Growth and inequality in southern America

Note: The charts in this post can be explored interactively and for many more countries here. Source code and data are here.

This post has two parts, a commentary on the charts, and a more technical discussion on the visualization.

Comments:
Recently I posted a chart on the evolution of the economy and social inequality in Argentina. The chart was a reproduction of one made by Alberto Cairo for Brasil, where it was shown that starting on the governments by Lula (in principle more leaned to the left) the country grew and inequality was reduced. The same trend can be seen in the Argentina chart starting from the governments of Kirchner and Fernandez (perhaps even from the interin Duhalde government). From the begining of this exercise my attention was drawn to the point that the trend starts around 2002 for both countries, so I thought it would be interesting to make the same chart for the countries in the region:

Growth and inequality

Here I reduced importance (by lowering color contrast) to presidential periods, so we can focus in the curve trends. As countries have very different sizes, putting them in the same chart is not super-helpful. Let’s try a separate chart for each country (now with more colours):

Small Multiples

I think it can be well appreciated that yes, all the countries of southern south America (the southern cone as we call it in Argentina) have grown economically and lowered inequality from 2002 on. Without entering a discussion on the causes of the trend (which would require a rigorous statistical study and a good theoretical base), there are many interesting details we can see:

  • Chile is the only country that has a clear and constant trend for the whole observed period, even though its Gini coefficient is higher than Uruguay or Argentina (however comparing Ginis between different countries can be tricky, it’s best to compare them when methodologies are the same)
  • Paraguay, Argentina, and Brasil suffered huge swings in the late 90s.
  • Bolivia and Paraguay are much smaller economically, although in the interactive version you can see that actually all of latin america is was smaller than developed countries.

I have the feeling that the charts above do not make the best job at highligting how coupled the countries are. For this purpose, I created a second chart in which I used a single color to distinguish the four combinations of larger or smaller GDP or Gini. The idea of this chart is that when countries change all in the same direction (irrespective of precise direction or size of change) it will look like a solid color block. This is the result:

Direction_english

I am pretty happy with the chart, the joined trend after 2002 is now very evident. I am still lingering about how to include at the same time the size of the change without loosing this strong highlight. It could be very useful, take for instance Chile that has a few bad years between 1998 and 2000, but they are actually way smaller than Argentina’s 2001 crisis–but in this chart they look the same, so bad chart, bad.
In a continuation post we shall study how to include this information as well as presidential periods in this deconstructed Cairo chart.

As before, the source for the data is the World Bank (this table y this table), and presidential periods were extracted from here.

Technical discussion:
Having many countries together in the plot makes it complex to distinguish presidential periods — which is in my opinion what puts the original chart by Alberto Cairo in a different class than a simple connected scatter plot (maybe we can call it a Cairo chart?). In this case I lowered the colour cacophony on purpose to highlight just the direction of the curves, but in doing so I maybe should have distinguished before-after 2002? Perhaps we can plot a simpler variable like left or right leaning government? I would need to catalogue all those governments, though…(you can help in this repository).

Placing the labels in the interactive is a nightmare for which I don’t have time. Literally, I’ve had it in dreams haunting me. The charts here are heavily stylized in Illustrator, but it’s not simple to place labels automatically without putting them on top of interesting things. Map people know this too well.

Perhaps the interactive could be helped by having presidential periods come to the foreground when you hover on top? I mean, not just the label, and reduce the rest?

The multiple scales are a discussion on their own. I left a few of the best options in the interactive. The default version is the one I like the most, but it is certainly a little misleading. It is more accurate to see all curves with the same scale, but it makes it difficult to see the details in each countries trends.

The only important scale option I left behind is an isometric on both axis (same percentage change). The closest I have is the combination of seeing all curves in the same plot, and then using a reference year to see percentage change. Just by coincidence, the x axis changes about 75%, and the y axis a 60%. So, almost there.

The list of presidents I found online is not what you think for some countries like Germany (and others), that have a president (head of state) AND a chouncellor or primer minister (head of government) who is the one holding the actual power. Adding this information is easy if I can get help (and if the World bank has the GDP and Gini data)

Finally, on the direction chart: I’ve been trying small lines under the squares to denote presidents, a colour gradient instead of a single colour for each direction, and little arrows instead of a single colour block. None is too satisfying, but I think it’s worth to keep trying. Ideas?

