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

Chuck McKenney With COVD-19 forcing widespread adoption of virtual communication for much of the world, some wonder if these remote business practices will become the norm. Before the pandemic, international business travel was a 1-point-5 trillion-dollar annual expense – an expense that’s increasing about 7-percent a year. Why have corporations been willing to absorb this cost when technologies such as Skype, FaceTime, Zoom, WebEx, etc., have been widely available for the better part of a decade? Growth Lab researchers have been studying this question for years. You see, the Growth Lab’s approach to development puts particular emphasis on knowhow. We’re not talking about the information that exists in bo oks, computer files, graphs and algorithms. Knowhow only exists in brains, and it was very slowly from brain to brain through years of on the job, learning and interacting with experience counts. So to move knownow, you have to move brains. Now for more on the importance of moving knowhow, its relevance to business travel and some findings in our research, let’s bring in our guests. Ricardo Hausmann, Director of the Growth Lab and a professor at the Harvard Kennedy School. Frank Neffke, Research Director at the Growth Lab. And Michele Coscia, Assistant Professor at the University of Copenhagen. Welcome. Can you first elaborate on the concept of moving knowhow and its role in economic growth?

Ricardo Hausmann Sure. Chuck, thanks for setting this up. The idea in our mind is that really the secret of development is the adoption of technology and technology comes in three flavors. It comes as tools, which we call also embodied knowledge. So the knowledge is in tools. It comes in the form of codes, recipes, formulas, algorithms, how to do manuals. And those come as codified knowledge. And then there is knowhow that resides as you said before, just in brains. And it moves very slowly from brain to brain. So if you want to deploy technology, it’s very easy to move the tools. It’s very easy to share the codes. It’s very hard to move the knowhow. But we were puzzled for a long time on: How does the world get to move knowhow? And we had studied how knowhow moves between firms through workers that move from firm to firm. How knowhow moves between regions and you know, who are the entrepreneurs or the business organizations that deploy new technology and new knowhow from one region to another? And how knowhow moves between countries. And there we studied FDI and migration and so on. So we posited the idea that maybe there is a difference between moving information, call that bites, and moving brains.

Chuck McKenney So Frank, are there some other ways to move knowhow that had not yet been well studied?

Frank Neffke That’s a good question. The research that Ricardo talked about that we did before typically involved people of firms moving more or less permanently to a place. So there are firms who set up new subsidiaries abroad or there are people who migrate to a new place, a new region, new country and they bring their knowhow with them. And we know that from our prior research that that is a very strong channel to transmit knowledge between places. However, from personal experience, we know also that knowledge often doesn’t need permanent migration or permanent movements to be transmitted because we go to conferences and workshops all the time as academics. And there the only reason why we do that is so we can be face to face and talk to our fellow researchers across the globe. So that suggests that knowhow could actually also travel in a much shorter engagement. And firms do the same, firms and business travelers abroad at tremendous costs in terms of the money they spend on it, but also in terms of the time it takes sitting in airplanes and waiting at the airports and so on. But what was very hard was to map this movement, this trend story movement of people. Migration, there are good global statistics on migration. There are good global statistics on FDI. But there are no harmonized statistics on how many business travelers visit a place, how many business travelers move from the US to Germany, for instance, in a year, or from Germany to Austria and so on. But we actually at some point realized that business travel will leave a paper trail. And the paper trail that we thought about was the payments they make abroad. So when a business traveler travels to a foreign place, they typically take a corporate credit card with them. And if they make a payment with such corporate credit cards, that transaction is recorded. So we would see that a business traveler from the US going to Germany would pay for a restaurant bill or a hotel bill or something like that with a corporate credit card. And that way, if we had information on this, we could actually map the global business travel flows. Now, unfortunately, didn’t have that information ourselves, but we were lucky that we could team up with the MasterCard Center for Inclusive Growth. What that center allowed us to do was to access aggregated and anonymized data based on information of payments that were made by corporate debits or credit cards issued in one country, but the payments were taking place in another country. So that information was enough for us to build a network of global business travel that connected countries by how many business people we estimated would be traveling from one country to another.

Chuck McKenney Tell us a bit what you learned from looking at these data

Frank Neffke So the first thing that we did with the data is that we had to look at what do they actually reveal about business travel. One of the things that we found quite surprising was that business travel had grown tremendously. So we looked between 2011-2016 and it grew by 40%, whereas the global economy was more or less flat in the same period. So why did people want to go abroad and travel on business? What was the most important reason that we found in the data that would explain business travel? And it turned out that business travelers do one of three things. Either they are there to set up trade relations so to export to a country, or they want to set up new establishments abroad so they do greenfield investments, or they tried to manage their existing establishments. So that is people going from the headquarters to establishments abroad to make sure that everything runs smoothly, to be up to date with the problems and the processes of these local units. When we did the numbers, it turned out that by far the most important reason why business travel was happening was that last component. So managing the business units firms owned the abroad.

Chuck McKenney Michele, how did you work with the data to reach your conclusions about business travel?

Michele Coscia To be able to make the prediction of how much knowledge a country received from business travels, we need to guess in which industry a business traveler is active. In our data, we only have the country of origin. But what we are interested in is the industry of origin. In order to make this reconstruction, we are using what we call the Principle of Maximum Ignorance. Since we do not know which specific economic establishment in a country is sending business travelers, we just assume that any establishments in the country is equally likely to have sent the business travelers. What this means is that, for instance, if 20% of the firms in Germany are car manufacturers, then we also assume that 20% of the business travelers originating from Germany are involved in the car manufacturing business

Chuck McKenney Let’s dig into the findings. What did you learn from the flows of business travel in terms of its impact on countries?

Frank Neffke So now that we had an estimate of how many business travelers arrive in a country with a background from a certain industry, we knew how much relevant knowledge for each industry in a country would arrive. And the more relevant knowledge for industry arrives in the country, the faster that industry would grow and the more that industry would start exporting. And that is exactly what we found. So when we looked at the business travel at the beginning of the period in 2011, and then we analyzed how fast different industries in the recipient countries would grow over the next five, six years after these business travelers had visited the country. We found that the industries that grew fastest were exactly those industries for which we inferred there was a lot of knowledge inflow coming with the business travelers that arrived in the country. So not only that, we also found that if you received a lot of business travelers from a certain industry or that we associate it with a certain industry and you don’t have that industry yet, you’re more likely to start building that industry up in your country. So, for instance, take the case of Paraguay. Paraguay had a baseline probability of starting to make work clothing of about 8.6%, according to our models. But due to the business travel it received and the knowledge that was embedded in the business travel, that likelihood actually went up to 11.4%. Slovakia had a baseline probability of 1.3% of making waterproof outerwear, and that baseline went up to 5.3%. So that’s about four times as large simply because of the knowledge inflow that came with the business travelers and that arrived in Slovakia.

