 I would ask the presenters to join me on stage now. Unfortunately, there seems to be an issue with a robot connecting our discussant of the University of Ghana. That leaves us more time to discuss here in the room. So as the presenters are joining us, any immediate questions, concerns here in the room on the presentations, but also in terms of already picking up some of the homework that Annalena left us with, basically. Please raise your hand, and then we have mics in the room. Mine is not so much a question, but just a couple of observations to stress the relevance of this type of work. I mean, two observations. One is that this links very much back to a discussion that Martin Marvellian has been quite sort of strongly discussing over the years and taken somewhat strong views on. So I think it will be kind of relevant in relation to this to sort of make sure that it's linked back to his arguments and so on. And this is just observation. I haven't had the chance to read the paper, so this is potentially already in there. But it will be kind of interesting to hear whether you have any reflections on his rather strong recommendations and why he did that, and then the results or recommendations that you're coming up with. The other observation is that we've just been going through the corona crisis. And when one does a very careful analysis of corona responses or measures taken due to the corona and try to compare low-income African countries with other countries in the world, there are basically two extremely interesting things that stand out in terms of where do the differences lie. African countries in general did exactly the same sets of measures that the developed world. When you go through, I mean, controller movements, et cetera, et cetera, et cetera, all of that looks very much the same. But there are two very different things. One is the capacity of the public sector to respond because of fiscal constraints. And the other one is the long-term consequences of the inability to respond. I mean, those two things are essentially the key differences between the African continent and the rest of the world. And that, of course, stresses the relevance of the kind of work that you're doing. And it suggests, for example, a reference to Yucca's point, where is it that the African countries really are in terms of this sort of thing? So maybe I would sort of suggest that that's brought out clearly that actually we are finding the African countries up here, rather than down here, to get that message across. Because it is so fundamental in our policy discussions and thinking about the implications of this work. But those were maybe more comments. But thank you. Thank you, Fendt. We take Pekka, and then you get a chance to get back. Yes, I'm Pekka Seppala, coming from foreign ministry, so from eight world, more than a research world currently. Thank you for presentations. They're very nicely complementing to each other, getting from technical targeting towards this more political sphere in Anna Lena's presentation. Just one observation for this Yucca's Adnan's paper is question on data. I remember that in Ethiopia, the latest poverty data is from 2016. So what kind of data sets you can use to get the sort of national coverage? And that somehow relates to Michael Miehel's paper on because in eight, if you look at the Ethiopian case, you have an interesting, you have about 20 million poor people, but then you have like 5 million internally displaced people and many million refugees from other countries. So in addition to the normal poor, supported by social protection schemes, and which are supported by a normal aid, there is humanitarian aid targeting differently different sets of people which are partly overlapping. So my question is that you have studied the official development cooperation impacts. Do you also have located in some of these countries separately the impact of humanitarian measures? Is that somehow included? Yeah, and Annalena's paper was a very nice on this over-targeting politics, under-targeting. I'm always wondering myself about the seasonality of poverty and whether these protection schemes could be seasonally sort of distributed and whether that has been analyzed in any of the studies that you have come across. Because that could be, if you think about the effectiveness in rural food deficit households, so that could be definitely an important way of creating. It's not a kind of a targeting, but kind of a distribution method. So has that seasonality ever been sort of located as a distribution method issue? Thank you. OK, so thank you. So I just want to pick up on the last point that has been raised, the capacity to respond and the long-term consequences. And in fact, one interesting case study on the African continent is South Africa, which is by no means, of course, a typical African country. But for the first time during the pandemic, in my understanding, and now my South African colleagues can correct me, the country provided cash transfers to the working-age population who wouldn't be eligible for the unemployment benefit. And the eligibility conditions for that are quite stringent. So this meant a major change in the social protection environment. And the long-term consequence of that is in this ongoing discussion on whether that should be a permanent solution to have support for. And I see Aayanda in the audience, so maybe she wants to weigh in here on what the current policy discussion there is. But maybe this is a silver lining of the crisis that this can act as a catalyst. I mean, of course, there were issues in terms of the delivery of these transfers, et cetera. So that also highlights your point. And then, of course, there's the fiscal sustainability issue. So in that respect, the crisis was interesting. And then some analysis done by the SASPIR colleagues actually showed that at the height of the crisis, because of these transfers to the very bottom of the distribution, their incomes actually increased during the crisis, in comparison to the pre-crisis situation. So the system more than compensated for that. And it was not because these transfers would have been very large. It was just because the incomes to begin with were close to zero. So then the relative change is pretty large. Adnan, do you want to comment on the data? Yeah, Adnan is a question regarding the data. Yeah, there's two broad surveys in Ethiopia. The main one is social household consumption survey, which was recently administered in 2020. But the official poverty line is computing using the earlier version of the survey, which is 2060s one. But for ETMOD, we want also other variables, income and demographic variable. So this household consumption survey doesn't cover other variables, other than consumption and welfare variables. So