 Zrpšte, zrpšte... Kaj z nami? S tebe. In kaj... Smo pa... Ok, dobro, se. Tako. Ok, so povedajte v svoju. To se počite. To je pravda, da je dobro doprestvar, doktor Maria Franco-Gavunel. arrow neck's presenter and she will talk about the links between migration and sustainability. Thank you. Thank you for the invitation. Good morning. So today I am going to discuss work that has been developed in collaboration with Professor Neil boarding and Dr Ricardo Safarecampos from the University of Exeter in the v Uniji. This is collaborative work. Before I go through the outline just to introduce myself a little bit. I have a background in economics, but my PhD is in international development, so I normally draw from other social sciences in my work. So today I'm going to present about what I'm going to motivate a little bit in the talk, then I will discuss what we call the Migration Sustainability Paradox. I'll explain a little bit about the role of international migration, so throughout this talk I'm going to discuss mostly about international migration, and then I'll show what the empirical evidence that we have on this and how we got these results, and I'll go into more details, and then I'll conclude. So theories of transformation to sustainability tend to overlook migration, despite it reshapes societies and politics around the world. So by theories of transformation to sustainability, I mean what Ian Schoonz calls these different typologies, such as market-led transformations or state-led transformations, technology-led transformations, and citizen-led transformations. So these ones tend to assume static populations, and do not necessarily incorporate flows across different areas. Whereas on the other hand, migration transition theories tend to see migration as a catalyst of social transformation. So they basically, the work of castles for example, looks at how migration represents a window of opportunity in which people move and tend to change, they not only change their place of residence, but they also then have to adapt, and therefore that means to put a lot of effort and to change attitudes and behaviors. And this eventually scales up to more aggregate, at the more aggregate level. So current migration trends to consider at the moment are the first one, the globalization of migration. So here what I mean is basically that there are more and more flows and these flows are more diverse. So people from more countries are moving around and then there is a change in the dominant flows. So for example, until after the World War, it was mostly Europeans moving to the Americas, but then after that now we are seeing much more south-north movements, like global south to global north movements, and also movement to the Gulf countries. Then we have a diversity of reasons. So it's not only labor migration that is the main flow, but also we have people, refugees, for example, that run away from conflict. We have people that move for family formation and so on, and most of the times these reasons are interlinked. We also see a proliferation of the migration transition. So basically areas that before were sources, and by sources I mean that I have a net migration rate that is negative, so they have more immigrants than immigrants. These places are becoming now more destinations, where it's the opposite. They have a positive net migration rate, which is that immigration is greater than immigration. And in this case, for example, we have Mexico, which is a country that in the past it was mostly an emitting country, but nowadays it's also receiving a lot of immigrants because it's basically a transition place where people from Central and South America move to go to the US, but very often they are stuck there. So then we have the feminization of labor migration, which is that in the past it was mostly male people moving, whereas now we have more and more women, and in some cases women are the majority of the flows. And finally, and more definingly, there is a growing politicization of migration. So it's becoming a security issue. Now borders are militarized almost everywhere and this is something that we didn't see prevalent as before. So the paradox. So basically what we claim is that migration can have two counteracting effects on sustainability. So on the one hand it's one of the three pillars of globalization. So apart from free flow of goods and services and capital, we also have movement of people. So it's one of the three pillars, but that also drive unsustainability. But on the other hand, it's also a potential force for transformative change. As I was mentioning the work that sees migration as a catalyst of social transformation. So here I just want to clarify some definitions. So as I was mentioning migration, I'm going to focus mainly on international migration. So this is defined as people foreign born populations because there are other definitions that take into account nationalities and other things. But in this case, we're going to focus on foreign born. So if someone is foreign born, it's considered a migrant, an international migrant. And then for sustainability, we are looking at the interplay of three things which ties nicely with the previous presentation that looked at the three circles of economic, social and environmental. So here we are taking the definition of the Bruntland report. The Bruntland report, as many of you already know, it was a report in 1987 commissioned by the Environment and Development Commission, World Commission. And it was led by Groharlem Bruntland, the then Prime Minister of Norway. And he wrote this report where basically he defines sustainable development as the already well known definition that it's the development that meets the needs of current generations without compromising of those of future generations. But he didn't say that only. He also talked about the interplay of these three systems, of the economic, social and environmental systems. He was very critical of how countries in the global north were increasingly industrializing and therefore polluting more. And this was affecting countries in the global south. And this also ties nicely with the previous presentation which is basically it's related to the limits to growth. Like how much a country can grow without compromising the environment and even societies. And