Professor Ricardo Hausmann, director of the Kennedy School’s Center for International Development, and Tim Cheston, a research fellow with the center’s Growth Lab, explain how they leveraged data from the Atlas of Economic Complexity to assess the knowhow of more than 130 countries and predict their economic growth over the next eight years.

Featuring Ricardo Hausmann
May 30, 2018
31 minutes and 34 seconds

In the field of economic development, few models have proven themselves as effective at predicting the future as the Atlas of Economic Complexity. By gathering detailed data on the economies and trading relationships of more than 130 countries, it allows researchers to see what each nation’s strengths are — what they know how to do already. From there, it’s as simple as connecting the dots.

For example, a country that already produces automobile parts is better poised to branch out into car manufacturing than a country without that existing industry.

No one is better at connecting the dots than the researchers at the Center for International Development, who run the Atlas of Economic Complexity. Each year they release economic growth projections, updated with the most recently-available data. You can find this year’s projections here.

In this episode, CID Director Ricardo Hausmann, and Research Fellow Tim Cheston discuss the latest projections, which peer into 2026 and find India and Uganda ready for major growth in the coming decade.

Hosted by

Matt Cadwallader

This episode is available on Apple Podcasts, Spotify, and wherever you get your podcasts. 

Note: This transcript was automatically generated and only lightly edited.

Matt: So first of all, what is economic complexity?

Prof. Hausmann: Well economic complexity is essentially a measure of how much technology has diffused into a society. We think of technology as being composed of tools, codes and know how that is embodied knowledge and tools, quantified knowledge and recipes, protocols, how to do manuals. And then tacit knowledge or know how and brains. Technology involves tools and codes which are easy to move but it also involves know how, which is very hard to move. A more harder than individual know how to move is the know how of teams that are needed to implement technologies.

So, what we measure is what is, how much technology has diffused but it’s mostly how much of this know how has diffused. What does the society know how to do well. We’ve discovered that this is a fundamental driver of the difference in incomes between countries and it’s a fundamental driver of their capacity to grow over time.

Matt: Now, I would think that in a globalized world we live in, knowledge if anything, information seems to spread easily. Why is it that different countries can be rated individually?

Prof. Hausmann: Well, it’s interesting that you say because Malcolm Gladwell would have said that it takes 10,000 hours to become good at something. It takes years and years to become a violinist or to become a dentist or to become a lawyer. So it’s one thing for information to be freely available on the web and that’s what we call codes. Those move very quickly. But it’s very hard to reprogram the brain so that it sees things that normal people don’t see and so that it knows how to respond, how to react, how to move the body, the hands in the way say a violinist would move them. So know how is a very slow moving variable. It moves from brain to brain with enormous difficulty and through a long process of imitation and repetition. It’s not something that moves conceptually. You don’t teach children to walk by explaining to them the concepts.

You can talk about baseball with Mickey Mantle or with Sandy Koufax but it won’t improve your baseball game. So it’s not things that move that way. That is in our mind what slows down the whole development process. It’s the international, geographical movement of know how, and not just the know how of a person. in the know have a person who can put the person on the plane, you can move them around. It’s the know how of coherent teams that are needed to implement technology such as for example, making cars or making antibiotics or doing open heart surgery. So these things require teams of people who know about different things and that know how to collaborate in the implementation of something.

Matt: So how do you connect that knowledge to economic growth?

Prof. Hausmann: So poor countries typically do few things that are relatively simple to do and rich countries do many things and things that involve very, very large networks of people collaborating. In any movie you’ve seen for example that towards the end of the movie they put a sign that says the end. But that’s false advertising because after they put this sign the end, they start putting the credits. The credits go on and on and on and on. You have actors, you have people casting, you have makeup, you have sound editing, video editing, special effects. All of these skills have to come together to make one movie. That is an expression of a complex technology.

Matt: So, one thing we struggle with is to say in a globalized society in which tools can be put on ships and shipped around the world. So an iPhone can reach the furthest parts of the world and then embedded code can be put, codified code can be put online. So all the codes of how to produce a machine can be put on Wikipedia to reach the furthest parts of the world, then why are we still seeing this large divergence in incomes and productivities and also in growth. And so, we think it is that third element of technology and tacit knowledge of what we call know how that is the key to describe these differences in growth that we see today.

So, of course we’re here to talk about your latest growth projections that go to 2026. How did you come up with these figures? What was the process behind it?

Prof. Hausmann: So essentially, to prove that our theory of technology and growth was right, we show that we have ways of characterizing how much you know relative to your current income and how easy it would be for you to make more progress. We’ve shown that these two variables and I’ll say a little bit more about them, they have an enormous capacity to predict the future. So the first thing we measure is how much you know relative to how rich you. Do you know more than enough to be richer than you are so that you just have to express what you know, an income. Or you are too rich for how little you know and you better get your act together because otherwise you probably are not going to be able to sustain your position.

