 each other. So let's see if we could go to the next slide. So the first on the left hand side here is as Megan introduced, a paper called Snakes and Ladders and Loaded Dice and essentially what we wanted to do in this paper was update some prior research that we've done on social class, social mobility and poverty dynamics in South Africa with the full five waves of the national income dynamics study panel data. So this is really nice longitudinal data in which we follow the same South Africans between 2008 and 2017 and we really observe how these South Africans, a nationally representative sample of South Africans move into and out of poverty over time. So that's the strength of this first paper and we'll get I'll explain a little bit more about that now what we then wanted to what we're then going to discuss and I'm going to hand over to Simone for this is a follow-up paper that we've written on the livelihood impacts of COVID-19 in urban South Africa and where these papers speak to each other is that in that first paper using exploiting this the feature of the longitudinal feature of the NIDS data, we could estimate vulnerability to poverty and we developed a social stratification schema which was really rooted in this vulnerability concept and when we speak about vulnerability here we mean vulnerability the inability to protect oneself and one's household against a negative and unexpected shock that's one element of vulnerability and and COVID represents a large shock of this nature a large simultaneous shock of this nature so so that's where we tried to map these findings from this first paper that we did onto onto the COVID context and here we used a continuation of this panel the NIDS cram data which I'm sure many of you have heard of which uses the same sample as as this first paper as the NIDS panel data and then we supplemented this with some in-depth qualitative interviews in a way this was also a qualitative panel because we've previously done research in 2017 with these same individuals so we followed them over time as well but Simone will give us more details about that all right so the first paper I'm going to give you a very quick 10 minute synthesis of of this research and there are a couple of things that we wanted to look at and achieve the first was we wanted to give a descriptive picture of South Africa's social stratification landscape and as I said before root this based this the schema of social stratification on this vulnerability concept of the likelihood that people have of staying of remaining in poverty moving out of poverty or falling into poverty okay and the rest Simone is going to take us through you can go ahead Simone so and again all right so to give you a summary here is what we usually start with when we when we undertake poverty analysis is we try the most basic possible scenarios we measure the number of people who are poor at a given moment in time and these those might be identified as poor because their household income falls below a given poverty line that's a snapshot at a moment in time this snapshot at a moment in time underestimates the number of people who will experience poverty over time so the number of people who are measured as non-poor or amongst the people who are measured as non-poor at a particular moment in time some of those people have come from poverty and some of those people will fall back into poverty or fall into poverty equivalently some of the non-poor some of the some of the poor will end up escaping poverty so it's important to or what this panel data does which follows individuals is it allows us to understand who's moving into and out of poverty who constitutes the chronically poor who constitutes the the stably non-poor and what is that group that's in between those people moving frequently into and out of poverty so we do this as I said using the national income dynamic study which was implemented by soldier at uct from 2008 to 2017 to provide this dynamic perspective and we can use this which is what is a very rich data set to not only observe poverty patterns but also to use household and individual level characteristics to predict the propensity that individuals face the the probabilities that individuals face of falling into poverty if they're not poor or escaping poverty if they are poor and we use this this predictive approach to divide the population into different class strata all right so to start with this is just a descriptive snapshot of poverty dynamics in the population so focusing just on the left hand side here under total what we have is the darkest section of the bar represents those people who are observed in five out of five waves of the nid's panel data so at every point we observe those individuals from 2008 to 2007 the darkest section of these bars represents those people who observe to be poor in every single one of the five ways so dark is bad dark is more often poor and light is less frequently poor so the lightest bar represents the proportion of the population which was never poor and the different shades of blue represent those gradations so what we can see is that approximately 35 percent of the total South African population was poor consistently in every wave at which we observed them between 2008 and 2017 only about 15 percent were consistently not poor but these these poverty dynamic these these this poverty this poverty dynamic landscape is correlated with household and individual level characteristics so Africans as you can see black South Africans are much more they're living in a different poverty universe compared to white South Africans white South Africans are almost always not poor whereas only uh just under 10 percent of black South Africans were not poor in every wave that we observed them um the same or a similar pattern holds true for education for for gender and for the urban rural divide as you can see here where rural people are more