34:18 uh of the host government to make sure,
34:21 uh,
34:21 again,
34:22 uh,
34:22 that also the,
34:24 the,
34:24 uh uh.
34:25 Uh,
34:25 the interests,
34:26 um,
34:27 uh,
34:27 and the needs of the local population
34:29 are being kept,
34:30 uh,
34:30 uh,
34:30 uh,
34:31 in mind,
34:31 and,
34:32 and so,
34:32 uh,
34:33 this is all,
34:34 uh,
34:34 designed not only to,
34:35 uh,
34:36 improve the lot of refugees but also make sure that local population,
34:39 uh,
34:39 uh,
34:39 benefits,
34:40 and when they benefit,
34:41 they're more likely to accept refugees.
34:42 So that's what,
34:43 what's,
34:43 uh,
34:44 11 aspect of inclusivity,
34:46 uh,
34:46 is thinking about resource allocation.
34:49 The second way to think about uh uh uh inclusive policies
34:53 is a set of policies that are designed.
34:56 To,
34:57 uh,
34:58 uh,
34:58 to increase self-reliant on,
35:00 of,
35:00 of refugees,
35:01 um,
35:03 that has obviously,
35:04 uh,
35:05 uh,
35:05 uh,
35:05 economic,
35:06 uh,
35:06 benefits for,
35:07 for the,
35:08 the refugees,
35:08 but also,
35:10 uh,
35:10 this reduction in,
35:11 in,
35:12 in,
35:12 in dependency,
35:14 uh,
35:14 in the medium to long run has also positive implications
35:18 to
35:18 relationship between,
35:20 uh,
35:20 refugees and,
35:21 and host communities,
35:22 uh,
35:22 as the host community sees that refugees.
35:24 Uh,
35:25 uh,
35:25 contributing member,
35:26 uh,
35:27 of society,
35:27 and so Uganda in 2006 passes the,
35:30 uh,
35:30 National Refugee Act,
35:31 uh,
35:32 then it gets,
35:32 uh,
35:33 operationalized in 2010 but has like these
35:35 really nice features that we don't see in many countries.
35:38 There's freedom of movement,
35:39 uh,
35:40 obviously freedom of religion,
35:41 right for family reunification,
35:43 and,
35:43 but maybe most important for our,
35:45 our context is also right to work,
35:47 right to own land,
35:48 right to rent land,
35:49 uh,
35:49 and,
35:50 and right to,
35:50 uh,
35:51 receive and transfer assets.
35:53 Um,
35:54 This figure,
35:55 uh,
35:56 shows you,
35:57 uh,
35:57 so,
35:58 uh,
35:59 uh,
35:59 and,
35:59 and,
36:00 and this is coming from my,
36:01 my work with,
36:02 with,
36:02 uh,
36:02 Yang Yan,
36:02 uh,
36:02 Xu and,
36:04 and,
36:04 and,
36:05 uh,
36:05 Shunning and
36:06 OK,
36:07 um,
36:08 uh,
36:08 we try to,
36:09 uh,
36:09 estimate what are the implication of this change in
36:13 policies,
36:13 this,
36:14 this inclusivity of,
36:15 of the Ugandan government with respect to,
36:18 uh,
36:19 uh,
36:19 uh,
36:19 hosting refugees.
36:20 What does that do,
36:22 uh,
36:22 both to,
36:23 uh,
36:23 the,
36:24 uh,
36:25 uh,
36:25 what are the social and political,
36:27 uh,
36:27 sorry,
36:27 social and economic,
36:28 uh,
36:28 implications for host communities,
36:30 OK.
36:31 Uh,
36:31 and so just to walk you through this slide on the,
36:33 on the x axis we have a year,
36:36 on the
36:37 Y axis we have the number of refugees,
36:39 and I want to separate between
36:41 three different periods,
36:42 uh,
36:43 that we,
36:43 we use in order to,
36:45 uh,
36:45 test what are the implications,
36:47 the social and economic implications
36:49 of
36:49 inclusive refugee policies.
36:51 If you look at the left here,
36:53 the left of the orange
36:55 lines,
36:56 uh,
36:56 these are.
36:56 2004 when the DA got adopted and 2006 when the National Refugee Act on the left here
37:03 we have an era,
37:04 a period where we have
37:05 a relatively,
37:06 uh,
37:07 you know,
37:07 small number of refugees,
37:08 around 200,000,
37:10 and this is before Uganda adopted its inclusive refugee policies.
37:14 If we look at this
37:16 area between the orange line and the red line,
37:18 the red line is when the South Sudanese civil war broke.
37:22 We have.
37:22 Uh,
37:24 stability in the number of refugees,
37:25 so the number of refugees didn't change.
37:27 The only difference between this period
37:29 and the period before that
37:31 is that now Uganda has adopted,
37:33 this is post the adoption of inclusive refugee policies,
37:36 so it can tell us what happens when refugees,
37:38 uh,
37:39 uh,
37:39 policies,
37:40 uh,
37:40 uh,
37:40 inclusive refugee policies get adopted,
37:43 uh,
37:43 without a change in the number of refugees.
37:45 And then if we're looking on the right side,
37:47 uh,
37:47 this is.
37:48 Still a period after Uganda adopted its inclusive refugee policies
37:51 but with a dramatic increase
37:53 in the number of refugees,
37:55 so it allows us to see whether
37:57 these the possible positive outcomes that we see
38:00 uh on,
38:01 on,
38:01 on social cohesion and,
38:03 and,
38:03 and,
38:04 and,
38:04 and,
38:05 um,
38:06 and some of the economic benefits for host communities,
38:09 do they survive even after this dramatic increase
38:12 in the number of refugees.
38:14 And here's what,
38:15 what we found.
38:15 This is a paper that has been recently published in
38:18 World Development.
38:20 Two things that I want you to take,
38:21 you know,
38:22 from the big,
38:23 big findings that we,
38:24 we have.
38:25 The first one
38:26 is that
38:28 Hosting refugees,
38:29 if you look at like communities
38:31 that have high refugee
38:34 uh uh presence,
38:35 so that as we increase refugee presence and for us to increase refugee presence,
38:39 it means
38:40 these are
38:40 localities
38:42 that are closer to areas that have
38:44 a larger number of refugees.
38:45 That's how we operationalize that.
38:48 As you get closer to,
38:50 uh,
38:50 as,
38:50 as,
38:50 as you move to,
38:51 to localities that have high refugee presence,
38:54 we see that there's an improvement
38:56 in,
38:57 uh,
38:57 public policies,
38:58 uh,
38:59 and so in social,
39:00 in social,
39:00 uh,
39:01 um,
39:02 uh,
39:02 in access to,
39:03 to social services
39:05 this we find it in education,
39:07 we find it in health,
39:08 we find it in vote quality,
39:10 um,
39:11 and so
39:12 there's,
39:12 there's,
39:12 there's real dramatic benefits,
39:14 but these benefits.
39:15 Only kick in after Uganda adopted
39:18 its uh inclusive refugee policies so that's one finding we're finding that
39:23 uh it is the case that when you design
39:25 policies in a way that can benefit
39:27 local communities they actually benefit from that.
39:30 The second finding is that we show
39:33 that as the benefits increase,
39:35 we see that host communities are more supportive
39:38 of refugee,
39:40 of refugees hosting
39:41 and uh an inclusive refugee hosting policies in particular,
39:45 OK,
39:45 and so.
39:47 And so we do not find,
39:48 not only that we do not find a backlash against refugees,
39:51 we actually see that
39:53 areas that are highly
39:54 uh uh uh affected by,
39:56 by refugee hosting areas that are,
39:58 uh,
39:58 have a large number of refugees nearby
40:01 are more supportive of other areas,
40:03 uh,
40:04 and,
40:04 and we attribute that to the fact that they,
40:06 they benefit from,
40:07 from,
40:08 uh,
40:08 from refugee hosting these,
40:09 these,
40:10 these positive spillovers.
40:11 I just wanna mention that the fact that we,
40:13 we're finding that doesn't mean that everything is,
40:15 is,
40:16 you know,
40:16 um,
40:17 is,
40:17 is rosy.
40:18 Uh,
40:18 Eric and I engaged in,
40:20 in,
40:20 in a new project in Uganda where we recently conducted a large,
40:24 uh,
40:24 number of,
40:25 of,
40:25 uh,
40:26 uh,
40:26 focus group discussions,
40:28 uh,
40:28 in refugee hosting areas and,
40:30 and we find that there's still quite a bit of tensions,
40:32 right?
40:32 Like,
40:33 um,
40:33 the,
40:34 the,
40:34 the.
40:34 The tensions,
40:35 uh,
40:36 uh,
40:36 can arise.
40:37 Uh,
40:37 we,
40:37 we,
40:37 we found that there's,
40:38 for example,
40:39 a bit of a,
40:40 uh,
40:41 uh,
40:41 a gap between people's personal experience with,
40:43 with refugees and,
40:45 and how they might think about,
40:46 uh,
40:47 uh,
40:47 refugees
40:48 more generally.
40:49 So they might say,
40:50 yes,
40:50 the people that I interact with are amazing,
40:52 but there is a refugee problem,
40:54 uh,
40:54 uh,
40:54 in,
40:55 in,
40:55 in Uganda,
40:56 uh,
40:57 and this is something that.
40:57 We need to kind of,
40:58 we're trying to dig in to understand what,
41:00 what,
41:00 what exactly is the source.
41:01 Is it because of news coverage?
41:02 Is it because of social media,
41:04 uh,
41:04 but there's clearly still some,
41:06 some tensions,
41:07 uh,
41:08 and then we also wanna,
41:09 uh,
41:09 mention the fact that they are in Uganda,
41:11 as many places,
41:12 uh,
41:13 uh,
41:13 other than Uganda,
41:14 there's going to be,
41:16 uh,
41:16 dramatic cuts to the level of support that
41:18 refugees are receiving from UNHCR and the world.
