#DevTalks: Solving The Impossible Problem of Sovereign Debt Restructuring

DISCLAIMER: This webinar transcript was loosely edited and there may be inaccuracies.

Ernesto Stein Hello and welcome everyone to today’s Development Talk titled Using Economic Complexity for Policy Making: the Case of Cordoba, Argentina. Dev Talks is a series of conversations with senior policymakers and academics working in economic development. I am Mr. Stein, a Professor of Public Policy at the School of Government and Public Transformation at typically Monterrey, and I am honored to moderate this talk. And thanks Andres Fortunato and Ricardo Hausman for the invitation. I have known Ricardo for 30 years. I was one of his first hires when he built the research department at the ADB and spent a year at Harvard in the early days of the Growth Lab as a growth Fellow, and in recent months, working with the Lab and Andrés and Ricardo on a project in Hermosillo. I have heard Ricardo talk about the mission of the Growth Lab. Ricardo is always great with metaphors, and he relates the role of the Growth Lab to that of a teaching and research hospital. So a teaching and research hospital combines patient care with teaching and training, and develops through research, new ways to diagnose and treat patients with ailments. And these new methods to diagnose and treat patients are not meant to be appropriated by the teaching and research hospital. They’re meant to be shared with other medical practitioners for the benefit of patients around the world. And in the same vein, the Growth Lab trains students and practitioners on how to do policy work and develops research tools and methodologies to diagnose and treat countries, regions, and cities economic ailments. The Economic Complexity Framework is one such tool, and it’s key to identify new opportunities for economic diversification and growth, and these methodologies help guide the work of a policy of the Growth Lab, but are also meant to be used more broadly by governments, analysts, and practitioners around the world. And today’s talk Using Economic Complexity for Policy Making: The case of Cordoba, Argentina, is an excellent example of the use of this tool by governments and policy practitioners. So it is a great pleasure to welcome to the speakers, Andrés Michel, Secretary of Economic Policy, Government of the Province of Cordoba, Paula Luvini, Researcher in the Data Science area, Fundar. And Matías Gutman, Coordinator in the Productive Policy Area at Fundar. So I met and worked closely with Andres and Matias when they were both at the Secretariat of Productive Transformation within the Ministry of Production in Argentina during the Macri administration, and I have followed their great careers as they went into the government of the city of Cordoba and then the Province of Cordoba in one case, and into from that in the other. And it was a great pleasure to meet Paula more recently. So. Andres, Paula, Matias, welcome. The floor is yours. You have 20, 25 minutes to present, and then I’ll ask a few questions before we open it up to questions from the audience. So the floor is yours.

Paula Luvini Let me know. The if it’s, if you can see the screen.

Andrés Michel Yes, I can. Thank you. On my thumb. Good morning everyone. It’s a great pleasure to be here today, sharing our experience in formulating product policy. Or perception, as we call. We, we see in the presentation our PPE strategy and making intense use of, economic complexity tool. And I believe there is no better place to review it and discuss on and discuss areas, of opportunity there and improving this tool. So, thank you very much for the invitation to present, a show work, for this sharing space. Next, please. Yes. The roadmap for the roadmap for the questions I will start with, the first. Why? Why we doing. We chose this, economic complexity to try our product development. Then how we handle, with the data and adapt the methodology to our reality. What what do we what do we find, with, when diagnosing the economic, complexity of the province? Then the last question. Now what? I will start with, why then Paola with, is going to tell you about, how when what next? Please. Okay. Some figures. First of all, it’s the second largest city of Argentina. 1.5 million inhabitants. 40% of the province. More than 600 for the film, 53% of the province. $2.1 billion. Of experts, 25% of the province. The province includes, agricultural, exports. Finally, $16 billion of, GDP, 33% of the gross. Express. And the corridor has a productive profile. This is mostly specialized on, in services. So 75% account for, from from services. 25%, come from good. Would but, I have to mention this importance in the three main industries hub of the province, maybe more or less 50% of the industrial production of the premise is based on oncology. Uncorrelated. Thanks. Well, services and growth, we define, two different strategies to avert, this in this end challenge, we want to pioneering, CD level. So we needed to find vacancy areas, in productive policies, in services. We design a cluster policy. We said button up, approach in search of that. Mostly that our mode is mostly a productivity enabler, like, we, the technology, translator services franchise in, in audio visual analysis includes we want you to focus on on niche sectors, how to find them. This is a question. That is a question with complexity tools. This is the answer. And finally, why economic complexity? For at least four reasons. First of all, time we need quick wins. Second, soundness. We need to to find, a tool that compares the comparison with the policymaking or, academic work. This is high level support. You need high level support to to develop this. This tool apply and find it a new, new opportunity for productivity policies. Finally, a list of partners. You need a list of of of partners, act or search to find, opportunities to make it able to, to find, public vertical public goods, quality coordination, filers and others. That’s all for question, Paula.