So that’s our first variable. How much you know relative to how rich you are. How much you know meaning as a society, as a country, not at the individual level. So it’s a societal measure. It’s how many things the society knows how to do and how complex are the things that the society knows how to do. The second variable is given what you know, how easy would it be for you to start doing other things. Are the things that you know things that are stepping stones into more things or are the things that you know more like dead end streets or particular things that don’t necessarily open up new doors.

So for example, if you are assembling microwave ovens, it should be relatively easy for you to figure out how to now assemble air conditioners or refrigerators or other things in that line. If you know how to plant coffee trees in a mountain at 3000 feet above sea level and so on. Well, with that knowledge and those skills and those productive capabilities what else can you do? Well, it’s not so obvious that those skills will translate into, and those capabilities would translate into many other things. So what you know also has what I like to call the adjacent possible. Given what you know, how rich is your adjacent possible.

So these are two objectives things that we measure in all the countries in the world for which we have data, which is like 130 countries. We’ve shown that in the past it predicts growth 10 years ahead and so we’ve downloaded all the data for the world now for 2016 and we use that data to project to 2026.

Matt: Tim, in the report it talks about how there’s a shift happening from oil and commodities to more diversified economies. It seems to be exactly what you’re describing Ricardo. Can you talk about that a little bit?

Tim Cheston: Exactly. So as Ricardo mentioned there’s these two key dimensions. One is how complex the product is, how many different set of capabilities or Know how is required to produce that product. The other is how connected that product is. How easy is it to redeploy those products. So what we see is those economies that are focused on a single commodity often find out that commodity doesn’t allow those skill sets to be easily re-deployable.

So for example, we see the fastest growing countries in sub-Saharan Africa last decade were heavily concentrated in West Africa and benefited from the commodity boom. While now, the fastest growing countries in sub-Saharan Africa concentrate heavily in East Africa where there has been a small amount of diversification into certain manufacturing sectors that should allow for future diversification to open up new opportunities and lead to faster growth in the coming decade.

Matt: What kind of sectors are they getting into? Are they moving into similar areas because of their proximity?

Tim Cheston: Certainly. So one of the new findings that we have is, take a country like Uganda which is the country we predict to grow at the second fastest rate out of any country globally for the next decade. Uganda has moved into certain products and paints and hair preparations. That specific growth into those products segments allow for new openings into cleaning products and packing lids. So redeploying that work into paints, that work into plastics opens up the related capabilities that are connected to new products that should lead growth in the coming decade.

Matt: So, you mentioned Uganda as the number two. of course your number one was India. Can you talk a little bit about what India’s got going for it that it’s going to be growing faster than anyone else.

Prof. Hausmann: Well, India has two characteristics that make it quite unique. The first one is that it’s really extremely poor for the level of know how it has. So it’s into very sophisticated things, into highly diverse things. So it knows a lot and relative to how much it knows it’s very poor. So we think that it’s just diffusing domestically the know how they have should be an important engine for growth.

But in addition, it is also the country in the world that has the richest adjacent possible. Given what they know, there’s many many things that they can use that know how to to move into related things better than any other country. So we think that these two elements are going to be the drivers of India’s growth going forward.

Tim Cheston: One of our challenges there also is that you know we’re not fully rosy on India’s growth projections, that there still needs to be actions taken to see this growth happen because in the past decade we have not seen any growth in India’s ranking in the economic complexity index. So there has been little diverse, continued diversification, that what we see is that India will realize income gains given previous diversification that happened. But in order to sustain this growth that we project there are still a lot more work that needs to be done given the relative stability of their current ranking.

Matt: This this idea of the adjacent possible, how do you connect the adjacent possible with the political reality of a particular country. That those opportunities are there doesn’t mean a particular country is going to jump at them. Do you work those into your analyses?

Prof. Hausmann: Actually we don’t. In the sense that a lot of these things that you would want to add to it they are already implicit in the things we look at. Take the case of India. We know if with extra information because we’ve worked on India, that a lot of those capabilities are in one part of the country and not in most of the country. So the domestic diffusion of the things that part of a country knows how to do should energize so like the rest of the country. There are things that Bangalore or Hyderabad, Goad, Dheli, Mumbai know how to do that have to get to spread to other parts of the country.

So the technology is sort of there, it needs geographical diffusion. When you look at it at the aggregate level you’ll just notice that things will have improved on average through the domestic diffusion of what’s there.

The second thing is that the government might be messy, this, that and the other but if it was messy, too messy they would not be where they are. Bad governments are behind the fact that countries are unable to implement technology but because bad governments were there in the past we see it in today’s inability to implement technology. So all of these other factors it’s not that they’re not important, it’s that they are implicit in the variables we look at.