41:21 Uh,
41:21 uh,
41:22 uh,
41:22 a food program,
41:23 um,
41:24 and,
41:25 and,
41:25 uh,
41:26 it's,
41:26 it's still an open question how these cuts in,
41:29 uh,
41:30 in levels of support in,
41:31 in,
41:32 uh,
41:32 of refugees
41:33 might affect
41:34 not only the refugees but also the relationship
41:37 between refugees and host communities that we know
41:40 are highly dependent,
41:41 uh,
41:41 on the fact that the locals also benefit from
41:44 the aid that goes to refugees.
41:46 So
41:47 this was about inclusive refugee uh policies in,
41:50 in,
41:50 in Uganda.
41:51 Uh,
41:52 um,
41:52 I,
41:52 I,
41:53 I,
41:53 I wanna mention
41:54 that this is
41:55 not just about
41:57 uh how visas uh allocation uh uh is done.
42:00 There's other,
42:01 other,
42:02 uh,
42:02 other ways,
42:03 um,
42:03 uh,
42:04 uh,
42:04 the other aspect of,
42:06 of.
42:06 Uh,
42:07 of inclusive refugee policies,
42:09 um,
42:09 uh,
42:10 pertains to
42:11 the economic integration of,
42:12 of,
42:13 of this place.
42:13 So,
42:14 uh,
42:14 Eric already mentioned the study of muha in,
42:16 in Greece,
42:17 so I'm not gonna
42:18 repeat that.
42:18 I'm gonna,
42:19 uh,
42:19 mention,
42:20 um,
42:21 uh,
42:21 a study in,
42:22 in,
42:22 in Lebanon that,
42:23 you know,
42:24 as,
42:24 as you know,
42:25 uh,
42:25 Lebanon.
42:27 Is,
42:27 uh,
42:28 is the largest,
42:29 uh,
42:29 hosting,
42:30 uh,
42:30 one of the largest hosting refugees countries in the world in,
42:33 in per capita,
42:35 uh,
42:35 term,
42:36 uh,
42:36 uh,
42:37 and.
42:38 Uh,
42:38 this study by,
42:39 by Lehmann and Masterson,
42:41 uh,
42:42 looks at,
42:43 uh,
42:43 a UHCR program that provided cash transfers
42:47 to refugees,
42:48 uh,
42:48 in,
42:49 in winter months to,
42:50 uh,
42:51 uh,
42:52 uh,
42:52 to with some of the,
42:54 of,
42:54 of the bad weather,
42:56 uh,
42:56 in,
42:57 in Lebanon.
42:57 This was a program that was designed to people,
42:59 refugees that live in mountainous areas,
43:02 uh,
43:02 and they showed that.
43:03 Uh,
43:04 refugees that were receiving that were,
43:06 were eligible for the cash transfer,
43:09 uh,
43:09 uh,
43:10 program also reported much better relationship,
43:13 uh,
43:13 with
43:14 host,
43:15 uh,
43:15 communities.
43:16 They reported,
43:17 uh,
43:17 less hostility,
43:18 uh,
43:18 less,
43:19 uh,
43:19 uh,
43:20 uh,
43:20 uh,
43:20 including less,
43:21 uh,
43:21 uh,
43:21 uh,
43:21 uh,
43:23 uh,
43:23 violence,
43:24 uh,
43:24 and the,
43:25 the authors attribute that.
43:28 To,
43:28 uh,
43:28 the fact that refugees were able to use
43:30 the cash transfer to purcha purchase services,
43:33 uh,
43:33 and goods from local neighbors and that,
43:35 that kind of increased the,
43:37 the support,
43:38 uh,
43:39 uh,
43:39 of,
43:39 of hosting refugees
43:41 among the local population.
43:42 I'm gonna also mention in briefing,
43:44 uh,
43:45 uh,
43:45 a study of,
43:46 uh,
43:46 of,
43:46 uh,
43:47 um.
43:49 Of,
43:49 uh,
43:50 Colombia,
43:51 uh,
43:51 that in 2018,
43:53 uh,
43:53 as many of you might know,
43:56 uh,
43:56 uh implemented this large amnesty program,
43:59 uh,
43:59 uh,
44:00 providing with,
44:01 with Venezuelans,
44:03 uh,
44:03 refugees in,
44:04 uh,
44:05 uh,
44:05 or displaced,
44:06 uh,
44:06 Venezuelans in Colombia,
44:08 uh,
44:08 with,
44:09 um.
44:10 With uh access to employment permits,
44:13 um,
44:14 and,
44:14 and obviously also freedom of movement
44:16 and,
44:17 uh,
44:17 a couple of years after that,
44:19 uh,
44:19 a study has,
44:20 has document
44:21 a dramatic increase in,
44:23 uh,
44:24 in,
44:25 uh,
44:26 in
44:27 a,
44:27 a,
44:27 a set of indicators for,
44:29 for Venezuelan displaced,
44:30 a 31% increase in income.
44:32 About 60% increase in
44:34 uh in consumption,
44:36 uh,
44:37 about 10% point increase in labor formalization
44:40 with also
44:41 uh positive implications to the,
44:43 the local population.
44:45 OK,
44:46 so until now,
44:47 I,
44:47 I,
44:47 I,
44:48 you know,
44:48 we discussed
44:49 two types of interventions,
44:51 uh,
44:51 uh,
44:52 you know,
44:53 one pertaining to resource allocation and one pertaining to.
44:56 Uh,
44:56 uh,
44:57 um,
44:58 ways of increasing economic integration.
45:00 Uh,
45:00 I would just mention that the economic integration is mostly we,
45:03 we can think about it through freedom of movement,
45:05 right to work,
45:06 um.
45:08 Uh,
45:09 that,
45:09 uh,
45:10 that have
45:10 positive implications not only
45:13 to,
45:13 uh,
45:14 to the refugees but also to refugee
45:16 host,
45:17 uh,
45:17 relationship,
45:18 and now I wanna move,
45:19 uh,
45:19 but these,
45:20 these are,
45:20 these are the policies that you really need the,
45:22 the,
45:22 the government,
45:23 right?
45:23 You can't,
45:23 you can't implement,
45:24 uh,
45:25 uh,
45:25 the,
45:25 the policies that we've been discussing in
45:27 the last few minutes without the government.
45:28 Um,
45:29 but I wanna briefly mention also two types of interventions
45:32 that don't necessarily need the intervention of the government,
45:34 and one is,
45:36 uh,
45:36 the first one would be through
45:37 psychology like trying to affect psychological dispositions
45:41 and in,
45:42 in particular prejudice.
45:42 So when we,
45:43 we,
45:43 we,
45:43 when we discuss or when we,
45:45 when we talk about prejudices,
45:46 this is usually defined.
45:48 By social
45:49 psychologists as,
45:50 as preconceived
45:52 negative judgments or opinions
45:55 uh about
45:56 uh a person or group,
45:58 uh,
45:58 and a lot of times these are rooted in,
46:00 in,
46:01 in misconceptions and,
46:03 and,
46:03 and stereotypical,
46:04 uh,
46:05 uh,
46:05 thinking
46:06 and so when we talk about prejudice reduction,
46:09 we're talking about a set of interventions that reduce,
46:12 uh,
46:12 these or change these negative attitudes and perception.
46:16 Uh,
46:16 uh,
46:17 among a dominant group,
46:18 which in this case will be the host community towards a more marginalized group,
46:22 which in,
46:22 in our case is going to be,
46:24 uh,
46:25 uh,
46:25 uh,
46:25 refugees and,
46:26 and indeed there's growing evidence that these psychological approaches
46:30 could be
46:30 quite effective.
46:32 Uh,
46:32 one of the,
46:33 uh,
46:33 most,
46:34 uh,
46:34 effective,
46:35 uh,
46:36 uh,
46:36 interventions,
46:37 uh,
46:38 uh,
46:38 is termed perspective taking,
46:40 uh,
46:41 so I'll say a few words about that.
46:42 Uh,
46:43 we can think about perspective-taking
46:45 as
46:46 An intervention that has the goal
46:49 of transporting
46:51 uh members of the
46:53 uh dominant majority group,
46:55 in our case,
46:56 these are host communities,
46:58 so transporting them into thinking about refugees' experience and perspectives.
47:03 And the idea is that when you're transformed into,
47:06 so transported into these experiences,
47:08 you are less likely
47:10 to counter argue and you're more receptive
47:13 to messages
47:14 that promote
47:15 uh uh cooperation and,
47:17 and,
47:18 and,
47:18 uh,
47:19 and
47:20 a mutual
47:21 uh recognition and,
47:23 um,
47:23 and,
47:24 and you can do it in,
47:25 in,
47:25 in multiple ways,
47:26 uh,
47:26 researchers have,
47:27 have
47:28 You know,
47:29 uh,
47:29 had people read passages,
47:31 uh,
47:31 from,
47:32 uh,
47:33 from refugees,
47:34 uh,
47:35 sometimes it's personal narratives that you listen to.
47:37 This could be about the hardship in the country,
47:40 uh,
47:40 uh,
47:40 of origin.
47:41 This could be about some of the traumas that
47:44 refugees have had to endure,
47:46 uh,
47:46 in the,
47:47 uh,
47:48 during the,
47:48 the travel from.
47:50 From,
47:50 uh,
47:51 from,
47:51 uh,
47:51 uh,
47:51 uh,
47:53 from the host,
47:54 from the,
47:55 from the home country to the host country,
47:57 uh,
47:58 and this has been shown,
47:59 uh,
47:59 to be quite effective in,
48:00 in a variety of contexts from,
48:02 from the United States,
48:04 uh,
48:04 to Kenya
48:05 and elsewhere.
