 So, in fact, I'm not going to present the paper. I'm going to present results from a survey we carried out with the World Bank, a joint work with Javier, who's also here. He was part of the World Bank Group. So, we're going to look at the uneven recovery that Latin America had after the pandemic. And we're going to be looking at gender topics and specifically how are women left behind or not after the pandemic. So, first of all, and given that I'm showing you the data, I want to describe you a lot of information. And I'm going to show you at the end some QR codes so you can download the data if you want to use it, the micro data set, and also all the reports that we have been doing in different topics and for different countries are available there. So, regarding the description of the data, so the World Bank started doing these surveys in the first phase in 2020. They collected information for 13 countries in three waves. So, you have three waves of information there. They have this publicly available as well. And in the second phase of the surveys, of the high frequency phone surveys, they were in 2021. There were 24 countries in a first round of surveys and 22 countries in the second round of surveys. The colors here of the countries are indicating that the gray ones were for the first round and second or first phase and second phase. And the new countries that we included are the blue ones. So, as you can see, there are several countries that were included from the Caribbean. And this is very powerful in terms that we don't have much information or very good household service in the region. So, there's available data at least for checking what's going on with these countries. Okay, what is the information that we have in the household surveys, in the high frequency phone surveys? We are following a random digital dialing sampling. So, these were phone surveys collected with this type of sampling. And it was representative for individuals older than 18 and with a cell phone or a land phone. So, in fact, they are not household service but they're service for individuals or the older than 18. We get some information about the household but it's not describing the whole household but the information of this individual that we got on the line. And what's the information that we have here? We have some respondent characteristics. We have information on health. So, access to health services, vaccination and mental health. We have food insecurity indicators. We have information about education for six to 17 year olds and in the last round of service we collected a module for early childhood. We have labor market information. So, income and transfers and remittances are there. We have some demographics. We have the gender module. So, that's what I'm gonna show you in terms of the results that we have there. We have a module on digital and banking services that were very important during the pandemic and that grew a lot and were used or where there's something to innovate after the pandemic there. And we have for the last round of service for the last way we have coping mechanisms and natural disasters for the Caribbean and a brief model on migration. So, this is it. I'm gonna focus on the results that we had on the gender module. So, gender and labor markets. So, what we see by mid 2021, which is the first wave of this phase of surveys, we found a declining employment that was more pronounced for females and for males and you can see it here. This is the green bars for females and the blue bars for males. So, the percentage of changing the rate of unemployment was lower for both but more for females and males. In addition, we have that woman that worked before the pandemic. So, who had a job were more likely to leave the labor force. So, this is this blue and green bar. Again, this is females and this is males. But they left their employment and I'm gonna show you later. If they left the labor force or if they were unemployed. And there's also, even though there's exit of the labor market, there's also entrance into the labor market that we see a lot here in the data. So, we find that that woman who were not employed before the pandemic were less likely to enter the employment but there was a big reshuffle into entering and trying to look for a job both for females and for males. This is the same number that I showed you about job loss which is here in this bar for Latin America but this is throughout all the countries in the region or the countries that we collected. And what I want to show you is that the gaps in terms of job loss for females and males are all over the countries. I think the only country that is very similar in terms of how much job loss was there for males and females was in Lucia which was kind of similar. And this is the breakup that I was telling you about in terms of job loss, women are twice as likely to have lost their jobs compared to men and there are more and on over half of them left the labor force. So, this is the 24% that we have here. So, in terms of unemployment, 14% of females out of this 34 were unemployed but 24% of them left the labor force. And we're gonna try to do some kind of correlations to find out what was going on there or some kind of messages that we have from the data. I put also these two bars because I wanted to show you if there was a big difference in terms of leaving the labor force or unemployment when you have small kids or not, when you have younger kids or not. And you see that the bar for females is a little bit higher when you have younger kids. So, you lose your job a little bit more than the ones that have older kids but it's not that different for males is pretty similar. And this is the same information I was showing you about job loss but comparing the random service that we did in the mid of 2021 and at the end of 2021. So, what we can see is that there's a bit of recovery. Like after six months we are recovering but still we're not getting the, not all the people who were employed before have jobs right now. And I just want to show the trend in terms of reducing the number of people who had a job, lost their job and are still out of the labor force or unemployed. And this information is showing us about the inactive ones who are very interesting