Katya Gonzalez-Willette Hello and welcome to another episode of the Growth Lab podcast series. 

Katya Gonzalez-Willette What drives economic development? Or, more precisely, what constrains economic development? An emerging consensus on this question surrounds the role of locally embedded productive capabilities and the idea that countries build on their existing capabilities to move into new economic activities. In new research, published in Nature Communications, Dr’s Neave O’Clery, Muhammed Yildirim and Ricardo Hausmann develop a mathematical model based on capability accumulation of countries and use this model to construct a directed network of products called the eco-space. They uncover a modular structure in the network and show that low and middle-income countries move from product clusters dominated by few capability products to more advanced products over time. They also show that the network model is predictive of product appearances in countries over time. In this episode of the Growth Lab Podcast series, Research Analyst Ana Grisanti interviews the authors Neave O’Cleary, Muhammed Ali Yildirim, and Ricardo Hausmann to better understand their new research on productive ecosystems and the Arrow of Development. 

Ana Grisanti Thank you all for being here. We’re here to talk about the Productive Ecosystems and the Arrow of Development paper that you just published. So I wanted us to start with what is the framework of your paper and what is the research question to be answered here? How did this research question come about and what discussions based? Is it relevant? 

Neave O’Clery So I guess I’ll start with how the paper came about. I arrived at the Growth Lab in 2013 as a former Ph.D. student in network science, and I knew very little about the field of economic complexity. And one of the key tenets of the economic complexity theory, which I’m sure Ricardo will elaborate on in future questions, is the idea that countries are endowed with capabilities and it’s the presence of these capabilities that constrains their ability to grow right. There’s some kind of directed process by which countries accumulate capabilities, and it enables them to move into new economic areas, new products, new industries, etc.. And so when I started to think about this from a network perspective, it seemed to me that this was very much a directed process, right. That there was a process by which countries accumulated capabilities, but that the modeling tools that were currently being used were not necessarily directed. In essence, a specific network approaches, right. They were using a static, whereas a cross-sectional network which didn’t describe this process of capability accumulation over time. So the real motivation for the paper and for the research was to better capture using a model and using data this directed process of capability accumulation, which if you were to explain how a development work through capability accumulation, that was very much present in the literature at that time, but the modeling techniques didn’t quite capture that process. 

Ana Grisanti Great. Thank you. 

Muhammed Ali Yildirim The area that you’re thinking about, product space, which is a cross-sectional look at the capability correlation, I would say, but we’re also thinking about this dynamic process, which products should be there to grow other products because it how we see capabilities are through the products that we have. So that was the basic idea behind the paper by looking at what products are often there. When we see a jump of a country to a new product, we can identify this ecosystem. That’s what we call this space instead of a product space, and to mathematically show that this ecosystem captures the capability of overlap between the products. So we can say that this product has that much overlap with other products. And this leads to for us to understand this arrow of development in terms of capability accumulation. 

Ricardo Hausmann Yes, I like both descriptions. To me, the idea of arrow of development implies that, you know, you’re more likely to first make a car and then make an airplane. It’s very unlikely that we will start making airplanes and then move to making cars. The idea being that an airplane is something harder to make, requires more things so that we are more likely to start with the simpler things and then move to more complicated things. So first you have to learn from something that’s happening over time. But I think in this paper there’s that idea and there’s a different idea which says that instead of asking yourself which other product is there when this product is just product or product, it’s really a relationship of product and all the other products that tend to be already present in this product. So it’s a relationship between a product and a basket of products. And on the whole, that’s an appliance in the business because we talk about business ecosystems. Right. That’s the typical Karlan’s in business groups. Economists don’t like that too much, but it is sort of like what are all the other species that are around when this species arises? And I think that idea is a core idea in this group. And the second idea is the arrow of time. Some things happen before others. 

Ana Grisanti Great. Thank you. Can you explain the way in which you redefined capability and relationships between products in this paper? 

Muhammed Ali Yildirim So what we do is basically the capabilities are somewhat elusive. We know that that we can taste and we can smell them, but we cannot really identify all the capabilities extensively. So this is the nature of capabilities. So you need to look at how you can quantify the relationships between these capabilities. So in our work, when we write this capability, in terms of mathematical models and relate the probability of jump to the capability overlaps between products, we think that we can identify the extent of the length of the capability because we don’t still identify what the capabilities are exactly, but we kind of capture the extent of the capabilities required for a product by looking at this arrow of development and by capturing this extensive margin of the capabilities, we can say that these products are more complex. So it arrives at a different definition of complexity because if you require a lot more capabilities, it means that this product is very sophisticated and it becomes a kind of ladder of development. So that’s the new way that we are measuring capabilities here. 

Neave O’Clery So I think we have two components to the paper, right? We have a model which as Muhammed explained if I can write a product in a country that are endowed with capabilities and we have a model that tries to capture the gap in capabilities between what a country has, and what a produce requires, and what we do as we relate this model of capabilities to an expression for product presences and appearances, right. And that’s something that we can empirically measure and data. So we use international trade data to estimate the capability overlap between products. So we take this quite similar approach to the product space in the sense that we use international trade data to infer the capability overlap between products. But what is quite different is the way in which we actually calculate that overlap, because what we do is we use the time dimension in this data, the sequence of products presences, products appearance’s for countries, and we sort of mine a much greater amount of data because we use it all the way back to the 80s in order to try to infer these capability overlaps to create instead of a cross sectional, undirected network, we create a direct network. So that’s one of the key differences between what we do in this paper to construct the network and what was done in previous work. 

Ana Grisanti Great. Thank you. And this question kind of stems from what you were just talking about, Neave. What contribution does this method make to the theory of how countries move forward and diversification? And how does the ecosystem space add to what is learned from the product space? 

