I’m thoroughly enjoying William Deringer’s Calculated Values: Finance, Politics and the Quantitative Age – almost finished. The book asks, why from the early 18th century did argument about numbers, statistics, come to have a special weight in political debate? Often, the growing role of statistics (as in numbers relevant to the state) is seen as part of the general Enlightenment spread of scientific discourse and rationality. Deringer argues that in fact the deployment of numerical calculation about the state of the nation was one of the weapons of choice in the bitter political division between Whigs and Tories. The sphere of public debate was, as he puts it, “uncivil, impolite, sometimes irrational”.
The book presents plentiful evidence of this use of numbers. For instance, pamphlets proliferated about hot issues such as the payment to be made to Scotland for its Union with England, or the balance of trade – and were packed with errors. Printers, and presumably readers, “did not seem to care about getting the numbers right.” They were only there to slug against somebody else’s numbers. Deringer writes (in the context of the fierce debate about the ‘Equivalent’ England should pay Scotland on their Union], “Critics of quantification in the modern era argue that efforts to address political questions through quantitative means often have the effect of foreclosing political controversy by translating substantive political questions into ‘technical’ ones. This was not the case in 1706; if anything, the opposite was true. The Equivalent calculation brought new (technical) questions into public view and revealed their political stakes.”
The book therefore argues that the emergence of partisan politics after the 1688 Revolution was a major reason for the emergence of the political life of numbers. Starting with a more or less blank slate, a good part of the contest was epistemological: what were the right categories and classifications to even begin to measure? What was the right methodology? For example, one innovation was the introduction of discounting future values, something many contemporaries found both hard to understand and unsettling: “It placed almotst no value on anything that happened beyond one human lifetime. This peculaira claim clashed violently with many Britons’ intuition about what the future was worth to them.” It probably still clashes with intuition, to the extent the typical Briton thinks about it.
Of course, one can’t read this history and not think about the notoriously misleading £350m claim on the Brexit bus, or the claim and counter-claim about the likely Brexit effect on UK trade. It isn’t that both sides are equally true or false – far from it – but the political clash is putting statistics centre stage. David Hume was sceptical about the usefulness of the quantitative debate for exactly this reason: “Every man who has ever reasoned on this subject, has always proved his theory, whatever it was, by facts and calculations.” I’m with Deringer in concluding that nevertheless the conversation about numbers is essential.
As Calculated Values concludes, “modern quantitative culture is fundamentally two-sided.” People think numerical evidence has a special, trustworthy status; and at the same time that it’s especially easy to lie with statistics. These are two sides of the same coin. The adversarial debate reveals how useful the numbers and calculations can be to interrogate and test the opposing claims.
Attitudes have shifted over time. In the 19th century, the partisan contest abated. Dickens for one saw numbers as a dry, soulless window on society when he portrayed Mr Gradgrind in Hard Times. The bureacratisation of statistics, and development of official agencies, made statistics seem just a tiny bit dull. Needless to say, they are centre stage again now for reasons of both political conflict and epistemological uncertainty. Once again, some politicians wield numbers without any great concern about their accuracy or meaningfulness; the victory in debate is all that matters. Once again, given the profound changes in the structure of the economy, we can’t be sure what categories and methods will give us the understanding we would like. This is a terrific book for reflecting on contested and uncertain statistical terrain.
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