48:06 I would just mention
48:08 that
48:09 most of our evidence on perspective-taking.
48:12 Comes from
48:13 laboratory,
48:14 uh,
48:14 experiments and that leaves open
48:16 the question of how
48:18 you can implement some of these at scale and so there's different,
48:22 uh,
48:22 ways that we might be able to do that.
48:24 Uh,
48:25 there's discussions on trying to,
48:26 uh,
48:27 integrate perspective-taking in,
48:29 in CDD programs,
48:30 but there's other,
48:31 there's other options,
48:32 for example,
48:33 embedded,
48:34 embedding some of these stories and narratives,
48:36 uh,
48:37 within,
48:37 uh,
48:38 uh,
48:38 uh,
48:38 edutainment programming,
48:39 and this is something.
48:40 Thing that Eric and I
48:41 are working on as I'll uh have an opportunity to describe,
48:44 uh,
48:44 in a few uh minutes.
48:46 Um,
48:47 the last,
48:47 uh,
48:47 type of intervention that I,
48:49 I wanna mention,
48:50 uh,
48:50 ones that increase contact between,
48:53 uh,
48:53 uh,
48:54 uh,
48:54 host,
48:55 members of the host,
48:56 uh,
48:56 uh,
48:56 community and,
48:57 and refugee,
48:58 um.
49:00 And so there's a really large literature
49:01 on intergroup interaction and how contact might
49:04 uh improve,
49:06 uh,
49:06 uh,
49:07 um,
49:08 improve relationship and reduce,
49:10 uh,
49:10 prejudice,
49:11 uh,
49:11 and this,
49:12 this has been,
49:12 this has been,
49:13 uh,
49:14 found in,
49:14 in a variety of,
49:16 of contexts
49:17 that increasing,
49:18 uh,
49:19 uh,
49:19 contact can alleviate,
49:21 uh,
49:22 anxieties between group can induce empathy,
49:25 um.
49:26 And,
49:26 and,
49:27 and also forge,
49:28 uh,
49:28 uh,
49:29 friendships.
49:29 Uh,
49:30 I think,
49:31 uh,
49:31 I suspect that many of the,
49:33 the people on,
49:34 on,
49:34 on,
49:34 on,
49:35 on this call,
49:37 uh,
49:37 also know that,
49:38 uh,
49:39 that while contact could be quite powerful,
49:41 um,
49:42 uh,
49:42 just increas.
49:43 In contact between
49:44 uh groups doesn't always,
49:46 uh,
49:47 uh,
49:47 uh,
49:48 reduce prejudice.
49:49 It doesn't always,
49:50 uh,
49:51 uh,
49:51 contribute to,
49:52 uh,
49:52 to cohesion that has to,
49:54 uh,
49:54 contact has to satisfy certain conditions to be more likely
49:57 to,
49:58 to,
49:58 to work relatively well.
50:00 Um,
50:01 and so I'll just mention some of,
50:03 uh,
50:03 some of the conditions,
50:04 the context needs to be positive.
50:06 It works better when it's voluntary,
50:09 uh,
50:10 contact
50:10 tends to have better outcome
50:12 when,
50:13 uh,
50:13 it is endorsed and,
50:15 and condoned and encouraged by,
50:17 uh,
50:17 local leaders,
50:18 um,
50:19 and so when the community members receiving this positive,
50:22 uh,
50:22 enforcement from,
50:23 uh,
50:24 from,
50:24 uh,
50:25 authority figures.
50:26 Um,
50:27 it's more likely to be effective
50:28 when there's equality of status between the groups,
50:31 um.
50:32 And it tends to work best when you design,
50:36 uh,
50:37 uh,
50:37 the contact,
50:38 uh,
50:39 uh,
50:39 where the 22 groups
50:42 work together
50:43 to achieve,
50:44 uh,
50:44 some,
50:44 some common goals.
50:45 This could be,
50:46 uh,
50:46 uh,
50:47 the common goals could be,
50:48 uh,
50:49 you know,
50:49 things that relate to community life,
50:51 but they could be as prosaic as
50:53 winning in,
50:54 in,
50:54 in,
50:54 in,
50:54 in a sports game and so there's the,
50:56 uh,
50:57 uh,
50:57 we wanted to,
50:58 uh,
50:58 highlight uh,
50:59 a study by Salma Mussa.
51:01 Uh,
51:01 that shows,
51:02 for example,
51:02 the positive,
51:03 uh,
51:04 benefits
51:04 of,
51:05 uh,
51:06 uh,
51:06 of creating
51:07 a Christian and Muslim soccer teams,
51:09 uh,
51:09 and how this,
51:10 uh,
51:10 in,
51:11 this is a study in Iraq and how this,
51:13 uh,
51:13 manifested itself in improved relationship across sectarian lines even in,
51:17 in,
51:17 in,
51:17 in a deeply divided society,
51:19 uh,
51:19 like Iraq and the,
51:20 the kind of the common goal
51:22 is,
51:22 is,
51:23 is,
51:23 is,
51:23 you know,
51:24 could be as prosaic as,
51:25 as soccer,
51:26 uh,
51:27 so.
51:28 Uh,
51:28 so what we've done in the,
51:29 in the last,
51:30 uh,
51:30 a few minutes is go through like 4 different types of interventions.
51:34 Some of them,
51:35 uh,
51:35 uh,
51:35 really need the,
51:36 the,
51:36 the,
51:37 the,
51:37 the,
51:38 the active,
51:39 uh,
51:39 endorsement of,
51:40 of the state,
51:41 the host community state.
51:42 These are
51:42 about,
51:43 uh,
51:43 uh,
51:44 uh,
51:44 inclusive refugee policies with respect to resource allocation,
51:47 with respect to poli to economic integration.
51:50 And then we discussed also two other interventions,
51:53 one of the,
51:54 the,
51:54 the type of psychological interventions and one that increased eye contact,
51:58 and so this is a good time to,
51:59 to,
52:00 to stop.
52:02 Thank you.
52:03 Uh,
52:03 thanks a lot,
52:03 guys,
52:04 uh,
52:04 and thanks,
52:05 Eric,
52:05 for,
52:06 uh,
52:06 for both of your presentations.
52:08 Um,
52:09 so I think that sets the scene nicely for,
52:12 uh,
52:12 what's coming next in this session.
52:14 Uh,
52:14 we were planning to have breakout rooms,
52:16 uh,
52:17 but,
52:17 uh,
52:17 I,
52:18 I didn't want to interrupt the presentations.
52:19 I thought they were great,
52:20 uh,
52:21 and we ran a little bit over time.
52:23 Um,
52:24 so,
52:24 um,
52:25 I,
52:25 I believe the questions that were posed in the chat were all answered.
52:29 Otherwise,
52:29 we could take one.
52:30 if anybody wants to raise hands,
52:32 uh,
52:32 we could have,
52:33 uh,
52:34 uh,
52:34 one question from the floor.
52:36 If anything is outstanding that uh was uh not answered in the chat,
52:40 or if anyone has a new question,
52:41 we could take it now.
52:47 Yeah,
52:47 sorry for going a bit over time.
52:50 No problem.
52:51 No problem.
52:54 I don't see,
52:55 yes,
52:55 I see Juan Pablo.
52:57 Um,
52:58 uh,
52:58 please come in.
52:59 Uh.
53:01 Hi,
53:01 thank you.
53:02 Great presentation.
53:04 Uh,
53:04 I,
53:04 I,
53:05 I paused my question almost to the end,
53:07 so
53:07 I'm taking the liberty to using the floor.
53:10 Um,
53:11 I would love to hear more about
53:14 The effect on wages of integrating refugees into a formal market.
53:19 As you might know,
53:20 in Latin America,
53:20 we have
53:22 A huge informal economy and
53:24 there is,
53:25 um,
53:26 well,
53:26 the majority of the economy in some places
53:29 are,
53:29 are informal,
53:31 but we are uh trying to push or to advocate for integrating refugees
53:36 into a formal economy where they can have
53:39 social security and they have more prospects of social mobility.
53:43 So,
53:44 11 question that always comes to mind.
53:47 Is that uh what are the effects for
53:50 workers when
53:52 a large group of people
53:54 uh are integrating in
53:57 um
53:58 in the economy and we usually say that
54:01 uh when they are placed only in low paid jobs um.
54:06 Wages could be depreciate
54:08 even though we have like
54:10 sticky wages with,
54:12 you know,
54:12 the minimum wage,
54:13 so probably they are not like severe affected
54:17 when we place refugees into according to their abilities and skills,
54:22 there might be an,
54:24 a positive effect
54:25 uh
54:26 for,
54:27 for workers overall,
54:29 but
54:30 I would love to hear more
54:32 if you know,
54:33 more papers or more evidence about that point.
54:37 Thank you,
54:38 Juan Pablo,
54:39 and uh you are with the UNHCR right?
54:42 Yes,
54:43 I'm with you.
54:44 Yes,
54:44 that's great.
54:45 OK,
54:46 uh,
54:46 Guy,
54:46 Eric,
54:47 I'll turn over to you,
54:48 uh,
54:48 for that question,
54:49 um.
54:51 Feel free to unmute
54:55 Guy,
54:55 you wanna go ahead.
54:58 So the question is about
55:00 uh the effect on,
55:01 on
55:02 uh wages.
55:04 On formal sector employment.
55:06 Yeah,
55:07 so there's no,
55:09 so at least the evidence that we have,
55:10 uh,
55:11 out there
55:12 suggests that,
55:12 uh,
55:13 I would just say 222 things briefly.