a third point just to highlight is that although here I'm discussing mainly aggregate flows, like flows at the country level. If you, so we also as part of this project we made, we undertook a survey among around 6000 individuals in six cities and we asked them how do they define sustainability. And the result of that survey is that people also perceive that sustainability can be defined across these three dimensions, economic, social and environmental. So although we tend to talk more about the economic and environmental, the social aspect, the social cohesion aspect is also really important. So what we propose is then given that this, taking on board this definition of the three dimensions, we propose that if migration increases material well-being, reduces inequality and lowers environmental burden, then we would have an increase on sustainability or like the country would be on track towards a sustainable development path. I will park it there for now, but the idea of this project was to test this hypothesis. So just before I go to the results and to the methods, I would like just to go through what is the role of migration in each of these dimensions, on these of three dimensions. On the economic dimension, immigration contributes to aggregate output in two ways, directly in that basically more workers means more output, but also indirectly through innovation and public finances. So basically through innovation because having a more diverse workforce, first innovation, that's what student and colleagues found, and on the other hand, public finances are benefited from migration inflows because migrants tend to pay more in taxes than what they receive in benefits from state benefits. So and these are of course very political claims, but that's what Rothern finds. So then we have the social dimension, where the evidence is mixed. So there's no settlement on which, what's the direction of the relationship. First we have the debate about immigration and social cohesion. So here the political scientist, Robert Patnam, argued that in the US the immigration flows or the excess amount of immigration flows are deteriorating social cohesion. And he argued that these also had implications for political and civic participation and so on. Whereas on the other hand, Alejandro Portes, who is a sociologist, found that he actually challenged this view and he argued that societies like the US or other developed countries have such strong institutions that it's very difficult for a migration inflow to change them because these institutions govern the ways in which societies interact, then immigration does not necessarily deteriorate social cohesion. On the other hand we have the economists, which also do not agree on the evidence about this. So the relationship between immigration and wage inequality has been very contested over 30 years of debate and where, for example, David Card in 1990 found that the inflow of what he called Marielitos, which was an inflow of Cuban migrants to Miami. And this was the setting in which they were trying to analyze whether this big inflow of migrants affected wage inequality. So he found that this was not the case, whereas George Borjas contested this and he basically, it was a very long debate, it was mostly methodological and how the counterfactual was measured. So basically you know that when you compare treatment and control, it really depends which control you are using to see what's the effect that you find. So in this case Borjas challenged this and he basically said that there were some adjustments that had to be made and he found that the relationship here was negative. Finally, we have the environmental dimension where there is very limited evidence, although it's also equally political. So we say, they find that in Liang et al, this study looks at how immigration affects CO2 emissions. It looks at data from all over the world and they find that it increases CO2 emissions globally. So basically because they argue that sender countries are net exporters of CO2 whereas destination countries are net importers of CO2. However, this also has to be balanced with some other studies that find that countries, so country specific studies basically obtain divergent results, like it's not all settled as well. Some of them find that there is an increase and some others find that there is no effect. So now the role of emigration. Now the previous slide was mostly about how migration relates to the destination areas, like how the inflow of migrants affects these three dimensions of sustainability, whereas this one looks more at how, from the source areas, like from the emitting areas, how does emigration affect these three dimensions. So the first one, there are two forces that basically affect emigration and economic growth. The first one was posed by Bagwati in the 70s where he argued that basically there was a brain drain. So there was a loss of talent that had negative externalities at the origin and therefore more emigration meant less economic growth. So it was detrimental for the source areas. On the other hand, more recently in the 90s, Mountford proposed that actually the prospect of emigrating increases investments on human capital at origin. So if I know that I'm going to migrate tomorrow, today I will study more years. Therefore this increases the stock of human capital and therefore this is positive for economic growth. Now the social dimension here. David McKenzie from the World Bank finds that there is an inverted new relationship between emigration and inequality. And the logic behind this is that normally a migration and especially international migration is a very costly endeavor. So when households or individuals want to migrate they have to invest a lot and therefore not everyone can afford it. So at the beginning when migration rates are low, only relatively wealthier households are able to send migrants. So this increases inequality because then they receive remittances and they are even more wealthier. So this is the positive part of the relationship and then the negative part comes when there are social networks increasing and therefore lower income households start also sending migrants through these networks and then the relationship becomes negative. And then finally the environmental dimension. Well here as I