Data and prediction
Via Scott Sumner we saw the following article that mentions economic data and economic predictions. The statements that stood out to me were:
(Economic) predictions are, of course, the bread and butter of economic institutions. But can we believe them?
In recent years, some economists have begun to express doubts over predictions made from huge volumes of data, but they are in the minority. Most embrace the idea that more measurements mean better predictive abilities.
Hold up.
For one, as we have mentioned prediction is not the central element of what economists do – and even when they do predict the goal of such prediction is to give some view regarding risks and movements, not direct figures (it is more ordinal than cardinal in some sense).
Secondly, ever since the Lucas critique economists have been very nervous about predictions from large amounts of data without theory – I would say that the majority of economists doubt the usefulness of econometric models relying solely on huge amounts of data.
Economists would like data with less measurement error, that is closer to representing the true economic variables we discuss in theory – we aren’t looking for an infinite number of measures we can stick together to find a result. An economist that doesn’t use theory to inform their discussions of the economic outlook, but uses lots of data, isn’t an economist – that is all.