55:15 One is like
55:16 there's no,
55:17 uh,
55:18 one answer that is right to all contexts,
55:19 right?
55:20 As Eric mentioned before,
55:21 it really depends on,
55:23 uh,
55:23 on a host of issues,
55:24 right?
55:24 Like,
55:24 you know,
55:25 uh,
55:26 impact,
55:26 uh,
55:27 it depends on,
55:28 on the,
55:29 um,
55:31 Uh,
55:32 the relatively skilled set of the,
55:34 uh,
55:35 refugees compared to those of the local,
55:37 uh,
55:38 population.
55:38 So do they have complementarity of skills or substitution,
55:41 right,
55:41 if it's only substitution.
55:43 If it's mostly
55:44 a substitution usually that can depress wages,
55:46 if it's,
55:47 if they're complementarity of,
55:48 of skills,
55:50 right,
55:50 that,
55:50 that can,
55:51 that doesn't necessarily mean that we will,
55:53 we'll see
55:54 a depression of wages and sometimes we even see an increase in wages
55:57 uh because,
55:58 uh,
55:59 you know,
56:00 that,
56:00 that can increase the pie.
56:01 So,
56:01 so I think that,
56:02 the most,
56:02 maybe I would say that the most important
56:03 thing that we know from like economic literature
56:05 is that it's a mistake to think about the size of the pie.
56:08 As constant,
56:09 right,
56:09 like if refugees come,
56:10 it's not that there's a number of,
56:12 of jobs
56:12 and,
56:13 uh,
56:13 that is constant,
56:14 and then if there's more refugees there's gonna be,
56:16 you know,
56:16 either displacement or that there's a depression of,
56:19 of wages,
56:20 right?
56:20 We know that,
56:21 uh,
56:21 the,
56:21 the number of jobs can,
56:23 can,
56:23 can increase,
56:24 uh,
56:25 uh,
56:25 and,
56:25 and the pie can increase and,
56:26 and that can have like positive implications,
56:29 um,
56:29 but,
56:30 but,
56:30 but the,
56:31 the two big factors,
56:32 uh,
56:33 the question.
56:33 One is about the complementarity of skill versus the substitution of skill.
56:37 The other question is about,
56:38 uh,
56:39 the,
56:39 uh,
56:40 labor market,
56:40 uh,
56:41 uh,
56:41 uh,
56:42 policies,
56:42 you know,
56:43 to what it,
56:44 you know,
56:44 how,
56:44 how many frictions,
56:45 uh,
56:46 they put on,
56:47 on refugees' uh,
56:48 mobility and,
56:49 and ability to work.
56:50 So the more,
56:51 the more restrictions you have,
56:52 for example,
56:53 on mobility,
56:54 uh,
56:54 you will find more depression of,
56:56 of wages because they're all concentrated in,
56:58 in a small.
56:59 Number of of places,
57:00 right?
57:01 Well,
57:01 if you allow freedom of mobility,
57:03 like you can,
57:03 refugees can live wherever they want,
57:05 they keep moving to places where they have more opportunities
57:07 and then
57:08 there's less pressure on one single local labor market and that that tend to have
57:12 to have a much pos much more positive
57:14 implication.
57:15 So,
57:15 so it's not only about like the right to work,
57:17 it's also freedom of movement
57:19 uh is affecting so,
57:20 uh,
57:20 so,
57:21 you know,
57:21 so the policies matter
57:22 and the complementarity of skills matter.
57:26 which is,
57:26 um,
57:29 dynamics in hosting countries oftentimes militate against formality.
57:33 Um,
57:33 so for instance,
57:34 when you look at something like doctors or lawyers
57:36 where
57:37 or other sectors where you're gonna have a higher incidence of formality,
57:41 oftentimes the certification
57:43 that
57:43 that the
57:44 refugee might have had from their home country is not.
57:47 Recognized in the host country.
57:49 And the implication of that is that the labor market matching is very,
57:51 is especially inefficient,
57:53 um,
57:53 at higher levels of education and skill.
57:56 And the implication of that is that those folks have a,
57:59 you know,
57:59 it's not very easy for them to place,
58:02 uh,
58:02 in the formal sector.
58:03 And that just makes it hard to gather evidence of the sort you're talking about,
58:07 because this is just not something,
58:08 you know,
58:08 it's just,
58:09 it.
58:09 Doesn't happen in,
58:10 in huge numbers.
58:11 And,
58:12 you know,
58:12 I think one implication is making it easier
58:15 um for
58:16 the displaced
58:17 to
58:18 gain access to the source of certifications that lend themselves to formality,
58:23 you know,
58:24 that,
58:24 that is,
58:24 uh,
58:25 you know,
58:26 that seems like an,
58:26 an obvious place to,
58:27 to push,
58:28 even if that would likely be hard from a political point of view.
58:33 Paula,
58:33 I'll stop there.
58:35 Yeah,
58:36 thanks,
58:36 Eric,
58:36 and uh thanks I,
58:38 um,
58:38 uh Juan Paul,
58:39 I think uh that was,
58:40 uh,
58:40 those were some exhaustive uh
58:42 Um,
58:43 responses and,
58:45 uh,
58:45 and indeed what we see also from overall the building the evidence program
58:49 is that there's a divide between,
58:51 uh,
58:51 what's the policy,
58:52 so refugees,
58:53 um,
58:54 being allowed to work,
58:55 uh,
58:55 legally in the host country
58:57 and what's in practice are the challenges they face,
59:00 uh,
59:00 such as,
59:00 uh,
59:01 what Eric mentioned,
59:02 documentation,
59:03 or,
59:04 um,
59:04 even just downgrading in the,
59:06 in the labor market regardless of them being able to occupy the,
59:09 the jobs they're qualified for.
59:12 Um,
59:13 so,
59:13 um,
59:14 I'll,
59:14 I'll close this,
59:15 uh,
59:15 Q&A,
59:15 but we'll,
59:16 uh,
59:16 have more time in the end.
59:18 And,
59:18 uh,
59:19 it is my pleasure now to turn over to Gina Kuzmito Bradley.
59:22 Um,
59:23 uh,
59:23 she's,
59:24 uh,
59:24 as I mentioned,
59:25 I introduced you,
59:26 Gina,
59:26 earlier,
59:26 but you are in the session.
59:28 Um,
59:29 she's the regional economist,
59:30 uh,
59:30 for the UNHCR in,
59:32 um,
59:32 covering West Africa and Central Africa,
59:35 and she'll be,
59:35 uh,
59:35 telling us about her work,
59:37 um,
59:38 and how it concerns,
59:39 um,
59:39 uh,
59:40 social cohesion in the region.
59:42 Over to you,
59:42 uh,
59:43 Gina.
59:44 Thank you so much,
59:45 Paula.
59:46 Thank you so much for the great introduction.
59:48 Great to be here with you,
59:49 uh,
59:50 colleagues,
59:50 and apologies,
59:51 I was not,
59:51 uh,
59:52 here from the beginning of the session.
59:54 Uh,
59:54 while I share my screen so we can start discussing social cohesion,
59:58 I just want to say,
59:59 guys,
59:59 latest comment really
1:00:01 resonated with me
1:00:03 because we're working in,
1:00:05 for example,
1:00:05 Chad,
1:00:06 where really,
1:00:07 even though the framework
1:00:09 allowed refugees to work,
1:00:10 the element of not being able to move freely within the country
1:00:14 made the the restrictions in terms of employment really,
1:00:18 really visible.
1:00:19 And we're very happy that the new law
1:00:21 that has been adopted has removed this constraint,
1:00:24 but we were yet to see the results in practice with uh with mobility.
1:00:28 But that comment really resonated with me.
1:00:31 So social cohesion uh in UNHCR work in Western Central Africa.
1:00:36 I would just like to start us off by looking a little bit at uh
1:00:41 uh what do we mean?
1:00:42 Why do we even.
1:00:44 Uh,
1:00:44 look into this.
1:00:45 Why do we even engage in our humanitarian work,
1:00:49 what we call with um.
1:00:51 When what we understand when we talk about social cohesion
1:00:55 and efforts to boost social cohesion is what we within UNHCR called
1:01:00 community-based protection area based approaches,
1:01:04 which all are there to support our strong willingness to ensure
1:01:08 that we have out of camp approaches for refugee situations where refugees
1:01:13 are embedded in the communities that are hosting them.
1:01:15 They're not
1:01:16 set outside.
1:01:18 and unable to participate and be active
1:01:20 and positive contributors in the community.
1:01:24 So social cohesion is critical in
1:01:27 places where you have forced displacement for reasons of peaceful coexistence
1:01:32 to ensure that the community that is hosting
1:01:35 does not endure undue costs and the costs are supported
1:01:40 by the funding that comes to support the displacement situation.
1:01:44 As well as ensuring that there is uh the structures and avenues
1:01:48 for the the displaced and the the host community to meet,
1:01:52 understand each other,
1:01:52 exchange
1:01:54 also the grievances
1:01:55 and um a place where they can have a dialogue.
1:01:59 So this,
1:01:59 this is
1:02:00 the ideas with which we we frame this area of work on,
1:02:05 on social cohesion.
1:02:07 So social cohesion for us is another is a prerequisite for one of our
1:02:12 three solutions to a refugee situation.
1:02:16 So we say that the refugee situation is
1:02:19 solved and the,
1:02:20 the,
1:02:21 the,
1:02:21 the
1:02:22 UNHCR does not have to engage anymore when we achieve one of three solutions
1:02:27 either local integration,
1:02:30 um.
1:02:31 Resettlement or repatriation when they return
1:02:34 to their country of origin.
1:02:35 So
1:02:36 in order for us to consider refugee locally settled,
1:02:39 they have to.