was saying there is very limited evidence and I'm going to cite just the same paper as I was citing before, the one from Liang et al in which they find what I was mentioning that developing regions are generally net exporters of CO2 basically because they are net senders of migrants and developed regions are actually net importers of CO2 because they are destination areas. So the work that we have done, we tried to operationalize these dimensions, these different dimensions of sustainability. And so we use as proxies for the economic dimension GDP per capita. This is very valuable as we have seen throughout the presentations but we are still using this as a measure of the economic dimension. We also are interested in the social dimension which as a proxy we use income inequality. The way we are approximating this concept is also debatable but I'll go through this in a little while. And finally the environmental dimension is basically the CO2 per capita. So and we want to test whether migration affects each of these three simultaneously. Well the three of these simultaneously. So we used a multi-country computable general equilibrium model developed by the Global Trade Analysis Project. This is a project based at Purdue University in the U.S. And I understand that there are a lot of limits to general equilibrium models to CGs but still we are going ahead with this method. I'm happy to discuss in more detail later on. So GTAP as it's acronym has also developed a model specifically to account for energy inputs and outputs. And that's why it's called EGTAP. So we use this model that uses data from 2019 for 118 countries grouping to nine world regions. These regions are the U.S. EU just to note that this is in 2019 so it was still including the U.K. Russia and Central Eastern European countries. Japan, other OECD countries that are not included in the previous four groups. Net energy exporters which are basically Gulf countries and some countries in Latin America like Venezuela and even Mexico is there and I'll show how this affects the results. China, India and the Global South. The Global South is very diverse but it was grouped into a single category and this is something that we are still revising but that's the way we had basically categorized this. So then based on these nine categories we group every region into net destinations and net sources. So we look at the net migration rate of each of these regions and whether it's positive or negative we see whether it's a net destination region or a net source region. And then we also classify the flows by high-skill and low-skill migration. So high-skill migration is defined as basically the share of graduate college, sorry, of college graduates in each region and low-skill the complement of this group. And this was, sorry, and the data comes from, the migration flows come from Abel and Cohen and the share of high-skill migration comes from the Kier and Grappoport. So these are the net migration rates between 1990 and 2020. They just have mostly fluctuated for other OECD countries and for the US. They follow a downward trend since 2005. And then we can see that there is a big difference between these two regions and the rest of the other regions which mostly fluctuate around zero. So still, but still it's possible to disentangle like who is a net destination and who is a net source. So the main migration flows. In this exercise we wanted to focus on the main migration flows. So on the largest flows for each destination and for each source. On the left column we have the nine regions where in blue font we find all the net destinations and red font, those are that are net sources and net energy exporters which are fluctuating around zero. So they were partly both. So for example, for the case of the US the top source comes from Mexico so it comes from the net energy exporters. And by the way this table was developed taking into account interregional migration. So we don't account for example moves within the EU which are actually the most prevalent type of flows. So we have that for the EU, Japan and the net energy exporters the global south is the main source. For other OECD countries it's the EU. And then on the third column we have following the same logic we have the top destinations for the net sources, so for all the ones that are in red font. So we have that the top source for the Russian CE is the EU, for China is the global south and so forth for India and the global south for the net energy exporters. So this is basically the table of inputs that we use to go through the simulations and these are changes with, the first panel shows the changes with respect to the labour force whereas the second panel shows the changes with respect to the population. And the use of these two is basically because the model is adjusted per capita so it requires population shares as well as labour force shares which are reflecting the migration flows. So none of these, the range is very low. It goes from, for the positive numbers it goes from 0.32 to maximum 5%. And similarly for the negative ones from minus 4% to minus 0.06%. So from this, so, okay, I didn't mention the most important thing, we had four scenarios. So we created the net destination high skilled, net destination unskilled, net source skilled and net source unskilled. So for each of these scenarios we did these simulations. So each column basically reflects a single scenario. And these are the results for the first one. So for the net destination and high skilled we find that for example in the case of the US there is a 0.7% increase in GDP per capita as a result of these flows. Now the way in which we are interpreting this income inequality that I was mentioning before is actually, so it looks basically factor prices. So for high and low skilled labor we are looking at high and low skilled wages whereas and price of capital. So in the case of the US for example we see that an increase in high skilled migration leads to a reduction in the wages of skilled labor because basically more skilled people means that there is a shift in supply and therefore wages go down. And then we have the opposite effect for the unskilled wages and for the price of capital. Assuming that there is some level of substitutability between high skilled labor and capital. And finally in