Nassim Taleb's New Book Explains Why Governments Always Miss Their Own Budget Targets

Nassim Taleb

The question of governments’ ability to meet budget deficit targets is a huge issue in the eurozone right now. The more governments demonstrate that targets can’t be met, the rockier the relationship becomes with international creditors who have agreed to bail them out.

Spain and France, for example, both recently released 2013 budget plans that have been widely criticised by Wall Street and the press.

But there’s a simple mathematical basis for why governments continually miss their deficit targets (and it also could explain why they always seem to be so over-optimistic in general).

Nassim Taleb, the author of Black Swan, explains in the appendix of his upcoming book, Antifragile: Things That Gain From Disorder, where the disconnect comes from.

(The book isn’t actually out until late November, but Taleb posted this appendix, entitled WHERE MOST ECONOMIC MODELS FRAGILIZE AND BLOW PEOPLE UP, on his website today.)

The problem is that the economic data forecasts the government uses to plan its budget around – like where unemployment will be a year from now, for example – are pretty much taken as a given, instead of looked at as mere likelihoods with some given probability.

When the government plans its budget this way, it tends to underestimate the damage when things get worse than they initially expected.

Taleb illustrates how this mistake causes governments to continually underestimate the size of their budget deficits and miss their targets:

Say a government estimates unemployment for the next three years as averaging 9 per cent; it uses its econometric models to issue a forecast balance B of a two-hundred-billion deficit in the local currency. But it misses (like almost everything in economics) that unemployment is a stochastic variable. Employment over a three-year period has fluctuated by 1 per cent on average. We can calculate the effect of the error with the following:

  • Unemployment at 8%, Balance B(8%) = −75 bn (improvement of 125 bn)
  • Unemployment at 9%, Balance B(9%)= −200 bn
  • Unemployment at 10%, Balance B(10%)= −550 bn (worsening of 350 bn)

The concavity bias, or negative convexity bias, from underestimation of the deficit is −112.5 bn, since ½ {B(8%) + B(10%)} = −312 bn, not −200 bn.

In this example, Taleb identified that since unemployment typically varies around 1 per cent, one should take estimates of what happens when it goes 1 per cent lower than expected and when it goes 1 per cent higher than expected.

When the forecaster does that, he or she realises that a rise in unemployment of 1 per cent from the baseline estimate of 9 per cent actually has a much bigger effect on the size of the deficit than a drop of 1 per cent does.

This just goes to show that it’s a lot easier to be wrong on the downside in this type of situation.

Below is a nice chart from Taleb’s book that illustrates the concept:

Antifragile chart

Photo: Nassim Taleb

The upshot of the chart above is that as unemployment increases, it begins to have a larger and larger effect on the government’s budget deficit. This is the very consideration that Taleb believes isn’t being taken to account by government forecaster sand their unlikely budget projections.

Taleb writes, “This is the exact case of the inverse philosopher’s stone,” which sounds like a more polite way of saying that governments have perfected the art of unwarranted over-optimism.

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