Guest Post by TUSHAR DHARA

In May this year the investment banking powerhouse Goldman Sachs released a report that predicted Brazil would win the FIFA world cup. The prediction relied on statistical modelling and used tools like “Regression Analysis”, “Poisson Distribution”, “Stochastic model” and “Monte Carlo Simulation”. In other words, the methodology is incomprehensible to anyone except those with an advanced degree in Statistics or Econometrics. In hindsight, the prediction looks silly, given the 7-1 score line in the semi-final match between Germany and Brazil. However, the report is a perfect example of the failures of modern economics, particularly the financial voodoo economics pushed by the likes of Goldman Sachs.

When “The World Cup and Economics 2014” was released on May 27 it gained a lot of press publicity globally. The report predicted that Spain would reach the semi-final stage and lose to Argentina, which would lose to Brazil in the final. Goldman’s research division analyzed reams of data, including about 14,000 matches since 1960, national teams’ Elo rankings, average goals scored per team, home country and home continent advantage. To be sure, the report states that the predictions are just “probabilities” of teams advancing. Still the report states, “The most striking aspect of our model is how heavily it favours Brazil to win the World Cup”, and, “the extent of the Brazilian advantage in our model is nevertheless striking.”

The report also blends economic commentary with football. The 32 teams that participated in the world cup feature countries from the BRICS (Brazil and Russia), Northern Europe (Germany, Netherlands), PIGS (Portugal, Italy, Greece, Spain), South America (Argentina, Colombia, Uruguay), North America (Mexico, USA) and Africa (Nigeria, Cameroon, Algeria). To round out the report India and China are thrown in under the section “When will China and India Play in a World Cup Final?” What could be a better opportunity for Goldman than using the beautiful game to comment on national economies?

The report is a perfect example of how financial economics is practiced in the real world. Take a bunch of assumptions, build a complex statistical model around these assumptions with a lot of jargon and numbers thrown in, add a few disclaimers and use your brand name and “credibility” with investors to aggressively market your products. In fact, this is the paradigm under which neoclassical economics, the dominant philosophy of the last 4 decades, has operated. It has also been responsible for growing inequality and economic crises, including the 1997 Asian financial crisis, the 2001 dotcom bust and the 2008 financial meltdown.

The economic climate before 2008 was strongly in favour of “free markets”, “minimum government”, “trickle down” and the “invisible hand”. Elaborate statistical models of financial markets with lots of assumptions legitimized financial chicanery. They usually involved so many numbers and equations that critiquing them required a degree in maths and statistics. At the same time deregulation of markets led to a move towards the “financialization of everything”. Everything was up for sale: home loans, subprime mortgages, pensions, commodities, football.

It ended in the 2008 financial crash, when a tremor in the subprime market in the USA spread rapidly through the interconnected global financial system and brought down several countries. Much of the world is still grappling with the after effects. Unemployment remains strong and growth remains weak in several nations. Global inequality has widened.

Even as Wall Street’s top financial firms pushed dodgy financial products onto each other in a deregulated market and overleveraged themselves, American tax payers had to pay the tab to stabilize the financial system. Meanwhile, profits and sales are back to pre-crisis levels at Wall Street and no big names have been prosecuted for their role in the crisis.

The theories that led to the crash were full of assumptions that do not hold up in real life, similar to Goldman’s football report. For instance, it is assumed by mainstream economics that “free markets” will lead to prosperity. In a country like India this doesn’t take into account social and political realities. Inequality, oppression, illiteracy and caste and kinship networks distort the “free market” and lead to different outcomes. But why let ugly reality get in the way of a beautifully constructed model!

Similarly, The World Cup and Economics 2014 report says the model does not use any information on the quality of teams or individual players. “For example, if a key player who was responsible for a team’s recent successes is injured, this will have no bearing on our predictions,” the report says. This statement now looks ridiculous, given Brazilian player Neymar’s injury to the outcome of the Brazil-Germany game. By operating on assumptions and disregarding extreme swings the report dismisses the possibility of real life occurrences influencing the outcome. Exactly what the pre-2008 economic models did.

The widely used and criticized Black-Scholes model helps in pricing financial securities and led to an explosion in the trading of options. Yet its assumption about the swing in the prices of securities isn’t borne out under real life conditions. Similarly, a 7-1 World Cup score line was considered such a chance occurrence that the possibility of it happening was dismissed, just like the 2008 crash was missed by mainstream economics because it fell outside the bounds of the economic models.

As the Wall Street Journal put it, Paul the psychic octopus had a better rate of predicting match winners than Goldman Sachs. Yet, when Goldman Sachs speaks (or in this case, writes), investors listen to the “most profitable firm in Wall Street”.

Tushar Dhara is a former economics journalist who works with rural communities in Rajasthan at the School for Democracy/Loktantrashala