we use the survey which jointly administered by Ethiopian's statistics office in World Bank. The survey called Ethiopian Social Economic Survey. So this survey administered usually once in two years. So the recent one is 2021 wave. So we use absolute poverty line from 2060 survey, and then we inflated to 2020 in order to measure the effect of the crisis on the poverty. And thank you. There you go. Thank you. It's, I think it's working. Okay, okay. Well, thank you so for the comments. So I would try to link the comments by Fina and our colleague in relation to crisis. For example, what we know from COVID, which is the last major shock that the globe has faced. There were about 3,000 responses to mitigated effect of COVID globally in terms of the area of social protection. After 12 months, just about 20% of the programs remains in place, which also speaks to two, at least overall things. One is the financial requirements to sustain these programs beyond the crisis period. And the other one, the institutional ability to also maintain these kind of policies. So what we know, the importance of these systems really reflect the fact that if you think about what we don't have sufficient data to look at the effect of COVID substantially in this context, probably in a couple of years we will be able to do it. But in relation to previous crisis like the financial crisis of 2008 and 2009, we know that primarily middle income countries who had social protection systems in place at that time were the ones able to absorb the financial assistance by international agencies to mitigate the effect of these shocks, as contra-cyclical measures. Many countries that didn't have those systems weren't unable to actually capture those resources available by multilaterals and also development banks. So this also underscores the importance of building these institutions, but also again connects to the issue of the fiscal space that Yucca was referring to. So there's an issue or a connection in this area. So in terms of the humanitarian assistance, I think this is a very relevant point. The way certain countries are facing displaced populations also reflect an attention. Usually if you look at the data by population data, I use data that reflect population and also aid. We can capture assistance to humanitarian responses, but in the data of population, many of the displaced populations are not captured. So we will need to do an additional work to actually look at this. But this is a very important point, thanks. Anna-Lena. I would say a more of a big picture, thank you sir, I can't speak to the technicalities in as much as you can. But I really appreciate also the comment on seasonality. I think it's what I was trying also to say with adaptive social protection, which is learning from climate change, early warning systems and so forth. I think what I would like to stress really is like, okay, after, and I was talking with Miguel about this, I haven't been in the social protection space for very long, but it's the kind of debate seems to be coming back to the same points. I think what we were talking about in 2012 or what we were talking about after the crisis, even for me, sounded very familiar. And it was a moment where I was a bit surprised to be honest. So I was wondering if like after decades of development, we still have systems where people are not able to participate in all spaces of the economic system. They are becoming increasingly complex. They are becoming increasingly volatile because while we might treat COVID as an isolated event, there's of course a lot of reason to think about the future and climate change and all of these different crises that have very different outcomes. So it's a state of not knowing as well. And I wonder what happens if we let go of that need paradigms thing beyond it, right? Because that's the political foundation that underpins targeting. It's trying to identify groups based on need. So what happens if we let go of that? Can we think a bit broader in terms of like, I don't know, I'm kind of pushing this possibly in a bit of James Ferguson's corner and having the rightful share for people and perhaps design systems a bit differently going forward. I think that's the kind of point I was trying to stress a little bit. Thank you. If there are more questions, please. Yes, the lady in the middle there, please. Thank you. Thank you very much for those very good presentations. My name is Karen Kandier from the National Treasure League in Kenya. Just some comments. In your research, did you take into account the sufficiency of social protection? For instance, in Kenya, what we have is some transfer of 2,000 Kenya shillings to persons aged 65 years and above. 2,000 shillings I've translated for you. That's about $13 per month in current exchange rate. Probably six months ago, that rub in $15 is not enough at all. So we could say there is social protection, but is it really protecting? Because they amounted so little. That's just one meal. If I go to McDonald's or somewhere there. Then there was one of the presentations. I don't remember who the presenter was, but he talked about very low social protection for pregnant mothers. I was wondering whether there's been any focus on expecting mothers because I believe that is where it all starts. Expecting a mother who is not well taken care of, who doesn't eat enough, produces a child that will probably need medical care throughout their lives. They won't do well in school and their cycle continues. So I don't know whether there has been very specific targeting of expectant mothers. Then there is one of the presentations that spoke about on the number of women in parliament. But I didn't get that point. If you could please elaborate on that. What was the impact of having more women in parliament? I didn't get the point you were making with that reference, but I thought it is an interesting reference, especially because women are generally underrepresented in parliament. Thank you. We have a space for one to a question. I see now two hands. Two short questions and then a quick last round. Then maybe one person gets back to each question so that we make sure every question is correct. Thanks a lot for the presentations. I have a question about the modality of delivery of donor funded social assistance perhaps for Miguel because you alluded to it in the last point of your presentation, saying that in certain cases donors directed their funding towards project aid because of your regime capture. So basically configurations where the budget is held by external agencies rather than national governments where key decisions about registration, targeting and delivery are done by these external agencies. Have you found some effects on the outcomes or are there potential effects