Converging Europe- what the numbers say

Numbers, numbers, numbers…

the more I read newspapers (online and offline), whatever country the specific newspaper is coming from, the more I keep thinking: are we confusing data analysis with data collection?

It is a general trend, but within the scope of this article I will focus just on European Union.

What can say publicly available data to any ordinary citizen about our progress moving from a simple economic treaty with political undertones (the Treaty of Rome), to a different kind of union?

No, not a “United States of Europe”, but something different, as our shared past in Europe is sensibly more complex than the past that between the XVII and XVIII century was shared in what an old English friend (or acquaintance- depends if you consider intensity or duration) used to call “the former colonies”.

My American friends used to remind me that the USA are actually a continental state, and, within the country, each member of the Union is often “clustered” with other members that share one or more characteristics- therefore, the “rust belt” states had more in common with each other than with, say, Delaware or Nevada- and they did not expect to ever converge.

Ask most ordinary citizens around Europe- and they do expect such a convergence to eventually occur: maybe it is just a communication issue, or maybe we have yet to understand what this “convergence” means or implies (also if routinely calls for a EU-wide welfare or taxation system reinforce this expectation).

I said “ordinary citizen”, but I should obviously remind that when, as a teenager, I had plenty of time available to think, I spent quite of bit of it on European integration issues, up to the mid-1980s.

Thereafter, I kept following European integration issues, but my work required to shift the development of my analytical skills first from the qualitative to the quantitative, and then alternating both number crunching and (trying) to understand what made organizations “tick”.

While I began refocusing when I first published this blog, in February 2009, over the last few months I started doing an almost daily exercise.

Aim? To share few ideas derived from my experience and observations, complemented by a daily run through the news across few countries (online only when I have time to format my selection of articles TAD).

By chance, not by design, 2011 overlapped with the expansion of two “fault lines”, Northern Africa and the Euro, and other events that could have longer-term effects.

This article is split in 7 short sections- if you want, jump to the conclusions, and then backtrack.

As usual, any comment is welcome.

1. Start with a dream…

I think that most would accept that the design of a unified Europe had an idealistic streak.

It was partially a side-effect of two increasingly destructive wars fought on European soil, wars that basically resulted in Europe losing the political pre-eminence that it had for few centuries (say, from the Renaissance), with the ancillary loss of empires, and their relatively controllable and relatively cheap provision of labour and natural resources.

In the 1950s, we had to start looking at how we would be able to sustain our way of life, for ourselves and future generations.

I gave an inward-looking bent to the “European dream”: because from an historical perspective most of our shared home was built thinking about Europeans and a new world role for Europe, notably after the end of the Cold War.

We are different from the USA, as we are coming from a long history of rivalries and empire-building exercises (probably started even before the end of the West half of the Roman empire).

My main question is simple: is Europe converging, creating a future homogeneous economy, or is Europe becoming like any other continental country, with more developed and less developed areas?

2. Get the numbers…

Before mid-1990s, accessing data and statistics usually required a trip to your local library, and also newspapers were giving limited quantitative information (i.e. numbers) to support their analysis.

Since the democratization of the Internet, or, better, universal access to its content with the World Wide Web, you can find more statistical information than you will ever need- and, even more than in the past, anybody can go online and see how a selective use of the appropriate numbers can lend “objectivity” to any assertion.

What are numbers good for, if you do not have a starting point, i.e. the reason “why” you are looking for numbers?

Let’s assume that still holds true the principle outlined by the European Court of Justice long ago- practically: getting inside the European Union changes a country to such an extent, that it becomes impractical to leave it.

I will use some numbers, but I will avoid the usual quantitative orientation (e. the level of integration, as represented by the internal trade).

Instead, I will adopt my ordinary citizen perspective: what can we expect from the EU? What do the numbers tell us about the current state of our integration, and the future development of its members?

3. Guiding the data selection

The first point is selecting the sources: I heard plenty of talking heads focusing on just one source, and building theories out of that.

I know that some sources are “circular” (i.e. A uses B as a source, that in turn uses C, which, surprise, surprise, uses A).

And I already suggested long ago in this blog to read a short but interesting book on how to “vet” data- before assuming that you have information.

Time is scarce, and I wanted to select sources that any ordinary citizen could have access to- therefore, I went for ILO, IMF, OECD, and Transparency International.

From each source, I selected some data that I assumed as re-verified by each source, i.e. ILO for employment and demographic data, IMF for information on financial flows, OECD on development and industrial production, and Transparency International on corruption, avoiding data that is not “atomic”, i.e. data that is filtered by an interpretation model (therefore, I removed all the famous indexes, except the corruption index).

My focus? Something that could have side-effects beyond the next election.

4. Selecting a perspective

But beside the data, I have also to select the focus of the analysis: and I chose te so-called PIIGS countries (Portugal, Ireland, Italy, Greece, Spain) and the two “engines” of the European Union, France and Germany.

Let’s assume that I still think that Europe should probably be different, and create a different kind of continental political entity where harmonizing laws and regulations isn’t enough.

As an example, I wrote already before about the “attractor” role that the scattering of specialized agencies by industry or trade already done in Europe could do in creating “research hubs” or at least “educational poles”, improving the use of scarce economic resources by allowing companies to access talent in their own district.