1:02:41 Uh,
1:02:41 have this element of social cohesion,
1:02:44 which is understood as
1:02:47 being part of their community and
1:02:50 being participating and having avenues to discuss with their
1:02:54 community and being a member of their community.
1:02:57 So I wanted to share this really interesting work that our senior economists did
1:03:04 in Ner right before I joined this region.
1:03:07 So we were in the process of evaluating our targeting
1:03:10 approaches for forecast assistance that we were giving in is there
1:03:14 and for that we were looking into the welfare of different refugee households.
1:03:18 And indeed we found that the second most important parameter
1:03:22 for whether refugee household with the uh
1:03:26 for the welfare of a refugee house household
1:03:29 would be the high incidence of inviting others to tea in their homes,
1:03:34 which in a way is a proxy for social cohesion,
1:03:37 having networks being part of your community.
1:03:40 Uh,
1:03:40 the first most important parameter was,
1:03:42 of course,
1:03:42 household size,
1:03:44 but we were really surprised to find that inviting other people's
1:03:48 people for tea and being part of the community and the network
1:03:51 was just as important as the number of durable goods that a household had.
1:03:56 So this.
1:03:57 This result,
1:03:58 I think,
1:03:59 really speak to the value of the work in this in this area to ensure
1:04:04 that refugees are really part of their
1:04:06 communities and that there is social cohesion,
1:04:09 even in situation of displacements.
1:04:11 I want to touch upon four
1:04:14 elements here.
1:04:15 Community centers.
1:04:16 I'm sure I'm talking to humanitarians and also development.
1:04:20 I'm sure you've heard of them,
1:04:21 but I just want to briefly touch upon it because it's so important for
1:04:25 social cohesion in our work,
1:04:27 then
1:04:28 targeting
1:04:29 and finally,
1:04:30 two projects that we have in.
1:04:32 Our region that I think we're quite innovative in the in the approach
1:04:35 that they took in terms of social cohesion and these are project 21
1:04:39 and C4C projects communication for communities.
1:04:44 So let's
1:04:45 look at
1:04:47 the targeting.
1:04:49 Yes,
1:04:50 let's look at our targeting.
1:04:51 So in terms of of targeting,
1:04:54 as I mentioned earlier,
1:04:56 earlier,
1:04:56 units here tries to take area-based approaches
1:05:00 in order to ensure that we have peaceful
1:05:02 coexistence with the community and that we don't create
1:05:06 adverse effects through our humanitarian
1:05:09 programming and ensuring that we maintain
1:05:12 so.
1:05:12 cohesion.
1:05:13 So in in that sense,
1:05:15 we set different benchmarks in our own programming to
1:05:18 include the host community so that they participate.
1:05:21 And that's a standard practice across programming within UNHCR.
1:05:25 Now the different projects may have different types of targeting
1:05:29 and will have different ranges and percentages of host communities
1:05:34 versus um.
1:05:36 Versus uh um
1:05:38 displaced populations.
1:05:39 So for example,
1:05:40 for caste-based interventions,
1:05:41 it may be
1:05:43 more like 80 refugees,
1:05:45 20 host community,
1:05:46 and then for projects that we work in financial inclusion,
1:05:49 we really truly take
1:05:51 an area-based approach for access to microfinancing
1:05:53 and then we're looking at 50/50 even.
1:05:56 Uh,
1:05:57 so this is quite,
1:05:58 it varies very much based on the nature of the project.
1:06:01 Uh,
1:06:02 one interesting practice that uh I would like to
1:06:05 bring attention to is that in Western Central Africa,
1:06:08 we often
1:06:09 do community involvement in our targeting,
1:06:12 and that is
1:06:13 the rule rather than the exception,
1:06:14 meaning that the targeting
1:06:16 is not
1:06:17 only calculated by economic models with their budget constraints and so on,
1:06:21 but Primarily discussed with the community and
1:06:24 ensuring that we get community buying.
1:06:26 The reason for this is that
1:06:28 in West Africa,
1:06:29 refugees
1:06:30 often live in areas that are very poor
1:06:33 and the community is equally poor and under-resourced and underfunded.
1:06:37 So it is very important that we ensure that the,
1:06:41 the,
1:06:41 the criteria that we set for our targeting are not artificial.
1:06:45 And one example I can bring.
1:06:47 From one of the countries in the Sahel was that the
1:06:49 the nice modeling that we did for our criteria told
1:06:52 us that the cutoff points would be 4 children.
1:06:56 So
1:06:56 families with 4 children would not get the assistance.
1:06:59 Families with 5 would get the assistance.
1:07:00 But
1:07:01 when we talked to the community,
1:07:02 they realized this,
1:07:04 this really does not resonate with the community.
1:07:07 So we changed it
1:07:08 and use different categorical criteria.
1:07:12 So here we're looking at um.
1:07:15 P21,
1:07:16 which is actually a very interesting protection monitoring tool,
1:07:19 uh,
1:07:20 where we're trying to identify trends and uh negative,
1:07:23 uh,
1:07:23 uh,
1:07:25 negative um protection concerns and uh and uh threats to um
1:07:31 refugees and that area,
1:07:33 that,
1:07:34 that uh assessment.
1:07:36 That includes a social cohesion,
1:07:39 uh,
1:07:39 subcomponent.
1:07:40 Here you're looking at uh
1:07:42 the results from the questionnaire from TAA in September.
1:07:45 TAA,
1:07:46 this is the,
1:07:47 the Sudanese,
1:07:48 uh,
1:07:48 refugees that have been displaced due to the Sudan war.
1:07:52 And as you can see,
1:07:53 they're being asked whether they feel integrated or not
1:07:56 and uh why do they feel integrated or they feel
1:08:00 not integrated in the community in which they live
1:08:03 and.
1:08:04 Where would they seek assistance if they need it and what areas
1:08:09 make them feel safe or unsafe.
1:08:11 And then other questions that are within the same social cohesion module
1:08:16 involve whether there are xenophobia incidents,
1:08:18 whether they are incidents that are violent that are
1:08:22 related to their status.
1:08:24 But what's interesting is that this questionnaire
1:08:27 is not only administered to the refugees,
1:08:29 but Also the host community so that we try to
1:08:31 take the pulse from both sides and try to understand how
1:08:35 the the community also feels in real in real time as the emergency unfolds.
1:08:41 So I think this is quite an interesting
1:08:43 tool and interesting practice from the field.
1:08:45 And I would like to highlight that this is standardized
1:08:48 and it happens across the different countries in West Africa.
1:08:50 So I think that's also quite innovative that we can track cross border.
1:08:54 So then community centers,
1:08:56 sorry to interrupt,
1:08:57 just to say you have one minute.
1:08:59 Thank you.
1:09:00 Thank you,
1:09:01 thank you.
1:09:01 Um,
1:09:02 I am not going to go as I have only one minute.
1:09:05 I'm not going to go super into this.
1:09:06 I'm,
1:09:06 I'm sure we all understand and know the value of community centers and then
1:09:11 finally looking at our,
1:09:12 uh,
1:09:12 connectivity versus uh.
1:09:14 Activity for communication project.
1:09:17 I think why this was interesting.
1:09:18 This was a project that was trying to establish
1:09:21 avenues of communication with the communities and the refugees
1:09:25 and giving them
1:09:27 a mechanism
1:09:28 where they could basically refer their needs but also respond and give complaints.
1:09:34 So
1:09:35 For that we were assessing whether that would be
1:09:37 possible to have a component that uses a telephone,
1:09:40 so that's why we launched the study for connectivity for communication.
1:09:44 We saw that in in certain countries that was possible because
1:09:47 more than half of the community had access to a telephone,
1:09:50 but then when we see that the parameters of um.
1:09:55 Not having a stable access,
1:09:57 you're looking here at the different parameters and then
1:09:59 we try to work on the different parameters in order to establish
1:10:04 this,
1:10:04 uh,
1:10:04 this project on the ground and have this line
1:10:07 with the open line communication line with the community.
1:10:10 So these are the elements we measured and then we try to work
1:10:13 on on making them better so that the community would actually have.
1:10:17 A valuable avenue
1:10:20 to uh
1:10:21 to connect and raise needs and concerns.
1:10:25 So then finally,
1:10:26 I just wanted to say that that as I was talking about social cohesion and how this all
1:10:32 leads to inclusion from our side is not viewed as OK,
1:10:36 we do this work,
1:10:37 we ensure the community.
1:10:38 Accepts the refugees and then that means that this is a quick exit for us.
1:10:42 On the contrary,
1:10:43 we understand that we need to remain engaged and stay,
1:10:47 stay focused
1:10:48 and stay monitoring and evaluating the situation and ensuring
1:10:52 that we're supporting the communities that host displaced population.
1:10:55 And I understand my time is up,
1:10:57 Paula.
1:10:58 Uh thank you very much.
1:11:01 Thanks to you and Gina.
1:11:02 Uh,
1:11:02 this,
1:11:02 uh,
1:11:03 this was great to,
1:11:03 to know how central social cohesive considerations are to the UN
1:11:07 historic work and the examples I thought were also very,
1:11:10 uh,
1:11:10 inspiring and,
1:11:11 uh,
1:11:12 representative.
1:11:13 Um,
1:11:14 Guy,
1:11:14 I'll turn back to you,
1:11:16 uh,
1:11:16 for our last presentation on designing programs
1:11:19 in order to measure their impact and,
1:11:21 uh,
1:11:21 uh,
1:11:22 finally,
1:11:22 uh,
1:11:22 the final takeaways from the session.
1:11:24 Kindly be mindful of,
1:11:26 of time.
1:11:26 Thank you.
1:11:32 Thanks.
