Conspiracy theorists have a field day whenever official statistics look conveniently better just before elections. Whether statistics are really manipulated for political gain is hopefully less frequent than what they assume. We know it is currently done in Argentina, was done by the Soviets and their allies, and used to be done by some countries to qualify as poor in the United Nations' eyes. Those cases were rather obvious, but how could you recognize the more subtle ones?
Tomasz Michalski and Gilles Stoltz use Benford's Law, the distribution of first digits in economic figures, to determine the likelihood of manipulation across a large set of countries. While this does not catch a country red-handed, it gives probabilities, and one can analyze this against a set of indicators to determine what would drive them to cheat. Michalski and Stoltz find that higher likelihood of cheating is associated with fixed exchange rates, high negative assets, negative current accounts or subject to capital flow reversals. So it seems that this kind of cheating is not for internal consumption, but rather to deceive international financial markets. The authors did the analysis on balance of payments data, though, so the picture may be quite different when looking at unemployment, GDP or inflation data.
Tomasz Michalski and Gilles Stoltz use Benford's Law, the distribution of first digits in economic figures, to determine the likelihood of manipulation across a large set of countries. While this does not catch a country red-handed, it gives probabilities, and one can analyze this against a set of indicators to determine what would drive them to cheat. Michalski and Stoltz find that higher likelihood of cheating is associated with fixed exchange rates, high negative assets, negative current accounts or subject to capital flow reversals. So it seems that this kind of cheating is not for internal consumption, but rather to deceive international financial markets. The authors did the analysis on balance of payments data, though, so the picture may be quite different when looking at unemployment, GDP or inflation data.
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