The wealth of nations


Author: Cesar Hidalgo

Emphasis Mine

Why are some nations wealthier than others? What, precisely, does it even mean for a nation to be wealthy? And why, as a matter of practical and political importance, do some nations become wealthier more quickly than others? If we ask why a crystal grows in solution, or study how a bacterial colony grows in a sugar medium, it’s clear that the answers come down to physics – to matters of entropy and order, of information and organization. Yet such concepts, oddly enough, rarely play a role in economic analysis.

Traditionally, when judging the wealth of a nation, or assessing its growth potential, economists have looked to a handful of aggregate indicators – things like gross domestic product (GDP), total resources, levels of education and so on. In predicting future growth they’ve done much the same, by looking at past growth, debt burden, the flexibility of the labour market and the quality of government. The reasons why they took this approach are understandable: economic systems are complex, so it is important to simplify and reduce the analysis.

César Hidalgo is a physicist who thinks this situation should change, and that economists should take concepts such as information, order and organization much more seriously. He asserts that these physics-inspired notions hold the key to understanding the origins of wealth and economic growth in a deeper way, and as director of the Macro Connections group at the Massachusetts Institute of Technology Media Lab, he leads researchers using large, modern data to better understand the networks of people and technology that bind our global world together. His new book, Why Information Grows, offers an impassioned argument for the advantages of an information-centric view of economic growth, and for understanding the different capacities of nations to provide solutions to human problems.

The trouble with the traditional approach, Hidalgo argues, is that it misses most of what is important in determining both the wealth of a nation and its potential to grow further. Economies aren’t just aggregates. They’re networks of interacting people and firms, of individuals and groups with highly specific skills and capabilities. Economies, in his vision, are like systems of distributed computers, and what such systems can accomplish depends on fine details of the diversity of skills they possess, and how these skills fit together to create the capacity to get things done, whether it be growing and exporting vegetables or producing high-quality jet engines and consumer electronics.

Understanding wealth and how it grows, he argues, requires thinking deeply and in very specific terms about how knowledge and practical know-how spread from one place to another, and also why they often fail to spread. You may wonder, for example, as many economists have, why the sophistication of modern manufacturing – in the aerospace industry, for example – can’t simply be transplanted from developed nations to less developed ones, to spur economic growth. If the knowledge and know-how exist in one place, surely it is merely a question of transferring it elsewhere? But as Hidalgo points out, the barrier to doing so is actually immense, as this knowledge isn’t actually held in any single brain or even any single company. A nation’s ability to produce quality aerospace products depends on a distributed network of complementary skills, know-how, practices, habits, ideas and resources – and these are held in many brains, in many places, so dispersed that perhaps no-one understands it completely.

The chances of replicating an industry therefore depend strongly on having many of the prerequisite skills, knowledge and capabilities in the new setting. There is a natural tendency, as Hidalgo argues, for industries to emerge in places that already have related industries. Economic growth, then, isn’t just something to transplant, but demands growth in a more organic sense – with new capabilities being realized only when they can build on an existing framework.

Why Information Grows explores how this idea has been developed in research over the past decade by Hidalgo and his colleagues. Its organizing vision is one in which economic advance, and greater wealth, depend ultimately on economic complexity, meaning the possession of a great diversity of valuable skills. Much research has therefore aimed to measure such complexity. The most obvious idea is that the overall diversity of products a nation produces might reflect its capabilities and wealth, but this isn’t quite true. Getting a better measure of economic complexity requires looking at not only the diversity of products a nation produces, but also the sophistication of those products, which can be measured by how few other nations produce them. Many nations, for example, produce fruits and garments, while only a few produce advanced electronics or aerospace products. Out of this mix, in 2009 Hidalgo and his colleague Ricardo Hausmann introduced a quantitative measure of economic complexity that correlates very closely with wealth (as measured by GDP), but also goes beyond it by making better predictions about which nations will grow faster in the future.

In Why Information Grows, Hidalgo persuasivelyT demonstrates the value of this approach by placing the ideas firmly in their historical context, both in information theory and in physics.  The origins of order in systems far from equilibrium are almost never mentioned in any economics text. Yet, as Hidalgo points out, this topic is a completely natural starting point for any examination of organization in human systems, which only possess order for the same reason that biological systems have order: because our world is driven far away from equilibrium by the flow of energy from the Sun. Only this energy influx allows order to emerge locally. The existence of solids is fortuitous as well, as they allow information to endure, and for complexity to grow.