often chronically poor than urban people women more often chronically poor than men etc all right and this maps these these poverty dynamics also map into also have correlates in the in the employment landscape so employment contracts which are temporary um or self or those who are working in the informal sector as as self-employed workers also experience higher rates of chronic poverty and higher rates of of transient poverty in particular the a large the the large majority of those people in unprotected forms of work um are moving into and out of poverty with some with some frequency few of them are stably non poor all right so using so with this poverty poverty this landscape of poverty dynamics in mind um I'm going to introduce our poverty uh our schema of social socioeconomic stratification and this is going to be useful in Simone's part of the presentation where we map this onto the COVID context so focusing just on the left hand side here on the left hand side in gray we've got the standard subdivision of society between poor and not poor middle class here it's just we can simply understand is not poor all right and above that we've got the elite which we sort of arbitrarily define as as much wealthier um than the rest of society but this poverty threshold is simply the poverty line so uh the status a um poverty line which is around 1,300 per person per month that's the poverty threshold that we're using here just to divide the non poor from from the poor but then what we do in addition is we try and we within each group so focusing just on the poor within the poor we um we distinguish those with a below average probability of exiting poverty as the chronic poor and those with an above average probability of exiting poverty as the transient poor okay so essentially what we've done is we've further subdivided the poor into those who are likely to remain poor and those who are more likely than the rest to escape poverty we do the same for those who are not poor so for those who are not poor we identify those who have gotten above average probability of falling into poverty as the vulnerable and those with an above with a below average probability of falling into poverty as the stable middle class so we could think of this as the genuine middle class all right so what we've done for them for the non poor I said some of these non poor are likely to fall into poverty over time some of them are going to stay non poor and that's a relevant distinction what we find is that um I actually could you go back a second Simone if you see on the right hand side here the transient poor and the and the vulnerable are highlighted here because what what we expect is that these people are going to be swapping places frequently over time the transient poor are going to be below the poverty threshold at any moment in time but they're likely to move above it over time and just like the and the vulnerable as well are above the poverty threshold but they're likely to move below it so we expect these two groups to be somewhat similar we expect them to be swapping their swapping positions over time all right we can move on all right so applying this schema to the South African data the mid-stator we can estimate the size of these different groups for each year's for each year of mid-stator that we've got and what we see is that about half of the South African population is chronically poor and repeating what I said earlier what this means is that not only are they poor but they're unlikely to escape poverty all right then about 20 percent of the population this is the yellow sub bar here about 20 percent is stably middle class that is they're not only not poor but they're also unlikely to become poor all right and in the middle we've got this big chunk of people about one third of the population which is occupies this this position of precarity of straddling the poverty line some of them are above the poverty line some are below but they're going to be swapping places over time all right and I'm going to give a quick snapshot of the of the labor what the labor market characteristics of these of these two groups are and what we see is that while the chronic poor is most of the chronic poor are simply excluded from the labor market so the gray bars and the light brown bars here are economically inactive or unemployed so the vast majority of the chronically poor are simply not in the labor market that's not the case for the transient point the vulnerable and actually the labor market characteristics we could go into this in more detail but a very broad snapshot as I'm presenting here the labor market characteristics are quite similar and the salient point here is that a lot of them are employed in highly precarious forms of labor where they're unable to avail avail themselves of the labor market protections which characterize the the middle class and the elite all right I'll end on that and hand over to Simone to introduce our work in the covert context thanks a lot great thanks so much rocker and yeah I think you already introduced this research very well so all what we were just seeing is what we did before covid hit south africa and as rock explained covered in a way presents this large covariate shock that we can then analyze how those different groups of people who we already know are more or less vulnerable to these types of shock how they fare during this difficult time so I'm going to start with some quantitative snapshot from the nitscrumb data and then we move into our own qualitative field research um so just as probably most of you know like south africa was one of the countries most affected by covid-19 it had one of the earliest and strictest government reaction also to it so you had a very strict lockdown that lasted from the 27th of march up to basically the first of june so the um restrictions and movements were only actually relaxed with level three of the lockdown