The political choices behind 'hard figures'
Vidi laureate Daniel Mügge is researching why government authorities prefer certain economic measurement formulas to others
Ostensibly, a simple glance at key figures on inflation and unemployment would seem an easy way to see how a country is faring. But what do such figures really tell us, and how are they derived? Politicologist Daniel Mügge received a Vidi grant for his research into the political choices behind the figures.
Key figures on areas such as inflation and unemployment appear very truthful and objective, says Mügge, but fundamentally they are not. After all, the way in which such figures are derived is decided by the people who compile them and determine the underlying mathematical formulas.
Political prices
'The Gross National Product (GNP) is a good example. What do you choose to include in that calculation and what do you choose to leave out? The calculation doesn't factor in unpaid work such as housework or informal care, for example, whereas these activities certainly involve an undertaking that generates a product. And what do you do with the public sector, with activities such as government services and education? Prices in education, such as the tuition fees a student pays, are currently determined by politics, so you can't use them to calculate education’s contribution to the GNP. Instead, that price has been fixed at the cost of education. This calculation can lead to a massive overestimation (for example, because the overhead costs are sky high) or, conversely, to an underestimate. Some years ago, the UK decided to adjust the equation it uses to value public services – causing a prompt drop in the GNP on paper.’
Military production as revenue or cost?
There are many more examples. In the US budget, military production is
counted as production, while in European countries it is a government
expenditure – in other words, a cost. Another example: a country's informal
economy is often not included in the calculation – in the Netherlands this
accounts for 10% of the total economy, but in developing countries its can
easily be as much as 40%. ‘So if you ask the question, “How big is the Nigerian
economy?” and you don't count the informal economy, the result will be a very
low figure – and it's debatable whether that's justified.’
Closer to home, there is the method used to calculate the Dutch figure for
inflation. Traditionally, this has been based on the price calculation of a
shopping trolley filled with a number of standard products. The price of
property is therefore not included. ‘Had we included it, we would have seen the
property bubble coming much earlier than we did, because our inflation figures
would have been considerably higher. But what actually happened is that we were
saying, to put it bluntly, “well, the price of apples and bread hasn’t changed,
so everything must be fine”.’
Political motives
What difference does it make, having all these various calculations? ‘They
have policy implications – governments make plans and design interventions based
on these figures. That's why I am keen to study how and why certain choices are
made to calculate figures in a particular way.’
To do this, the first subproject in Mügge’s study compares four countries:
Germany, Great Britain, France and the United States. Focusing on four economic
key figures (economic growth, inflation, unemployment, budget deficit), he is
examining what is and is not included in the calculation of that figure. The
next step will be to find out how these figures were derived and which players
influence(d) the underlying formulas.
The second subproject, being carried out by a doctoral student, focuses on the
top-down approach applied by the Organisation for Economic Cooperation and
Development (OECD) and the European Union. ‘They want to make data from
countries comparable. This raises questions such as: What exactly is the
motivation for doing this? Which standard do they choose to apply? And what are
the consequences for various countries if this standard is chosen?’
Painting a rosy picture
In the third and last subproject, Mügge is using the findings of the first
subproject to test hypotheses that operate across the breadth of the OECD. For
instance, is it really true that the power of a trade union influences how the
unemployment figure is calculated? If countries have a huge military or
financial sector, are they more likely to paint an overly rosy picture of their
wealth? And how great is the influence of producers and service providers
themselves on these figures?
Mügge is chiefly interested in using his research to expose the political nature
of so-called ‘hard figures’ – not only for the general public, but also for
policymakers and his fellow academics. ‘I wouldn't go as far as to say it's all
a lie, but I do want to make it clear that these figures are based on political
choices – that they are the result of a socio-political negotiation process. We
must not lose sight of that political component if we are going to draw such
far-reaching conclusions as we currently do.’