Paula Luvini Okay. Okay. Thank you. Andres. Well, the second question is the how how we did. Because the main obstacle that we found to apply this methodology in Argentina was data. Basically, because in the first place, when you data from provinces in the UK to analyze the complexity of the province of Cordoba and of the rest of the provinces and of the city of Cordoba in the first place, you didn’t have and it is not published data on exports by province and public. So we need to do a public query with the national agency with whom we work. And we did an assiduous data cleaning process because sometimes exports, for example, are wrongly allocated. They are located in the port of departure and not in the province. So we have to work a lot, on that. But we reached a new database of subnational data of experts at four digit. That’s what that was the first travel. The second one was to get information for the city because as you might know, this is, a wide problem that is usually lack information of experts in on a granular basic meaning, a four digit level. And also, we haven’t explored, other methodologies like using employment with economic complexity. So what we did was to work with a data science team from the city’s government, cleaning and creating a new database, not of exports, but of companies that export inputs. So, the data team, it’s graph in some websites from some agencies or from promotion from best investment. And we got a new database of companies and goods at the four digit level that we needed. So now with that, what we did was to map all the the indicators that we calculated nationally with exports data, with the location of these companies. So we reached for example, we know where the products are in the city of Cordoba under complexity. As a result, we reach like these are these two graphs I think, that show what what we found in the first place. We calculated the economic complexity indicators in the traditional way and using exports data. So for example, we found the economics complexity index of all the provinces of Argentina. So in that in the map on the left you can see Argentina and the complexity of all the provinces. And you can see that in the center, for example, complexity is greener. That means that it is higher. And Cordoba, the province of Cordoba, it is there. Cordoba, in fact, is the fourth most complex product that sorry province of that of the country, basically because it exports a lot of automotive parts and vehicles, which are high, highly complex products. So that was the first part. The second part was, okay, let’s match the product complexity index that we have in the traditional economic complexity way with our new database of companies and locations. And finally, for example, what we use, what you can see in the second map on the right, the product complexity index on the exporting fields in average. So for example, the capital city in the city, of course, there in the center, I don’t know if you can see that square is quite complex, which makes it I mean, it’s remarkable because as Andres mentioned, is specialized in therapy and yet is the big, most complex municipality of the province. There are other municipalities, for example, in Marcos Juarez, which is neighboring Santa Fe. They export a lot of machinery for agricultural processes. So there is a big competition there. So what we did now was to okay, we have the companies, we know where they are. In fact, as you can see in this map, this is a map of the city of Cordoba. And of the dots are the companies and the color is the complexity of the product, the exports. So we know precisely what they export, the complexity of the product. And we know, for example, the we can compare this with the rest of the province. As I was mentioning, for example, the city of Cordoba exports 254 products, and it’s a slightly more complex than the rest of the province. In fact, we did a lot 12 of complexity of product complexity index, but we were looking for a way to find very little comparative advantages because, as you might be familiar with the economy complexity methodology, the original comparative advantages are calculated with exports values. And we didn’t have that. So what we did was to do it a twist in the methodology and say, okay, we know that we do the comparative advantages of the province by the traditional way, and we know which of these products are exported by the city by this grabbing method. So when we said what we did was okay, we started products which I supported by the city and have a really good comparative advantage in the province, are going to be our regular comparative advantages in the city. And this is quite important because when you read these values to calculate the rest of the work and also of recommendations, for instance, when you need to calculate the complexity index to know, okay, what we know that the city is complex. In fact, it’s like more complex than other cities from Cordoba. If we take it like you see in the in the chart of the complexity index and the Complexity outlook index, it is even more complex than other provinces of Argentina. But we need to know, okay, is it growing? It is going to be more complex in the near future without doing anything. And the answer is, well, not so much. And we need some product in both, because the complexity output index of the city is growing at a slower rate, in fact slower than the provincial average. So we need to think about, apart from all the questions that we had, okay, productive policies and how to get there. And we went to a certain part of the world which was which were the recommendations. Basically, we have the diagnosis. We have the products. I want you to know now, where should the city and the