Title: Atlas of Economic Complexity: Mapping Paths to Prosperity
Author: Ricardo Hausmann, Cesar Hidalgo and others
Scope: 3 stars
Readability: 4 stars
My personal rating: 5 stars
See more on my book rating system.
Topic of Book
The author’s use the concept of “Economic Complexity” to measure a society’s productive knowledge.
Hausmann and Hidalgo are at the center of an emerging sub-field within economics called “Economic Complexity.” The field is summarized well below, so I will not go into to detail here. I encourage you to check out the free online Observatory of Economic Complexity.
- Modern societies acquire productive knowledge by distributing that knowledge among many specialized workers.
- Organizations and markets combine that knowledge to make products.
- Skills needed for industries can only be taught face-to-face making knowledge transfer difficult.
- If an industry is missing only one key skill, it cannot be competitive.
- New industries cannot be built without the requisite knowledge and skills already being in place, but the knowledge cannot be in place without the industries. This creates a fundamental gap that developing countries have difficulty traveling.
- Developing countries grow new industries by repurposing similar skills from industries that they already have.
- The gap between a country’s complexity and its level of per capita income is the best predictor of future economic growth. Economic complexity can explain about 73 percent of the variation in income across all 128 countries.
Other books by the same author
Important Quotes from Book
This progress was possible because we got smarter. During the past two centuries, the amount of productive knowledge we hold expanded dramatically. This was not, however, an individual phenomenon. It was a collective phenomenon. As individuals we are not much more capable than our ancestors, but as societies we have developed the ability to make all that we have mentioned – and much, much more.
Modern societies can amass large amounts of productive knowledge because they distribute bits and pieces of it among its many members. But to make use of it, this knowledge has to be put back together through organizations and markets. Thus, individual specialization begets diversity at the national and global level. Our most prosperous modern societies are wiser, not because their citizens are individually brilliant, but because these societies hold a diversity of knowhow and because they are able to recombine it to create a larger variety of smarter and better products.
The social accumulation of productive knowledge has not been a universal phenomenon. It has taken place in some parts of the world, but not in others. Where it has happened, it has underpinned an incredible increase in living standards. Where it has not, living standards resemble those of centuries past.
Just as nations differ in the amount of productive knowledge they hold, so do products. The amount of knowledge that is required to make a product can vary enormously from one good to the next. Most modern products require more knowledge than what a single person can hold. That is why the average worker in a rich country works in a firm that is much larger and more connected than firms in poor countries. For a society to operate at a high level of total productive knowledge, individuals must know different things. Diversity of productive knowledge, however, is not enough. In order to put knowledge into productive use, societies need to reassemble these distributed bits through teams, organizations and markets.
Accumulating productive knowledge is difficult. For the most part, it is not available in books or on the Internet. It is embedded in brains and human networks. It is tacit and hard to transmit and acquire. It comes from years of experience more than from years of schooling.
This process, however, is tricky. Industries cannot exist if the requisite productive knowledge is absent, yet accumulating bits of productive knowledge will make little sense in places where the industries that require it are not present. This “chicken and egg” problem slows down the accumulation of productive knowledge. It also creates important path dependencies. It is easier for countries to move into industries that mostly reuse what they already know, since these industries require adding modest amounts of productive knowledge. By gradually adding new knowledge to what they already know, countries economize on the chicken and egg problem. That is why we find empirically that countries move from the products that they already create to others that are “close by” in terms of the productive knowledge that they require.
The Atlas of Economic Complexity attempts to measure the amount of productive knowledge that each country holds. It is much more predictive than other well known development indicators.
Markets allow us to access the vast amounts of knowledge that are scattered among the people of the world.
Markets and organizations allow the knowledge that is held by few to reach many. In other words, they make us collectively wiser.
The amount of knowledge embedded in a society, however, does not depend mainly on how much knowledge each individual holds. It depends, instead, on the diversity of knowledge across individuals and on their ability to combine this knowledge, and make use of it, through complex webs of interaction.
The secret to modernity is that we collectively use large volumes of knowledge, while each one of us holds only a few bits of it. Society functions because its members form webs that allow them to specialize and share their knowledge with others.
Because it is hard to transfer, tacit knowledge is what constrains the process of growth and development.