Muhammed Ali Yildirim So I think what we see is the title of the paper says, the area of development. So we see countries jump from some type of products to others. And often this is from that low complexity to high complexity products, for instance, what we observe in the data. So one of our findings in the paper, we show that this relationship goes from low complexity, low PCI, that from the Economic Complexity Network to the high complexity products in terms of diversification in the future. One might ask whether the countries that achieve these terms today have different type of properties and other things that facilitate these jumps. It’s an open question, but in terms of diversification, what we observe is it’s often the case that we see this pattern of diversification repeatedly and on top. It’s generally from the store complex. It’s of a complexity nature. 

Ricardo Hausmann So essentially, I would say that what you’re doing as Neave was saying is you look at a country’s production of all products and you’re learning from the whole history of diversification of all the countries in the world over all the previous years to infer what is likely to be a jump from this country, given all the things that it’s is currently making. And the model allows you to make that prediction and sometimes to choose to identify which are the most likely next steps for this country. 

Muhammed Ali Yildirim I would add in the product space, think of you look at all the products the country makes and how close they are to this particular product divided by how close all the products are to this particular product. So it looks at the monkey and the forest analogy that Ricardo devised. It looks at how many trees that you have monkeys on and how close those monkeys are to the tree that you want to jump to here. What we do is we basically come up with a different type of density measure that is a direct result of the mathematical model that we developed. 

Ana Grisanti So what are some of the advantages of calculating complexity and density in this way rather than the way the product space does it? 

Ricardo Hausmann Well, the paper shows that you get more predictive power. 

Muhammed Ali Yildirim And it’s also dynamic. That’s the direction to the relationship in the product space. The distance between products are symmetric. Here, you can make it asymmetric. So it’s a choice to minimize the noise that we do in the product space. But what we do is we come up with something that has an arrow that goes from product A to product B, and it’s generally if the arrow from product A to product B is really straight in one direction it is not as informative in terms of jumps.

Neave O’Clery As we were saying before, because we include so much more data from the past. It’s unsurprising in many ways that we get a better predictive power because we are learning from what has happened in the past and that can be quite a powerful addition to the model. 

Ana Grisanti Great, thank you. So let’s dig a little deeper into your results. Can you talk about how you created the product communities and how they differ in terms of the ecosystem size and ecosystem input? And what are some of what you call stepping stone communities? 

Neave O’Clery So for any network, we can first ask ourselves, what is the community? So in a network of communities, a partition of the nodes into groups, and those groups are typically characterized by high internal connectivity. Right. So you have groups of those that are highly connected, but those groups are less connected, in a sense, externally or to other groups. And so when we think about our network, a group of nodes is a group of products and they are connected by some kind of high degree of capability overlap. So these are groups of products that acquire similar capabilities. So when we apply an algorithm which is based on a sort of random walk around a network, so this random walk around the network detects areas of the network with high density of edgeways, we find I think it’s five communities and we study the characteristics of the nodes, the products in these different communities. And we have some communities that are full of things like food products and low complexity type activities, things that very much developing countries might be active in. And then we have other communities that are full of sophisticated, complex products such as pharmaceuticals and electronic manufacturing, etc. So we can characterize these communities based on the size of the ecosystem. This is going back to what Muhammed was saying about being able to characterize the vector of capabilities. In a sense, for a product the size of an ecosystem of a product is really how many other products tend to be present before this product appears. A product with a large ecosystem size tends to require many products that were present in the past and is a complex, in a sense, in the lingo, a product that has a high ecosystem input score tends to be part of the ecosystem of many other products. So it tends to be almost a springboard products that you might start from to move into other products in the future. So those would be the low complexity, things like food and sort of first games and things like that. So we have the different communities we characterize in terms of we see quite some distinction between communities in the paper. For example, what we term the yellow community is full of these low complexity products, which are mainly ecosystem input products, and then the blue community, which is very complex and has manufacturing in pharmaceuticals. This is characterized by-products with a large ecosystem size. So they require many other existing capabilities and products to be present before those products tend to emerge in countries. 

Ana Grisanti We also would like to know a bit about how ecosystem size is related to wealth of countries. 

Muhammed Ali Yildirim So while we are building this ecosystem measure or other measures all the information that we used is which countries export which products. So we don’t put any price information or any other measure that can capture the wealth of the nations. But surprisingly, if you look at the mean ecosystem size of a country’s products and it’s gross GDP per capita, we see a super high correlation. So because the large mean ecosystem size means that these products are requiring a lot of capabilities and countries making these products are going to be making in many other products, like the economic complexity measures that we do. And not surprisingly, we see that kind of relationship. So the ecosystem size of a country is highly correlated with GDP per capita of the country. On the other hand, we have this system input capacity of a product. So the product that’s more fundamental can lead to many other products. So the product could be a source to many other products. And when you see that look at the mean ecosystem input size, we see a negative correlation instead of a positive correlation. So it means the countries that have only fundamental products, those really unsophisticated products, they can go to many places they can. We can devise them many different parts. But its current status if. You have predominantly products that are inputs to many other products, then generally you have less GDP per capita. 

Neave O’Clery Yeah, so, I mean, the next thing we did was we used the aforementioned communities to characterize, in a sense, the development path, the arrow of development of different countries. Right. So we looked at how countries change their share of products in each of these different communities. So we thought up, for example, we could see this kind of clear trend that countries over time would move out of this sort of low complexity community and they would move into the blue and purple communities which were characterized by these large ecosystem science complex products. And so we actually tracked for many countries. At which point did they kind of transition from having more products in yellow to having more products in blue? And we saw some really interesting patterns. We saw countries like Singapore transition in the 80s and we had a raft of middle-income countries transition around the US and Malaysia, Mexico, China transition and much more recently. And India is still on its way to transitioning. So it was kind of an interesting way of capturing and visualizing, in a sense, the development of the kind of export baskets of countries over time in the network. 