on perverse effects on capacity building, bad targeting, things like distrust vis-à-vis these programs as well? So it's a more political, political economy question about delivery. Thank you. My name is Paola Kuma from Uganda, EPRC. Mine is a follow up from the comment from the official from the Kenyan Treasury. We do have a social protection for the elderly in Uganda also. Much lower, maybe $5 a month. The amount received. But in the context of the study by Yuka and the gentleman from Ethiopia, it's little for many reasons. One, of course, resources. There are not enough resources. Even the design right now depends mostly on the UK government. A lot of the funding comes from the UK government. Probably the Ethiopian one also could be donor driven. Second, it's because also in Africa there are a lot of other systems existing side by side, informal social protection, which you need to take account of and it's big and very healthy and does deliver a lot of social protection. Family, friends, like in Uganda, you don't need to pay for your wedding. People will pay for it. Your friends will pay for it. The third and the last, it's because we are in experimentation stage. You don't want to pump in a lot of money when you don't have systems. You don't know how it's going to work. You want to put in a little bit of money and see how it's going to work. I guess a lot of African social protection systems are still experimenting, trying to build institutions and that's why the amount is also small. So I think these studies need to take those issues into account. Apart from South Africa where they already have something going on. Thank you. Thank you. So maybe let's start by Miguel because you also got a question specifically directed at you. Thank you again for your question. So let me briefly address the issue of the transfer size that they are not sufficient to provide coverage. If you look at the average of those programs cover about 30% of net labor income on average, which in my view also have quite, there is plenty of evidence and we can talk about this that even these small grants actually have a substantial effect in certain areas. But obviously this kind of the transfer size is related to the fiscal space that many countries have. So if you increase size you need to have the ability to finance those programs. But nevertheless there is a substantial difference in the transfer size. In cash transfers there is a small you look at pensions, I think the transfer is much greater and also the value of services for example universal health insurance provide a cost unit that reflects a much greater transfer in monetary terms. So it depends where you are talking about, no? But in terms of the political economy which is also a very important thing that we did I mean we complemented the study the econometrics and you know all the quantitative analysis qualitative approaches to to understand precisely the political economy dimensions of that and I interviewed several colleagues in different agencies trying to understand how choices from moving from you know bilateral aid or decisions taken at the national level how that influence or may you know diverge from the choices by multilateralism. Very often the main decisions are driven by political factors in donor countries, no in recipient countries, no? Because the consistencies or you know you think about many countries are moving towards lower income or low income countries many of them private states or authoritarian regimes it's very difficult to argue or get support by the population to continue financing those regimes so obviously there is a political impact on continue financing these and the choice is to do it through a neutral you know between practice neutral actor which is for example the World Bank or UNICEF no? So there are certainly effects in terms of the influence that countries, donor countries can have on this dialogue obviously the dialogue continues through multilaterals but obviously multilaterals make certain choices and decisions based on their policy priorities and this is also observed in South Africa in particular by the way programs have been shaped by the influence of the World Bank in particular the World Bank has been incredibly influential but what I can tell you from our qualitative analysis is that those choices reflect donor country politics. Thank you. And Nanyoka do you want to take the questions that came regarding your presentation? Thank you. Yeah, the resource allocated for the benefit program is very less, not only in Ethiopia this is the case for most of the sub-Saharan countries. For instance in PSNAP or PMET program in Ethiopia an individual who is a client is only 15 kilogram of white rice or wheat flour in a month. So our analysis shows that most of the recipients are in the button to quintiles. So even after getting the benefit most of the recipients still remain in poverty. So the main use program is not reducing poverty rate but it helps to only minimize poverty gap since it reduces the gap between the bottom income and the poverty threshold. So when you see also the coverage still less compared to the share of poor in Ethiopia per the national figure around 24% of Ethiopians are poor but the population is now above 100 million but the total in total the benefit covers around 8 millions individuals. So not only the amount even the coverage is lower. Thank you. Yes very little to add I basically agree on what was said and so certainly I would like to say that the poverty measure is low and then also quite a bit of depends on what one's poverty measure is because the head count rate we showed here is not the best possible measure in this context perhaps and that's why as Adnan Koraki pointed out we also look at the gap when it comes to the informal arrangement that's absolutely crucial with the kind of data that we have we don't work on panel data so we don't know how the in the household transfers react when income is declined but that's an important addition as well to the picture. Thanks. Anelina you want to say some final words? The final verse is a big responsibility. I pass that to you. I'll do the final final verse. I don't think there was a question. And also there's a coffee break so you can always catch the presenters as they go off stage for more discussion. Thank you very much first of all to the presenters for a very interesting session. Thank you to all of you for being here showing interest with questions and comments and I hope you carry on discussing. There will be a book coming out next year that will be around all these questions parts of these presentations you will recognise when you then have the book lying on your bed night table and will read it every night I'm sure. So thank you very much have a nice coffee break.