province invest their efforts, in which areas in which products and goods? So we, we made five criteria to select products. Are three of them. You’ll probably know them because they are like classic in the literature. In fact low hanging fruit balanced portfolio on the long jump. They are mostly using in all the papers that that come out from economic complexity, which are a waste of their product complexity of the indexes, the gains and the distance. Those measures calculated. How I told you using this, revealed comparative advantages. And we chose also two supplementary, criteria. Productive path. We wanted to know, okay, there were some products that, for example, did have a comparative advantage by the word like really close of getting one, really close of getting there. So we think that those products are interesting. Those are in the productive path. And even in the export recovery, we have all the products that the previous decade had original comparative advantage and lost it. With that, we had five criteria and we selected 50 products then of each of the five criteria and we said, okay, is it over now? No, it wasn’t because we, like we saw that we needed some help, particularly from a technical assistance from the the team, from addressing from the government with whom we were checking some qualitative filters, meaning that it makes sense to recommend to the city to both this, this area, for example, one of the recommendations was milk and some corn. And like it makes no sense to recommend to recommend to the city, which doesn’t have country fields to do something I recall. So that was I that was a shining example. But there were some others with which we needed some like knowledge of the field. I, we were it was crucial to work side by side with the government’s team in this case. After doing all that, like qualitative filtering, we reached a final selection of 28 products, 28 key products that. The city and the government should, should look into We went a step more analyzing them in terms of their similarity in sectors, meaning, okay, these 28 brought us down from five criteria for dynamic complexity, but we can also see them in index similarities. For example, we have like more or less nine products of machinery, meaning some engines, some pumps, some machinery for the agricultural industry. And we have low like food and beverages, which is a strong sector already in the city. And we have other for example. So congratulations. Like not some food supplements. And the third group which we got others because it has a it’s kind of a there are genius. But mainly you have to have some kind of a problem. And after we take a look like a while loop to the, on onto these groups, we said, okay, maybe we should do every box in this check of whether that it makes sense to recommend this. These products to the city have the capability to, for example, both the, the products and then to have the an advantage there. So we went to companies which was something that was the way we have to use the methodology, but also a really good outcome, which was we have information about the companies that produce them. So we analyzed two cases, interviewing, members of these companies that exported two of the products that we’re recommending to understand what were these capabilities that they have and why did they have them inCordoba? So just to finish with this part, I want to tell you about these two cases very quick. The first one is pumps for liquids. Pumps for liquids is the product from the first group, the machinery group. It’s a very highly complex product. In fact, only 15 countries in the world export this competitively. In Argentina,Cordoba exports is among the main exporters, although it’s not yet competitive. But in Guatemala,Cordoba has 13 companies, the city has six companies with 14 pumps and one of them 20, which we talked and we well, we we dig into how they get to do export and the main finding and which speak about the capabilities. If the partnership with Azure and German company in the late 70s, like more than 40 years ago, where they get the knowhow of doing. But with that they specialize. And after 40 years of working on that, today they produce more than 2000 different pumps, which are really customized. Every client has a different pump and they do it. And that was because they were able to learn that and also to have for it, for example, professionals who could work here inCordoba with them, which is a great they have a lot of universities and that also was important. And the second group also has this twist of okay food supplements. What supplements are for example, some some things derived from vegetables and fruits which are fortified with minerals and vitamins. In this case, we found that inCordoba there was a chemical company called LA who was exporting which was exporting cobalt, which is a supplement that treats, osteoarthritis and osteoporosis. And it’s kind of unique, a unique treatment because it uses about, bovine cartilage and not chicken cartilage as many other companies use. So they could experiment with that. First of all, because it was allowed to do this in Cordoba in the country. Second, because they could work with their civil court, which is the center for Research and Scientific Investigations of Cordoba. And with them they developed they basically the patent the method they could produce the. And they really highlight that this could have not been done in other provinces because they Cordoba brings the conditions for them to interact with this zebra core and develop these kind of things. And also, for example, to be able to be in the new plant, they have a new plant and they need industrial, industrial inputs, a local supplier and they found it.

