Egypt's forward Mohamed Salah training in Saint Petersburg during the Russia 2018 World Cup. Christophe Simon / AFP
Egypt's forward Mohamed Salah training in Saint Petersburg during the Russia 2018 World Cup. Christophe Simon / AFP

Football could be the great equaliser when it comes to the wealth of nations



Even for those of us who are not football fans, the World Cup in Russia offers significant points of interest. These chiefly revolve around economic theory and prompt some penetrating questions.

Why have the world’s two biggest economies – the US and China – consistently been so bad at men’s football? Is excellence in football – an inexpensive sport compared to swimming or skiing – entirely unconnected then to a country’s gross domestic product? Why have the world’s two most populous countries – India and China – failed even to qualify for the World Cup finals? Do abundant human resources not translate into competitive football teams? And finally, is it possible for a country to become a football superpower in three decades, as China set out to do in 2016?

Economists seem increasingly minded to address these and other questions. In fact, sports economics is a fast-growing area with its own field journal for the simple reason that the economics of spectator sport is both enormously important and because sports markets provide natural opportunities to test incentives, labour market behaviour, game theory and a great deal more.

Which brings us to the newest economic conundrum being addressed right now with respect to world football. It deals with a hoary theory, the convergence debate, or whether poorer countries are catching up with richer ones. That’s a well-worn subject but its application to international football provides fascinating insights into the role of globalisation, information technology and directly transferable human skills in a slow but steady convergence.

This might seem odd considering Europe and South America continue to dominate the international game, Asia doesn’t even get a look in and Brazilian player Pele’s prediction that an African nation would win the World Cup before the year 2000 might not come true even in 2018. But in the working paper they put out some months before this World Cup, economists Stefan Szymanski and Melanie Krause made a plausible case.

Using data from more than 25,000 games played by national football teams between 1950 and 2014, Szymanski and Krause attempted to discern convergence in performance as measured either by win percentages or goal difference. They found “clear evidence of unconditional convergence” and went on to argue “that transfer of technologies, skills and best practices fosters this catch-up process”, if only up to a point.

This is heartening because competitive international football is, as the paper says, “the epitome of competition and globalisation”. Just like the manufacturing industry, which is more generally used to test the theory of economic convergence, football is, the paper says, “a truly global activity”.

With 211 members, football’s world governing body Fifa has more affiliates than the 193-strong United Nations. World football has standardised rules, generates lots of data (roughly 2,000 games per year) and its global nature allows for the constant transfer of technology, skills and human capital.

What’s more, international football has regional institutional frameworks (Uefa in Europe, Caf in Africa), which roughly mimic trade blocs. Accordingly, football should offer us a way to assess the changes being wrought in our interconnected world. Are they for good or ill?

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Read more from Rashmee Roshan Lall:

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Szymanski, professor of sport management at the University of Michigan and Krause, from Hamburg University, say their findings point to an overall good from the globalisation of football and “a clear decrease in performance inequality”.

The study is notable because it is the first to find unconditional convergence in any sector other than manufacturing. It also seems to illustrate by means of real data the basic logic of connecting across borders, which is to say direct skills transfer and the​ creati​on of cross-cultural linkages.

The benefits of a Mohamed Salah, who links the Nile and the Mersey and represents the internationalisation of talent, cannot be precisely computed but are very real nonetheless. They come in terms of providing children in the Nile Delta region with a powerful role model and in giving young Britons a quite different idea of an observant Muslim than generally available in an era of rising Islamophobia. 

There is only one point at which the economists’ study gives pause for thought. Football performance, they say, will continue to converge because of the transfer of best practices from abroad but there will come a moment​ countries have to “build up their own long-term talent development techniques and playing styles”.

This has obvious lessons for countries like China, which is trying to build a football culture. In football, as in economics it seems, the mindset of those on the field makes all the difference.

QUALIFYING RESULTS

1. Max Verstappen, Netherlands, Red Bull Racing Honda, 1 minute, 35.246 seconds.
2. Valtteri Bottas, Finland, Mercedes, 1:35.271.
3. Lewis Hamilton, Great Britain, Mercedes, 1:35.332.
4. Lando Norris, Great Britain, McLaren Renault, 1:35.497.
5. Alexander Albon, Thailand, Red Bull Racing Honda, 1:35.571.
6. Carlos Sainz Jr, Spain, McLaren Renault, 1:35.815.
7. Daniil Kvyat, Russia, Scuderia Toro Rosso Honda, 1:35.963.
8. Lance Stroll, Canada, Racing Point BWT Mercedes, 1:36.046.
9. Charles Leclerc, Monaco, Ferrari, 1:36.065.
10. Pierre Gasly, France, Scuderia Toro Rosso Honda, 1:36.242.

Eliminated after second session

11. Esteban Ocon, France, Renault, 1:36.359.
12. Daniel Ricciardo, Australia, Renault, 1:36.406.
13. Sebastian Vettel, Germany, Ferrari, 1:36.631.
14. Antonio Giovinazzi, Italy, Alfa Romeo Racing Ferrari, 1:38.248.

Eliminated after first session

15. Antonio Giovinazzi, Italy, Alfa Romeo Racing Ferrari, 1:37.075.
16. Kimi Raikkonen, Finland, Alfa Romeo Racing Ferrari, 1:37.555.
17. Kevin Magnussen, Denmark, Haas Ferrari, 1:37.863.
18. George Russell, Great Britain, Williams Mercedes, 1:38.045.
19. Pietro Fittipaldi, Brazil, Haas Ferrari, 1:38.173.
20. Nicholas Latifi, Canada, Williams Mercedes, 1:38.443.

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