A 2012 report funded by the Irish Department of the Environment made the astonishing claim that earthworms contribute €723 million annually to the Irish agricultural economy. This figure demonstrates a central thesis of Lorenzo Fioramonti's fascinating new book - statistics can both illuminate and confuse. More importantly numbers can serve purposes far beyond their symbolic value.
Fioramonti argues that the tendency to use numbers to quantify, value and understand our wider social and natural environment, has "been used and abused in governance processes to entrench the power of markets and undermine public debate". The use of statistics doesn't simply reflect underlying economic systems, but actually furthers those interests. Fioramonti looks at how this happens in a number of areas. For instance, he discusses the flawed way that we measure economic well being - GDP. GDP reflects market transactions, but ignores whole areas of the economy - housework, pollution or natural resources.
He also shows how the use of statistics by those who want to rubbish global warming science has led in turn, to some scientists, being accused of misrepresenting their own data. Far more problematic though, are the attempts to mitigate climate change, by creating enormous emissions trading schemes that rely on the free market, yet fail to challenge the real causes of rising carbon emissions.
Take approaches to preventing environmental disaster. As I write this, the question of floods has been a major political issue in the UK. Government cuts to environmental defence measures have helped reduce the ability of whole areas to deal with heavy rainfall. Such cuts are irrational, some say, because for every £1 spent on flood defences, £8 will be saved.
This approach is not new. The 1936 US Flood Control Act introduced such cost-benefit analyses "by stating that no flood-control programme would receive federal funding unless it was proved that its benefits would exceed its costs." Such proofs might be hard to achieve and politicians that make their decisions based on such calculations can find themselves in knee-high water.
Nonetheless such sums might have value if they are done in the interest of society in general. But when those totting up the figures are themselves interested in making money, then the outcomes themselves can become distorted. Cost benefit analysis might have started out as a way of trying to make sure that "public infrastructure projects were transformed 'from a collection of local bureaucratic practices into a set of rationalised economic principles'." But it ended up meaning that
"practices of environmental audit, value for money audit, management audit, forensic audit, data audit, intellectual property audit...[etc]... acquired a degree of institutional stability and acceptance."
Nowhere is this clearer than in the behaviour of Credit Ratings Agencies. These are private bodies that make their profits by assigning a value to a company (or country's) credit. These ratings are of enormous importance to organisations, which naturally have a vested interest in improving them. This leads to dodgy dealings and dodgy figures (famously the CRAs considered Lehman Brothers a safe investment until the moment it went belly up).More worryingly it allows CRAs to have enormous power. The downgrading of the US credit rating in 2011, in the words of one CRA analyst
"reflects our view that the effectiveness, stability and predictability of American policy making and political institutions have weakened at a time of ongoing fiscal and economic challenges".
In other words an unaccountable and unelected CRA was able to take a political position which in turn had enormous consequences. The downgrading of countries like Greece, Ireland and Portugal caused misery for millions of people. It has also helped further the agenda of those who stand to gain from privatisation and the opening up of economies to the ravages of neo-liberalism.
It is extremely difficult to choose which parts of this fascinating book to discuss in this review. The chapters that deal with the commodisation of nature, and attempts to deal with pollution through the introduction of market mechanisms are notable in the way they expose the irrationality of these numerical approaches, but also the ineffectual nature of this sort of economic thinking.
Fioramonti says that "numbers do not possess any intrinsic normative value, their power is derived from the capacity to reduce complexity to a few observable facts." But he points out that when "numerical reasoning" is used to try and understand society, it produces all sorts of simplicities and confusions. In particular, "the complexity of social relations is lost through the cracks of mathematical algorithms".
The final section, which discusses how statistical analysis has distorted aid programmes and developmental work, shows this particularly clearly. Those charities, NGOs or philanthropists looking for simple casual situations, where money can be thrown at one thing to solve another, frequently find that the situation is far more complex. It also leads to quite warped thinking. I was particularly saddened by some economic gurus at MIT who asserted that "the stress of living on less than 99 cents per day encourages the poor to make questionable decisions that feed - not fight - poverty." In other words, it is the poor that causes poverty, rather than a system based on the rich getting richer at the expense of the majority.
Fioramonti's book is not an anti-capitalist manifesto, but it is a superb explanation of how the current economic setup uses numbers for its own ends, not as a way to improve things. As Lorezo Fioramonti concludes, "statistics tend to separate complex phenomena in measurable units, they hide the interconnectedness between systemic poverty, economic imbalances and uneven access to resources... the risk is to end up with results that distort reality and mislead policies."
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