so we have this relatively long phase of strict stay at home orders and despite these you see the rise in cases up to basically mid july when cases peak during the first wave and during the time cape town um or the worst and cape province emerged as one of the hotspots accounting for about 45 percent of confirmed covid-19 cases up to july and these stringent policies had had an effect on people's welfare levels as we can see from the nitscrumb data so here on the left hand side you have poverty figures from the 2017 nits where you see that about 46 percent of the population fell below the national upper bound poverty line and about 19 percent were food poor by national standards and if you look at the incidence of people who experience economic distress with the in the early phases of the pandemic we see that about 40 percent of the household has lost the main source of income since the lockdown had started in march about 47 percent of the household ran out of money to buy food in april so during the phase of the lockdown and this is not necessarily meaning that they were food insecure so they could still find other ways to put food on the table but they were clearly under financial distress and then about 24 percent reported that at least one household member is an adult or a child experienced hunger during may or june so those this is not directly comparable to the food poverty measure we have for 2017 it gives an indication of a potential rise in food insecurity during this early phase of the pandemic and this has been confirmed by other papers looking closely at this issue in the early nits ground waves um when we look at who experienced this type of financial distress during the pandemic what we see is those who were observed to be poor prior to the pandemic clearly were more exposed to the shock so they have a higher incidence of experiencing any of those three events since the start of the pandemic however you also see that a substantial share of the non-poor experiences events so they were enchilled against the effects of the crisis and we then wanted to look a bit more closely like what are the profiles of those people who were experiencing financial distress with the pandemic and something that we find is that the profiles are quite different from those who we historically know have always been poor in South Africa basically so as Rocco showed you before like from our earlier research with the earlier wave of nits we saw that the incidence of poverty was generally much higher in rural compared to urban areas for example however this geographic divide is much less pronounced if you look at the outcomes in 2020 so the gap between rural and urban areas has it's much narrower compared to the standard poverty matters so urban areas were much more affected than they used to be by normal poverty standards we also observed that actually the highest incidence of this three measures of financial distress and the early phases of the pandemic are highest among those living in informal housing so often housing at the fringes of urban societies so here we see that about half of those living in informal housing had lost the main source of income about two thirds ran out of money to buy food and about one third actually went hungry in may or June and if you see like the this is for at least for the first two events is even higher than those living in traditional housing mainly concentrated in the rural areas of the country so you have this kind of urban bias of those who experience financial distress another thing that we observe is those who experienced financial distress in 2020 were much more reliant on labor earnings compared to those who had previously been observed to be poor so previously we observed the highest incidence of poverty among those who were mainly relying on government grants so we had grant income as a main source of income now this financial distress is often experienced by people who also have labor earnings as the main source of income prior to the pandemic or also remittance income so we have high followings in these two sources of income so even though we see that the profiles are quite different so they are significantly more urban more often living in informal settlements and more reliant on labor earnings we suppose that many of those who entered into financial distress in 2020 had actually been on the brink of poverty before so they had faced an elevated risk of falling into poverty and were less well equipped to kind of deal with this type of economic shock meaning they were more vulnerable and to test us or to look at this we use the class schema that Rocco has been talking about before so we look at classifying people into those five classes based on the stratification schema we developed before so they have class status in 2017 we look at how the frequency of the share who experienced this type of three events measuring financial distress in 2020 and what we observe is that exactly those two classes that Rocco highlighted before so the transient poor and the vulnerable they were extremely likely to have lost the main source of income since the lockdown started and we attribute this to their vulnerable position in the labor market that Rocco was referring to before we also observed that they were almost as likely as the chronic poor to run out of money to buy food and they had elevated levels of going hungry or food insecurity during the early phases of the pandemic so this type of volatile these two volatile groups that had clear markers of ex-ante vulnerability actually were more likely to experience financial distress during the pandemic so this economic shock materialized for them okay and Rocco also mentioned that we had back in 2017 we had done some field research in Carlitsche also with the aim of actually looking at this type of vulnerable groups so exactly trying to find those people that are transient poor or vulnerable