 Thank you very much to all our presenters. Now we will have a video discussion by Vanda Castello from the Mosmon team. Good afternoon. Thank you for having me in this session, in this debate. So I would like to say some words on the three working paper, on the three presentations that we had here. Because what I saw is that those papers gather consensus on the crucial role played by social protection programs in supporting the most vulnerable people, especially when we talk about children and elderly people. What make those programs key instruments also in times of crisis such as the COVID-19 episode that we had two years ago. However, the existing problems in many countries' social protection systems, especially the least developed ones like Mozambique, my home country, I'm talking about the low coverage of the programs, the high level of informality, lack of well-organized database on vulnerable populations. And also it makes difficult to know exactly who are those vulnerable populations and the complexity of the eligibility criteria in many of the programs it makes it difficult to select or to target the beneficiaries. And because of all those issues that I have raised, the initiatives carried out by the government have limited impact during the period of shock. And the interventions made in that period have not been enough to reverse the reduction in consumption due to the loss of jobs and source of income of most of the population. And also was not the intervention those social protection programs, the initiatives that the government have undertaken during this period were not sufficient enough to counteract the worsening of poverty and inequalities in many countries during and after the pandemic. And also the other issue that we had before the pandemic crisis we see that many of those social programs the amount assigned to the beneficiary were low, were considerable low. And it's common in many of the countries. It's a situation that was, we see that was aggravated by limited fiscal space and it makes difficult to increase the amount and also difficult to expand the coverage of benefits in order to meet the national targets. So these realities call us to think on the need and the urgency of strengthening social protection systems and also take advantage of some initiatives that we saw during COVID-19 such as use of remote and digital solutions to reduce the cost of providing social assistance and enable the expansion of the coverage. And also it means that we need to continue thinking on how to make the eligibility criteria more flexible and also the best way of targeting the beneficiary so we can have an effective impact of those programs. So despite the limited impact of social support during COVID-19 there is no doubt as we saw in those presentations that social protection has acted, has an automatic stabilizer to protect people's incomes during the pandemic which also is an opportunity that can be catapulted into other subsequent cases of extreme shocks. So those are the words that I would like to address and thank you for this opportunity. Thanks a lot Vanda, I think she might be connected remotely and perhaps as Vanda rightly summarized some of the key issues related to identification, targeting but also other features of the design of policies like generosity and perhaps duration. I'll just invite our presenters to keep that in mind also when we now open the room for questions from the audience just to come back to those main issues that Vanda also pointed out. So perhaps I'll take the opportunity as a chair to ask some questions and then we'll have a second round to open to the audience. My first question to David and something he could not discuss perhaps due to time was validation. So for Latin American countries now we have actual data for the last quarter of 2020. So how good does the no casting perform and whether now with the actual data that we have for 2021, 2022 there has been more evidence on whether the economy has recovery and whether some of the social protection programs have been actually expanded. Perhaps I'll just give a set of questions and then I'll leave room for you. Catrin related to your presentation, I was also wondering so as we see very little effect of social protection in times of crisis, I was wondering then what other mechanism is acting. So do you have evidence on whether for example in times of crisis the data shows that there's more on produce so people rely more on produce or whether for example in terms of a shock in unemployment, whether informal employment starts acting as a potential stabilizer. So people move from formal employment to informal employment to cushion to some extent the extent of the shock whether you have any evidence on it. So what are people actually relying on in times of shock. And then finally, Guy and I was wondering so I thought it was extremely interesting to dig into the regional differences. So we saw cross-country differences in the first presentation whereas the pictures you showed were very interesting. First in terms of how the pandemic hit Vietnam across regions but then also in terms of the targeting and how the eight packages were distributed along the country. So I was wondering what are the main differences that drove first of all the impact of the pandemic. So do we also see regional differences in the healthcare system so in terms of quality in terms of size and then how does that open a question of you know where we're to invest in terms of healthcare or social protections or whether there are big differences also across those two dimensions. Okay, so for the validation part we tried several strategies. At the beginning we use approved and also some kind of means are estimated to now cast the incomes but the alternative that we used for the final version of the paper was the best. The idea is make this profit and also taking the difference in average earnings between groups and in terms of validation what we found is the distribution if you estimate a kernel for marketing incomes they are quite similar. We can compare this in Q4 because we have the complete information for Q4 so we can compare actual data for Q4 and our now casting technique and the distribution looks okay so the now casting seems to mimic the kernel distribution but if we go to Gini coefficients or poverty statistics is not fairing that well. In some countries it's good but in a couple of countries it misses the values that we observe in the data and regarding the policies in 2021 for most of the countries the policies