Muhammed Ali Yildirim And these countries are super stable. Right. So it seems that they haven’t diversified like they have in their direction towards higher complexity products or high input ecosystem sized products. So it means that these countries like to transition or get out of the poverty trap they need to transition, but they haven’t done that yet. 

Ana Grisanti That’s really cool how you can see the history of countries there, like what they’re exporting and how they’re moving from less developed to more developed Ricardo would you like to add anything? 

Ricardo Hausmann In another metaphor we like to use is that products are like words that are made by putting letters together, and if you want to know if a country can make a product, you are sort of asking the question, do they have the letters? Since we cannot observe the letters, but we actually observe is all the other products that would require those letters. And since every product requires a collection of letters, maybe those are going to be present in some of the products that you’re making in different products are made. So a very long work is going to require many letters. Those are going to be expressed in many of the other products that a country makes. So that’s this ecosystem of that product. It’s all the other products that use more or less the same letters. And because those products already preexist, it means those letters are there. It means that this new product can appear. And so rich countries would be countries that have a lot of letters. Consequently, they make many products. And among them they make products that require a lot of letters. They make long words. And so these products at the end of the process are these very long words. They have these big ecosystem requirements and poor countries start with these short words. So they don’t have big ecosystem requirements because it’s just a short word, very few letters are that you need to get into those industries. And the whole challenge is to add letters in a way that can be transformed into more words and longer words. That process, if you send them to a very poor country or nuclear engineer, most likely that nuclear engineer is not going to be very useful because he needs a whole lot of things to be there for him to do his thing. These ecosystem requirements tell us, is this transition likely to happen, given that this new product that you’re trying to make requires all of these letters? But if you have them, then all of these things should be also present and they’re not. So maybe that transitions happen. And the fact that transitions that we say are likely still don’t happen means that this process of capability accumulation must be challenging. 

Ana Grisanti Thank you. So what are some of the limitations, if any, of this model? 

Ricardo Hausmann I think that the fundamental limitation that we’re struggling with is that we wish we knew what these capabilities were. We wish we could observe them, that we could identify them explicitly. We this metaphorically when the difference between the genotype and the phenotype, genetics started by just looking at the properties of beans or rain. And Mendel had no idea about where these properties came from. But he found some relationship between what happens if you make seeds from a tree with beans of this shape, with sex organs of trees that create beans of this other kind. What happens when you mix them and you put infer the properties of these mixes just from the beans because Mendel had no idea of the genes. He did not know about DNA. he did not know about these things. So he could only measure things at the level of the species and not at the level of the genetic code. So we are a little bit trusting that we can see very easily the products. We have some very broad categories of the requirements of those products. We can look at the labor inputs that are used in making the products according to some classification. We can look at the input-output characteristics of this product, but many of these things that a product requires are things that, you know, you don’t have them. It doesn’t matter because you can just import them. So which ones are the ones that really are critical that they have to be in place for this product to appear? That’s something that we still don’t know and that we are making progress in different papers on that question. There is a current paper by Dario Diodato and Ulrich Schetter which they are working on trying to say, well, let’s assume that these inputs are really occupations or the occupations that have to be present and are those occupations present in this country and try to predict from that? You don’t get as good predictions from a purely predictive point of view as this paper, because you’re not trying to maximize the predictive capacity of trying to maximize understanding of what may happen or what may be the mechanism. And so I think that that’s a little bit this research has to go. 

Neave O’Clery If we look at the limitations of this specific model in terms of if you were to try to replicate it or apply it in your own context, you mentioned a couple of limitations in the paper. The predictive power is good, but we still have quite a lot of false positives. So things that our density metrics that should appear that don’t. Right. So this is of course, there’s a lot of things going on in the economy. There are a lot of things we don’t observe in this data. And so certainly that’s something to keep in mind when policymakers will be looking at a granular level. And so one of the things that we suggest is that this could be quite interesting way of identifying market failures, for example, trying to understand why things that seemingly have the perfect ecosystem in place don’t end up appearing at all. And the other limitation that we mention in the paper is that, of course, the technological requirements of products and policy overlaps evolve over time, not very fast, but they still evolve. And so when one is looking to the future and thinking, what could you use this type of metric for when you’re predicting we suggest that a sort of five-year time frame is probably roughly appropriate, that if you were looking further into the future, you possibly could neglect this change in the network structure that would occur over that time, even though we do find that it is really quite stable over the time period that we. 

Ana Grisanti Great, thank you. Let’s end with how is the ecosystem electric helpful for policymakers? What would be the next steps for policymakers to use this metric in a practical way? 

Ricardo Hausmann I would guess that this paper will be of interest to anybody who’s interested currently in the atlas of economic complexity in the product space because it is an improvement figuring out which things are likely to happen in your country if you push a little bit if you figure out these market failures that he was talking about. So that includes, you know, people who are in the interest of promoting investment, whether it’s at the national level, at the state level, at the city level. It also is useful for anybody who’s planning to invest in a particular industry in a particular place. It helps, you know, if the ecosystem that is in place is appropriate for the appearance of this product. So I think that’s the activity activities. So investment promoters, investors, firms, et cetera, are trying to make allocation decisions. Those are the two that come to mind. 

Muhammed Ali Yildirim In the paper we mentioned what Neave said about identifying market failure because I assume the product that should be there is not appearing remeasure indicates that with a high likelihood that product should be that gives you this identity of the products that you can go. And we also identify which products are the closest ones, have the closest capability over next. And you can go to that industry and ask what limits the jumped to this other product. So it provides you with a concrete tool to go and survey the business people and so forth in terms of identifying the market leaders and policymakers could use different policy tools such as those papers and also in the paper to say that this application of the idea of this ecosystem or the capability overlap is not just limited to products and countries. That’s why we published this paper with general interest scientific journal Nature Communications, because we think that this idea could be brought to the ecology methodology and some other literature. And on top, we think this idea of genotype versus phenotype, as Ricardo alluded to, is an important concept and we are approaching different problems in many different fields. 