non-poor and learning more about their lives and given this pattern that we are now observed in the quantitative data our idea was to call back those earlier respondents and see how they were doing during the pandemic and learn more about how their livelihoods had been affected and kind of dig deeper into the experiences during the lockdown and with the lifting of the lockdown so what we have here is two rounds of semi-structured phone interviews with 15 respondents each so we interviewed the same respondents twice once in around June so between 11th of June and 7th of July and then the second time between the 28th of August and 24th of September so in September essentially and the timing roughly coincides with the two waves of NITS data so it's kind of a similar time frame as we have for the quantitative data that we have been looking at and yeah the first wave was collected during level three so just after the lockdown has been lifted but we had a number of like recall questions during the interviews retrospective questions asking about how the situation had been back in February before COVID hit South Africa during the lockdown say April and then at the point of the interview and what is like in the original study in 2017 we had a combination of focus group discussion and life history interviews involving both wealth ranking exercises across four welfare level that were indulgingly defined within the township context so here four is actually the lowest welfare level and one is the highest level within the local township context and during the life history interviews in 2017 we went through with respondents through their lives and tried to figure out what events had happened and have some rank to what extent those were associated with welfare transitions and we did the similar thing now when interviewing them again so for each respondent we have kind of this life course of welfare and we have the self assessment of how the pandemic had affected their life so this gives us these lines and here just pick two examples to give you an idea of what this looks like and basically in all cases we observe a drop between February and June and then either a more modest drop or a stabilization or also in some cases a recovery up to September so this is a type of evidence that we have I'm running out of time but I'm trying to give you some of the snapshots of what we find so there's three main messages that basically were from this is that the pandemic affected the livelihoods of our respondents in three main ways so one is the drop in earnings and employment so it mainly acted through a strong shock to the local labor market what we also observe is a decreasing resilience to future crisis so an increased or deep and vulnerability and I'm quickly going to talk about this and then elevated levels of psychological distress and if you're interested we also wrote this opinion piece that's published on news 24 in case you want a quick snapshot of our findings so as I said the labor market shock was kind of the main threat to people's like livelihood so we see a collapse of survivalist livelihood strategies mainly small businesses fully suspending the activities at least during the lockdown but often also having difficulties to fully resuming thereafter so out of those who were in informal self-employment only one was operating again at full capacity in September in addition we also see a temporary suspension of formal jobs so those weren't necessarily securing we also observe an informalization of these so for example here we have this quote of one respondent who had been working in a formal job and then got basically registered from social security contributions which was a clear sign of worry to him and in addition we also observe indirect effects through social networks so even if people didn't have direct access to labor market income quite frequently systems of support dried up because other relatives who had lost their jobs and couldn't no longer sense the same level of support and in this context given the shock to the labor market grant income was quite an important source sustaining people's livelihoods the second one is this amplified vulnerabilities so here we see a clear loss of access to both formal and informal insurance mechanism so given the shock to earnings we see people defaulting our funeral policies trying down savings witnessing rotating savings associations disintegrate as people were in no longer able to contribute to disease and these clearly put people in a more vulnerable position considering potential future crisis in addition we also observe that children that struggling with homeschooling often not having access to the technical equipment to continue schooling why schools were closed and this may put a limit or could constrain future social upward mobility and again we have a few quotes here on this and then the third channel is this increased level of psychological distress so here we observe kind of a general sense of loss of individual control and agency during the pandemic so this was partly due to their fear of the virus itself which mainly affected those with families and older people but we also observed this kind of more insecure position in the labor market that was particularly varying younger males in our sample and overlapping with this we also observe kind of elevated levels of domestic abuse and from two key informants that we talked with who also pointed to potentially increasing crime which could add to this more insecure and volatile environment people were facing yeah so summarizing basically from the qualitative research we have these three main channels that start that kind of led to a deepening of vulnerability so this is the decline in labor earnings and employment prospects the increased exposure to present and future economic shocks and this general sense of loss of individual control and agency and our findings