Because embedding tacit knowledge is a long and costly process, we specialize. This is why people are trained for specific occupations and why organizations become good at specific functions.
Ultimately, the complexity of an economy is related to the multiplicity of useful knowledge embedded in it.
Economic complexity, therefore, is expressed in the composition of a country’s productive output and reflects the structures that emerge to hold and combine knowledge.
Countries do not simply make the products and services they need. They make the ones they can.
Increased economic complexity is necessary for a society to be able to hold and use a larger amount of productive knowledge.
The gap between a country’s complexity and its level of per capita income is an important determinant of future growth: countries tend to converge to the level of income that can be supported by the knowhow that is embedded in their economy.
If we control for the income that is generated from extractive activities, which has more to do with geology than knowhow, economic complexity can explain about 73 percent of the variation in income across all 128 countries.
Countries whose economic complexity is greater than what we would expect, given their level of income, tend to grow faster than those that are “too rich” for their current level of economic complexity. In this sense, economic complexity is not just a symptom or an expression of prosperity: it is a driver.
In short, economic complexity matters because it helps explain differences in the level of income of countries, and more important, because it predicts future economic growth. Economic complexity might not be simple to accomplish, but the countries that do achieve it, tend to reap important rewards.
The Economic Complexity Index captures significantly more growth-relevant information than the 6 World Governance Indicators, either individually or combined.
Analytically, human capital indicators (such as education, test scores) try to measure how much of the same knowledge individuals have.
In contrast, the Economic Complexity Index tries to capture the total amount of productive knowledge that is embedded in a society as a whole and is related to the diversity of knowledge that a society holds… the skills acquired in school may be a poor proxy for the productive knowledge of society.
Countries are more likely to move into products that make use of the capabilities that are already available. These capabilities are available, however, because they are being used to make other products. An implication of this is that a country will diversify by moving from the products they already produce to others that require a similar set of embedded knowledge.
Imagine that the product space is a forest, where every product is a tree. Trees that require similar capabilities are near each other in the forest. Distant trees require very different capabilities. If countries are a collection of firms that make different products, we can think of firms as monkeys that live on trees, meaning that they exploit certain products. Countries differ in the number and location of their monkeys in this common forest. The development process, which implies increasing product diversity and complexity, is akin to monkeys colonizing the forest, occupying more trees, and moving especially into the more complex or fruitier ones.
When monkeys jump to nearby trees it minimizes the chicken and egg problem of having to accumulate several missing capabilities at once. Furthermore, if trees are densely packed together it will be relatively easy for monkeys to move from tree to tree and populate the forest. But if trees are far apart, monkeys may be stuck in their current activities.
A positive relationship between how centrally located the communities are in the product space and how complex their products are. Poorly connected communities such as petroleum, cotton, rice and soybeans tend to be low in complexity. Machinery, by contrast, is very complex and highly connected. Sectors such as garments, textiles and food processing are, on the other hand, in an intermediate position, being connected but not very sophisticated. Electronics and health-related chemicals, however, are also very complex but not as connected as machinery. This suggests they use specific capabilities relevant within their communities but not outside of them.
Countries with low levels of complexity tend to have few opportunities available. This is because the products they do create tend to be peripheral in the product space. Complex economies tend to have few remaining opportunities because they already occupy a large fraction of the better part of the product space. Countries with an intermediate level of complexity, on the other hand, differ largely in their opportunity value.
What limits the speed of this process? Since capabilities are useful only when combined with others, the accumulation of capabilities is slowed down by the chicken and egg problem. New products may require capabilities that do not exist precisely because the other products that use them are not present. Moreover, since capabilities are chunks of tacit knowledge, accumulating them is difficult even when there is demand for them, because the country does not have any exemplars to copy.
Most important, why does this process of development occur in some places, but not in others? Our approach adds an alternative answer by showing that a country’s position in the product space determines its opportunities to expand its productive knowledge and increase its level of economic complexity. But the product space is highly heterogeneous, placing countries in radically different settings.
The policy message for most countries is clear: create an environment where a greater diversity of productive activities can thrive and, in particular, activities that are relatively more complex. Countries are more likely to succeed in this agenda if they focus on products that are close to their current set of productive capabilities.