Neave O’Clery I would echo those sentiments. I think the path forward for us, in a sense, is to think about many of the product space metrics have been implemented on a regional and urban level using other types of data. So export data, when we look at countries primarily because it’s a very clean, standardized, reliable data set, when you go to the national level, you have use of all sorts of different types of data sets that capture a lot more activity in an economy. So employment in industries which captures domestic activity as well as exporting activity. So I think there’s a lot of scope to develop this model in that direction and try to create similar metrics that can be used for urban development experts. 

Ana Grisanti So thank you all for being here, so this paper is published in Nature Communications and the link to the paper can be found in the podcast notes. 

Katya Gonzalez-Willette If you want to learn more about the Growth Lab’s latest research and events, please visit growthlab.cid.harvard.edu.

Katya Gonzalez-Willette Hello and welcome to the Growth Lab at Harvard University’s weekly podcast.

Sehar Noor Could you give a picture of the economic situation in Buenos Aires and Argentina as a whole when the Growth Lab began this engagement with the City of Buenos Aires and partnering with the Center for Evidence-Based Evaluation of Policies, CEPE, at University Torcuato DiTella?

Miguel Angel Santos Yeah, sure. Well, by the time we arrived in Buenos Aires and our work kicked off on the first half of 2019, the country has been undergoing a significant slowdown that had started around 2011. The growth rate has slowed down significantly from the primary commodity boom for the country as a whole. And Buenos Aires has managed to grow at a faster pace than the country. And when the country slowed down, slowed down at a slower pace. So we were amidst a recession. Significantly enough, the median wage had grown, whereas the GDP per capita has fallen. So it gave us a hint on the potential power of labor unions in the city. At the time we went there also, President Macri was approaching the possibility of reelection. And as it happens in Argentina, all authorities are renewed at the same time. So that meant that the Chief of the Government of the City of Buenos Aires, Horacio Rodriguez Larreta, whose first term had been 2015-2019, was finishing his first term and was starting to prepare the plans for reelection. Eventually, he was re-elected for a second term 2019-2023. The first term of the Horacio Rodriguez in the city had been strongly focused on infrastructure, urbanization of slums. He had done a great job urbanizing Las Villas as they are called in Buenos Aires and had done a tremendous effort to improve the parks and the public spaces in Buenos Aires. And there was a strong recognition in the city for that work. However, he hadn’t made much progress on productive diversification and how to increase the productivity of the private sector. And in that context, the momentum for our work was very favorable.

Sehar Noor So it seems that there’s a two-pronged approach of the paper, on one hand we’re talking about the case of Buenos Aires, specifically how it can achieve that sort of productive diversification you are talking about, but then also more generally, how a subnational unit, a state or a city, can decouple its growth trajectory from that of its country. So what do you think makes Buenos Aires such an ideal case study in growth trajectory decoupling?

Douglas Barrios I think we didn’t originally get into it thinking about this issue. I mean, originally we were thinking about the evolution of growth in Buenos Aires. But when we were there, we had a lot of interactions with stakeholders that tried to explain the trajectories that we were observing via the national trajectories. So they would say, “No, what happened there was that there was a national boom and we benefited from that. And what happened there was that there was a natural slowdown and we were affected by that.” And we saw that those trends matched somewhat. But there were still some diverge. And the divergence was not explained by the fact that Buenos Aires was particularly more intensive in industries that performed better nationally, it was explained by the fact that certain industries, Buenos Aires demonstrated a competitive advantage vis a vis the rest of the country and outperformed the growth of the rest of the country. And some of those are essentially business services, business intermediation or financial intermediation, some health care sector, construction, retail, so on and so forth, which were not things that were directly related to the commodity boom. So we started questioning and saying, “OK, so yeah, there was a national trend that somewhat shaped the growth of Buenos Aires, but not completely. And the things that diverge Buenos Aires from the rest of it were things that were not necessarily related with the boom.” And we started to come up with a narrative of how this could happen. And part of the narrative of what had happened in the case of Buenos Aires was… what happened was that a lot of stakeholders that probably were engaged in the commodity business understand that commodity cycles are not permanent. So when they benefit from the upswing, they consider what is the best use of this unexpected windfall? Should I put it back to my productive activity, knowing full well that this cycle probably is not permanent or should I find other productive activities within my context? And where are those other productive activities concentrated? And the hypothesis that we landed on was saying, well, maybe what they found was that those more productive activities in the non-commodity business were concentrated in Buenos Aires. So even though the growth was being generated in the regions of Argentina, when these stakeholders were looking for how to best use this unexpected windfall, they found that these opportunities were in the Buenos Aires real estate system, that they in Buenos Aires retail, that we’re in Buenos Aires business services and financial services. So we came up with this logic of saying, well, this is a very unique feature of a city that allows it to diverge from the rest of the country. And in the case of Argentina is very, very obvious because you have a very high concentration of the knowledge-intensive activities, or of the service economy, within a few big cities, particularly Buenos Aires, and then the rest of the country is mostly concentrated on primary activities. So this dichotomy of types of activities kind of came of interest and say, well, maybe there is something about a city being able to diverge of its country.

Douglas Barrios It was also interesting because a lot of the analysis regarding growth in Argentina is concentrated on macro variables, on political stability, on the quality of institutions or macro-fiscal planning, etc… So our question also was, and the other reason why Buenos Aires was interesting, was to understand if a city that had a different economic structure than the rest of the country was still able to grow, even though it was constrained by these international level factors that were not under its control. So the first was it was an interesting example of the stark difference between the economic structure of Buenos Aires and the rest of the country. The second was the question of: if you are able to grow despite being imposed some national-level restrictions that are very hard to move? And based on two things, we try to compare the case of Argentina. I mean, now at that stage we start to say, “OK, so is this a general feature? Are cities able to diverge from their national-level counterparts?” And what we are able to found is that, yes, the cities similar to other cities that are in other countries are able to diverge from national counterparts in ways that are much more significant than Buenos Aires. So it became an interesting question then also saying, “Yeah, if this is a good prospect, then why is Buenos Aires not diverging as fast as other places?”