give rise to concerns that the COVID-19 pandemic may not only be a temporary shock but have lasting implications through this so I'm going to stop here and thank you very much and looking forward to see viewers' comments thank you thanks Simone at Seguirre go ahead good afternoon and thank you to Rocco and Simone for the very insightful presentation I'm sure that many will agree that you've provided us with some very useful context for understanding the social and economic crisis that we're seeing with the COVID-19 pandemic so some key things that stood out to me while engaging with both of these studies was firstly the need for more longitudinal analyses like these to understand the reality of the highly unequal nature of the South African economic system but also how it's experienced by the poor and working class and that while you know there have been some changes in South Africa in terms of political freedoms and to a certain extent economic freedoms as demonstrated by the rapid growth in the African middle class in your paper it is striking that race and gender continue to be key determinants for poverty persistence and vulnerability to poverty in the post-19th day period and so while these findings may not necessarily be surprising for those of us who are engaged in this type of work I think that it's very important to show these realities especially now in thinking about the kinds of policies that will be required you know moving into the post-COVID-19 economic recovery and it's clear from this presentation that there is a great need for economic policies that recognize the multi-dimensional inequalities that many South Africans are faced with but also going forward economic policies need to be targeted at protecting livelihoods but also creating an enabling environment for more and more people to move or transition out of poverty. An important finding that these studies have shown is that a majority of South Africans are either chronically poor or they lead precarious livelihoods and that this has been exacerbated by the global health and economic crisis with those as you show who were initially non-poor now falling into poverty as a result of the COVID-19 pandemic and at the same time consistent with the recent international studies both of the papers have shown that food poverty is also on the rise and this raises some serious concerns when we also consider that once again you know race and gender play a determining role in people's vulnerability to high levels of food insecurity around the world and that women and children in particular are more likely to experience you know food insecurity despite women's critical role in sustaining livelihoods around the world and as the livelihoods impact report presented here today suggests during the lockdown period poor household faced additional pressures on their budgets leaving many prone to food poverty as a result. In addition both of these studies argue that employment and employment type are key determinants of poverty status among individuals and households of the South African population and I think you know this is very important to show given the fact that in recent years there have been a lot of studies to show kind of the growing precariousness of work in the post-abidant period but not many you know have really explored the relationship between work and livelihoods and I think both of these studies do a very good job of showing that an important contribution that these studies have made therefore is showing the nuances of inequality in South Africa and how poverty isn't as you know clear cut as is commonly understood and that it can't just be characterized as only the poor or the middle class and that rather seeing and understanding the reality of poverty in the South African context as a spectrum with varying degrees of vulnerability based on households and individual level characteristics may help to determine the types of policies that are required by each of the groups that you identified going forward so some key policy takeaways that you highlighted in the first paper with the longitudinal analysis on poverty were the closing the skills gap and increasing the quantity and quality of jobs understanding and supporting those working in more precarious forms of work so to raise stability productivity and real earnings ensuring the provision of basic services and that the health education and nutritional needs of the chronically poor are met and finally the need for social transfers of the basic income for the chronically poor however specifically in regard to the point on you know closing the skills gap it has been argued that the problem isn't so much the supply of low or high quality labour that determines the supply of good or bad jobs in the economy and that rather what we're seeing in the poster by date period is more so the replacement of you know full-time stable jobs in the formal sector with low low wage unstable and insecure jobs that are characterized by informality and the lack of social protections a trend which your livelihoods impact report suggests has been exacerbated by the COVID-19 pandemic with rising informality and increased instability in some sectors following the national lockdown and so therefore it can be argued also that you know policies to protect workers and ultimately the sanctity of work need to be prioritized at the same time if not more than those that are you know simply based on skills development and as these studies have highlighted as well there is an important role for the state to play in the provisioning of social protections and social services that are also not work-based just you know save lives but also to protect the livelihoods of the chronically poor and the large numbers of unemployed in South Africa and this is you know particularly important when we also consider the critical role that expanded social protections during the lockdown played