the third graph we are looking at the percentage change in CO2 per capita which is also great, so it's greater for example in the case of the US and the global south because the US is a net destination. You are seeing that the CO2 per capita moves together with the GDP per capita. So basically more production means more CO2 whereas in the global many of these flows are netted out not netted out but are reflected on the source areas like the global south where this is actually a negative result. Again a negative result on GDP correlates with a negative result on CO2 per capita. And I'll discuss this a little bit like the limitations of this in a little bit more detail. But GDP and CO2 do not necessarily have to correlate or at least positively, but this is something, it's part of the inner workings of the model. So we have similar graphs for each scenario and I just want to show you the summary of the results. So basically for each scenario we have grouped the results for GDP inequality and CO2. In the top left quadrant we have high skilled net destination where we have an increase in GDP and also an increase in CO2 but a reduction in inequality because as we saw in the distribution of income if we have an increase in wages of high skilled people so there is a decrease in the wages of high skilled people and an increase in the wages of low skilled people then we have a compression of the distribution and therefore we have less inequality. So that's the way that we are inferring this. We're not using the GIMI or TALE or other measures of inequality because the model does not allow for that but we can infer this from the changes in the direction of the changes in which the wages and the price of capital move forward. So then we have the low skilled net destination where the three elements go up, GDP inequality and CO2 and then when we look at the high skilled net source we have a reduction in GDP, an increase in inequality but a decrease in CO2. So this is basically the result of getting rid of labor and therefore you lose output. So then you have a decline in GDP and thus a decline in CO2. However, when doing sensitivity analysis what we found is that so in any of these scenarios the three dimensions move in a normally positive way. There is no increase in GDP reduction in inequality and reduction in CO2 at the same time in any of these four scenarios and therefore the answer, the blunt answer for the hypothesis would be we don't find this. However, what we find doing sensitivity analysis is that for the top left quadrant we found that if the parameter is the elasticity of substitution between capital and energy. So this basically reflects how easy it is to substitute or how linked are capital and energy inputs. So the higher the dependence between these two the worse it's going to be for the effect on CO2. Whereas if this becomes, sorry, the more substitutable they are the better it is for CO2 reductions. Whereas the lower the more compliments they are the higher is the increase in CO2. So this is what we call the potentially sustainable scenario and how this parameter is changed is actually a very challenging thing because it basically depends on the structure of the economy and how it's not something that can be just so basically it implies green technologies and machines depending less and less on energy inputs so it requires a transition. So just to conclude, so migration has the potential to change these three dimensions not simultaneously just potentially because this potential depends on two things. The first one is the selectivity of migrants and what we are here just discussing about education but this need not to be the only dimension that is taken into account. Migrants are more heterogeneous in various different ways and also the post migration condition. So like for example the structure of the economy like whether it's a green air economy or not this is going to affect whether the CO2 goes up or down and that's that. Thank you. Thank you and now it's time for questions. Thank you very much for your presentation. I am a bit puzzled by one thing though you've spent the first half of it telling us about flows and highly complex flows and then you told us you were using a general equilibrium model when actually all these flows make me think of a strongly out of equilibrium system. What do you have to say about this? Could you elaborate further? Well when you have flows and complex flows you expect long relaxation times to equilibrium and so I wouldn't go for a general equilibrium model. Yeah, okay I agree. So just like this was discussed in previous days I mean the general equilibrium models have a lot of flows they actually assume many things and frictions are one of those that there are no frictions. So I agree that a general equilibrium model is limited to some extent and I think that actually taking into account all the situations in which migration in particular affects these types of things like the lags or for example the fact that this also assumes competitive markets which are not necessarily the case for labour markets and especially for labour markets in which migrants work. So yes, I completely agree. It may not necessarily be the most ideal but this is like just a first step towards that. But thank you. Well thank you very much for your talk, it was very interesting. I want to make one observation regarding the penultimate slide that you showed, that's it. The GDP inequality CO2 combination and this puzzling. And I wonder whether the following observation might help between the findings that you have, the disappointing findings that you have, disappointing in the ethical sense. So Managi and Kumar in their cross-country estimates of inclusive wealth had one finding which I think is quite very interesting. It wasn't exclusively CO2 which was natural capital but CO2 was such an important part of that in their computer. So let's just ignore that. So the idea was the footprint, ecological footprint of which CO2 is a major component and GDP is related monotonically, because 170, 60 countries in this sample I guess. But the functional relationship between GDP and footprint and GDP was concave, strictly concave, sort of bending like that, which has a following implication that any redistribution, egalitarian redistribution increases the