Sehar Noor It’s interesting, you mentioned we see that there’s different economic structures, the industries in Buenos Aires specifically are not commodity-based, commodity heavy, things like that. But even with that economic structural difference, how vulnerable, I could say, are those industries in Buenos Aires to the macro instability at the national level?

Douglas Barrios I think that it plays out in different ways, the case, particularly of Buenos Aires. So I think the first situation is that even though it’s a different economic structure is still right now focused on serving internal industries. So the financial sector, the business services sector, largely is serving local industries, it’s not necessarily serving international industries. So one of the things that we figured out when comparing the capability to decouple from national trends of Buenos Aires vis a vis other places, is that the intensiveness of Buenos Aires exports is rather small compared to other similar cities abroad. So that means that it’s very, very dependent of local dynamics. So that’s one way. So one is because the businesses are dependent of local demand and local demand is triggered by either commodities, and local demand is also impacted by these macro-fiscal planning first. Second is because there are some regulations that hamper the development of nascent industries in Buenos Aires that are decided at the national level. So even though the city can carry out certain activities to try to circumvent these restrictions, there are certain restrictions that are not within the policy space of the city to be able to move. So therefore, you kind of are stuck living with those kinds of restrictions. So I think that that’s the second importance of why this happens.

Sehar Noor Exactly, and so I think there’s a lot of dynamics going on here, both looking at industrial composition, but then also some of the sort of constraints that you were talking about. In the paper, we look at the growth trajectory of Buenos Aires vis a vis the rest of the country, and we’re comparing it to that of international peer cities and their respective countries. So maybe we can walk through what this process looked like. And how does this analysis help us understand the relationship between Buenos Aires and Argentina and whether that decoupling is possible?

Miguel Angel Santos As all of our applied research projects, we define a peer group of places that we can compare to the place we are working in. I mean, differences in performance can be driven by a large number of factors. And basically the goal of the peer group is to fix a few of those factors, ideally factors that the place cannot change, and reduce the universe of comparison to a set of places that are relatively similar to yours in a number of variables, but have differed in trajectory and therefore you look for the drivers of the difference in trajectory by looking at a diminished number of factors. So in the case of Buenos Aires, as we came up with a process to define peer groups at the regional level in Latin America, which is a process that basically took into account cities of a certain size for which we have information, a structure of exports, the structure of employment, type of FDI that the places received. And then we limited the number of cities to two per country so that we wouldn’t have much peers of a single country. And we did that for Latin America. And we came up with a number of peers that include Bogota, Ciudad de Mexico, Lima, Rio, Sao Paulo and Santiago. And then we had what it’s called the aspirational peers, which are cities worldwide you aspire to be like that you would love to be compared with. And that was a much larger list of cities, including cities in Spain, cities in Australia, cities in Europe. And the first thing we did is to map out the trajectory of Buenos Aires against those peers. Within Latin America, Buenos Aires had grown faster than almost any other city, with the exception of Lima during the boom period. But after 2011, between 2011 and 2019, which is the moment in which we arrived, the growth performance of Buenos Aires had been so dismal that on aggregate Buenos Aires lagged in growth, all Latin American capitals, with the exception of the Brazilian ones Rio de Janeiro and Sao Paolo. I mean, as much as an Argentinean can get happy when it’s told that it’s doing better than the Brazilian counterparts, the fact is that Buenos Aires was lagging behind all other cities, peer cities and countries, and it was lagging behind by a large margin, all other international peer cities. The closest one to Buenos Aires in international group was Houston, and it was still having a growth performance between 2011 and 2018 that was 20% above of Buenos Aires. So that led us to think well on the trajectory of growth of cities versus the trajectory of growth of the countries that are embedded in, which is what Douglas said. We didn’t arrive with the goal of how can we decouple Buenos Aires from Argentina? But that goal became prevalent as we moved on to the analysis. We discover that if you consider the growth trajectory of the country and the growth trajectory of our peer cities, Buenos Aires it’s one of the cities that had managed to decouple less from the trajectory of the country within Latin America and within the group of international peers. I believe only Bogota had decoupled less from Colombia, than Buenos Aires decoupled from Argentina and we trace what allows a place to decouple its trajectory from the country it is embedded in to the export capacity. As Douglas was saying, Buenos Aires had a significant knowhow agglomeration in industries that were selling to the domestic market and not exporting. So the industries were there. There was some knowhow there, but it depended on domestic demand. And therefore you are more subject to the fates of your own country.

Sehar Noor It seems that the strategy to turn a city or any subnational unit into an autonomous engine of growth is to focus on export competitiveness. So with that fact in mind, what are the strategies that we found for increasing the competitiveness of Buenos Aires’ exports? And what are some of the constraints to achieving that?