in sustaining these livelihoods as also demonstrated in the report. Finally I think one thing that I think future studies could explore a little further are the gender impacts of the COVID-19 pandemic amongst the poor in South Africa and the role that women have played in securing livelihoods at a time where as your study suggests where the coping and informal insurance mechanisms had been compromised and this is particularly important because you know there are studies that have shown an increased that you know as a result of the health and economic crisis there the burden of dependent care work that women have had to engage in throughout their everyday lives has also increased with many women having to balance paid and unpaid care work in the household and at the same time estimates from the UN women gender equality in the wake of COVID-19 report also suggest that the feminization of poverty will be exacerbated as a result of the COVID-19 pandemic and that about 47 million more women and girls are expected to be in extreme poverty by the end of this year with every 100 men 118 women also being expected to be extreme poverty by the end of 2021. In addition and as the livelihoods impact report presented here today suggests there's also been you know and there's there has also been an increase in domestic violence predominantly against women however despite evidence of these gender trends and vulnerability to the COVID-19 pandemic little attention is being paid to the kinds of policies that are required for protecting women and girls in the you know medium to long term but also and the advancing efforts towards gender equality in the long run so therefore feminist interventions such as increasing social protection recognizing the informal economy and supporting it as well as supporting the invisible unpaid care work that women engage in to sustain livelihoods and I think will be critical for addressing issues of poverty and inequality going into the recovery. Thank you. Thanks very much to be there for that insightful response. I'm going to hand over to Rocco and Simone to reflect on some of the points that you have raised and then I'm going to take questions and so if anybody has a question please will you raise your hand or write it in the chat. Thank you yeah maybe I can start and then Rocco can come in um yeah thanks to you for this I think very good reflection and very good summary of some of the main messages that emerge from the papers and I fully agree on the important gender dimension of COVID and the studies you cited unfortunately in our work as we have a relatively small qualitative sample we couldn't get deeply into this gender differences but I fully agree and also we have a similar other study on Ghana actually where we see this gendered effects on female workers so females being overrepresented and this kind of informal unstable labor market spectrum and therefore also seeing their earnings and employment prospects collapse more and recovering more slowly compared to male workers so I definitely think there is an important gender dimension which we couldn't fully cover in this work basically. I think we were like when we did this stratification research and of course we were kind of concerned about this vulnerable spectrum or transient poor and vulnerable spectrum and knowing that they were more exposed to shock but we were or at least I was in first seeing this kind of statistics of how they experienced the crisis across those groups and seeing that they were so similar in the exposure and actually how this shock manifested in an increased vulnerability and really dragging those people into a more difficult situation was kind of shocking to me and we do see some signs of recovery in the later waves of nitscrum and also in our second round of interviews but it remains to be seen like how long lasting these effects are and I think that the effect on education like specifically can be varying even though as you said like education it's no guarantee of receiving a stable job afterwards but it is one of the enablers of social mobility for sure and it's one of the channels through which COVID-19 I think may have lasting implications for future social upward mobility and the same as you mentioned like there's a varying trend of people jobs being kind of informal like formal jobs being potentially informalized or losing stability with the crisis which I think are those kind of more long-term varying trends that we need to keep in mind. Um Rocco did you want to come in over it? Yeah sure no uh first of all thanks to you for really thoughtful reflections um yeah that was great I've taken notes um and we'll think about this uh just a couple of comments that I made I want to make a couple of comments on the um on the quality and quantity of work uh discussion so apart from the COVID context it seems like to the extent that there's a trade-off between the quality and the quantity of jobs in in the economy and the policies that would support increase increasing the quantity of jobs versus the quality of jobs um to the extent that there is that trade-off um it seems like I think what uh what our research does is allows us to crystallize the what policy question and what potential consequences that trade-off might have in terms of the policy of the poverty landscape so going back to us the schema we can think of there being three classes really that the chronically poor you don't have I mean I'm going to simplify to the point of the distortion here but the chronic poor who for all intents and purposes don't have jobs there's they're the vulnerable those who are straddling the poverty line who often have jobs but have very precarious attachment to the labor market and then they're the middle class who have who have stable permanent generally well-paid positions uh which insulate them to some extent from shocks so if if we want to let's if we let's ask the