In this second part we will look at the online interactive visualizations as a companion to the first part’s Atlas of Economic Complexity. It’s interesting that the authors chose the title “Observatory”, as if to convey that with a good (perhaps optical) instrument you can reveal otherwise hidden structure. To repeat one of the fundamental tenets of this Blog: Interactive graphics allow the user to explore data sets and thus to develop a better understanding of the structure and potentially create otherwise inaccessible insights. This is a good example.
The two basic dimensions for exploration of trade data are products and countries. The most recent world trade data is from 2009 and it ranges back between 20 to 50 years (varying by country). I worked with three types of charts: TreeMaps, Stacked Area Charts, and the Product Space network diagram. Let’s start with Germany’s Exports in 2009:
Hovering the cursor over a node highlights it’s details, here “Printing Presses”, a product type where Germany enjoys a high degree of Revealed Comparative Advantage (RCA). (For details on RCA or any other aspects of the product space concept and network diagram, please see the previous post on the Atlas of Economic Complexity.) We can now explore which other countries are exporting printing presses:
While Germany clearly dominates this world market with 55% at $2.7b in 2009 with RCA = 5.6, the time slider at the bottom (with data since 1975) reveals that it has actually held an even bigger lead for most of the last 35 years. For example, with it’s exports in Printing Presses Germany commanded 72% at 3.7b in 2001 with RCA = 6.3 From the timeline one can also see how the United States captured about 20% of this (then much smaller) market for a brief period between 1979 and 1983. During this time its RCA for Printing Presses was just a bit above 1.0 – which shows as a black square in the Product Space – but the United States has since lost this advantage and not seen any significant exports in this product type. Printing Presses being a fairly complex product, only a handful of countries are exporting them, almost all of them European and Japan. There might be an interesting correlation between complexity and inequality, as the capabilities for the production of complex products tend to cluster in a few countries worldwide which then dominate world exports accordingly.
Another powerful instrument are Stacked Area Charts. Here you can see how a country’s Imports or Exports evolve over time, either in terms of absolute value or relative share of product types. For example, let’s look at the last 30 years (1978-2008) of Export data for the United States:
This GIF file (click if not animated) shows several frames. In Value display style one can see the absolute size and how Exports grew roughly 10-fold from about $100b to $1t over the course of those 30 years. The Share display style focuses on relative size, with all Exports always representing 100%. In the Observatory one can hover over any product type and thus highlight that color band to see the evolution of this product type’s Exports over time. In the highlighted example here, we can see how ‘Cereal and Vegetable Oil’ (yellow band) shrank from around 15% in the late seventies to around 5% since the late nineties. ‘Chemicals and Health Related Products’ (purple band) has remained more or less constant around a 10% Export share. ‘Electronics’ bloomed in the mid eighties from less than 10% to 15-20% and stayed on the high end of that range until around the year 2000 before shrinking in the last decade down to about 10%.
As a final example, look at the relative size of imports of the United States over the last 40 years, (1968 – 2008, sorted by final value):
The biggest category is crude petroleum products at the bottom. During the two oil shocks in the seventies the percentage peaked near 30% of all imports. Then it went down and stayed below 10% between 1985 – 2005. Since then it’s percentage has been steadily rising and reached about 15% again. (The data isn’t enough up-to-date to illustrate the impact of the 2008 recession.) Such high expenses are crowding out other categories. When the consumer pays more at the pump there is less to spend for other product types. Another interesting aspect of this last chart is that the bottom two bands represent opposite ends of the product complexity spectrum: Petroleum (brown) on the low end, cars (blue) on the high end.
As always, the real power of interactive visualizations comes from interacting with them. So I encourage you to explore these data at the Observatory of Economic Complexity.
Caveats: I noticed a couple of minor areas which seem to be either incomplete, counter-intuitive, poor design choices or simply implementation bugs. To start, there is no help or documentation of the visualization tool itself. Many of the diagram types on the left are grayed out and it is not always apparent what selection of products, countries or chart type will enable certain subselections. For example, there is a chart type “Predictive Tools” with two subtypes “Density Bars” and “Stepping Stone” that always seem to be grayed out? The same applies to Maps (presumably geographic maps) – all subtypes are grayed out. Perhaps I am missing something – would appreciate any comments if that’s the case.
In the TreeMaps for import and export one can not see the overall value of the overall trade (top-level rectangle) or any of the categories (second-level rectangles). Only the tooltips will show the value of a specific product type or country (third-level rectangle). The color legend is designed for the product space and designates the 34 communities of product types. When you hover the mouse over one product type, say garments (in green), then all imports / exports other than that product type are grayed out. When you show a product import / export chart, however, those same colors are used to designate groups of countries with color indicating continents (blue for Europe, red for the Americas, green for Asia etc.). Yet when you hover over the product icon in the legend (say garment), then only it’s corresponding color’s countries remains highlighted, which doesn’t make sense and can be misleading.
When you play the timeline in a TreeMap, the frequent change in layout can be confusing. A change from one year to the next played back and forth slowly or multiple times can be instructive, but a quick series of too many changes (particularly without seeing the labels) is just confusing.
In the stacked area charts when you click on Build Visualization it always comes up in “Value” style, even if “Share” is selected. To get to the Share style, you have to select Value and then Share again.
TreeMaps and Stacked Area Charts critically depend on the availability of data for all products / countries displayed. For years before 1990 there appear to be pockets of only sparsely available data, which then falsely suggests world market dominance of those products or countries. For example, the TreeMap for Imports in Printing Presses for 1983 shows the United States with 97% taking practically the entire market. In 1984, it’s share shrinks to a more balanced 28% despite growing very rapidly; simply because data for other countries from Europe, Asia etc. seems to not be available prior to 1984. In such cases it would have been better to show the rest as gray rectangle instead of leaving it out (if world import data are available) or just not display any chart for years with grossly incomplete data.
Navigation is somewhat limited. For example, looking at a country chart (say United Kingdom), it would be great to click on any product type (say crude petroleum) and get to a corresponding Stacked Area Chart diagram for that product type. One can do so using the drop-down boxes on the right, but that’s less intuitive.
There are two export formats (PDF and SVG). The vector graphics is a good choice since the fonts can be rendered fine even in the small print. I obtained poor results with PDF, however, as often the texts in TreeMaps were not aligned properly and printed on top of one another.
None of the above is a serious problem or even a showstopper. It would be great, however, if there was a feedback link to provide such info back to the authors and help improve the utility of this observatory.
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