With the current and foreseeable technology, there is no reason why a multinational company operating in Europe should keep everything in a single country- if we share the same legal framework and at least part of the taxation framework, it will gradually make more sense to scatter business units across the European Union, setting each one where the balance between efficiency and efficacy is optimal.

So, after this disclosure (my “bias”), I will discuss few indicators that I used to compare the countries within my model.

As a preview, I published on Facebook a first chart: everyone is focusing on the current unemployment figures, and making an indirect association with the 2008 crisis, the Euro crisis, etc.

Instead, if you just look at the data, you can see something interesting: unemployment figures started to diverge significantly at least since mid-2007.

But, as any ordinary citizen, I am more interested about the future than the past.

5. Comparing the future

Recently I attended a conference, where the discussion was focused on competitiveness (as defined by the World Economic Forum), while the underlining data was inferred from the competitiveness index- and not the other way around.

I would like to consider something more down to earth, concerning both the citizens, and the attractiveness of each country to potential investors.

My concept? Quite simple.

Each country within the sample (PIIGS, France, Germany) is a developed country member of the OECD: its business attractiveness is defined by something more than cheap labour and tax credits.

A mix of what used to be called the “human capital”, and the economic environment created by rules and regulations, along with the commitment by citizens (including industrialists) to their own country and the development of its economy.

I selected few indicators (using the most recent confirmed data- I am looking long-term, not on current issues- otherwise, I would have used the same year as a reference for each indicator):

corruption index
it affects the ability of the State to finance infrastructure, both human, e.g. R&D, and physical, while discouraging citizens and businesses, by distorting competition and access to information and services source: Transparency International 2009
unemployment, youth’s unemployment, unemployment age bias
while unemployment maybe linked to other issues, the “age bias”, i.e. when youth’s unemployment is significantly higher, is an indicator of a potential longer-term issue (some countries have a significant bias; the lower the values, the better)source: ILO, update 2011, data for 2010
fertility rate
it is partially a side-effect of the previous one (confidence in their own future), but also an indicator of the economic model (few EU countries are above the replacement rate, i.e. the number of children required to keep the population at the current level) source: OECD, update 2010, data for 2009
GDP growth
albeit it is true that, with the current low levels in most of the countries considered, it could be simply “improved” short-term by creative accounting, it is still an indicator of the ability of a country to sustain its own development (I am critical about those suggesting that contracting our GDP growth is just a matter of choice) source: IMF 2011, data for 2010
public debt as per Maastricht
the national public debt as a percentage of nominal GDP (the lower, the better) source: Eurostat via OECD 2010, data for 2009
exports on GDP and imports on GDP (% change on the previous year)
if a country imports more than it exports… even more relevant, now that countries within the EUR cannot use competitive devaluationsource: IMF 2010, data for 2009
FDI inflows and FDI outflows, as % of the EU27
not just the attractiveness for foreigners (FDI stands for foreign direct investment), but also the willingness of local citizens and industrialist to reinvest in the future of their own country (instead of investing elsewhere) source: OECD 2010, data for 2008

6. Do not compare apples and pears

Yes, you can build indicators on anything- and more than once, in my business activities, I had to review business and marketing plans that were using data that had no correlation whatsoever, and trying to present (of course) a “tremendous business opportunity”.

Frankly, sometimes it was quite tough to keep a straight face: amazing how many people take figures for grant, without asking some basic questions.

Thinking about the future, I wanted to include also the (mis)use of EU funding: partially covered by the corruption index, but also a more precise indicator of the willingness to invest in the future.

After reading this article reporting 5bln in frauds in Italy (50% of the EU frauds) I went for the source, OLAF, and while still significant (e.g. the role of organized crime), the matter is more nuanced and complex: if interested, read the statistical annex on the OLAF website: building a single indicator would imply mixing (statistical) apples and pears…

Therefore, it is not only because I hold an Italian passport that I decided to remove this additional indicator, and to replace it with the “corruption index” from transparency international (that, incidentally, pushes both Italy and Greece to the bottom of the sample, while listing both Germany and Ireland as the least corrupted).

As for the article about Italy: I waited first for the results of the elections, and today is a national holiday- therefore, I will post my comments on the current status, also considering the data reported in the article linked above.

And now, the (visual) conclusions.

7. Conclusions

Information overflow? Well, I just wanted to identify few forward-looking indicators (thinking beyond the next election cycle), and then compare the “shape” of the economy of the countries involved.

I already wrote in the past that I like using a visual approach to compare apparently complex phenomena- and therefore I simply considered the data:

  1. 11 indicators, using values that are relative within each country
  2. 7 countries (i.e. the best has 7, the worst 1, on each indicator)
  3. question 1: is there a single country that is “the” reference model?
  4. question 2: are countries converging, i.e. moving toward a similar “visual shape”?

Therefore, I produced this chart: the closer to the external border, the better a country is positioned vs. the other countries.

I did not apply any transformation to the data- simply, I assigned a value from 7 (=best) to 1 (=worst), clustering on a single value countries that, on a specific indicator, had close values.

As you can easily see from this chart… Germany, as expected, is a country that more often than not is the best in class- but I must admit that I was surprised to see that, after France, Spain is the second recipient of FDI, even before Germany, and quite a distance from the fourth (Italy).

Of course- my ignorance.

Thinking about the future… Ireland and France seem to be better than I expected.

Considerations? Plenty. But, as I said at the beginning… I wanted just to share something more structured than my usual TAD links to interesting articles.

And if you are curious about the data… let me know.

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