question do we want to grow the middle class okay then we got to improve the quality of jobs and what that'll essentially do is move people out of the vulnerable class straddling the poverty line into the middle class okay then we'll get a bigger middle class but maybe we want to move people out of chronic poverty and into this vulnerable space um which is still far better than chronic poverty and then we might want to increase the quantity of jobs so to the extent that there is a trade-off between those two those two we can see through our schema what consequences that would have on the poverty landscape maybe their complementarity is between improving quality and quantity at the same time and creative solutions but anyway it's maybe it's one way of looking at that policy challenge the other thing is not from a policy perspective is just to just and I think an open question is what has COVID has the COVID 19 shock on the labor market done to this picture has it not through some policy intervention but through but just through the pure shock to the labor market um hasn't increased uh this vulnerable the size of this vulnerable group by sort of decreasing the size of the middle class for instance or has it decreased the size of the vulnerable group by swelling the size of the chronic poor or something else you know and I think that's an open question that that will will need will still need to be answered um I'll stop there thanks there's a couple of questions in the chat um but I'm quickly going to come in with my own question and reflection and in in response to what you've just said Rocco I think that we are very happy to acknowledge the trade-off when it comes to policy interventions in the context of limited resources in these types of conversations but the reality is when we set those policies or we set or we formulate our kind of strategic visions or you know guiding documents there's less willingness to make clear what those trade-offs are and to sacrifice one option in order to achieve the other so whether it's like you're saying now there's a trade-off or some balanced um negotiation between quantity and quality of jobs the question that came to my mind when I read these papers was there's a clear impact of the loss of earnings and the loss of employment prospects um on people's livelihoods which the second paper showed but at the same time you identified this tenuous attachment to the labor market and kind of caveat your findings that in fact the reason it doesn't look as bad as it probably is um with when when you look at the impact of job loss on livelihoods is because so few people have jobs to begin with um and then and then you talk about the the minimal risk management mechanisms that people have and I'm not sure if you mean that in terms of livelihood strategies within the household or as I understood it um as kind of social protection measures embedded in jobs but if there's such a tenuous relationship with jobs in the first place is it really worthwhile for our um poverty alleviation strategies to be so um tied to this ideal of creating employment for people or should we see that as a much more explicit trade-off between whether it's a basic income grant or some form of uh some form of grant versus some type of active labor market intervention and I think that um CBC's question in the chat is related to this he asks what are the policy implications for this work how should policymakers prepare for the next macroeconomic shock and what should the um what role should be played by the public and private sectors so if you were touched um at a high level on what policy implications your paper discusses but perhaps you could go into some more depth sorry can I come in quickly on that someone um there's a there's a lot there so uh I apologize in advance for not touching yeah for I'm sure missing some things um and in response to CBC viewers question as well uh something interesting that we found was so in in 2017 when we spoke to um when we spoke to our respondents in Cailliccia a lot of them spoke about hustling in the township as uh and working peace jobs in particular as something somehow degrading so working peace jobs in that social stratification schema that we introduced to our respondents in Cailliccia working peace jobs was was was characteristic of the bottom strata of society you worked peace jobs if you had nothing better to uh you know if you couldn't get a good job uh in in the uh yeah in the sort of formal economy then you worked peace jobs suddenly in the COVID context these peace jobs these peace jobs to a large extent disappeared for a short for a short period of time so when we spoke to these people in 2017 they spoke somewhat disparagingly about peace jobs now in 2020 they spoke nostalgically about about peace jobs you know it's the absence and all of this all of this is just to say these are survivalist livelihood activities isn't there is nothing aspirational about working bad jobs um but there are there are an indispensable often uh means of surviving and the same and and the same thing I think applies to grants no one aspires to a basic income grant you know no one aspires to the special COVID grant but if grants would be taken away their real importance would be revealed for it is which is sort of in in many cases the sort of cornerstone of household livelihood strategies strategies in South Africa so anyway what what do we learn from that I don't think people I don't think people aspire to be supported by by the government um through through grants um but at the same time that doesn't mean for a second that the support uh that that households get through grants isn't something which should be uh encouraged and supported and to Sibu Sisu's question a question I think what would have been a more appropriate policy response in the South African context and which what we can learn next time is is do more and do it much quicker