Chuck McKenney How do you know if the business travel caused the exports and not the other way around?

Ricardo Hausmann Well, we found that business travel precedes growth in exports and productivity. So that’s the first hint that it may be causal. It may not just be, you know, a correlate. It may be causal. But in order to dig even deeper and get through our referees, we have to use more sophisticated econometric tools. One of them called instrumental variables. And what we did is we looked at the consequences of differential business travel caused by different visa regimes between pairs of countries. In some countries, business travelers need no visa. They can travel freely. In other pairs of countries, there are more restrictions. So we use that as a source of variation in the intensity of business travel. And we found that that variation caused by differential visa treatments had a significant impact on exports and growth. So we think that it is actually the way in which the world deploys its knowhow and makes it available to different firms, different establishments across the world.

Chuck McKenney In your study, which countries benefited the most from business travel?

Frank Neffke So if you turn to the countries that actually benefit most, it’s composed mostly of the countries that are very close to rich countries that sent most of the business travelers. And that’s because the business travel network is very unequal. It is basically mostly comprised of rich countries visiting other rich countries and the developing countries have a much harder time to attach to this network, and they therefore also reap far fewer of the benefits of business travel. And in that sense, business travel, as it is right now, is a phenomenon where the rich get richer.

Ricardo Hausmann So in some sense, business travel represents another of those development divides that if you’re out of the business travel network, then you’re not benefiting from the flow of knowhow. And that slows your development path. There are some countries that are getting more than others – Mexico, Colombia, Peru, Chile, Argentina, South Africa, Morocco are getting more than other countries, say, like Bolivia, Ecuador, Venezuela, Nigeria, West Africa, Angola. So it’s a differential effect even in developing countries. But the system is somehow one of the obstacles to a broader spread of technology across the world.

Chuck McKenney Michele, how can people explore the data and your findings to learn more about this research?

Michele Coscia If you want to interact with our research, there are many ways you can do that, depending on your level of bravery when it comes to analyzing data. The first thing you can do is to go to the website of the Growth Lab. We created a Web page where you can read a text explaining our findings and our methodology and you can see different visualizations that will allow you to understand the data better. For instance, you can see the network of global business travelers and you can see the local effects that Frank was talking about, the fact that this network of global business travels is very well clustered geographically. . Another thing you can see is an  interactive visualization that allows you to understand the effects of the disappearance of business travelers originating from a specific country. You can select a country, for instance, Japan, Italy or the United States, and the map will show you which are the countries that will be harmed the most if that country of origin will stop sending business travelers. At a deeper level, you can also access data that we use to make these inferences. This data is being hosted by the MasterCard Center for Inclusive Growth. And these are versions of the data that are manipulated in order to preserve the anonymity and the data confidentiality of our data sources. But they still allow you to reconstruct our observers effect.

Chuck McKenney In light of the COVID-19 pandemic, business travel has come to a screeching halt. What does this mean for the global diffusion of knowhow moving forward?

Frank Neffke So at the end of this statistical analysis, what we had in mind was to ask the question, what would happen if a particular country in the world from one day to the next would stop sending business travelers abroad? By how much would other countries be hurt by that? And by how much would the global economy be hurt by this exclusion of business travel from one particular origin? And we call that the outgoing knowledge index. So for Germany, which is the biggest contributor to the global knowledge diffusion through business travel, according to our study, that was close to 5%. So if Germany stopped sending business travelers abroad, we estimate that the global economy might shrink by up to 5%. We looked at what happened if a single country stops sending business travelers abroad, what we never imagined with that, the entire world would stop traveling. This, according to our estimates, if we extrapolate from what we see from a single country, would have a detrimental effect to the flow of knowledge and the capacity of firms to manage their subsidiaries abroad.

Chuck McKenney Could the negative effects of COVID-19 on business travel be mitigated by digital alternatives to travel? 

Frank Neffke Now, we’ve all been living for a while now with the alternatives to business travel. We are doing this podcast over Zoom. We have a number of meetings on Skype. We are using Slack. We are trying to connect in digital means as well as we can. To what extent this actually will work and to what extent this is a good alternative for business travel remains to be seen. Mind you, these technologies existed in the period that we were studying. We started in 2011. Skype was around, a number of platforms to work remotely and collaborate remotely were available. But firms still chose to travel. So the question is, now that we’re all in a new world where we are so used to connecting through digital means. Does that mean that we also have learned how to connect to one another without business trouble? Or will we see long term adverse effects of this stop the global business trouble in the near future?

Ricardo Hausmann I think this point just raised by Frank about the world without business travel is something that we have not thought enough about. There are many ways in which organizations have structured themselves to maximize the impact of the knowledge that they have. Whether it’s a company that knows how to do something and is trying to figure out how to do it in other countries. And that’s foreign direct investment. Or whether it’s consulting firms the McKinsey’s, the BCG’s, the Bain’s of this world that possess a certain capacity, knowledge, problem-solving capacities that they deploy internationally. So suddenly you have all of this business travel being shut down. Well, part of it cannot be substituted by Zoom, part of it would require to go see, verify, etc. And that is probably slowing down certain forms of business organizations. So in many industries, for example, there is some competition between locally controlled firms and international firms. Well, maybe the margin of competition of those industries will change. Maybe if your access to this global knowhow in your corporate network is no longer available to you, maybe you are not as competitive vis a vis your local competition as you used to be. So this may lead to different forms of business organization. On the other hand, the things that can be done through teleworking. Right, so that the activities that can be done through Zoom. Well, maybe if you can do it from home, you can do it from abroad. That may open up new avenues for internationalization in tasks that can now be done more remotely than we thought they could be done before. So I think that the shock to a global economy may be more significant than we think. Many negative impacts in things that used to require business travel that is now impeded. But maybe the technological solutions may have differential effects on some activities vis a vis of the others.

