Can national statistics be self-fulfilling?
John Kemp has a timely reminder, in the wake of the news that the UK is now back in recession after posting a -0.2% GDP figure:
Modern societies have made a fetish of official statistics, particularly the national income and production accounting (NIPA) system developed by Nobel Laureates Simon Kuznets and Richard Stone during the 1930s and 1940s.
NIPAs, especially the top-line figure for gross domestic product (GDP), as well as monthly employment data such as U.S. nonfarm payrolls, have become the arbiters of economic policy and the success and failure of politicians.
In a strange way, Britain’s ONS, and similar agencies like the Bureau of Labor Statistics (BLS) and Bureau of Economic Analysis (BEA) in the United States, hold the fate of politicians in their hands because they help write the political narrative.
It is only a slight exaggeration to say BEA is one of the most powerful agencies in the U.S. government. It may not have as many tanks as the Pentagon, but by measuring the success and failure of economic policies, it can make and break presidencies, as President George H W Bush could confirm and Barack Obama fears.
As Kemp points out, it’s silly to imagine that the UK’s Office for National Statistics can measure the entire economic output of the United Kingdom between January and March, hone it to within a single decimal point, and release an accurate figure before April’s even out.
But I do wonder about all those studies tying election results to various economic statistics like GDP growth or the unemployment rate. To what degree are voters responding to economic activity and joblessness, and to what degree are they responding to statistics? On an individual level, of course, no one has the kind of direct sensitivity to national economic growth which would make vote one way if it was low and another way if it was high. That’s why we need statistical offices. Still, in aggregate, it’s plausible to believe that the population as a whole will be happier, and more well-disposed towards incumbents, when the economy is growing and unemployment is low.
Certainly there’s a very strong way in which national statistics — rather than the underlying economy — drive the national conversation, especially in an election year: Jim Surowiecki’s column in this week’s New Yorker is a prime example. And the strongest word of all is “recession”: it’s incredibly hard for a politician to win an election so long as her opponent can correctly say that she has driven the economy into a recession.
That’s the real reason why there was so much anger when the ONS released its first-quater GDP statistic in the UK: the fact that everybody now knows (or thinks that they know) that the economy is back in recession is itself going to slow down the pace of economic activity in the second quarter.
None of which is to say that national statistical agencies are a bad thing, or that they shouldn’t release their data as efficiently and quickly as they can. It’s just to say that, in good Heisenbergian fashion, they affect the economy just by observing it. It’s even possible that all those lies told by the Argentine statistics office were more than just spin, and actually helped the real economy, somehow. Not that I’d ever recommend such a course of action.