were erased for instance in Ecuador we don't have policies at Q4 maybe there is one at the beginning of 2021 but for most countries the emergency policies were dropped from the menu so the idea is now with the updating of the models for the south model to see the new policies, the effects. Thank you about what coping strategies households apply in times of crisis because in our case we are interested in an artificial shock and how the system reacts to it we are not really focusing on changes in informal employment or own produce but what we see is that if households have other households members with employment incomes or household members that are supported by the existing social protection system that these income sources of other household members provide some sort of insurance in times of crisis I mean they cannot cushion all the income losses but they provide some protection to a shock to household incomes. Thank you. So I think you raised a very important question about the regional difference in the social protection and the healthcare system in Vietnam so in Vietnam as I mentioned there are 63 provinces and in Vietnam the living standard is very different across the region and across the provinces for the social protection actually the social protection they targeted at the household level so basically there are no differences in the social protection across the provinces or across the region because they targeted at the household level so they targeted at the poor and ethnic minority and the policy household so but in terms of the healthcare system it's more in the poor area in the mountain and the remote area the healthcare system as not good compared with the richer region however in Vietnam during the pandemic so actually the poorer area they are less affected in terms of the COVID because the COVID cases were very high in the cities in the area with the higher population density and because they have the high population density and especially in the south of Vietnam they did not implement the lockdown policy very well so that's why in the south Vietnam there are more COVID cases there are more people affected and a lot of people die in that time when they don't have the vaccine so in that time the healthcare system although in the city it's better in the poor area but because the higher population density and higher COVID cases so they are more affected so I think that also for the COVID it's not only problem of the social protection but also as a policy like the lockdown policy they are also important in Vietnam in the north in the city like Hanoi city they also have the higher population density but the lockdown policy seems better than in the south so the number of COVID cases is smaller in Hanoi so I think the social protection is important here also important but maybe especially for the pandemic like COVID the lockdown is also the most important in case when the people they don't have the vaccine so that's important Thank you again to the presenters now we give the opportunity again to the audience for any further questions So I should partly know this myself but I'll blame it from having been away from the job for a little bit there's been always a lot of talk of what can we learn from COVID is there at least some learnings we can take from a really bad crisis also in terms of policy half is already sad everything was kind of just dismantled again from the emergency measures but I'm wondering now over time and the countries that you've worked with or that you've also been visiting and done trainings in I mean it clearly must have the debate on social protection was on during COVID and I'm wondering in your research but also in your exchange with countries have you seen any changes maybe not forcibly yet in policy but in the way how people look at social protection and the way how it should be run I'm not I'm not asking for a silver bullet for proxy means testing versus income testing but just how you feel the debate might have shifted or changed now that we are more or less out of COVID Okay so in my country I think that after the pandemic well during the pandemic there were difficulties to reach the poor in need so one difficulty was for instance that the people that did the cash transfer didn't have at the moment a bank account or access to the financial system so the government implemented some digital alternatives to make the transfer and after the pandemic they realized that this was very important so for instance the government now is trying to deploy a social registry trying to capture more easily the information for the people not receiving the transfers because they have a robust system for those receiving the typical transfers for instance conditional cash transfers this is a very good database but for during the pandemic well there were some beneficiaries that were not some potential beneficiaries due to the pandemic that they were not receiving anything so the government went door to door looking for them so I think that's the change but not a change in the in the tax system but in the way that we have information for the potential beneficiaries that's the main change that I see yeah thank you so much for the presenters congratulations for the good presentation my name is Yosef Atma from Tanzania Revenue Authority so I'm just adding up on issue of social protection I think it should go case by case for example in Tanzania the social protection went to exemption to the companies to the companies which we are producing this mask so to the government provided mask to some people to protect them so even though we didn't have the lockdown but the issue of social protection was considered because the exemption was provided to some importers who are importing this mask for the people and even the companies which we are producing the senators so those they as what we apply to the hands so so that's what was provided by the government and the exemption was granted to those companies which we are producing it so if we say the protection was provided by the government so thank you so much I just want to add that thank you for the comment and perhaps to come back to the comment and to Vanda's questions I guess all the presentations were taking a stake about what happened but perhaps the main the second aim of the presentation was what do we learn and where do we go from here so I'd like just to give perhaps two to three minutes to each presenter to let us know so then what or how should social protection look like if we were thinking about systems that would