Douglas Barrios On that front, I think when we try to analyze what were the opportunities for Buenos Aires to expand its exports, we took two approach. First is trying to understand what is already there and out of those things that are already there, what we call the intensive margin, what opportunities are there for those activities to continue to grow? And the other front was on the extensive margin, meaning those activities that are not there currently, but maybe are nascent or maybe they share common knowledge capabilities or productive capabilities with the things that are already there that could happen. So we take the universe of potential industries and we try to classify them as these two things. And what we try to do is that we identify a series of filters to figure out which of this universe of potential activities that already exist or that could exist have a higher likelihood of occurring in Buenos Aires and to contribute towards the sophistication of the Buenos Aires economy. And after we go through that iterative and very quantitative heavy process, we arrive at a set of individual industries. These individual industries we tend to group into what we call a set of export themes. And the idea of why we try to group them in export themes is because the economic complexity methodology that we use, even though it’s indicative in nature and points you in the right direction, is not necessarily precise. You shouldn’t assume a high level of precision on the specific economic activity. You should assume that an economic activity like that has a higher chance of appearing. So generally we tend to group these into themes because when you are eventually thinking of promotional activities, then you’re thinking about how do we promote this cluster or this grouping rather than promoting an individual activity in which the likelihood of success is a bit lower. So when we did this for Buenos Aires, we landed on a set of groups that are essentially creative industries, health services, tourism services, educational services, business services, financial services and I.T. services, which is, I mean, a lot of services. But in essence, it also already speaks to some of the inherent nature of the city. So this wasn’t necessarily a surprise. So it’s a combination of things that are surprising and things that are not surprising. So Buenos Aires already has a very vivid creative industries cluster, it is already a point of attraction for tourism. And also it’s a regional hub for exporting educational services. And it’s also the home of the biggest share of Spanish-speaking tech unicorns in the region. So there is already an I.T. services cluster. So the idea is how do you combine those sets of activities that already make sense given the nature of the city and complement them with business services, financial services and other set of activities that are maybe more longer shots, perhaps, if you will? Health services included as well. So once we have identified these potential industries, one thing we do is to say, “OK, we arrived at this basically through an economic complexity approach. But maybe city officials and potential investors require a more specific roadmap of saying which of these activities actually makes sense on the ground or not? And why do they make sense or not?” So what we try to complement this analysis with some metrics of attractiveness and feasibility, meaning are there other tangible ways of measuring if this is something that would add to the Buenos Aires economy? Are there other tangible ways to measure if there are explicit constraints to this happening in the Buenos Aires economy? So some of the criteria that we try to include in the feasibility vector, for instance, was how big a presence does this industry already have in the city? Because if it already has a big or a nascent presence, it means that some components for its development are already there. And also you have stakeholders on the ground to help you identify industry-specific constraints. The second was if we can approximate if you have the right type of occupation, meaning does the type of talent required for this industry is it available in the city or not? Similarly, is a type of intermediate inputs required by this industry, as approximated by how this industry develops worldwide, already accessible in the city or not. And particularly we figured out what was the level of exposure of the city to some binding constraints, particularly some labor constraints and some taxation constraints. But essentially we try to identify industries that were able to operate at small or medium size because some labor regulations at that level are less stringent. And also we try to identify the level of exposure to a particular tax that we found to be distortive, which was a gross income tax or the ingresos brutos tax. So we tried to figure out industries that once we’re pursuing reforms at a national, regional or city level that we are able to grow in the current environment. In terms of attractiveness, we try to consider things that were part of the goals of the city. For instance, ability to incorporate female workforce was an expressed goal of the city so that is something that we included within potential attractiveness features. We also included the ability for it to become an export activity. Just as we said before, the idea for you to decouple growth is that you are able to serve global markets. So we tried to figure out if these industries in the global sense, do they tend to be able to export these services or not? We were also considering the ability for you to enter a global production chain. For instance, you could have a foreign investment that happens in Buenos Aires, not to serve the Buenos Aires market, but from the Buenos Aires market, serve the world. And we also try to figure out the ability to attract foreign direct investment, both at a global level or at a regional level, namely because we believe that foreign investment is also a vehicle for you to add missing productive capability. So is this an industry in which knowhow travels through investment or not and has knowhow travelled through investment in the past to other places in the region? And what we did is that we took the industries and the groups that we had identified through the economic complexity methodology, and we applied these metrics of attractiveness and feasibility as a way to order the efforts carried out by the city. So the idea was those industries that are either already present and have room to grow or are nascent but score particularly high in these metrics of attractiveness and feasibility, let’s prioritize them and let’s start working on those first and then we will work after we have done some progress in those and after we have learned what type of initiatives makes sense and what type of the policies make sense and what type of processes make sense, we can go and tackle later on in the least. And this has an implication that the diversification opportunities are a living document, meaning that once we have interacted with these things that tend to be the very high potential activities in terms of complexity, feasibility and attractiveness. Once we have tried being successful in that, then let’s try to be successful in other things that perhaps are more difficult for you to achieve. And in this sense, part of the learning from our stakeholders was to say, “OK, we get this prioritization, but we’re going to start with an industry that we feel is a very, very low hanging fruit and that also has a low-ish impact if we don’t succeed at first. So let’s start with the food service industry within the tourism grouping or gastronomy, if you will, offering.” And they started developing groups to interacting with these players within the city, potentially international players as a first step, as a pilot initiative. So the idea of the process was you can have a sense of what are the city-level constraints through independent analysis. But it’s much difficult to understand what are the industry-specific constraints? The only way you can identify the industry-specific constraints of these high probability industries is for you to interact with stakeholders that are present or stakeholders that could be present. So the idea was to set up institutional mechanisms that will reveal this information and that will reveal this information by coordinating with stakeholders on how they identify these constraints and what plans can we come up to solve those constraints? So, again, as I was saying, once we have all this array of potential industries, we try to constrain those industries to those of the highest potential, to the complexity metrics, the attractiveness metrics and the flexibility metrics. And then we come up with an institutional mechanisms to connect with those. And by connecting with those, we attempt to identify industry-specific, not citywide, but industry-specific constraints. This is a policy process that is new. So in order to tease them out, you start piloting these efforts with some industries and progressively you add more and more industry. So there was the desequencing effort that in the case of Buenos Aires, I think it was interesting that it started with what they perceive was a low hanging fruit with a low potential negative impact if it didn’t work out. And the idea is from that process, they iterate, they fix the kinks and then they interact with other industries and they fix the process through which they do it.