1:11:32 Uh,
1:11:33 I,
1:11:33 I'll try to be brief,
1:11:34 uh,
1:11:34 you know,
1:11:35 um,
1:11:37 Two things I kind of want to underscore as we talk about um
1:11:41 uh designing
1:11:42 uh evidence,
1:11:44 uh,
1:11:44 designing,
1:11:45 uh,
1:11:45 uh,
1:11:45 studies to improve our evidence base
1:11:47 of interventions that increase social cohesion.
1:11:50 The first one I,
1:11:51 I want to,
1:11:52 uh,
1:11:53 to underscore this idea that on one hand,
1:11:55 we have a growing
1:11:56 body of work and this,
1:11:57 you know,
1:11:58 Eric mentioned the 26 studies that the World Bank has been funded and,
1:12:02 and it,
1:12:02 it's definitely we are in 2023 in a better place than we were in 2021.
1:12:06 Uh,
1:12:07 but there's still,
1:12:08 uh,
1:12:08 much that we,
1:12:09 we don't,
1:12:09 we don't know,
1:12:10 and,
1:12:10 and we believe that the,
1:12:12 the,
1:12:12 the,
1:12:13 um,
1:12:14 evidence,
1:12:15 uh,
1:12:15 uh,
1:12:16 base for what types of interventions and,
1:12:18 and what context,
1:12:20 uh,
1:12:20 can improve social cohesion,
1:12:22 uh,
1:12:22 is still,
1:12:23 is still wanting.
1:12:24 There's still
1:12:24 a lot more that can be done to,
1:12:26 to strengthen,
1:12:27 uh,
1:12:27 the evidence base.
1:12:28 That's the first thing I want you to take.
1:12:30 The second thing I want you to take that,
1:12:31 uh,
1:12:32 um,
1:12:32 uh,
1:12:33 from this,
1:12:33 from this slide is it's,
1:12:34 it's,
1:12:34 it's,
1:12:35 it's a hard question,
1:12:36 right?
1:12:36 Like it's,
1:12:36 it's not that easy to study
1:12:38 what policies
1:12:39 and interventions improve social cohesion
1:12:42 uh because
1:12:43 uh you know,
1:12:45 refugee situation is dynamic because a lot of times the policy
1:12:50 uh
1:12:50 design needs to be
1:12:52 uh adopted in,
1:12:53 in,
1:12:53 in,
1:12:53 in really,
1:12:54 uh,
1:12:54 fast and,
1:12:55 and,
1:12:55 and moving conditions.
1:12:57 Uh,
1:12:58 data collections tends to be,
1:12:59 um,
1:13:00 expensive.
1:13:00 It's also very time-consuming,
1:13:02 um,
1:13:03 uh,
1:13:04 but also social cohesion itself is,
1:13:05 is a hard to measure concept.
1:13:07 It's sometimes,
1:13:08 um,
1:13:09 um,
1:13:09 it's hard to measure.
1:13:10 It's,
1:13:10 it's subjected to social desirability bias,
1:13:13 um.
1:13:14 And,
1:13:15 and not in all uh uh uh uh it's not always,
1:13:19 there's a shared understanding of what exactly is the thing
1:13:22 that needs to be,
1:13:23 needs to be measured.
1:13:25 Um.
1:13:26 So
1:13:27 So here's a few
1:13:28 things to keep in mind as we're thinking
1:13:32 uh about
1:13:33 uh the evidence base.
1:13:35 How can we improve our understanding of what works and what doesn't work,
1:13:40 uh,
1:13:40 in,
1:13:41 uh,
1:13:41 with the goal of improving
1:13:43 uh social cohesion.
1:13:45 Uh,
1:13:45 the first thing that I,
1:13:46 I want to,
1:13:47 uh,
1:13:48 underscore
1:13:49 is
1:13:50 that our ability
1:13:52 to generate,
1:13:54 uh,
1:13:55 for our,
1:13:55 our,
1:13:55 uh,
1:13:56 uh,
1:13:56 generate evidence,
1:13:57 our,
1:13:57 our,
1:13:58 our ability to,
1:13:59 to support a growing understanding of what works and what doesn't work,
1:14:03 uh,
1:14:03 has to begin,
1:14:04 uh,
1:14:05 a very early stage,
1:14:06 uh,
1:14:07 even before we implement the,
1:14:09 the,
1:14:10 the policies in place,
1:14:11 uh,
1:14:12 because sometimes when.
1:14:13 Uh,
1:14:13 when researchers are approached and are asked,
1:14:16 uh,
1:14:16 to study an intervention that took place in the past,
1:14:19 sometimes it's too late
1:14:20 to,
1:14:21 to be able to,
1:14:23 uh,
1:14:23 to rigorously assess the impact of the program or,
1:14:27 or the intervention that took place in the past.
1:14:29 So,
1:14:30 so,
1:14:31 uh,
1:14:31 I wanna,
1:14:32 uh,
1:14:32 kind of encourage all of the people on,
1:14:34 on this score that if you know that like you are,
1:14:36 you're part of the discussion.
1:14:38 Uh,
1:14:38 of implementing some interventions,
1:14:40 some policy
1:14:42 that could affect,
1:14:43 uh,
1:14:43 not only
1:14:45 the,
1:14:45 uh,
1:14:45 economic,
1:14:46 uh,
1:14:47 well-being and the mental
1:14:49 well-being of refugees,
1:14:50 but also the relationship between,
1:14:52 uh,
1:14:53 host communities and refugees.
1:14:55 You know,
1:14:55 you want to start thinking about like how do you implement that policy
1:15:00 in a way that lends itself
1:15:01 to learning and so one thing to keep in mind and,
1:15:03 and,
1:15:04 and I,
1:15:04 I'm gonna refer you to also model,
1:15:06 module 3
1:15:07 in this series,
1:15:09 um,
1:15:09 uh,
1:15:10 you know,
1:15:10 was a lot about like uh learning agendas.
1:15:13 Um,
1:15:13 so one thing to keep in mind is this idea of thinking in,
1:15:16 in counterfactuals,
1:15:17 right?
1:15:17 Thinking about like
1:15:18 Uh,
1:15:18 uh,
1:15:19 what would have happened,
1:15:21 uh,
1:15:21 had,
1:15:22 uh,
1:15:22 those beneficiaries did not receive the,
1:15:24 the,
1:15:24 the interventions or,
1:15:26 you know,
1:15:26 thinking about the control group,
1:15:28 uh,
1:15:28 and the treatment group,
1:15:29 where treatment group,
1:15:30 you know,
1:15:31 receives an intervention and the control group is,
1:15:33 is,
1:15:33 is the,
1:15:34 you know,
1:15:34 or,
1:15:35 or comparison group serves as a counterfactual of what would have happened
1:15:39 had those people received the,
1:15:40 the,
1:15:40 the intervention,
1:15:41 right?
1:15:41 So,
1:15:42 uh,
1:15:42 and this doesn't necessarily mean,
1:15:44 uh,
1:15:44 uh,
1:15:44 a randomized control.
1:15:46 Although that's,
1:15:47 that's uh definitely a design that might be
1:15:49 useful in,
1:15:50 in some contexts.
1:15:51 Sometimes it's,
1:15:52 it's not possible,
1:15:53 but it could be also a,
1:15:54 a natural experiment.
1:15:55 So I'll give just an example
1:15:57 of a study that I'm involved now in collaboration with UNHCR.
1:16:00 So UNHCR in Uganda with World Food Program,
1:16:03 uh,
1:16:03 as I mentioned before,
1:16:04 uh,
1:16:05 they are cutting the provisions for refugees,
1:16:08 uh,
1:16:08 by,
1:16:09 by 50%,
1:16:09 so,
1:16:10 uh,
1:16:10 for many of the refugees,
1:16:11 uh,
1:16:11 by 50%,
1:16:12 so from.
1:16:13 And base level of support,
1:16:15 uh,
1:16:15 uh,
1:16:16 in terms of cash transfers and,
1:16:17 and,
1:16:17 and,
1:16:18 and,
1:16:18 and,
1:16:18 and,
1:16:18 and food,
1:16:19 uh,
1:16:20 uh,
1:16:20 uh,
1:16:20 uh transfers,
1:16:22 uh,
1:16:22 the level is being cut by,
1:16:23 by half,
1:16:24 but the way this was implemented is that all households in Uganda,
1:16:27 all refugee households in Uganda,
1:16:29 data was collected on them and they,
1:16:31 uh,
1:16:31 there was an,
1:16:32 an,
1:16:32 an index that,
1:16:33 uh,
1:16:33 a score for each household
1:16:35 of,
1:16:36 uh,
1:16:37 uh,
1:16:37 of,
1:16:37 of,
1:16:38 of need
1:16:39 and the idea was that there was a,
1:16:40 a,
1:16:41 a,
1:16:41 a cutoff where above.
1:16:43 Uh,
1:16:43 a level of need,
1:16:44 the level of support stays the same and below
1:16:47 that,
1:16:47 uh,
1:16:48 level of below this,
1:16:49 uh,
1:16:50 uh,
1:16:50 cutoff,
1:16:51 uh,
1:16:51 uh,
1:16:51 the,
1:16:52 the provisions are cut in half,
1:16:53 and,
1:16:53 and so what we're doing in collaboration with UNHCR
1:16:56 is we are
1:16:57 surveying
1:16:58 households in Uganda,
1:16:59 refugee households in Uganda just above
1:17:02 and just below,
1:17:03 uh,
1:17:03 the cutoff.
1:17:04 This is called regression discontinuity design.
1:17:06 It's,
1:17:06 it's not an experiment,
1:17:07 it's a natural experiment,
1:17:09 uh,
1:17:09 and we know that households just above and just below.