to analyze how did they enter the labor markets, yeah. So, the blue part of the graph is showing you if they found a formal job. The next one, the yellow one is an informal job and the rest is if they stayed unemployed. So, as you can see, males have a bigger, let's say, advantage in terms of getting formal jobs compared to females. And other than that, I think, well, another message from this and I'm gonna show you later is that there's a lot of unemployment going on. Like lots of people like try to enter to get more income and to pass through the pandemic, let's say, but many of those jobs and that income was coming from informal employment, which is not good for the region at all because we have very high levels of unemployment, of informality. Regarding the gender gap in terms of unemployment rates, the blue bar is showing you what's the gender gap by region for Latin America before the pandemic. So, this is February 2020. So, as you can see here in the graph, Central America and the Caribbean had a big gap initially and when the gap increased by a little, not as much as the other regions in mid-2021. So, there's a gap but it was not, it was not rather than as much as it was for the other two regions, for Southern corn and Indian region. We rewrite it that way. But if you want to see the detail of country by country, you can see it in the notes that we have on the webpage. And it's here. This is a very nice and interesting chart, let's say, that we can do because we collected information retrospectively. So, we asked the person, what were you doing? So, we surveyed them in mid-2020 and in 2020 and asked them, what were you doing in February 2020? So, that's something that you can have from these surveys that you cannot have from most of the household surveys, which is how many informal, so it's like the transitions, let's say, because sometimes you see the net effect of a formality or the net effect of unemployment but you don't see how many did they switch. So, as you can see here, this is the chart for males and this is the chart for females. So, formality is much larger for males than for females and there's a lot of going out into informality, into unemployment and into inactivity. But as well, there's an entrance of some informals and some inactives into the other, let's say labor market conditions. Another thing to raise up here to show is that inactivity for females is much higher than for males. Okay, and the other thing is that, I have the number here, there's the inactive females who enter the labor force was 1.4 higher than for males in absolute values. Okay, so another fact from the labor force, women experience a smaller net declines in formality and there was an increase in self-employment. This is in percentage points, so this is kind of hiding the initial levels that are different for males and females but that's the result of the data. Less loss in informal employment for females than for males. This is also another interesting thing that we found which is this is the pre-pandemic female employment, so in which sectors they were employed and this is the share of post-pandemic employment losses. So there was a big loss in sectors which females were employed, for example, domestic services, restaurants and tourism. These might be correlated with the problem of not being engaged again or not going back as fast as you would want to for females and they have been, the share of women that are employed in sectors have been changing over time. This is worse during the lock down time. Okay, now I'm gonna show you some data about the time use and gender and this is a very interesting question which is showing us if the time that you spend on different activities, so domestic work, childcare and education assistance, has increased, stayed the same or decreased. So the blue dark line is the ones that are reporting that it has increased the time that you spend on those activities and what I want you to highlight is that females are always increasing more at the time, are reporting that they're increasing more at the time but something also very interesting is that males are saying that they're increasing. So it's not as much but they are increasing the time that they're spending in household activities. And this is precisely during lock downs and school closures. This is related to the last slide and we divided here these same types of so domestic work, childcare, we have it. How much did it increase? This is just the percentage of increase. Only for cohorts. So I wanted to highlight that the younger cohorts are the ones who are telling or saying that they had a biggest increase in terms of the household or the activities at home, non-paid activities at home. This is, I'm not gonna show you these. Okay, no. There's a slight decline in time that people spend on children's children care and there's also a slight decline between mid-2021 and end-2021 in supporting education assistance for kids. And this is, it would have been very nice to see that this is very correlated with the opening of schools but you can only see it if schools are back to normal for let's say for these three countries, Dominican Republic, Argentina and Nicaragua which were really open at that time. So you see the correlation of people saying that they're reducing the time that they are spending on education with their education assistance with respect to the education being in person. And just two more correlations. One is the change in female employment with respect to the share of women who reported an increase in education and school work confinement. So you might expect that you need to shuffle times within the activities that you're doing. This correlation is showing the percentage of employment rate, the percentage change in employment rate from February to mid-2020. So when you have a reduction in employment, we're seeing an increase in the mental health index. So we're seeing a correlation of stress at home or problems of mental health related to losing their jobs. And just for you to get the data and to get more information about different type of notes and different topics, you can see a thematic notes there and the overviews and all the data is here, the micro data if you want to get it from there. And thank you.