protect better vulnerable populations and also what are the financing options clearly Vanda referred to that so if you were to propose something to do an exact evaluation of what social systems should look like for in order to cushion income shocks from future crisis what would you be suggesting well I think I think for us it's important to first of all show that there are now tools in place that help you to carry out exact evaluation so in our case we are not focusing on covid per se but we are providing more general results and we are using tax benefit micro simulation models that are openly accessible so we are hoping that by also showing these results we can start a conversation in different countries about how can we use the limited budget to improve the social protection system and how can we not only prepare the population for life cycle shocks or more general shocks but also how can we improve the design of our system to provide insurance in times of crisis so I think maybe a message that we would like to push is that exact evaluation is important we are aware that the fiscal space is really small and by using tools such as tax benefit micro simulation but also other tools governments now have the possibility to test and to understand the design of their system better and to test how they can use the fiscal space and of course increasing the fiscal space is also important and how can we improve not only the coverage of benefits but also the amount of benefits is important so we need more fiscal space and I'm sure there are various options where we can, I guess that's also the theme of this conference right, how to increase revenues and of course one important agenda is also to bring more people into formal employment and so that they contribute to a larger tax base and to more revenues. There are various tax exemptions that we have already learned about this morning that could be thought about I guess in many cases increasing the revenues is not only looking at households but really looking at companies and other actors in the economy but for me one important message is really to use the tools that are out there to carry out the exact evaluation of social protection systems to start thinking about the design of measures and to understand better how the system works and where we have maybe coverage gaps and where the system is not sufficient. Thank you. Well one thing that I pick from my presentation and Catherine sees this role of automatic stabilizers I think as we saw that automatic stabilizers are not important in the context of crisis and for instance in Latin American countries they had to increase suddenly a lot of government expenditure but if you have automatic stabilizers and these are well designed you don't have to do that in times of crisis so I think we have the models and we can think for instance on some kind of unemployment benefit that is not currently in some countries in Latin America maybe that they automatically cushion the effect of crisis so I think that is one message important from our research and we can model this with the tax benefit micro simulation for Latin America or for Africa to see how to cushion this kind of event. Thank you. So from experience from Vietnam so I think so that time the Vietnam failed to impose a lockdown in the south of Vietnam so that caused many people died that time and one reason is that because the government they have the limited resources so they try to identify the people the most affected people and provide the support for them but it takes very long time to identify the correct one so I think a better lesson maybe during the pandemic so the government they should provide the full coverage the full coverage the support for all the people so and once all the people they can receive their support timely and then the government they can able to impose the lockdown because if they impose a longer time of lockdown and the people they don't have the job they don't have their support so they cannot they cannot follow the lockdown so I think one lesson maybe during the crisis like COVID-19 and if the government want to impose the lockdown for long time they have to provide the social assistance for all the people they don't need they shouldn't care much about the leakage they don't need to care about how to identify most affected people they should provide the full coverage of course that got a lot of money but we need to do that we should do that I think thank you and I think all points are very very interesting coming to the last point that's something that happened for example in Brazil in Brazil is the only country in Latin America where during the pandemic 2020 inequality dropped because these eight packages were given almost universally there was a big expenditure from the government and actually what we see now is the reversal so in 2021 now inequality has increased so perhaps goes in the direction as you said perhaps is not only thinking about the generosity and targeting is thinking about the duration so how timely this the government can react to in terms of crisis if there's any last comment from the audience okay thank you very much for your good representation my name is Issa from Zanzibar I want to address my question to last presenter about the estimation techniques we know when we want to propose a policy implication we need it to rely on the finding of the result but I'm not sure whether the estimation technique the last presenter used it was robust or not so I just want to know the justification of selecting fixed regression model in studio for random regression model thank you okay thank you so actually in the I use a panel data something like a panel data and with the three year in the baseline in the 2019 no one affected so there are no lockdown no catch and for support for COVID and then in the 2020 and 2021 the lockdown time and the eight package level they are very across the individual and very across the provinces so that's why we can identify the impact for other characteristic level maybe you can take my report so it's a more fully description of the method but I think it's a quite simple and straightforward question yeah great so not only can you take a look to the report you can also catch up with any of the presenters during the coffee break so please free feel free to interload them and if you have the opportunity so thank you very much to everyone especially to our presenters to have asked questions in the audience and I hope you enjoy the coffee break and the rest of the conference