Tim Cheston: India has had success moving into new chemical sectors as well as certain areas of vehicles and electronics. So it is to say that their current export basket is more complex than would be predicted by their current income level and that’s why we think they can grow. And that again has to do with the nature of technology as being tacit knowledge driving this income difference. That what is done and the electronics being created in one state in India are not transferred to another state much less to a mile down the road to other highly unequal living conditions there.

So one source of growth could potentially be to analyze the domestic transfer of this know how in society from one state to another can be a strong source of growth for the future of India.

Matt: I think a lot of people associate growth with innovation. You come up with new ideas and once those ideas are implemented you see economic growth. But your report kind of says, hold up, that’s not quite the case. It’s less about pure innovation and more about the technologies that already exist implementing them. Is that accurate?

Prof. Hausmann: That is accurate. If you are talking about a very advanced country, developed country that has pretty much implemented all of the technologies that exist then it has diversified into a full set of things that the world knows how to do pretty much, then growth comes from what we call innovation at the global scale. Something that is new to the world. But for developing countries, a lot of what innovation is is to learn how to do things that somebody else in the world might know how to do but you haven’t known how to do yet.

So it’s a lot of adoption but the process of adoption always involves adaptation. So adaptation is also a form of innovation. In fact, a lot of the innovation in the developed world also is not done in huge steps but very minor steps of adopting preexisting technologies to solve new problems or new little things so that in general, the same way as they say that progress is 99% perspiration, 1% inspiration, I would say that progress is 99% imitation and adoption and 1% invention.

Tim Cheston: We would divvy up our growth projections into three groups. One of the sort of countries with too few, too little know how or too low diversification of know how to be able to diversify into many other goods and we would lump Bangladesh, Ecuador, Guinea into that group. The second set are those that have made progress in diversifying their know how into increasingly complex sectors and so they should be the leading growth leaders. And again we see India, Vietnam and Indonesia in that group. And then finally it’s those advanced economies that Ricardo mentioned that are truly at the technological frontier in which innovation is the name of the game for their growth potential, but innovation being a costly and high risk process that means that their growth should be moderate for the coming decade.

Prof. Hausmann: It’s a feature of the world that the advanced countries grow at something like 2% and some countries in the developing world can grow at five, six, seven percent. The reason why they can grow faster than the advanced countries is precisely because there’s so much technology that they have yet to adopt and the process of adopting technology is easier than the process of pushing the technological frontier of the world.

Matt: When I think of economic growth, immediately I think of China of course because of the last 30 years of miraculous sustained growth. It fell to, I don’t know if it fell but it was 25 I believe in this ranking. Is that good or bad when you’re thinking about China’s economy?

Prof. Hausmann: China is a miracle. Never in the history of humanity has there been a country, a large country that has grown at these rates for this long. Now, a lot of it had to do with the fact that they started from an extremely low base. A lot of it is implied by the fact that they may be approaching something like $10,000 of income per capita. The US is at $60,000 of income per capita. So there’s a lot of technology that allows humans to live at 60,000 and they are very far from that. So there’s a lot that they can improve on.

They’re urbanizing so they’re moving people from a low agricultural, low productivity agricultural activities to urban areas in which they can get them into manufacturing and into other things and so on. So that’s just a diffusion of existing technologies and incorporating more of their people into these high productivity activities. We think that given where they are and given how quickly they have grown, their know how is no longer that distant from their current income precisely because their current income has gone up so so much.

They’re still relatively well positioned in terms of having a fairly rich adjacent possible. So there’s still a lot of areas in which they can progress. But we’re putting them a little bit south of five percent of growth, and in any other period you would have thought gee man, that’s a fantastic rate of growth for a country that has essentially zero population growth. So it’s all growth and real incomes. In the US population growth is about one percent a year. So if the US grows at two you discount one percent from population growth it gives you a rate of growth of one or one and a half percent per capita. Well China is at five. That should be spectacular, fantastic etc.

It will feel like a recession in China and very different from the recent past or from the last 30 or 40 years since 1978. But it’s still a very high rate of growth by international standards. Most Latin American country countries would give their life to have those rates of growth.

Tim Cheston: What we’ve seen over the past few decades is as China goes so goes global trade. So we see some worrisome signs in the fact that we’ve seen year on year or consecutive years of downturn in China’s export totals for the first time since 1966. There are signs especially in computers where we’ve seen a 28 billion dollar fall in exports in the past two years. So there are signs that we are monitoring closely. Again, China is the 18th most complex economy in our study which is up 13 ranks in the past decade. So progress has been made. They’re still more complex than is currently being expressed in their income but it’s precisely because they’ve gone through this process of becoming more complex that they’ve realized those income gains that will now slow down growth but again, China will continue to be in the top quartile of countries for the coming decade as it relates to growth.