Hidalgo’s perspective on economic wealth is wildly fresh and creative. Physicists will enjoy reading about familiar ideas in new ways, and will also find value in learning how these ideas can be applied fruitfully in areas seemingly far away from physics. Economists and other social scientists will find new concepts ripe for profitable use. Hidalgo’s big point is that, even though economies involve people, and hence seem uniquely bound up with human thoughts and desires, they are also founded, ultimately, on the capacity of matter in its various forms, human and non-human, to do computations. And the most powerful engines of such computation are those networks of people and firms that embody and share diverse forms of knowledge and know-how. Economic growth, funnily enough, is also about finding better ways of computing.

About the author

Mark Buchanan is a science writer and the author of Forecast: What Physics, Meteorology, and the Natural Sciences Can Teach Us About Economics, e-mail


New Dark Matter Map Confirms Current Theories

Source: Scientific American

Author:Jennifer Ouellette |

Emphasis Mine

The American Physical Society is holding its annual April Meeting at the moment in Baltimore, Maryland, and one of the highlights, research-wise, comes to us courtesy of the Dark Energy Survey (DES) collaboration. This afternoon, the researchers released the first in a series of maps of the dark matter that makes up some 23% of all the “stuff” (matter and energy) in our universe. The map was constructed based on data collected by the Dark Energy Camera, the primary instrument of the DES. The camera is perched high on a mountaintop, mounted on a telescope at the Cerro Tololo Inter-American Observatory in Chile, the better to get high-resolution images with minimal interference.

Now in its second year, the DES began taking data on August 31, 2013, with an eye toward better understanding dark matter’s role in the formation of galaxies. The resulting map unveiled today is, as one might expect, spectacular — the first to trace in fine detail how dark matter is distributed across a huge swathe of sky, although it’s a mere 3% of the area the DES will cover by the time it finishes its five-year scheduled run. It’s not the first dark matter map ever, but it’s the largest and highest resolution so far. Check it out:  

The analysis — carried out by a team led by Argonne National Laboratory’s Vinu Vikram and Chihway Change of the Swiss Federal Institute of Technology (ETH) in Zurich — looked at very subtle distortions in the shapes of two million galaxies to construct the map, thanks to a technique called gravitational lensing, whereby the invisible gravitational effects of the dark matter bend light around said galaxies in predictable ways.

And so far, the researchers have found that the distribution of dark matter is pretty well in line with current theories — namely, that because there is significantly more dark matter than visible matter (a mere 4%) in the cosmos, galaxies were formed in those places where there are large concentrations of dark matter, and thus stronger gravity. Think of it as a delicate interplay between mass and light.

You can see that clustering in the color-coded image above, where the blue areas are where the density is about average, and the red and yellow areas depict regions of far greater density — places where there is more dark matter. The circles represent galaxies and galaxy clusters, which do indeed show up more in the higher-density areas. “Zooming into the maps, we have measured how dark matter envelops galaxies of different types and how together they evolve over cosmic time,” Chang said in an official press release. “We are eager to use the new data coming in to make much stricter tests of theoretical models.”

As more data becomes available over the next few years, the DES will further improve the scope and resolution of its dark matter maps. But the ultimate goal is to find out more about the accelerating universe, and more specifically, to suss out the nature of the mysterious dark energy that physicists believe is driving that acceleration. Dark energy accounts for a whopping 73% of the “stuff” in the universe, so, yanno, it’s pretty important. Like, Nobel

Prize worthy important. In fact, it’s among the top research questions in 21st century physics.

The tools and techniques the survey will use to do so aren’t limited to gravitational lensing. DES researchers will also study data from certain kinds of supernovae — the most common “standard candles” used to estimate cosmological distances. (Side note: a new paper in theAstrophysical Journal questions whether those standard candle Type 1a supernovae are as uniform as astronomers have assumed, which means the universe might be expanding at a slower rate than previously inferred.) They will also keep track of how many galaxy clusters are detectable by the Dark Energy Camera. Monitoring how that changes over time should shed more light on the ongoing tug-of-war between gravity and dark energy (essentially an anti-gravity).

Finally, the collaboration will study sound waves (a.k.a. baryonic oscillations) to map how the universe is expanding. Sound waves were created hundreds of thousands of years after the big bang that left an imprint in that galaxy distribution. Measure the positions of some 300 million galaxies, and physicists should be able to detect the pattern of that imprint, and use it to make inferences about the history of how the universe has been expanding.

As it happens, the Dark Energy Camera just won Symmetry‘s Physics Madness contest for favorite big physics machine, beating out the heavily favored Large Hadron Collider. Serendipity! Given this lovely new map, and the promise of even better ones to come, I’d say it’s an honor well deserved.About the Author: Jennifer Ouellette is a science writer who loves to indulge her inner geek by finding quirky connections between physics, popular culture, and the world at large. Follow on Twitter@JenLucPiquant.