Chuck McKenney Thank you all for taking the time to discuss your latest research, and you can explore this work at: www.growthlab.cid.harvard.edu/business-travel.

Katya Gonzalez-Willette: Hello and welcome to the Growth Lab at Harvard University’s weekly podcast. In today’s world, most workers are highly specialized, but this specialization can come at a cost, especially for those on the wrong team. New research by Growth Lab Research director Frank Neffke assesses the importance of the skills of coworkers. Finding coworkers who complement and not substitute one’s skills can significantly impact earning potential. The impact is equal to having a college degree. Coworker complimentarity also drives careers and supports urban and large plant wage premiums. 

Chuck McKenney: Thank you, Frank, for joining us. Your latest research on skills recently published in the journal Science Advances reveals the importance of teams and coworkers when it comes to productivity, earning potential and stays of employment. Can you tell us why it is important to study skills and teams? 

Frank Neffke: So the way we have been thinking about skills or what economists typically call human capital is that they are something that belongs to an individual. So we have skills and we sell them to firms. When we work for a firm, basically we offer them our skills. And if we have a high level of skills, or maybe if you have a high level of education, those skills are more valuable to the company than if you have lower levels of education. So in that sense, there are two things that are implicit in such a worldview. First is a very binary view of what skills are they are either high or low. And the other thing is that they are an attribute of an individual. And I think both are not that helpful if you really want to understand how skills work in a modern economy. So let me first get to the binary part. In reality, workers are not high or low skilled. Workers have skills that cannot be ranked along one particular metric. They come with different types of skills. So architects and accountants have both very high level skills, but they have very different skills as well. Just like carpenters and bakers may have similar level of skills, but they cannot do each other’s job very easily. So that’s the first part. The second thing has to do with the fact that if you just think from the individual, you’re missing an important part about skills. So why do carpenters and bakers have different skills? And why do architects and accountants have different skills? Well, the reason is that they specialize in something. So they took a long education and long training, long work experience to become good at a particular set of tasks. But now that we become specialized, we do not just gain the skill, we also lack a whole lot of other skills. And if we want to make something complex, then typically we don’t have the skills anymore to do that. And we need the help of others who have skills that are not ones that we have, but that would be needed to make the product that we’re trying to make in a team based setting. So nowadays, to achieve almost anything because we’re so specialized, people will have to work in teams in which others know the things that we don’t know how to do. But we still need to be done to produce a good or service. So, for instance, if you’re a Mason and you want to build a house, you will also need electricians and architects. You might need fire inspectors. You need a whole lot of other people to help you out with that. So in this world, a specialist, what is actually important is not just the skills that you have yourselves, but the skill set you can mobilize through others who have different skills. So by working together, you can actually mobilize a whole lot of different skills and add them to your own to be able to produce the complex products and goods that modern societies produce on a regular basis. 

Chuck: So what are some of the major takeaways of your research on skills? 

Frank: Well, I think that the single most important takeaway in the paper is that although your own skills are important, they matter for your career and for the wage that you will earn. What is equally important is how well they match the skills of your coworkers. What the paper argues is that coworkers can actually do two different things. They can either provide the skills that would be useful to combine with yours, but that you do not have yourself. So those would be workers who compliment your skills. But coworkers can also provide skills that are very similar to the ones you have. And in that case, these coworkers would be your substitutes in your firm. Now, complimentary coworkers are typically good for your wages and good for your career prospects, whereas workers who can substitute you are not good for your career. They typically tend to be associated with lower wages and also with you leaving the establishment where you work sooner. So what the research stresses is that your coworkers should be different but relevant. So the skills that your coworkers have there should be different from yours, but they should still be relevant to the kind of things that you are trying to achieve. Now, this is actually this is related to something that others have pointed out about themes and skills, but it sheds a slightly different light on these issues. So on the one hand, people often think that the best place to go if you’re a specialist is to go to another place with many of such specialists. So if you are a graphic designer, the best place to go is the place where they have a large number of graphic designers. Now, the problem with that is that in that place, there are a lot of people from whom you could learn undoubtedly, but there are also a lot of people who can do your job. So you are easily substituted by your coworkers. So that might be less than ideal. Instead, if you were to work in a firm that hires not just graphic designers, but also software developers, database managers and so on, in that place you would benefit from the fact that these other workers have skills that are useful when combined with your skills, but they cannot easily substitute for your skills. So that is actually much better environment. So another thing that people have often said about teams is that the diversity of people in a team makes the team more productive and more innovative. And I think that’s true. It’s just slightly more nuanced, according to this research, than just saying we need large set of diverse people with diverse backgrounds. Actually, what you need is complementary people. So complementary people are diverse. But they are also relevant to one another. 

Chuck: Were you able to determine the impact on wages for someone who’s on a team with complimentary coworkers versus someone who’s working with a bunch of workers who are substitutes? 

Frank: Yes, definitely so a lot of research has focused on the relation between wages and the complimentarity to coworkers. Now it turns out that if you have a lot of complimentary coworkers, you typically earn a higher wage and the increase in wage is comparable to the increase in wage if you go from a high school to a college degree, when it comes to substitute substitutes, do more or less the opposite. If you have a lot of substitutes around you, your wage typically is substantially lower. And as a consequence, you’re also more likely to leave the establishment where you’re working. 

Chuck: Can you elaborate on the data set and the networks that you constructed in the research? 