in terms of the the social policy the social protection which is extended by the government there must be and I think this is a consensus which is emerging more or less universally is there need to be mechanisms in place for governments to quickly uh distribute emergency relief uh uh to populations in in moments of crisis like this um not as a solution but as a as a as a as what it is a sort of extending a um uh a means of survival to to to households um I think there was much more to your question but perhaps Simone has something else to say as well yeah I fully agree with the points you mentioned I mean it's kind of hard to have a full solution to it but I think as you said like we have seen that grants were extremely important in sustaining the livelihoods at least with the initial shock but as you say people don't want to rely on those grants and also it's still little income right so we also had a number of respondents who were basically relying on one pension grant but as a children had lost their jobs the whole extended household was relying on this one grant so it's it is an important floor to sustain livelihoods at the minimum but it's not enough to actually keep people out of poverty so this kind of labor market recovery would be really important in that sense but it's also something as you were saying South Africa has been struggling with way before COVID already um and yeah it's hard to say how to fully or I don't think that's easy fixes here essentially and the problems are kind of still the same as they were before they just got more exposed potentially with the pandemic um we have just a few minutes left so if anybody else wants to ask a question um I don't see any hands raised um if I've got I can say something if anyone's thinking in or here you go um I'll just read this out aloud from Jaco Rocco mentioned something important that no one aspires to be supported by the government I assume this is for average rational individuals do you know if there's been there have been studies looking into how rational individuals are the general comment always seems I know of person X that got five children just to get an increased amount of grants if this holds true then could it perhaps be seen as irrational everything that I've seen for instance the child support grant is is not that is that child the child support grant has not increased fertility uh for instance um and it sort of goes yeah I mean it is a really small amount um and yeah I don't think there's any evidence that that at least in the South African context at the level that the child support grant is is set at that that people that there's a fertility response to uh to child support grants um um all right uh or education um uh in response to Megan's comment the other comment that I wanted to make both to Megan and Sevilla's comment is on this on precarious work and let's say in this big group of people in the middle of this one third of the population which which is vulnerable in our schema what we see is that they is they're moving into and out of poverty a lot and a lot of these a lot of these movements in turn out of poverty are precipitated by um movements in turn out of a job okay uh so there's a lot of churn in the labor market which is which is underpinning this vulnerability now what are the what are the inequality what are the consequences of this labor market churn on inequality okay and x and t it's it's ambiguous right in one in one way if people are swapping jobs all the time then they're sharing the jobs and everyone else and everyone is more equal over time right so there's one mechanism which is which is which is equality which is pro equality right there's another mechanism which is anti egalitarian anti equality which is that high wage workers keep their jobs and low wage workers switch their jobs switch into and out of unemployment so imagine someone who earns uh 10 000 a month and someone who earns a thousand rand and another person who's unemployed then you follow then you see them in the next period the person who earns 10 000 rand earns 10 000 rand again and the and the person who earns a thousand rand is now unemployed and the person who was previously unemployed now earns a thousand rand so if you sum those incomes over those two periods what you've got is greater inequality over time than what you observed at a point in time all right so there are two dynamics here there's the churn might be equalizing all right if if churn is uncorrelated with income at the moment in time or it could be inequality increasing if the churn is correlated with income all right and these two processes co-occur me and another co-author Wimel did a paper on this recently and we find that that over the short term in fact using the net stator we find that inequality this churn is leading to increased inequality in the short term so this churn is is on net inequality increasing in South Africa anyway for for for what it's worth but i thought it related to to that discussion of do we want to really be do we want to really be increasing the number of vulnerable jobs is that a is that a sort of laudable worthy developmental goal in South Africa or is the sort of jobs that at all cost discourse just sort of barking up the wrong tree in a context in which employment universal employment is a pipe dream i don't think we have well at least i don't think we have a clear answer to that that question i know we're over time yes we have run out of time unfortunately and i think there's a lot more to say that we'll have to leave that for another day and just to close i think one of the most striking things when reading the paper is how you often describe the findings as distressing but unsurprising and when you see just the vast proportion of South Africans that are affected by poverty and it's quite scary that we've gotten to a point where it's unsurprising anyway but thanks everybody for joining