Sehar Noor So how does that institutional engagement differ between when it’s a national-level initiative versus the city-level? So when we’re doing this analysis and we’re ranking the sectors, industries and also talking about the potential constraints, how can this analysis be translated into actionable policy by the city.

Douglas Barrios In essence, city-level institutions in many cases are national-level institutions. So it’s hard for them to figure out if the job that they’re doing are they doing it for the city or are they doing it for the national level. And it’s hard to disentangle which hat you are wearing, first off. So second, when you’re engaging in supposedly if you have city-level institutions and national-level institutions, when you’re dealing with key stakeholders abroad, the question is who they want to engage with? Do they want to engage with a national-level institution or the city-level institution? So I think the first finding is to say this requires a lot of coordination across levels of government. So the idea is that how can you bring everybody on the table to make this happen, which can be difficult when there are a lot of polarization and politics first. The second is the role that the city can play differentially is to become hyper-specialized on industry-specific constraints. So a lot of things that we see when we observe investment promotion is that these institutions within governments don’t have the knowhow to analyze or to understand industry-specific constraints because it’s not expected that that knowhow exists in the public sector. So when they reach out to stakeholders, the conversation centers around how can we diminish regulation and how can we diminish taxes? And the reality is that those things, even though it may be important, they may not be the industry-specific constraints. And you end up finding a race to the bottom in which the investment promotion agencies try to de-regulatize as much as they can and lower taxes as much as they can. And in the end, some of the investments they attract are investments that would have come without you doing that, because they already know that the only thing missing was how do you make their bottom line better, but they knew they were not missing occupations or intermediate inputs or access to global markets or etc…  because you’re not talking about those things. So what we suggest that the city can do is that they have a narrower set of industries in which they could potentially focus on. They can become thought partners of these potential investors. And when they have these types of conversations with potential investors, they put off the table certain things that are outside of their control. There are certain taxes that are outside of control. There are certain labor regulations that are outside of control. There are certain macro-fiscal comings and dealings that are outside of control. But what is within our control is that we have gained a deep understanding of the type of talent that you need, a deep understanding of our pipeline of talent and how we can access that talent, given that it’s already existing but it’s concentrated in certain industries, it’s existing but it’s in our universities or can be acquired through targeted migration strategies. We have a deep understanding of the intermediate inputs you require and how are local industries would be able to serve that, or how we could be able to access it through imports, or how we will be able to access this through public and private investment. And what we’re trying to gain alongside you is what is the meeting industry-specific constraints aside from this that is inherent to your productive process that we together can find an answer to, and we have enough or the people sitting in this room have enough mandate to solve those issues in a timely fashion.

Sehar Noor So I think what would be useful is maybe delving in specifically to the main constraints that we found in Buenos Aires because I think it really illustrates how a city can address potential constraints in the absence of national reforms. So maybe we can specifically talk about the two main binding constraints and then some of the insights we learned about what the city could do to address those issues.

Miguel Angel Santos Yeah, well, we run all the drills on Growth Diagnostics and at the end ended up settling on taxes on business and labor regulations as the most important binding constraints. We did a number of tests that prove or provide a lot of evidence suggesting that these are the most binding constraints. That was reinforced by a large number of interviews we did on the ground with policymakers, but also with representatives from the most important industries in the private sector selected depending on the relevance and representativity, as Douglas mentioned before. And it turns out that one key question that was hanging out there when we started the project is when we find the constraints, is there anything we’re going to be able to do about them? Is there any lever at the city level that we can move to improve those constraints? And as it turns out, there is because out of our two constraints, the most important one was taxes. Taxes for business in both our cities are by far the higher in all Latin American relevant cities and capitals. And in the case of Buenos Aires, they’re mostly driven by a municipal tax.  A municipal tax that represents around more than 50% that the total tax burden a business faces in Buenos Aires is coming from a municipal tax called ingresos brutos or the gross taxes, which are taxes levied on the levels of sales. And as a consequence, they have a cascading effect in prices that it’s tremendously pervasive and negative. But it’s very easy to collect and represent a significant share of the state revenues. So in order to come around this, I mean, you not only need to say, yeah, it’s all driven by gross taxes or ingresos brutos. You need to find a way around it. Ingresos brutos was more than 70% of the public revenue of the city of Buenos Aires so it’s going to be really hard. Probably it’s worth beginning there. But the second thing checking across taxes in Buenos Aires, one of the taxes we found that, surprisingly enough, was not among the highest, but among the lowest in Latin America, where real estate taxes even lower than real estate taxes, collections of the stated real estate taxes. So, as it turns out in Buenos Aires the taxes on real estate are not collected often, but at the time of a transaction and the values are not fully adjusted to market values, but rather follow a very cumbersome formula that basically keeps the collection levels at a low. And if you think about what we were trying to promote in both cities and what the government is trying to promote right now, it’s an improvement and an increase of the knowhow agglomeration. You’re trying to bring in new business with new knowhow that can help the city to rise the productivity levels and support higher wages. But who benefits from that without contributing to that much? It’s real estate owners. The owners of real estate that purchase the flat there or a shopping mall or a land plot in Buenos Aires and have been waiting on it, get a huge benefit from the development of a knowhow agglomeration. And what we are suggesting is that that benefit, it’s also taxed and as it is taxed  the profits of business and it is taxed the income of workers. And we recommended beginning by not changing the framework, but improving the collection effort, which is already a lot, and then moving on to with that same framework, effectively making the tax payment yearly and not every X years when it happens, and then eventually revising this tax to low for the benefit that the owners of real estate are getting. And we also recommend that gradually substituting the ingresos brutos, and I emphasize gradually because again, it’s more than 70 percent of the revenue of the city by a proper value-added tax. A proper value-added tax that will be levied on different parts of the commercial chain and will not have a cascade effect on prices. And those two can potentially help the city to bring down the ingresos brutos, which is the tax that was driving most of the tax incidence in the city, it’s going to be hard, but it’s doable. The second thing, it’s labor regulations and labor regulations are affected by a framework that it’s defined at the national level. And I think here it’s interesting your previous question on how do what I’m doing at the city level or state relates to what the government is doing at the national level? This is a national policy, still you can get around it. In Argentina, it can be potentially damaging because when you reach an agreement with the labor union of a certain business in an industry, the benefits that have been granted to that business in that industry can be extended or demanded to be extended to other workers of that same industry. So it’s like a country-wide collective clause agreement. And what we suggested is coming out with a policy that the government has already started of special economic zone. They call that districts. The district policy is just setting up a perimeter within town and bringing in business, not in an indiscriminate way, because what happened to the previous district policy is that many businesses that were already in Buenos Aires, moved into the district. Therefore, you don’t have any increased economic activity nor employment, but you do have less taxes because they moved in and less taxes on labor. But targeting to these sectors, we were aiming at developing with the complexity work that Douglas described, targeting this zone to some of those sectors and then lobbying with the national government for a special labor regime to be applied within those areas. I think these are two representative constraints and reactions to constraints of the work when you go subnational. There’s one where you can actually do something, it falls within the realm of policy of the city or the state if it’s a larger subnational unit and there’s one that it’s national, but then you can have domestic policy responses to the national that yet to be coordinated with the national government.