Andrés Michel To.

Paula Luvini Give the word to Andres. It is important how capabilities affect this, this products. And it was really nice to find that the products that the economic complexity methodology recommended to us have the capabilities in Cordoba so it doesn’t come out out of the blue. And with that, I’m going to tell you a little bit about that. What? Know what?

Andrés Michel Oh. Thank you. What’s the next? It’s getting good enough at the toll to the province. The project. This project has finished, and last year. But the team continue to keep working on on this, on this project. But, now, we are in a different policy position. The province level, in charge of PDP at, is a great challenge for our team. The good news is that the the tool, is useful for each headquarter CD. At the province, you can see ten city, the ten most important series in the province. It is. It represents some difference in realities. Differ in complexity of the for the. I, I need to remark that the chart considers only products with RCA more than point six. Maybe the dots represent, the product. You can see the dispersion between without within between the series and inside the CD. So we need new allies to, to improve our diagnosis. Those allies are mayors, mayors of every city that are being introduced to the. So the PDP framework. By our team in what we call productive policy dialogs, where we highlight the value of coordination, public goods. The next. The problem. The province already has its own support structure for IDPs. For example, see agencies. The first is an competitiveness agency to support all types of firms recordable signals to support exporters. The third theCordoba eigenvalue printer to support the start without the complexity tool. we see this is to with tool. We want to to introduce a new approach. we want to to go to a proactive strategy, looking to those companies with great potential to contribute to making the economy more complex, for example, like Polus, mentioning where, we want to reach is reaching out the companies to enable us to, to achieve two important things. The first was an understanding the key in this. What are the the six international cooperation in the case of entry and collaboration with the local scientific ecosystem. In the case of Europe, the second was identifying the current obstacles, to continue growth. So from the experience in the application, this tool in the city, we know that the tool we can and the tool can have lower efficiency in for example, commercial missions identify bottlenecks and needs for sector includes a talent training standard and others. But I already seen some support for AI, R&D, promoting cooperative innovation for example. And to close. Okay. You can scan. Then you are, to to achieve the the the work. Thank you.

Ernesto Stein I have a question for you first. So in your work at the national level. I remember that you were one of the people responsible for the coordination of the missile sector. Is this a productivity sector? Roundtables that bring together the public and the private sector to identify missing public goods and other obstacles to the development of ascent of a sector, and then very quickly try to identify and deliver the solutions, at least to these obstacles. So I wanted to ask you, how does the work, how does the complexity work that you have perform fit within this Mesa sector? I know that you have taken the Mesa sector real estate to the city government, and now you’re also thinking, perhaps, of bringing them to the provincial government. So how does this the work on complexity fit within the Mesa sector really policy work?