Matt: The falling export numbers, is that because China is trying to focus on its domestic economy rather than be attached to the world and does that matter in this equation?

Prof. Hausmann: It’s a little bit the the following problem. That if you grow faster than the rest of the world, you tend to export faster than the rest of the world imports. You tend to import faster than the rest of the world exports. So as you try to do that you’re flooding the world with your exports, depressing the value of your exports. You’re increasing the price of your imports. You’re moving the terms of trade sort of like against you. A country the size of China grew enormously when they were a very small part of a global economy. Now they cannot sustain. If the global economy is growing at three or four percent they cannot have their exports grow at 15% because the world, who are they selling that to, they are a significant chunk of the global economy who would they be selling that stuff to. Nobody is increasing their imports at that rate.

So that causes the terms of trade to move against them and as they become richer they also want to move some of those, their wages are going up faster than say, to a level higher than say wages in Vietnam or wages in Cambodia or in Myanmar and so on. So suddenly you start seeing that a firm start to move from China to Vietnam and to other places that can pay lower wages so that they also lose part of their export basket to other competitors that are lowering in income.

So that’s why if you do not increase the complexity of your exports at the rate at which you grow, you may become too rich for your export basket. We see a few countries that are undergoing that problem. For example, a country like Sri Lanka, they got into, traditionally they would export tea and rubber, then they got into garments but they got stuck in garments. And so, when they got into garments they had a big boom and increased in garments and so on. Now that everybody else is getting into garments they should have been getting into electronics into machinery, into cars and so on. That never happened.

So now they’re being dragged down by the fact that their complexity is too low relative to their current level of income. So it’s harder for them to keep on growing.

Matt: What can policymakers and I guess folks in the business community take away from this formulation? Are there steps they can take to ensure that wherever they’re from, wherever their community is is sufficiently diversified to take advantage of this type of thing?

Prof. Hausmann: The first question is what do the projections say about the future and then I guess businessmen are going to decide what to do, how to exploit the opportunities of the places that grow. Policymakers, if they don’t like the projections, maybe they want to change strategy or change something to make the projections wrong. We welcome that actually.

But essentially, it goes back to the essential sources of growth. Can they do something so that more of their country is able to implement the things that part of their country knows how to do. Can they maximize the value of what they already know how to do by sharing that know how, implementing those technologies more broadly in the country. Can they coax their firms into diversifying tours, activities that are more or less related that imply leveraging the things that they know how to do and figuring out the gaps that have to be figured out to start implementing things that they don’t yet do.

Tim Cheston: The lessons of economic complexity is that countries grow by diversifying the sets of goods they produce and increasingly moving into more complex production. So diversification itself means learning to do the things that you don’t currently know how to do. So Ricardo has done major work recently on the issue of migration. How do you attract the know how if it’s just slow process of learning rather than creating into brains. It’s much faster to move brains across countries. So what is the role of immigration policy in allowing new know how and more complex know how to move into a country. Again, going back to the fact that it’s adaptation that is leading to higher growth currently. Adopting higher productivity products into your country is leading to faster growth and moving up the technological frontier. So how do you adapt a product into a locality.

We find that you can speed up that process by moving brains and focusing on the know how that you have and what additional know how you can add to diversify the skill sets and therefore the production that you can create.

Matt: So should we be building a wall to keep brains in? Is that …

Prof. Hausmann: Brains are are like viruses. They infect places as they go. It’s very interesting. A lot of people have, if you put a wall in the US, it’s interesting that you mention, 52% of the entrepreneurs of Silicon Valley were not born in the U.S.. But if you ask what percentage of entrepreneurs of Silicon Valley were not born in California, well, the number goes probably up to something like 90%. So the secret of California is not that they’ve taken kids from kindergarten and got them to become entrepreneurs, it’s that they have attracted talent from the world and that has generated enormous spillovers to all 40 million Californians and not just to know the individuals that were involved in leading these firms.

So, by the same token countries in the developing world have migration policies that are incredibly restrictive by U.S. standards, but incredibly more restrictive. They are especially biased against skilled migration. So it’s a policy that has been hijacked often by trade associations, professional associations that don’t want to compete with people from other countries that we might be moving in and so on.

So we’re currently working with the governments of Sri Lanka, the government of Saudi Arabia, the government of Panama and probably now the government of Mexico into looking into what about their immigration policies is preventing this know how from flowing in and as a consequence slowing down the process of innovation. The way the U.S. leads the world in innovation is because the U.S. has a trick in that they attract talent from the rest of the world. The percentage of professors here at the Kennedy School and at Harvard that are foreign born, myself included, is quite significant, quite significant.