Frank: So the real challenge in the research was to figure out which workers are complements and which workers are substitutes for each other. There is no variable in a data set that tells you about this particular feature of your coworkers. You just know what a coworker has in terms of skills, but not what the relation of the skills are to your skills. So that is something we have to figure out. So the hardest thing in the research was finding out which skills are complementary and which skills are substitutes for one another. And to do so, we actually relied on a very large data set. In Sweden, we had administrative data on the entire population of Sweden and some 9 million individuals for about 10 years of their working life. And we knew not just the level of education ahead, but the exact type of educational degree they acquired, so we know that somebody has a post-secondary degree in accounting or college degree in architecture, post-secondary degree in food preparation and so on. The other thing that we knew about workers was the kind of job they held. So the occupation in which they were employed and the work establishments where they were employed. So we knew exactly what people did and with whom they worked. And that last part was particularly important because the idea behind measuring complementarity of coworkers, which educations would be useful if they are used together? Well, we just ask firms because firms are in the business of making useful teams. So if we ask a lot of firms, which people would you put together in one team, we will get an answer that will tell us about how complimentary coworkers are. So we didn’t really ask firms. We just looked at what they did in practice. And we found that there are very strong patterns in the types of educational backgrounds that are hired in the same establishments. And by counting how often two educational backgrounds, so two educational degrees would be present in the workforce of one and the same establishment. We could get a sense of which educations are often combined by firms. Now, if you compare that against some random benchmark to see whether these core occurrences of educations are significant in a statistical sense, you get an idea of, what we call in the paper, which educations are synergistic. Now, the problem is that firms will not just hire complementary coworkers. So teams will very often also have duplicated workers. So if there’s a lot of work for workers with a specific skills, you will need to hire more of those workers. So many of the people in your team will actually not be complements to you, but they will be your substitutes. They will know how to do the same tasks. So we also needed to figure out which educations allow you to carry out the same tasks. Now we have actually information about that because we know which occupations, people held and occupations are sort of bundles of tasks. So by asking which educations allow you to get into the same types of occupations we could back out, which educations prepare you to do the same tasks? So which educations are substitutes to one another? Now complimentarity is basically the access synergy. Given these substitutability of your coworkers, so what we ask this, how synergistic are you to your coworkers? How often do workers with these particular educations work together? Controlling for how similar these educations are? And then you see that there are certain skills that are very different, but still very often used together. And those are the skills that we’re calling complements, given that you have nine million people in hundreds of thousands of establishments. You can actually get a pretty accurate measure of which educations are preparing workers to be substitutes for each other and which educations are preparing workers to become complements. 

Chuck: And you’ve constructed a tool which identifies right coworkers and wrong coworkers. 

Frank: Yes, so we visualize these educations in a network. These networks, they show all of the educational specializations you can get in Sweden – there are almost 500 different degrees. We connect two degrees in this network. If they are either very synergistic to each other or if they’re very substitutable, one another. So there is a synergy network and there is a substitutability network. Now you can look up each education and find which of my most synergistic educations starting from my own education. 

Chuck: How does this research relate to, say, an urban or a large firm wage premium? 

Frank: So this was actually a surprising finding in the paper. It is a well-known fact that large cities pay higher wages than small cities. Boston pays a much higher wage. And then Worcester, which is near by and large, firms also pay higher wages than small firms. The explanations that people have been giving for that tend to be very different. For instance, in a large city, you would have a higher learning rate than in a small city because some more people from whom you can learn. People have said that large firms are just very productive and they share part of this productivity with their workers. There are a number of other explanations that have been given for this. But what this paper actually suggests is that complimentarity to coworkers could explain both of these premiums. So what happens if you move to a large city is that it’s easier to find the right coworkers because a large city has many different workers with many different skills. So it’s easier to find the team in which you would be the complementary coworker. Similarly, in a large firm, the division of labor can be much deeper. Meaning that people in a large firm can specialize much more on the tasks that they’re really good at, but they can only do that if there are coworkers who do the other tasks. So if there are enough complementary coworkers and what we find in the paper is actually that if you control for the complimentarity to your coworkers, both the large plan premium and the urban wage premium become much less pronounced. So to a large extent, complimentarity explains why these premiums exist. But not only that, it turns out that both premiums are very dependent on having complementary coworkers. So the people who work in a large city but do not work with complementary coworkers, they get hardly any return to working in a large city so full of people have many complementary coworkers. The urban wage premium is about 9 percent, meaning that for every doubling of the city size, wages go up by 9 percent. If you compare that to people who work in the same large cities but do not find complimentary coworkers for then the urban wage premiums only 1 percent. Similarly, if you look at people who work in large establishments but then do not find complimentary coworkers, they tend to also not get a very high return to working in that large plant. 

Chuck: Does everyone benefit equally from complementary teams? 

Frank: No and that was another surprising finding. The returns for complimentarity are actually highly uneven and this was surprising because in principle, if I am complementary to you, you are complementary to me. That’s the way we constructed these measures. So there was a built in symmetry in this relation of complementarity. However, it turns out that people with a high level of education have a much higher return to complimentarity than people with lower levels of education. So this suggests that the people who really benefit from working complementary teams are people with the highest levels of skills. So why would that be? Well, we can only speculate. But one plausible reason for this is that what complimentarity does is that it increases the productivity of the team as a whole. So it basically increases the amount of output a team can produce, but it doesn’t tell us anything about how this extra output will be divided. We know that complimentarity increases the size of the pie, but we do not know who will get which share of this pie. 

Chuck: So how does this research fit into what you’re doing at the growth lab and what might be next? 

Frank: Well, that’s an excellent question. So the reason why we looked at this complementarity of teams is that we are very interested in understanding how growth works. So the way we have been thinking about why some places grow faster than others is that some places just have more capabilities than others. So let me explain that a bit. The way we think about economic production is that if you want to produce something, let’s say a car, you needs not just capital labor, but you need a whole lot of different types of capability. So you needs dedicated machines. You might need research institutes, but you also need a whole lot of different types of workers. So you need car engineers, you need car designers, you need people who do the marketing of the car. You need the accountants taking care of the bookkeeping in the home and so on. So, so far, we have mostly looked at what that means for economic growth. And they are. The idea is that for countries, but also for cities or firms, it’s easiest to move into new products if these products require many of the same capabilities to the ones that you have already. So if you want to diversify as a country, it’s easier to use the capabilities that are embedded in your current workforce than to train workers to get new capabilities. And that’s why we see that most countries, but also cities and regions and firms, they diversify in a very predictable way. They diversify into new activities at a very late to the old ones. If they want to diversify into something that is less related, they typically have to get capabilities from elsewhere. So that explains why we were very interested in looking at migration and how firms invest in foreign markets, because very often some firms invest in foreign market, they do not just bring capital, they also bring a team of specialists to this new location that allows this new location to diversify into things that without the help of these foreign firms that couldn’t have done. So the question that we had an answer is, is it enough to have just a lot of different capabilities? Does the coordination of these capabilities into teams, does that happen automatically? So the missing piece of the puzzle this research provides is that workers themselves become very dependent on each other in very complex economies, because these complex economies, they organize they coordinate the capabilities that are distributed across a lot of different workers into teams that then can produce high value products. Now, this got us actually very interested in the question of coordination. And how economies historically and also nowadays have managed to coordinate workers and teams of workers into networks that produce output. So currently we’re using this line of research to explore how the US actually managed to become the frontier of technological progress and the economic powerhouse out of this. Nowadays, where the organization mechanisms could be funded, but they could also be cities. We are also very interested in thinking about the future of work along those lines because what the future of work people have looked at, the future of work in terms of which skills are going to be replaced by machines. But this is not the only thing that happens when a technology changes how we do our work. It actually also changes how we can coordinate different skills in different teams. So we’re also trying to understand how jobs have changed throughout history and how different skills are being combined in different ways over the past 60, 70 years or so. 