Andrés Michel What question? In my personal opinion, I, I feel that, the this this whole issue in, in the previous station. Yes. This tool is useful to, to, identify in the sectors, you know, picking winners or not picking winners, in is is helpful in, in that, sense to, first of all, to identify them in sector. We say high potential to, to export. When you have this information, you can continue with another stage. So identify the actors. And then to call for for the for the table and identify failures or public good and and and others. I mean the then the tool is a feature and very well within the table methodology.

Ernesto Stein Things and race and actually think, thanks to to all of you for an excellent presentation. And it’s interesting to see that you did do separate presentations for the government and for that. It’s nice to see that you did a single presentation, which shows the level of articulation and collaboration between the government and the and the theme from that area, in particular Paola and Mathias. So Mathias, about that, how did funder develop the capabilities to work on complexity, and how did you come to work on these issues? Well, let me take this one. We went over in this mythology, in.2021.

Ernesto Stein When we’re when one of our researchers from, brilliant, a recent paper of mainly, take one on green complexity. At the time, we were working in green industrial policy. So we find very interesting the opportunity to contribute to the right here in Argentina about the possibility to to have both a productive strategy and to to push, in haste, growth of the same time, taking care of an environment. So with this methodology, we find that, for example, Argentina has great opportunities, to develop some green products that are, in fact, very complex and very helpful for our buck spade. So it was a very, a very. Fine for an experience with mythology. And then when we felt more comfortable with the mythology, we advanced to some of, unexplored areas, to apply the mythology in Argentina. Before us, I think no other institutions mentioned Xena and progressively work on this mythology, and in particular already at the national level. So we we started by there by trying to construct all the indicators or the indexes, at the national level. Then that was the moment when we first, the first challenges that Paola already mentioned about, national export data. After that, we are a think tank. We we don’t do in your research. We we we do applied research. So our main goal was always to assess, government, and assess that, and then policy and then the policymakers. So we try to, to make, conversation and we started to, to, to talk with different government institutions to unders to, to understand the the necessities are what, what are the main, concerns, of, of of the potentiality of the use of technology. Sorry, that that was the moment when we, we talk with rice, alongside that and then a few months, we, we like, find a good use of the tool, to assist one of the, the main concerns of analyzing that time in the city of Carlo. Thanks, Mathias. I don’t know if you want to throw it to add anything. I also have some some questions about what you presented the. And Paola, maybe you can jump in on this. So I was pregnant. In your analysis at the subnational level, Newcastle seems to be the province with the most the highest complexity. So I wonder if you can elaborate on on why what what is behind that. And then so you highlighted it bumps it as one of the sectors. It typically this methodology is used to identify products that you are not that that are not within your revealed comparative advantage, but that you could develop a but butCordoba already exports is one of the main exporters of these so so it was bumps reveal comparative advantage under under one in this case or not. And then you also discussed, that the fact that whileCordoba is quite complex from a point of view of the, of Argentina, that, complexity is not was not growing. And, and you mentioned the complexity of cooking the index to like but when the complexity of outlook index, as I see as I see it, is a little bit a predictor of future complexity rather than a measure of growth in complexity. So have you also looked at past tendencies, the past pollution of complexity inCordoba and also the identified that it has not been growing? Or is it just that the the complexity of looking indexes is low. So these are a few questions for for you guys.