total footprint. So the idea of course the rich are polluting more than the poor, the margin, the rich pollute less than the poor does at the margin, that's the concavity assumption, which means that inequality reduction moves, would need to be compensated by decline in average GDP if the footprint, the aggregate footprint is to be kept fixed. So that's the sort of a, it was to me a disappointing result again. I mean I was hoping it would be convex, that potential notions would all be going together, but that's how life is, at least that's what the data say. And I wonder if you want to use that to see. Thank you. So yeah, I think that there is still a lot more space for improving this exercise. We're still revising some of the things, but this pointing to this study is quite helpful, which reminds me actually to something else that is related to the limits to growth, which is that, and it's the distributional impacts of it, like exactly what you mentioned, that when we compare developed countries with developing countries and who pollutes more, there is, it's not that straightforward to just cut growth for everyone, but maybe at the top end of the distribution and also to take into account the fact that, that if we want the developing countries to actually transition towards a greener economy, there has to be some sort of redistribution there from the developed countries in order to enable this type of transition. Yes. Hi there. Hi Maria, thank you. Very interesting talk, very important subject. I was wondering, you know, in the last few years with COVID, but also with the kind of politics we've been having in parts of Europe in the United States, there have been a decrease, I think we saw, maybe we saw in your plot, of international migration incoming. I think your results would show from the point of view of the recipient country that their advantages, CO2 aside from receiving migrants. There's a long history of documenting that, but I wonder if using your methods or others could estimate the opportunity cost of reduced migration that we're experiencing at the moment in these destinations? Okay, so we are not looking at reductions. Let me just check, no, okay, I see. That might change the landscape. We haven't actually considered that, but yeah, I suppose that that could be an interesting avenue for exploring. With COVID, this data, although it says that it's from 2021, it actually considers up until June 2020. So it does explain partly why there's also a decrease in the 2015-2020 period. So it would be a matter of updating this in the next few years and see how it goes and what happens with the current situation, where we are still not fully over COVID, but yeah, it would be a matter of taking this into account. Sorry, slightly related to this. So my question is whether this is the right exercise in the sense that while in the end one is trying to describe what happens in a particular scenario, but then of course there are a lot of issues with general equilibrium, with other assumptions etc. So would it make more sense to pose a different problem? So given this scenario, given general equilibrium, given CO2, taking CO2 as, what is the best, what is the optimum? What is the optimal thing that an economy, because essentially in the end and what is the optimal, what does the optimal strategy look like? Because in the end I probably want to make suggestions for policy and for institutions to be created to manage migrations, which is essentially something that is completely lacking at the moment. So and of course maybe one could also estimate, as Luis was suggesting, what would be the benefit for society of what could be the benefit with all these limitations of say managing migrations for both the environment and for the economy and for the social. Thank you, thank you for your questions. So I think that if you wanted to go to the potential benefits of migration, okay, first of all... I mean in this setting, I mean there is an optimization problem, which is probably the wrong one. I mean in GTAB there is, so it's a general equilibrium, so there is an optimization problem. Probably it's the wrong problem, this is my question. Is that wrong? It's the wrong problem. The wrong problem. So one should look at the different optimization problem. Okay, I see. Okay, so just to say that given that this particular type of modeling has, I mean I don't want to take the results at face value and derive any policy from as it is at the moment. Because first of all there is one element that we are not taking into account, which is one limitation of this exercise, which is the remittances flow. The remittances flow can alter GDP. There is an increasing amount of remittances being sent from developed countries to developing countries. Okay, there is a whole discussion about whether at the macro level you actually see a positive correlation between remittances and GDP. At the individual level there is a lot of studies that find that there is a positive relationship between remittances and household income. So this could actually talk to this scenario actually to the bottom right where it could increase GDP. So it's not... As it is, I wouldn't want to propose any policy or to be in favor or against any migration policy just to say migration doesn't contribute to sustainability and that's it. But yeah, I agree that this is something that we should eventually take into account. Now the potential benefits, it would be... The way I see it is that it would depend on the weights that you assign to each dimension because in each country is a whole world. So if you want to, for example, if inequality is your worst or your key issue, then you might be happy being in any other quadrant as long as it increases it. So it's slightly context-specific as well and that would be a way to, in a sense, save these disappointing results because migration does not necessarily address the three of them simultaneously in a better way. Thank you. OK, so I've got a couple of questions. The first is that on this schematic, every time GDP goes up, CO2 goes up and with technological advances, that's not necessarily the case, conflating the two of them is dangerous because it will make countries less ready to do things that are increasing sustainability. So my first question is, how do you answer that or factor