Chuck: Thanks, Frank. Fascinating research. 

Frank: Thanks Chuck. We should do this again. 

Katya: If you want to learn more about the Growth Lab’s latest research and events, please visit growthlab.cid.harvard.edu. See you next week.

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

Women in Jordan are excluded from labor market opportunities are among the highest rates in the world. Previous efforts to explain this outcome have focused on specific isolated aspects of the problem and have not exploited available data sets to test across causal explanations. In this podcast, Emma Cameron, student at the Harvard Graduate School of Education. Interviews Growth of Research. Fellow  Semiray Kasoolu. Semiray discusses Growth Labs recent research on women’s economic exclusion in Jordan. The Growth Lab team has developed a comprehensive framework to analyze the causes, leading to low female employment rates and participation in the labor market and systematically test their validity using micro level data.

Emma Cameron: Thank you so much for joining us here. So for those listening, I was wondering if you could give us a brief summary of your background and why you’re interested specifically in this topic.

Semiray Kasoolu: Sure. Thank you for investing the time in this. My name is Semiray Kasoolu and I have been a research fellow at a Growth Lab for the past few years. Before that, I was studying at the Master’s in Public Administration and international development at the Kennedy School and the reason why I’m interested in this topic goes back to my undergrad thesis on Turkish women’s participation and how to improve it. And this is tied to my background. So it is a personally motivated passion that goes to research. And I was able to explore it in more detail thanks to the technical tools that I got while studying here and while working at the Growth Lab. And the second motivation is more on the professional side, because it was such a puzzle when we started working in Jordan to realize that a country that has this modern image has such a low female labor force participation, such high exclusion of woman from the labor force. It was a really motivating question and a challenge. And we really wanted to contribute to understanding it and eventually helping policymakers solve the problem. So I can summarize my motivation as a personal and a professional.

Emma: Great. Thank you. So before we dive into discussing the specific work that your team just did, can you give us some background on the current landscape in Jordan and what are some of the current important economic trends going on in Jordan?

Semiray: Sure. So I think we can summarize by saying that Jordan had a large growth acceleration from 2000 to 2008 when the economy grew, but then the recession hit and they have been in an economic downturn since then. I think the pressing questions for them is how they expand their private sector, how they create a vibrant private sector while also taking care of their debt. At the same time, they don’t have much fiscal space to spend. So this becomes a very constrained space through which they can diversify and grow their private sector in terms of current challenges that they have is that their public sector cannot keep growing, and this has been one of the primary employers of woman in the country and it has been the employer of choice for Jordanian citizens in general. So I think the question becomes, how do we provide employment opportunities for citizens that does not rely on government funds? And that’s where we came in a year and a half ago trying to help them solve this problem.

Emma: Great. Thank you. So now to get a little bit more into the research specifically. Can you please share some insight into the work that you and the Growth Lab have conducted in Jordan?

Semiray: So I can summarize it in a broad way, saying that we help form a strategy for growth for Jordan, given the constraints that it has in terms of limited fiscal space, in terms of water scarcity and terms of high costs of energy. So what we did is to analyze and identify sectors that would prove promising for growth and that would also employ woman. That’s one of the insights that we came to. It is that knowledge intensive service sectors are uniquely positioned to provide employment opportunities and solve problems that Jordan has right now. And those include technology, ICT, finance and just services that could be exported and not only provided to the local economy. On the other hand, this has been all done through different work streams. We’ve had an energy works team that tried to identify how to solve the energy constrained. We held macro work stream that looked into the debt sustainability of Jordan and we also had a labor market work stream that analyze the unique features of the Jordanian labor market. And finally, we also did a complexity analysis to identify sectors that have high complexity. But given the constraints that I mentioned in terms of water energy, in terms of female labor exclusion and in terms of trade ability, we ran them through this filter and identified sectors that are uniquely positioned to solve all of these problems while combining all the insights we had from all of these different work streams.

Emma: Okay. And so within that, you identified what was happening with women in the labor market in Jordan.

Semiray: Exactly, along with other issues that were going on in the labor market, such as the shortage of high skilled foreigners, for example, there have been examples of foreign direct investment in Jordan when a company comes to Jordan to open a local office. And in most of the cases, they have been having problems bringing in uniquely qualified foreigners because of restrictions on foreign employment. So we have been working with the government to ease those restrictions and also show that in most cases, these are very few individuals who have unique skills who could provide employment options for hundreds of Jordanians and shift their mentality about the substitutability of foreigners and Jordanians and create them more of a narrative around that these skills are complementary to Jordanian skills. So on the labor market, they have in those two work streams where we looked at foreign labor and also female labor.

Emma: Great. And so based on lack of women in the labor force. What do you believe are the biggest barriers for women to enter the labor force in Jordan?

Semiray: So I think our first steps was to identify who are the woman who actually have problems entering the labor force and through our work we came to the conclusion that these are women with low levels of education, with a high school degree or less. And for them, we did find evidence in the data to suggest that highly conservative cultural attitudes are constraining their participation, but they are also more actionable things in terms of policy, such as lack of quality and reliability in the public transportation provision. And we also have some signals to suggest that maybe something is going on in the daycare market that is restricting women from reaching nurseries, whether its costs with its provision. We will need further details, but I would rate transportation, highly conservative cultural values and with further data, maybe the nursery market.

Emma: So do you believe these barriers to participation in labor force are distributed equally across Jordanian society? Or do you believe that different groups of women are facing different barriers, for example, along socioeconomic or geographical lines?