Paula Luvini Okay. I’ll take the hardest one question, which is maybe no can because it is still an ongoing work from our side of my my the mention like we are still working with these. In fact now we are trying to use employment. We are analyzing the use of employment to see how complexity, outcomes this way, in the case of no, can we, we think that it is a, it is the highest, but it is like, it is not very well measure because we have a lot of imports that we can import things from our country, and then it exports like, for example, machinery for hydrocarbons. You have there and back and work that and a lot of new developments with with hydrocarbons and the province imports and exports a lot of machinery. So it is something that we’re still working on because we are comparing with other studies that have come out to see how we can clean that. It is the only case where it happened that we did the cleaning, and yet it is not a 100%. So I think that it’s not so complex, but somehow we can identify, identify which are the exports that are not exports. In fact, they are imports from another country. And that happens because of the industry there. And then often I think I don’t, I’m going to go first with the, the one from the outlook index because it makes me think about this comparison. We haven’t published a lot of of that yet. But we did analyze, for example, that it’s true that the outlook index is like a predictor of, okay, we are growing at a slower rate than the rest of the world, or your complexity is growing slower. Meaning if you don’t do anything, you are not going to be so complex in the future. But we also check that, Cordoba and also Argentina. I think it comes from like the situation of the whole country that lost a lot of, revealed comparative advantages in really good products, in competing products that were really complex. So there was something there that you are losing your capabilities there. And like you maybe in, for example, we compare it with the 2009, you had more machinery and now you had less machinery, and you have, for example, more agricultural products. You are more competitive in that product. So it was like a combination of both that I think it makes like at least a warning of, hey, you should pay attention here. And of all the bumps, no bumps. What? I’m not competitive in Cordoba, meaning Cordoba in Argentina. In fact, only one province is competitive, which was Mendoza. Which? Which brings us to the same equation that we were like, we’re having. Okay, you’re not competitive in bumps here, but obviously you have some capabilities. That’s why we like the criteria of explore recovery and productive path, because although according to the methodology, Cordoba doesn’t have a competitive, comparative advantage there. It exports the bumps and then he is exporting it to Brazil. So it has capabilities. Maybe they just need a little boost or some. Maybe it’s just bureaucracy, something that it’s making them not to be competitive as the rest. So the answer is no. They don’t have a comparative advantages, but they do have a lot of experience importing.

Ernesto Stein Think so. So a question for all of you. And after that I will turn it to the questions from from the audience. I think you can write the questions, in the chat and then Andrea Fortunato or someone will read them out loud. So, Andreas and Paola and Matthias. You have you have done this great work. Have you showcased this work? Have you presented it extensively within Argentina? Have you identified, interest in other cities, in other provinces, for for this type of work? Andres, what reactions have you found from other governments when, when when you tell them about what you’ve done?

Andrés Michel You first. Or Mathias.

Ernesto Stein Okay. Yes. We we first, presented a preview of this work. This work is a series of three documents. And we present the results of that, that the first, the second one, around a year ago, inCordoba, after the presentation, many different provinces, other, municipalities ofCordoba and showed interest, the, interest in replicated the study. But, yet we we we haven’t carry on on on that. But at the same time, we work with the Ministry of Interior on the interior is the ministry or Santina, which is responsible of that? And and the policy between the central government and the provinces. We we work with them, with the lobbying, a series of 24 panoramic, complexity profiles. It’s that’s the name we we call them. They are like. 12 pages. Like diagnosis of the evolution of complexity of each province. Is it really like. It’s a short review with some insights about how is the structure of each province now, and what are the different strategies that the different provinces all could use to develop? Some, some products, related to their situation. But that was, that, that work never saw the light because, it was like an interior document of the ministry. There was a shame, but gave us a lot of experience working with him. And also she, that’s or experience in this topic. Address.

Andrés Michel Yes. We have, conversations all the time with others and policymakers from other provinces, and so on. But, one important constraint is, is to find in properly the data and has the differential in this, theme. For example, we have a, a track record from broke of the data. This record is updating all the time when in one company, one. So to export, it always has this information, in real time. So this is very important. So, so we will, and so until we get the, the, the app or autoplay, it’s a logic to to a promise.