it into your models better? My second question is a question of scale. So I spent most of nine years living in China and China is an interesting place because domestically you have rural urban migration, you have people who have grown up in the countryside, providing labour in cities, but within rural environments you have net migration from neighbouring countries for low-skilled agricultural pickers, etc. So with countries that have that kind of dynamics, how do you figure those into your models or do we need to better consider sub-national levels of migration? Thank you for your question. I'll start with the second one and I'll go then with the first one. I really agree that the idea of internal migration is a completely different area of exploration. Internal migration is actually more prevalent than international migration, way more prevalent and especially among the global south. So as you will say you have rural urban, but actually the most prevalent flow is rural-rural. So the fact that you have these reallocations and that are not necessarily as the way we are thinking here makes me think that we should separate them, mainly because of the type of selection of migrants. When you have rural-rural, the pre-migration characteristics of these people are way different than the ones that are moving across borders. So that could be international migration. So in the borders of China, you've got very similar populations. So you've got people like the Karen and the Cayenne populations from Myanmar moving into Yunnan. Those would have been autonomous regions. In northern Vietnam, southern China you have the Hamong people. So you have quite similar populations and the borders in some ways have kind of been imposed retrospectively, but it's because the wage in cities is higher. So the rural Chinese are moving to urban areas to work in households, but because you then don't have enough agricultural labourers, you are getting in cheap agricultural labourers from neighbouring countries, which in some ways the preconditions are similar. The only barrier may be language, but because there are also indigenous populations that speak the same language, so where I was, people spoke Dai. Dai overlaps with Thai and Laotians was quite easy for people to actually integrate with local populations in some ways, though they have zero rights, zero healthcare, et cetera. Yeah, thank you. So yes, this latter point touches upon the conditions post-migration, which are like, I absolutely agree, but the situations in which many migrants live, they are not necessarily legal and they are not necessarily receiving healthcare and many other benefits. The case of international migration among neighbouring areas is a very particular one, which is different than going from a Latin American country to the US, for example, like longer distances. The characteristics are different. Just to give one example, in the case of the climate change and migration literature, it's mostly, the relationship holds mostly for internal migration and for bordering states. So people are not going to move like way further, but just if they go for international migration it would be to some neighbouring country. So I do agree, but it has like some nuances to be taken into account. Thank you. Question maybe? Thank you for this talk. I have one question is about, is the model dynamic or static? Static. Static model. Yeah. The second question is, I think that the three variables must be completed by other variables, for example, the average wage, or the share of wages in the GDP, because it is a very important, bring an additional idea about the situation of workers, because it is very important from the point of view of sustainability, from the point of view of the poverty of workers, because it is very important. The second thing, I think that the first, the three quadrants, there is a question of the premium of skilled labour. So you remark that in net destination countries the flows of high skilled workers reduces inequality. That means that the premium of skilled labour in these countries decreases. This is a good thing for workers from developing countries that do flow to developed countries or rich countries. I prefer that because there are some countries of destination of migration that are not developed by rich. The same thing for the net sources for the skilled labour increases the premium of skilled labour. In my country, for example, which is a net source of migration, there is a lot of people that are educated, good educated, they do migrate. That means that the persons that remain in the country, their wages increases, that means increases of inequality. The same thing for low skilled labour in net destination countries, inequality increases. But there is a lot of people of low skilled labour that come. And the supply of in skilled labour increases, that means that the relative scarcity of skilled labour increases, that means that their salaries will increase, that means that inequality increases. The fourth quadrant is, I don't know how to interpret the way inequality in net source for low skilled labour increases, I don't understand. The last remark is about what these guys say. I think that in general equilibrium, we have an equilibrium situation and an inequality situation and all the adjustment have been done by the elasticity stays and the relative prices between elements. Ok, thank you. Thank you. So, about poverty, I agree. The way in which migrants live can definitely not be generalized. We have high skill, low skill, but also conditions of poverty. Even if some migrants are high skilled, but do not have adequate rights. So, I agree that this is an issue. This could be measured, though, that could be inferred. And then for the fourth quadrant, so the net source low skilled, you were mentioning about the reduction in inequality. Is that what you, how does it work? So, basically for the net source, less supply of low skilled labour increases the wage of low skilled labour because of the relative scarcity that you will mention. Whereas, we have the opposite direction for the high skills. So, that's how the reduction in inequality holds in this case. Ok, thank you. I think we should move to the next talk. And I invite Aisha das Gupta to join the floor. We have a lot of demography this morning.