1:17:12 are very,
1:17:12 very similar,
1:17:13 we can show that,
1:17:14 uh,
1:17:14 and that allows us to and then we're gonna be
1:17:16 tracking them all the time and that allows us to
1:17:18 estimate the effect of
1:17:20 the reduction in provision,
1:17:21 OK?
1:17:22 So,
1:17:22 the,
1:17:22 the group above and below,
1:17:24 they serve as counterfactual.
1:17:25 Uh,
1:17:26 another thing that I want to mention is what,
1:17:27 what,
1:17:28 uh,
1:17:28 Gina was mentioning this importance of standardizing our collection tools,
1:17:32 uh,
1:17:33 in order to be able
1:17:34 to look at trends across,
1:17:36 uh,
1:17:36 across time and space,
1:17:37 really important.
1:17:38 I'm happy to hear that that's exactly what they're doing.
1:17:41 Um,
1:17:43 given the fact that social cohesion,
1:17:45 uh,
1:17:45 is subjected to social desirability bias,
1:17:48 we want to encourage also people
1:17:50 to think about different techniques
1:17:53 like survey experiments,
1:17:54 some list experiments,
1:17:56 and there's other techniques,
1:17:57 there's encouragement designs,
1:17:59 different techniques that we've been using.
1:18:01 Uh,
1:18:02 to measure things like hateful attitudes
1:18:04 that are subjected to social desirability,
1:18:06 but if people are interested,
1:18:07 I can give examples of how,
1:18:09 uh,
1:18:10 uh,
1:18:10 um,
1:18:11 this is done in,
1:18:12 uh,
1:18:12 in,
1:18:13 in the Q&A,
1:18:14 um,
1:18:14 given the fact that,
1:18:16 um,
1:18:17 uh,
1:18:17 uh,
1:18:18 social cohesion,
1:18:19 uh,
1:18:19 and prejudice
1:18:21 can manifest itself also in the behavioral.
1:18:23 Uh,
1:18:24 uh,
1:18:24 ways,
1:18:25 not only in attitudinal ways,
1:18:27 you can also,
1:18:28 uh,
1:18:29 design studies that measure interactions,
1:18:31 uh,
1:18:32 and,
1:18:32 and,
1:18:32 and this could reveal,
1:18:33 uh,
1:18:33 biases,
1:18:34 uh,
1:18:35 between,
1:18:35 uh,
1:18:36 uh,
1:18:36 hosts and,
1:18:37 and refugees.
1:18:38 So
1:18:38 a great example would be
1:18:40 Um,
1:18:41 uh,
1:18:41 we,
1:18:42 you,
1:18:42 you can send,
1:18:43 uh,
1:18:44 refugees and,
1:18:45 and,
1:18:45 and locals to,
1:18:46 to the market to,
1:18:48 uh,
1:18:48 to,
1:18:49 uh,
1:18:49 purchase the same goods,
1:18:50 and you can see whether,
1:18:51 whether they're receiving,
1:18:52 uh,
1:18:53 they can obtain them in the same prices.
1:18:54 It's a,
1:18:55 it's a classic example.
1:18:57 Uh,
1:18:58 I will just,
1:18:58 uh,
1:18:59 uh,
1:18:59 uh,
1:18:59 you know,
1:19:00 end by saying that,
1:19:01 uh,
1:19:02 you know,
1:19:02 going back to something that Eric mentioned
1:19:04 before which I think is really important,
1:19:05 this idea that we shouldn't only focus on.
1:19:08 Refugees,
1:19:09 we should,
1:19:09 and we should not only focus on,
1:19:10 on,
1:19:11 on,
1:19:11 uh,
1:19:11 uh,
1:19:12 uh,
1:19:12 because when we think about social cohesion,
1:19:13 it's about the interaction between them.
1:19:15 So we wanna encourage,
1:19:17 uh,
1:19:17 all of you
1:19:18 that are engaged in,
1:19:19 uh,
1:19:19 in,
1:19:20 uh,
1:19:20 uh,
1:19:20 in building the evidence base
1:19:22 to think about collecting data not only on refugees but also on,
1:19:25 on host,
1:19:26 uh,
1:19:26 community and,
1:19:27 and of course,
1:19:28 uh,
1:19:28 in,
1:19:29 in designing these,
1:19:30 uh,
1:19:30 the studies,
1:19:31 uh,
1:19:31 in designing.
1:19:32 The,
1:19:33 the,
1:19:33 the tools in designing the,
1:19:35 the types of
1:19:36 ways of asking questions that can
1:19:38 overcome things like social desirability bias,
1:19:41 uh,
1:19:41 uh,
1:19:41 we want to encourage you to also,
1:19:43 uh,
1:19:43 um,
1:19:44 turn to academics that
1:19:45 will be happy to collaborate with you.
1:19:47 There's a lot that they can,
1:19:48 uh,
1:19:48 that they can help,
1:19:50 um.
1:19:51 Yeah,
1:19:51 I'm gonna give just maybe,
1:19:52 uh,
1:19:52 I don't know if we have time to give uh an example
1:19:55 of the way,
1:19:57 uh,
1:19:57 you know,
1:19:58 we might approach,
1:19:59 uh,
1:19:59 building the evidence,
1:20:01 uh,
1:20:01 uh,
1:20:01 base of,
1:20:03 of,
1:20:03 uh,
1:20:04 of an intervention that we think might,
1:20:06 uh,
1:20:06 be useful for,
1:20:08 uh,
1:20:08 reducing,
1:20:09 uh,
1:20:09 prejudice and improving social cohesion,
1:20:12 um,
1:20:13 and so we,
1:20:13 we're gonna be looking at how to reduce.
1:20:15 Prejudice,
1:20:16 uh,
1:20:16 uh,
1:20:16 against displaced populations,
1:20:18 uh,
1:20:18 in Uganda,
1:20:19 and as I mentioned before,
1:20:20 there's a growing evidence
1:20:22 that,
1:20:22 but using lab experiments
1:20:24 that psychological interventions
1:20:26 like like uh perspective taking can reduce,
1:20:29 uh,
1:20:29 reduce prejudice.
1:20:30 The problem of these in,
1:20:32 of these laboratory experiments
1:20:34 is,
1:20:34 is twofold.
1:20:35 One,
1:20:35 there's a concern that like
1:20:37 any effect that you measure in the lab is very short-lived.
1:20:40 Uh,
1:20:40 and then there's another concern
1:20:42 that might be
1:20:43 that how,
1:20:43 how do you,
1:20:44 how do you move from the lab to,
1:20:45 to scale,
1:20:46 right?
1:20:46 Like how do you,
1:20:47 you design things that,
1:20:48 that,
1:20:49 you know,
1:20:49 can reach a large,
1:20:50 uh,
1:20:50 number of,
1:20:51 of people,
1:20:51 and
1:20:52 Eric and I came,
1:20:53 this is a study that Eric and I are doing together,
1:20:55 we came up with this idea that maybe we can
1:20:57 design a radio program.
1:20:59 Uh,
1:20:59 that has,
1:21:01 uh,
1:21:01 within its
1:21:02 purely,
1:21:03 uh,
1:21:03 uh,
1:21:04 uh,
1:21:04 uh,
1:21:04 with a higher entertainment values,
1:21:06 we sometimes refer to it as edutainment,
1:21:08 um,
1:21:09 where with,
1:21:09 uh,
1:21:09 which is serialized and,
1:21:11 and,
1:21:11 and a drama where the,
1:21:12 some of the protagonists are refugees
1:21:14 and through their stories,
1:21:15 through their
1:21:16 hardships,
1:21:17 through,
1:21:17 uh,
1:21:18 um,
1:21:19 through,
1:21:19 through the way that the show kind of progresses,
1:21:22 uh,
1:21:22 the listeners might,
1:21:23 uh,
1:21:23 develop greater empathy.
1:21:25 to the hardships of refugees and so
1:21:27 we're developing this program with the local
1:21:29 uh
1:21:30 organization,
1:21:30 a local media company
1:21:32 and,
1:21:32 and at the first kind of step,
1:21:34 we just worked,
1:21:35 you know,
1:21:36 really hard with,
1:21:37 uh,
1:21:38 uh,
1:21:38 local organizations
1:21:40 to first understand some of the conditions,
1:21:41 some of the possible tensions,
1:21:43 some of the,
1:21:44 uh,
1:21:44 in order to make sure that the,
1:21:45 the,
1:21:46 the,
1:21:46 the,
1:21:46 the,
1:21:47 the stories that we're gonna be telling in the,
1:21:48 in the show,
1:21:49 uh,
1:21:49 pertain to.
1:21:50 The,
1:21:51 the,
1:21:51 the real life and the real hardships,
1:21:53 we're developing this,
1:21:54 we're developing our pilot show.
1:21:55 We're gonna first like
1:21:57 uh uh study that in a lab setting where we're gonna just see whether
1:22:01 listening to
1:22:02 the show compared to not listening to the show
1:22:04 can move the needle
1:22:05 uh in a lab setting,
1:22:06 and if we show that we can
1:22:08 move the needle
1:22:09 and improve attitudes towards the future in,
1:22:11 in,
1:22:11 in,
1:22:11 in the,
1:22:12 in the lab setting,
1:22:13 we're then gonna
1:22:14 work to purchase,
1:22:15 um,
1:22:17 Uh,
1:22:18 uh,
1:22:18 uh,
1:22:19 airtime in local radio shows,
1:22:21 uh,
1:22:21 and,
1:22:21 and then we'll be able to,
1:22:23 uh,
1:22:23 look at,
1:22:23 uh,
1:22:24 attitudes towards refugees in villages
1:22:26 that receive the signal from the radio,
1:22:29 from the local radio,
1:22:30 and those that don't have access to these local radios,
1:22:32 right?