Inequality and economic growth in Argentina

A small clarification before we start: I am not pro or against the current Argentinian government, and if I had to vote in next sunday’s elections I would not be able to choose a side. The following is not a real political commentary, what I like is data visualization.

Recently I got to read Alberto Cairo’s The Functional Art, and I was strongly attracted to a great infographic about the evolution of the economy and inequality in Brazil. It got me thinking about how would that look for Argentina, so I went and got the data from the World Bank (starting in 1986, and only up to 2013), and reproduced the plot in a very similar style but using the Argentinian data.

Link to the original plot and discussion

My plot:

desigualdadArgentinav3

The chart’s interpretation is that points higher up represent more inequality, while points to the right mean a higher production of economic value. In the words of Alberto Cairo, one of the messages of the chart is that growth in GDP does not always mean a reduction in inequality.

A few technical comments:

Like in the original chart, I used the Gini coefficient to measure inequality. It is far from a perfect indicator, but it is a very popular one. To measure economic growth I decided to use the GDP per capita instead of the total one used in the original chart. I think this would be a little better since the country’s population grew significantly in the three decades spanned by the data.

I respected the original design and separated the presidential terms by colour, which I think is a brilliant decision. It totally makes the plot. There is one caveat though, and it is that each data point measures a whole year and president changes happen at different points during that year. Therefore there might be some leeway in how to put the color (and I did’t figure out an impartial algorithmic way to decide this).

With the risk of ruining the incredible work by Cairo and collaborators, I took the liberty of adding a few labels indicating important economic events (and I also changed fonts, colors, stroke widths, and other small stuff that makes my chart subtly but clearly worse, of course).

Comments on the content:

Like in the original chart, you can see a clear mark or general tendency that is very different for each presidency (including the difference between Menem’s first and second term).

More importantly, beginning in 2003, and coinciding with the Kirchner’s rise to power –just like Lula in Brazil–, the country grows economically and inequality goes down in an unprecedented manner (except for a small glitch under the global economic crisis of 2008). I could not find Gini estimates before 1986, but there are some for the urban area of Buenos Aires and they show that only in 1984, and before that in 1974, there were such low levels of inequality as today.

An important detail: reliability of the source

After a lot of comments by many of the readers in the original (in spanish) post, I caved and gave more hours to this project and included an alternative measure of GDP (alternative to the World Bank, that is).

Why? Well, for those not well versed in Argentinian politics, the current government intervened the official statistics institute, and since then their numbers (which feed the World Bank’s database) have been strongly questioned by many. The World Bank itself recognises that unreliability of the official data from Argentina and puts a disclaimer saying “the World Bank is also using alternative data sources and estimates for the surveillance of macroeconomic developments in Argentina”.

Many people asked me to get an independent source and check the data, so I did. I discovered other things in the middle, like for instance that it is terribly difficult to match different methodologies when measuring GDP. Therefore, I decided that the best (in terms of a compromise between easiness and correctness) was to give the official numbers for 2007 as valid, and then calculate the subsequent years from the relative growth (year to year percentage) measured with this other indicator (called ARKLEMS, it just rolls of of the tongue right?). The data from this analysis is shown in the alternative timeline in gray, which unexpectedly (from the comments), almost lines up with the data from the World Bank.

There are still things that bother me with this: first, I am plotting different things that maybe have no way of being normalized to the same values, and second, and perhaps more important, perhaps this indicates that the adjustment was already taken into account by the World Bank in my original data set (they say they are doing it, but not how). Hopefully this will lead to good conversations and discussions on how to recover the reliability of the INDEC.

New questions:

The evolution in Brazil, the original chart, is strikingly similar to that of Argentina. This makes me wonder how much is the effect of particular presidents (sure there must be some, but still) compared to the global and regional environment. To answer this question I got the full data set from the World Bank and maybe in one or two weeks I’ll get a complete infographic with a comparison (it won’t be easy as I have to rethink the design and maybe even go interactive…)

Note:
All the data comes from the World Bank, from this table and this table, except for the Gini coefficient from 88, 89, and 90, which I found in Gapminder.org. They cite the World Bank as a source but probably they took it from somewhere else. As a side note, Gapminder already let’s you do the comparison between countries of the region, only that there is no presidencial term information. The alternative GDP calculation from 2008 onwards was taken from ARKLEMS, which I adjusted for population growth, and only used the year to year change to estimate the movement of the 2007 World Bank data point.