Semiray: So I would say that to begin with, I think socioeconomic status is directly associated with educational attainment, for example. And what we could observe in the data was educational attainment. So I will speak about that dimension. And we found that women with low levels of education are more impacted by these barriers because they rely more disproportionately on public transportation and because chances are high that they come from a background in which conservative cultural attitudes will be more binding. So definitely there is the educational status component, which, as you said, it is associated with socio economic status and the geographical site. We did find some data, but in the opposite to our expectations because we saw that in governorates that are further away from a man and are less metropolitan and a man woman actually participate more. So perhaps in these governors there is the cultural component, but it is not that strong contrary to expectations. But the income effect is higher, meaning that these are governors that have a higher poverty rate than average and that may be instigating woman and stimulating them to participate at higher levels than in more metropolitan and modern places such as Amman. So to summarize, yes, there is the educational component and also the geographical component, but the geographical component is distributed in a way that is contrary to expectations.

Emma: So you talked a little bit about cultural and transportation as two of the main barriers right now. Would you mind explaining to the listeners just what you mean by those two terms?

Semiray: Sure. It is very difficult to unpack culture. But what we mean by our attitudes and beliefs that constrain woman’s ability to look for a job and some proxies in the data that we could identify to assess that were a question such as if a woman works to their children, suffer. Do you agree or disagree? Or if jobs are scarce. Should men have bigger right to that job than a woman? Or what do you prefer a woman to do it? To work, to take care of their families? Or do both? And along all of these questions, Jordan registers highly conservative attitudes, meaning that they strongly agree that the children are working. Mothers suffer. That is the highest rate recorded along all countries. They also answer that they would prefer a woman to only take care of their families. Forty two percent of Jordanian men say that this is at a similar rate to Saudi men, for example. And finally, when it comes to looking whether woman how the same right to get a job, they disagree. And Jordanian respondents, actually, 93 percent of them in the 2014 World Value Survey answered that men should have a higher right to a job. So by these cultural attitudes, I mean anything that could be constraining a woman’s ability to look for a job or get a job due to all of these social and societal and cultural beliefs that are ingrained in them. And when it comes to transportation, actually, that’s a good question. Because it captures not the infrastructure, but what we mean by transportation is the actual provision and the reliability of public transportation. What we found in Jordan is that the transportation provision is highly fractionalized and it is very fragmented and individuals control different lines that may not run down on time. That may not be well connected. And we found that because women with low levels of education rely disproportionately more on public transportation, they’re more affected by all of these inefficiencies that are going on there. And in the data, we can observe that in commute times, for example, where women self-select into jobs that have very short commute times. This is either due to safety concerns that come from being in a public transportation for a long time. While men can afford to spend about forty five minutes per day in public transportation, which is about 55 to 60 percent higher than the range that woman can expect to have. And also, I think the main thing, what we mean by transportation is the software of transportation, so to say, which includes things like reliability, accessibility, safety, and all of these measures that we find in the data in terms of commute times and a proxy by just looking at commute times. And we also find that in districts that have higher commute times, woman with low levels of education are less likely to participate. And that is not the dynamic we observe for other groups of woman. So there is definitely something about transportation and it’s inefficiency that is impacting woman with low levels of education much more.

Emma: Interesting. So I believe you said 42 percent of men believed that women should be at home raising their children as child rearing considered a noble profession in Jordan?

Semiray: So the survey we used was the World Values Survey to assess that. So I think that it is very hard to say. I believe that maybe there is some component of the noble profession that you mentioned. And it looks like it is ingrained in social views because also 31 percent of woman also agreed that they would prefer a woman to raise children. I cannot make the normative statement whether this is the case because I have even though extensive but very limited interactions and exposure to Jordanian society. But what I can say from the data is that we observe large drops in participation after the age of first birth, and that occurs pretty early for women with lower levels of education and a little bit later for a woman with a university degree. But it does look like it is prioritized whether this is prioritized, because the nursery market is not providing the services that women need or whether they are not accessible or a woman just don’t prefer to use them because of cultural views or they don’t trust nurseries. I can’t say. But it does look like child rearing impacts participation a significant way in Jordan.

Emma: In your opinion, what are the most important policy tools available to help increase women’s access in the labor market?

Semiray: I would think that improving the public transportation, safety and reliability and accessibility is a major one that is within the reach of policymakers and they have actually been working on that a lot in the past few years. But I would add that there are some low hanging fruit there that could have high improvements in terms of women’s access to the labor market. And these include bigger accountability around the timeliness of public transportation provision and that would increase the reliability and make it more accessible for women. The second point I would say is increasing the strictness and the implementation as well as of design of laws that are there to prevent gender based discrimination and sexual harassment. What we have found out visually reviewing in the cases such as the woman and the business and the law index published by the World Bank and also talking to organizations in Jordan is that even though there are laws to prevent sexual harassment, they’re very limited in scope, such as only your boss would be liable for that and not anyone else. There are also other laws that are there to provide a safe working environment for women. But actually, they put the burden of being safe on the woman rather than on society at large. One example is the law that prohibits night of work for women. So women are not allowed to work after, I believe, 7 p.m. until 6 a.m. or something like that. And that significantly reduces women’s access to some jobs that require overtime, for example, or work jobs that require night work. And while this law is well intentioned, it is ill designed in the sense that it shifts the burden of being safe to the woman by restricting her access to jobs. So increasing the type of laws that would actually make it costly for people to discriminate against women and to make it costly to have sexual harassment at work and at public places is another way that policymakers could make big improvements today.

Emma: Great. Thank you. And so what future work in questions does the Growth Lab have planned to further your research?

Semiray: Our formal engagement in Jordan ended in September, but there’s a lot of work to be done with the dissemination of the paper that we had and we would definitely like some wide dissemination of the findings to make sure that this paper reaches policymakers and is useful to them. And second, I think there’s a lot of work to be done regarding the nursery market just because the data is very scarce and we would like to find ways to collaborate with organizations or students here who could advance that level of research. But as of now, our work in Jordan and that end of September.

Emma: Great. Well, thank you so much for your time.

Semiray: Thank you for your good questions.

Katya: If you want to learn more about the Growth Lab’s latest research and events, please visit growthlab.cid.harvard.edu. See you next week.