Sehar Noor And just to add, I think that when your hands are really tied, you can even have this sort of policy option to in the sector identification process to particularly look at industries that are less exposed to those constraints from the beginning, whether it’s you know you’re at the lower end of the rate spectrum for taxes, or you don’t have to deal with certain labor regulations because of the makeup of your industry or whatever your requirements are as well.

Miguel Angel Santos Yeah, absolutely, and that’s something that the team did. We realized that business with a size of less than a hundred employees tended to be exposed to a lower labor regulation level. And therefore, we ended up looking at the world and industries of the ones we consider feasible in Buenos Aires, which of those tend to organize around firms of less than one hundred employees. And the likelihood of a firm in that sector being organized on less than one hundred employees is high, we sort of gave a higher score to that industry within the viability score that Douglas described before.

Sehar Noor Exactly. So just to wrap up, let’s talk about this engagement in general, this partnership with CEPE and the Development Unit of the Secretary of Finance of Buenos Aires, when we are working on developing these institutional mechanisms to tackle these constraints, what does this look like in action? What are the policy directions that we found working on the ground?

Douglas Barrios The nature of this project was a collaboration between us and a local university partner. The collaboration was very fruitful in the sense that we are bringing a methodology that we’ve deployed in many countries and in many other cities and regions, but we always benefit from additional color or particular expertize in local dynamics. So I think that the way we organize this work was that we did an initial set of analysis in trying to characterize the growth process and the binding constraints to growth and additional analysis in trying to figure out diversification opportunities and perhaps identify a set of potential inputs to carry out the pursuit of those opportunities. And we framed the results of these two analyses into a policy framework that tries to figure out if this is the issues that you have and if these are the potential industries that you can explore, how can you go about pursuing short, medium, and long-term reforms whilst at the same time promoting economic diversification? And from there we set out a set of principles of how we can do that. There, I mean, even though CEPE was doing other work, part of the work that CEPE did was it took this analysis, this higher-level framework, and they try to match with the specific offerings, public policy offerings that the city already has to try to identify gaps. I mean, what are the things that are already being pursued that may require adjustment and where things are being pursued, that are in line with what we’re seeing, and where things that are gaps that will require additional policies and try to engage with local stakeholders at the city level and local stakeholders outside government to decide how can we come up with a set of reforms that allows us to do this? In parallel to this intellectual product, if you will, alongside the way the city realized that it wasn’t in a position to wait for the research to be done before they were able to internalize it. So I think early on in the process, even earlier than we had anticipated, the city had worked really hard into incorporating this type of thinking into the work that they were doing and trying to appropriate it to the point that when the final recommendations from our joint work with CEPE came to arrive, some policy had already been done, some in the direction of the analysis and some not. But the reality is that they were in a position that they needed to make things happen and they have internalized it to do so. So I think in that latter part, which was the interaction of government, was part of the city government was tasked with incorporating these recommendations into the way that they were doing planning for the next potential period for the mayor. And even though there was a restructuring of functions after this, the idea was that some of the things that that came from this project would still inform policy later on. So our counterparts did a very intensive work in trying to adapt this work from technical language to concrete policy actions, also being very mindful of what things of these emerging suggestions should go into formal policy and what things should go into a way of doing things that is not necessarily a regulation or legislation, meaning that at some point they were thinking, should we pass a law that creates this institutional information regulation mechanisms like the productivity task forces or the investment promotion agency or gives this new task to the investment promotion agency? And part of their point, which I thought was very thoughtful was to say, let’s see how it goes. Let’s try to incorporate this into the way we already do things into the legislation we already have and let’s learn from doing this in practice. And once we have learned what works in practice and systematized what works in practice and we want to build institutions in the long-run that reflects what works in practice, then we do the legislation. Then we go to the city council and go to the national government and we seek to make this applied framework stick for the long-run. But I think that their interaction was saying, “Let’s not build institutions that we haven’t tested yet.”

Sehar Noor Exactly. I think the intersection of research work, that quantitative work and then policy implementation requires that sort of balance and that sort of feedback loop where the policy is being informed by the research but then also the research itself is being adjusted and calibrated based on what the requirements on the ground are. So I think this project really was sort of testament to how to make those two sort of elements work together. And I think that there’s been a lot of learnings from this project that can be applied to other Growth Lab engagements as well.

Katya Gonzalez-Willette To learn more about the Growth Lab, visit growthlab.cid.harvard.edu.