Ernesto Stein Thanks. So, I will now open it for questions. In the chat. I don’t know, Andreas, if you want to take over, then and I listen. Thank you. I’m going to be the voice of the of the audience. Thank you very much for, very informative presentations. I have I have a couple of questions that I will paraphrase a bit. I think the first one relates to, to the core of how we think about the capabilities, of, of the province, because, and the question I think relates to how should we should be different, differentiate different capabilities in terms of, for example, the value added, for example. So you mentioned in the case of notion that could be a case where. If you look only at exports, it would look differently as you look at net exports, for example. Should we differentiate between our export partners? For example, if we think about exports to Brazil, it could be different from any other market. Because maybe you have some trade relations that we have with Brazil that we don’t have with other countries. So that’s kind of the the first question, how should we think about different capabilities to treat them differently? The the second question relates to the initiatives to attract FDI. So I think that the audience wanted to to know a little bit more about, or if you can elaborate on, on how you approach, different companies or how did you approach, investors. And let me add that question. How should we think about the intensive margin on the extensive margin? So how we how should we think about and, and capabilities that the province already has? Or maybe that does it doesn’t have a competitive advantage, but that there’s some capabilities, as the case you were mentioning before, how should we think about the extensive margin? So, for example, capabilities that the province doesn’t have, today. No. And if you can elaborate a little bit more on that. I’m going to give you the third question. So we you can you can elaborate more. I think the third question relates to, to to add one more, layer to the complexity analysis and thinking about not only taking into account the complexity index for different industries, but also where the relatedness density, of, of different industries to kind of like have the, the right measure of, of the risk and incurred in relation to the expected gain of, of any new specialization. So let me stop there. I have three questions. Anybody that wants to take take those questions, please, please go ahead.

Paula Luvini Maybe I can start with the first one. I think that the first one is more about mythology. You can. Of course. I. I think that the question referring also to Brazil should be treated differently because, like, it is a special market and everything. I think the answer is customization somehow. And in the case of what you want to, am I that it happens? It happened to us sometimes that some provinces or some cities told us like, well, this mythology is not for me because I don’t export so much and that doesn’t represent my, capabilities in this case. So, when they told us that, of course, it’s well, it’s not just the expertise that you manage to do it, but there is something there that they told us you’re missing all. For example, the trade that we have inside Argentina, which is really important for us. Maybe I don’t trade with another country, but I do the insight. So for these cases, we thought, well, maybe a an approach using employment data is better or fits better because employment data is about all the production of a province or a country. It doesn’t always consider the trade. So we I think that from my point of view, in the different value added, different capabilities and how to measure that, I would consider like customized, strategies, because I don’t think I think that the tool proved to be really holistic. But of course we can maybe see the twisted using other data, using maybe a group of countries comparing with just a group of countries. So I would say that to analyze that, I would use customized, experiences for each case, because all the provinces are different and all the countries have different approaches.

Ernesto Stein Yes. I would like to to add to what Paola said. We work a lot in, in construction. Some other, indicators and indexes to be a complement of the traditional ones of economic complexity. For example, different other indexes about, formal employment for the case of Argentina, the high informality in different sectors, some other around the potential markets on the growth, how we grow in the different markets of different exportable products. Others about, for example, of, gender issues in inside different sectors. And so we think that, aside the compatibility issue of each sector, how how difficult was it for the, for example, city of Cordoba to develop some sector? Sometimes the government needs to align, other priorities to the prioritization of their product in the product policy. For example, if the main goal of the promise of cargo, nowadays is to have more for my workers. Okay, maybe some sectors are better to to address the challenge that others we try to to complement all the data with the previous analysis of economic complexity, to help the policymaker to, to take that, that kind of decision to, to to get to give them all the dimensions in, in the, in the analysis. And, and I think that with all the data, it’s easier to them. For example, as Andreas told us a little bit about the method security, is to address these issues with the private sector, in front of the public sector, addressing specific issues, and working on the solution together.

Andrés Michel Another question. If the AI you mentioned under it.

Ernesto Stein Yes, yes, the initiative is all about FDA.