Katya Gonzalez-Willette: Hello and welcome to the Growth Lab at Harvard University’s weekly podcast. The creators of Harvard Growth Labs Atlas of Economic Complexity are proud to introduce country profiles, a first of its kind platform that revolutionizes how to think about economic strategy, policy and investment opportunities for over 130 countries. Country Profiles invites users to take an interactive step-by-step journey to analyze a country’s economic dynamics and future growth prospects, including identifying what new industries are poised to take off.

Annie White: I’m Annie White, product manager for the Atlas of Economic Complexity. And today, I’m here with Professor Ricardo Hausmann, Director of Harvard’s Growth Lab. Ricardo, thank you for taking the time to chat about our new country profile.

Ricardo Hausmann: Thank you so much for having me.

Annie: Ricardo, can you start by telling us a little bit about the Growth Lab?

Ricardo: Well, the Growth Lab is a unique group of people. We are a little bit over 15 now and we are organized around three work lines. Some of the activities are about basic research. We’re just working on a question that is general about economic growth and development. A second line of activity is we work in countries with countries trying to understand their growth challenges and working on strategies to overcome those challenges and helping them implement those strategies. And third, we have a group that develops tools that are coming out of our research and allow our research to speak to the problems that people face. And our premier tool is this Atlas of Economic Complexity, which is this fabulous thing that you direct.

Annie: That’s right. So, Ricardo, when did the atlas come onto the scene and what was the inspiration behind it?

Ricardo: Well, the idea that emerged from a set of papers I wrote in the early 2000s with Danny Rodrik was the idea that countries don’t grow by making more of the same. They grow by changing what they make. And it seemed to me that the process of changing what you do is not random, that it has some structure. And I was trying to figure out a way of how can I capture the structure of how you move from one thing to another. You don’t go from making coffee to making airplanes in one fell swoop. And the reason why you don’t is because there’s a set of capabilities that are needed to make airplanes that are not needed to make coffee. But those sets of capabilities may be much closer to making cars than making coffee so that there’s a certain logic to the way countries are able to move from less, call it, sophisticated products to more sophisticated products. And that led me to an idea of how to go about it and to a very fruitful collaboration with Laszlo Barabasi and Cecar Hildago where we develop this concept of the Product Space, which is this like a space that relates each product to other products in terms of how close they are, in terms of the capabilities needed to make them. And when we published that initial paper in 2007, it became a good idea to try to make that tool available. And since then, we’ve been advancing both on the theory and on the implementation of that tool.

Annie: That’s right. So in the last couple of years at the Growth Lab, we’ve had a lot of discussion about wanting a big new feature called Country Profiles. What was the inspiration behind that?

Ricardo: Well, the tool that we had developed was sort of like a tool for ourselves that we made available to people. Now we know why we have developed a tool but it was not obvious for people how to move around the tool. The tool is super powerful because it has data on 6000 products. One hundred and thirty countries plus where you have all the exports, all the imports. So with that, you can do a thousand different things and you can, you know, lose yourself in asking yourself questions. Who exports macadamia nuts, who imports macadamia nuts or whatever other thing that strikes your fancy? The way we used it was as a window into what are the capabilities that countries have. Exports are a reflection of the things that a country is able to do well enough. It can sell them abroad. It’s a window into their productive capabilities and that’s what we’re interested in exploring those productive capabilities. Now we knew how we were using it, but our audience wasn’t necessarily initiated in this particular view of the world. So we decided that to make life much more accessible and to make our use of the data, our view of how we use the tool more accessible to more people, it would be great if we could insert it in a narrative, in a narrative about the country, in a narrative of, you know, what is this country in terms of the capabilities it has. Where is it coming from? What has it been? It’s recent evolution. Right. And then most exciting thing where it could possibly go. And we do this with 10 graphs that are automatically generated and that, by the way, you can play around with them, you can change the parameters and make them speak to details and aspects of the story. So these are 10 interactive graphs and with something that you developed, which I find incredible, which is the idea that the text is automatically generated.

Annie: It’s dynamic.

Ricardo: It’s dynamic. It’s incredible. The text is automatically generated. So, I mean, you’re going to drive us all economists out of a business, I guess. So it tells the story of one hundred and thirty plus countries in a very particular way. And in particular, it’s not about just where the countries coming from, but the most exciting thing where it may go to.

Annie: That’s right. When we start with a country profile, every country story starts exactly the same way. And that’s by showing its export basket. Why do we start the growth story with an export basket?

Ricardo:< I think the export basket reflects what a country is relatively best at. And as a consequence, it tells you something about in what areas of, say, the technological space it excels. For example, you can go to a country like my own, Venezuela, where you’ll see that essentially export basket is only oil. You go to a small country like Slovenia and you find that it’s a country of a couple of million people. They export 35 billion dollars of the most sophisticated products that you can imagine what is an enormous heterogeneity and say how could these people become so good at so many things? Relative to say, my country, which is a country of 30 million people, which is only good enough to make oil and sell it to the rest of the world. So I think the export basket is very telling.

Annie: Great. So, Ricardo, after we examine a country’s export basket, we transition in country profiles to its market share. Why do we want to examine the evolution of a country’s market share?

Ricardo: One of the most popular ideas in economics is the ideas that countries should specialize in their areas of comparative advantage. That’s probably one of the worst ideas that ever existed, and it’s one of the most misguided ideas. When you look at the evolution of a country’s market share in different products in the world. What strikes you is the fact that countries don’t specialize in to the few products in which they happen to be very good. But countries dramatically evolve the areas in which they’re good. If you look, for example, at the market shares of China, Thailand, Vietnam, you’ll see that they used to be very small exporters in agricultural products and suddenly they got into garments and fifteen years later they got into electronics and 15 years later they got into machinery and chemicals and so on. So that what they are good at, which means their export basket has been evolving, has been changing. When you find other countries that have stagnated, you find them, for example, that they got into agriculture and then they were more or less beaten around in progress, too much in agriculture. They got into garments, maybe say, like Sri Lanka or Tunisia, and then they got stuck and very little happened in terms of other things like electronics, machinery and so on. So looking at the evolution of a country’s market share in the world, it tells you how they have been able to evolve their comparative advantage. It is a dynamic story of what’s been happening to their capabilities.