1:22:32 And so
1:22:33 this will be our counterfactual group.
1:22:34 So this is just,
1:22:35 uh,
1:22:36 this is just an example of how
1:22:38 We can,
1:22:39 uh,
1:22:39 uh,
1:22:39 use also researchers,
1:22:41 uh,
1:22:41 to test some of the,
1:22:42 uh,
1:22:43 interventions that,
1:22:44 uh,
1:22:44 we think might be,
1:22:45 uh,
1:22:46 effective in reducing,
1:22:47 uh,
1:22:47 prejudice.
1:22:48 Let me end,
1:22:49 uh,
1:22:49 with,
1:22:50 with this slide
1:22:51 before we open it for a few minutes to the floor.
1:22:53 Here's just,
1:22:54 uh,
1:22:54 5 things that I want you kind of to,
1:22:56 to take away from,
1:22:57 from what we've done,
1:22:58 uh,
1:22:58 today.
1:22:59 The first thing I want,
1:23:00 I want us to appreciate
1:23:02 that
1:23:03 uh there are tensions,
1:23:04 uh,
1:23:05 especially at the short term
1:23:06 when a large number of refugees
1:23:08 reach host communities,
1:23:09 right?
1:23:09 This,
1:23:10 and,
1:23:10 and,
1:23:10 and,
1:23:10 and,
1:23:11 and these tensions uh manifest itself
1:23:13 uh by the fact that
1:23:15 locals might oppose
1:23:16 uh uh open border policies,
1:23:18 they might oppose inclusive refugee policies.
1:23:21 Um,
1:23:22 uh,
1:23:23 but,
1:23:23 but we think that the fact that we,
1:23:25 we might have this short-term,
1:23:27 uh,
1:23:27 uh,
1:23:28 kind of,
1:23:28 uh,
1:23:28 backlash,
1:23:29 uh,
1:23:30 means that there's,
1:23:31 that there's the need
1:23:32 to,
1:23:33 to,
1:23:33 to think about ways of improving social cohesion is,
1:23:36 is a first-order concern.
1:23:38 It's,
1:23:38 it's a first order concern because
1:23:40 the more locals support inclusive refugee policies,
1:23:43 the more we can design policies
1:23:45 that,
1:23:46 uh,
1:23:46 that improve refugees uh well-being
1:23:49 and,
1:23:49 but when we say well-being,
1:23:50 it's not only the economic conditions
1:23:52 but also the social integration,
1:23:54 their,
1:23:54 their social life.
1:23:56 Um,
1:23:57 we know that social cohesion is multifaceted.
1:23:59 It,
1:24:00 it,
1:24:00 it,
1:24:00 it touches in many,
1:24:02 many aspects of life.
1:24:03 It could be material,
1:24:04 it could be symbolic,
1:24:05 it could be psychological,
1:24:07 uh,
1:24:07 and that's why when we,
1:24:08 we discuss the different types of interventions that can improve social cohesion,
1:24:12 we,
1:24:13 we,
1:24:13 we talked about About interventions that can affect these different,
1:24:17 these different aspects.
1:24:18 Uh,
1:24:18 it's important to come out of this,
1:24:20 uh,
1:24:21 uh,
1:24:21 uh,
1:24:22 meeting today
1:24:23 with a recognition that there are promising policy interventions
1:24:27 that have been shown to improve social cohesion
1:24:29 and they could be taken to different,
1:24:31 uh,
1:24:31 context.
1:24:32 But having said that,
1:24:33 it is also very important to
1:24:35 come out of this meeting knowing that the,
1:24:37 that there is more that needs to,
1:24:40 we need to,
1:24:41 to do in order to improve our evidence base,
1:24:43 so more research is needed to identify
1:24:46 which policies,
1:24:46 which intervention.
1:24:48 Interventions under which context
1:24:50 uh will be
1:24:51 uh best to
1:24:53 uh to implement in order to improve
1:24:55 uh uh uh social cohesion and,
1:24:58 and of course,
1:24:59 uh uh you can help
1:25:00 uh a lot in
1:25:02 uh building this evidence base.
1:25:07 Thanks a lot,
1:25:08 Guy.
1:25:08 Uh,
1:25:09 it's great to,
1:25:10 to know not only about uh
1:25:12 social cohesion,
1:25:13 uh,
1:25:14 but also ways,
1:25:16 um,
1:25:17 it can be evaluated and programs can be evaluated and,
1:25:20 um,
1:25:21 to better understand um
1:25:23 their impact and uh
1:25:26 um what we can learn uh and improve um,
1:25:29 in the programming.
1:25:31 Um,
1:25:31 we're now left with the 5 minutes to,
1:25:34 uh,
1:25:34 to close today's session.
1:25:35 So I'd like again to open the floor to anyone that would like to raise a hand
1:25:40 and ask questions to any of our,
1:25:42 uh,
1:25:43 panelists.
1:25:55 As people are thinking about the question,
1:25:57 uh,
1:25:57 Eric and I also wanna mention,
1:25:59 uh,
1:25:59 Puddo that works with our lab at Tagbeji Ganesi
1:26:03 who has
1:26:04 been really instrumental in putting
1:26:06 a lot of the slides together,
1:26:07 so we just wanted to thank him and,
1:26:09 and recognize his,
1:26:10 his contribution.
1:26:18 Great.
1:26:19 Um,
1:26:20 I'm not seeing any hands being raised,
1:26:23 um.
1:26:25 So I'll share a slides on my end.
1:26:27 Uh,
1:26:28 I think this takes us to,
1:26:29 to closing,
1:26:30 uh,
1:26:31 the session.
1:26:32 Do you
1:26:34 Yeah.
1:26:36 Oh,
1:26:37 I can share with my hand,
1:26:38 and that's fine.
1:26:40 Of course.
1:26:46 Um,
1:26:48 Paula,
1:26:48 maybe,
1:26:49 maybe I,
1:26:49 I will just mention
1:26:51 that,
1:26:51 uh,
1:26:51 as I said also in the chat,
1:26:53 there's a list of,
1:26:54 so during the presentation,
1:26:56 we,
1:26:56 we cited quite a few papers,
1:26:58 uh,
1:26:59 and so at the end of the slide deck,
1:27:01 we created a list of all,
1:27:03 all papers that we,
1:27:04 we referenced and all papers that we used in,
1:27:06 in putting the slide deck,
1:27:08 uh,
1:27:08 together so,
1:27:09 so people can have easy,
1:27:10 you know,
1:27:11 can easily find,
1:27:12 uh,
1:27:12 the papers that pertain to whatever is,
1:27:15 you know,
1:27:16 point that we made that interest.
1:27:19 Yeah,
1:27:19 thanks,
1:27:19 thanks,
1:27:19 guys,
1:27:20 for clarifying that.
1:27:21 And indeed,
1:27:21 we're going to post all the resources from today's session,
1:27:24 the recording,
1:27:24 uh,
1:27:25 the slides,
1:27:26 um,
1:27:27 on our website,
1:27:28 uh,
1:27:28 so it'll be available to everyone publicly.
1:27:30 And,
1:27:31 as well,
1:27:32 uh,
1:27:32 this content will be translated into an e-learning,
1:27:35 a self-paced e-learning,
1:27:36 uh,
1:27:37 training program that anyone can take and we'll launch that early next year.
1:27:41 Um,
1:27:42 we'd love to hear your feedback,
1:27:43 uh,
1:27:44 from partici participating in today's session.
1:27:46 Anything we can improve.
1:27:47 We have one more session to go,
1:27:48 so it'd be great to,
1:27:50 to hear from you on things we did well,
1:27:52 uh,
1:27:52 the things we didn't do as well.
1:27:54 Um,
1:27:55 and,
1:27:56 uh,
1:27:56 uh,
1:27:57 I hope to see,
1:27:58 uh,
1:27:58 many of you again at the same time next,
1:28:00 uh,
1:28:01 Wednesday for the closing session.
1:28:03 And we'll talk about,
1:28:04 uh,
1:28:05 labor market impacts,
1:28:06 some of it we've also covered today,
1:28:07 but we'll go more in depth
1:28:09 and also look at the job interventions and a cost
1:28:12 effectiveness study that looked at various types of job interventions
1:28:16 and was able to provide some insights on,
1:28:17 uh,
1:28:18 what's more uh value for money in that uh domain.
1:28:21 Um,
1:28:22 I'll close today's session,
1:28:24 uh,
1:28:24 by thanking all the,
1:28:26 uh,
1:28:26 presenters,
1:28:27 all the participants,
1:28:28 all the people that I have helped prepare,
1:28:30 uh,
1:28:30 and deliver,
1:28:31 uh,
1:28:32 today's session.
1:28:33 Um,
1:28:34 and,
1:28:34 uh,
1:28:35 um,
1:28:36 we meet again next Wednesday.
1:28:37 Thanks a lot,
1:28:38 everyone.
1:28:39 Bye.
1:28:40 Thank you,
1:28:40 Paula.
1:28:42 Thank you Pala.
1:28:44 Thank you,
1:28:44 Paula.
1:28:46 Bye-bye.
1:28:47 Thank you.
1:28:47 Bye.
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The seventh module of the Learning from the Evidence on Forced Displacement research program highlights key findings from the World Bank’s research program on Forced Displacement and Social Cohesion and describes how these findings can be applied to improve social cohesion in displacement contexts. The format features real-world case studies and participant interaction.
Speakers:
Erik Wibbels - Presidential Penn Compact Professor of Political Science, University of Pennsylvania & Founder of DevLab@Penn
Guy Grossman - Professor of Political Science, University of Pennsylvania & Founder/Co-Director of Penn’s Development Research Initiative (PDRI)
Gina Kosmidou-Bradley - Economist, UNHCR