Andrés Michel Okay. So good. Good question. It was the first question when, when I started this, this project. Two years ago, we wanted to identify, companies. Interesting. Interested? You go to the one. So how to find these companies? And the answer was, to use, complexity. For example, you can identify, companies to invest in the supply chain of your, companies, the with RCA, height or to identify, clients or customers, abroad or invite them to invest in Guatemala City. For the government, it’s important to identify what, the what the this company need from the local government or provincial government or. That’s another one, for example. Yes. The case of, of injury is, is very interesting because you have, like when duty went to the, for example, more, six companies like the activity here. You go to that and you put it together, you call for a then for example, for a table, in together identifying, failures, needed support, and others. For example, it’s important to, to ask them, what company or what company are the supply chain in the global market? It’s possible to, to, to attract or to invite to invest in our city.

Ernesto Stein I don’t know, Fernando. André. I would like.

Paula Luvini No, I think that we didn’t mention of all the identity related identity that they stuff. I was like, I mean, we used the, the relative density, I think. So I mean, we did use it to the for the three criteria of the long jump. And they balance on the low hanging fruit portfolio. Like we weighted their, the relative density, of the each product to the, the like toCordoba, like a matrix. So for instance we saw that food and beverages of course was really close to the city because in fact the city has was already specialized there. So we had a lot of things that were really close. In fact, we didn’t show it. But we have the the graph, the graphs with the the network. I was really close and some things from machinery weren’t so much. But I think it it’s important because the comments also mentioned that market justification how to break these, not to be specialized in the things that you already specialize into. So I think that was kind of covered in the three criteria, like considering what is close, but also what it is not so close.

Ernesto Stein Fernando. Andres, I don’t know if there are any other questions, please. We have five minutes. So I let me ask the last question, I think, but it’s very interesting because we asked this question also in Buenos Aires when we worked in Buenos Aires. And so the question and I quote is, how are you thinking of this regional work within the context of a volatile national economic situation? Did you address this in any specific way in your work? What do you say? We shall work a reduction of work. Are you referring to regional like provinces or regional like? Countries around there to do that or, you know, I think we I think it means by by the subnational agenda. Okay. Go to the in this case.

Andrés Michel It. Well, the macro is in. It is in data. It’s in we can do anything to to change the macro at the local level. So, we can we need to adapt. So to this, context. The good news is in local governments, city governments or provincial governments, they have, enough, maybe not enough tool, but they have to use these, these tools, to, to identify opportunities. I can see areas, opportunities to, to attract, invest, create a shop, whatever. In our case, we find that we have a lot of work to do every day. Maybe the. Our results are in. It could be higher. We say in a macro or with less volatility of the economy. But, we can we can do a lot of things everyday to, to improve our, our, our productivity in the economy. So we have a productivity view of this, situation. We can change the demography. We need to adapt to it.

Ernesto Stein Yes I would. I would say that sadly for Argentina the last ten years, the volatility of the market is the constant. So but we think that we, we we can’t wait to them to. To the time that the micro small in order to start to do industrial policy or other activities. So I think this kind of, instruments help us to coordinate and extend the existing tools in order to both in one and in the first place to, like, use efficiently, efficiently that the, in the public resources, to coordinate with the private sector around some strategies or some fixed points, about these strategy, to strengthening the some institutions like, for example, in the case of, of, of the city of Cordoba was the case of Cordoba severa, was a public private organization to cluster different, productive activities. So these kind of local instruments are really important, to develop the that in the public sector, at the local level, to work with the firms at local level, at IBM, you need stronger firms to do and exports. So that’s, that’s kind of the the potency of which I see in this tool at the local level. Sorry. One more thing. If you applied applied, as Andrés said previously, you can identify some opportunities to to do some interventions with public goods. That are really important to increase the sector as an example. For example, some regulations, some infrastructure to, to enhance, the competitiveness of hospital chain, for example, if you don’t know where to look up for these or how to, how to apply. Make use of these interventions to alter, for example, the Governator or the governor. You have the, the right, the right, evidence to support that claims. Well, we are exactly on time. So let me thank Andreas and Paola and Matthias for an excellent session. Thank you very much. It’s been it’s been a great discussion. Thank you very much.

Paula Luvini Thank you.

Andrés Michel And thank you very much.