Annie: Ricardo, we know that the team here has determined that by understanding what a country knows how to produce today, we can start thinking about the higher complexity products it might be capable of producing in the future. So Country Profiles incorporates this really interesting prescriptive element, beginning with what we call the strategy space. Can you expand on how the strategy space can actually tell us something about a country’s growth opportunities?

Ricardo: Well, every country has to play with the cards it has been dealt with. And those cards come from history, come from geography. But you don’t start the game from scratch and not everybody starts at the same point. So we need to characterize where is a country starting the game. Where is it now? And we do it by looking at two dimensions. The first dimension is does it have more capabilities than are currently expressed in its level of income? That is. Is it more capable than is currently reflected in how rich it is? Or does it need more capabilities if it were to be richer? So we’d look at some relationship between its level of income and its level of capabilities. And so we split countries between those that have more than enough capabilities to be richer than they are and they have yet to express them. I like this expression by this pre Socratic philosopher called Pindar says, and “become who you are”, sort of like, do you already have what it takes to be richer than you are or not? And that’s the first dimension. The second dimension is how close are the things that you know how to do from the things that you don’t know how to do. We call it in our language how well positioned during the product space. The product space is like a forest where every tree is like a product. And there’s some parts of the forest that are very dense where one tree is very, very close to other tree. So if you’re in that part of the forest, it’s very easy for you to move to nearby trees because there are very nearby. There are other parts of the forest that are more barren. And if you happen to be there, you know, moving from one tree to the next tree may be much more challenging because the trees are much farther away from each other. So the second dimension is, are you close to nearby diversification opportunities or not? And this gives us sort of like a two by two matrix of saying, do we have more than enough capabilities? Is it easier for you to get more capabilities by just moving to nearby things? And that’s where we essentially start by assessing the strategic predicament that a country faces.

Annie: Great. Beyond a broad strategy for our country. What else can country profiles do?

Ricardo: >Well, they tell you not just, you know, what’s your predicament. They tell you what specific products you could potentially get into. And it tells you that in three dimensions, it tells you or in maybe more dimensions. The first one is it tells you what things are relatively near to your current productive capabilities. Number two, it tells you if you want, how sexy are those things in in a couple of dimensions. How large are those markets? How dynamic are those markets? And very importantly, how complex is that product? Because we find that the complexity of products is very important. If you export products that are more complex than your current level of income, you’re probably competing with countries are richer than you that pay higher wages and you soon might have an opportunity if you were good enough to get into those industries, to be competitive in those industries and so on. So second, it tells us if you want how sexy it is. The third dimension, it tells you in some sense how strategic is that move because tells you if you were to become good at that product, how much easier it will be for you to continue with other ideas of diversification? How much closer does it get you to other sexy products that you might want to get into in the future? And with these three dimensions, we’re able to create a recommendation or a ranking of products. And in the current version, we’re offering, you know, 50 products out of the 6000 if you want. So it’s not one product. This is, you know, it’s a whole menu of things, but it tells you more or less where your comparative advantage might evolve. And I think that these are things that are potentially useful, not just for policymakers, but for investors. If I’m an investor, I’m thinking, gee, I want to create an enterprise in this country that’s going to produce X. How likely is this X to be viable, successful in this country? And the same question of a country, for example, we’re now working on on Ethiopia and Ethiopia has been trapped in exporting only essentially agricultural and some mineral products and they might want to move into manufacturers. Okay. What are the manufacturers that look more feasible now and maybe from then, what would come next, etc.. So our Country Profile tells you this list of products that are most attractive in these three dimensions. How close they are, how sexy they are, how strategic they are in terms of opening up further doors to diversify down the road. And you can play around with it so you can play around with it, you can play around with weights, et cetera, and get an idea of what the future might look like.

Annie: A really cool feature is that once a user discovers those 50 new products, they can actually click through on any one of them and explore the import export market, the evolution of that product over a number of decades in the Atlas.

Ricardo: That’s incredible because you could your potential customers be who your competitors are going to be? How dynamic has this market been? Where is the market been growing? So all of these things are answerable through this tool.

Annie: Great. So one of the things a user will discover in a country profile is we actually say based on those two criteria, we think we can assign you a particular strategy based on which quadrant you fall in in the strategy space. So let’s say I’m a policymaker or an investor and I get to my strategy space and I’m assigned, for example, the light touch policy or a parsimonious industrial policy. What kind of insight can I expect to gain now that I’ve been assigned that approach?

Ricardo: Well, if you’re a country, say what you call a light touch policy, it means it’s a country that has more than enough current capabilities to be richer than it is. And if it wanted more capabilities, it’s easy for it to get them because there are many things nearby that it could move into. So in that country, you’re probably not going to need to make too many efforts to have this economy grow. For example, countries that happened today to be in that quadrant are countries like India, China or Vietnam. And in our mind, it’s no surprise that these are countries that are growing relatively fast. At the opposite end are countries that need more capabilities to be richer than they are. But it’s hard for them to get them because there is nothing nearby and the things that they could get into would require a lot of coordination. Solving a lot of chicken and egg problems that always hamper the development of new things. So for them, it will require a lot of effort, a lot of coordination, a lot of willful policies to get them to move. And they are in the space that we call strategic bets. And one strategy that you mentioned was parsimonious industrial policy. It’s countries that need more capabilities. They can’t become much richer than they are with what they have. But it’s relatively easy for them to do that because there are many diversification opportunities that are relatively nearby. So they would require a different a different strategy of how you go about it.

Annie: Country Profiles is now transitioned out of beta mode and we’re really excited for what comes next. Do you know what comes next for the atlas?

Ricardo: Well, that’s a great question. The atlas has been amazingly successful. We’re close to getting to our one millionth individual user and we have an open mind of what might come next. And we are listening. Now that the country profiles will be out we are going to expect to hear from our audience what new features, what new things they would like to see there. We’ve added a bunch of new features. There’s a lot of things that we want to do that we haven’t had the time to do. But there will be new releases going forward. But I want to invite people to test it out, try it out, and maybe make suggestions of where the atlas might continue to go.

Annie: Great. Thank you, Ricardo, for taking the time to chat today. And congratulations on your new tool.

Katya: If you want to learn more about the Growth Lab’s latest research and events, please visit growthlab.cid.harvard.edu. See you next week.