Friday Flyer: Economic Forecasting is time travel
Outside it is rather miserable. It is wet, windy and dark. And Blue Monday looms. But at the Institute January is a forecast month, so we are kept warm by the comfortable whirring of economists running models, assessing data, understanding deviations of outcomes from expectations and applying dollops of judgement.
Outside it is rather miserable. It is wet, windy and dark. And Blue Monday looms. But at the Institute January is a forecast month, so we are kept warm by the comfortable whirring of economists running models, assessing data, understanding deviations of outcomes from expectations and applying dollops of judgement. Some of the output will start be brought together over the next few days and we will start to make some sense of what has happened and think about what might happen once the winter is behind us. Even though many of our thoughts may not come to pass, like nightmares or dreams, it is quite necessary to think through the future using a model.
An economic model is a parsimonious and, by definition, imperfect reflection of reality. It might be derived from first principles and respect economic theory. Or it might be a set of relationships that capture observations and derived from empirical observation. The former and the latter are sometimes barely on speaking terms. But however we derive those relationships in a model, they collectively describe our view of how the world works. A forecaster, and perhaps with her judgement, would then crank that model into an unknowable future and traces a number of possible futures: some more likely than others.
The economic forecast is thus is an experiment in time travel not much different from those outlined by H. G. Wells, Ray Bradbury or Douglas Adams. The forecast allows the economist to articulate a future state of the world where each macroeconomic variable is consistent with every other macroeconomic variable. And a good forecaster will articulate a large number of possible states of the world but where each set of macroeconomic variables is consistent with each other. All measureable scenarios will give us our fan chart of possible outcomes. So as well as an artificial universe, the modeller is inventing parallel universes. Think of a set of statements about output, inflation, exchange rates, productivity, unemployment and asset prices which are all consistent with each other in each possible state of the world. Even better if we can incentivise different groups of modellers to articulate their model consistent views of the world, so the genuine uncertainty we have about models and data can be reduced somewhat by more information.
The problem for the evaluation of forecasts arises because from the perspective of today many possible states might obtain tomorrow but when we get to that tomorrow only one state will have obtained. And that will mean that a forecast comprising many states will tend to look as though it is “wrong”. This we know very well and we expect: forecast accuracy does not imply the absence of forecast errors. Although no-one may expect the Spanish Inquisition we expect to be less than perfect forecast accuracy when forecasting and actually welcome that. And there are three broad reasons. First if we collectively use information efficiently all that is left to explain the future is what we do not now know and because we do not now know it, the future will be unknown and a surprise, or what economists call “news”. Secondly, if we use the forecast to plan and set policy in order to minimise the worst expectations that will arise from our forecast, we will change the future. And the forecast will turn out, perhaps thankfully, to have a larger error than initially projected.
Finally, and most importantly, we want to use the forecast errors to understand the news that has accrued since we made our original forecast. Without the forecast, which is what we anticipate, we cannot decompose future outcomes into what was anticipated and what was news. The anticipated part reflects the projection of key inter-relationships in future time. The error from that anticipation or news ought to allow us to understand the economic story behind the forecast error but with a set of stringent side constraints. So if consumption is higher than we expected given our path for income, wages and the supply of funds, we have to construct a story that explains higher consumption but also then does not then fail to explain the subsequent path of income, wages and the supply of loanable funds. The model does not allow completely free thinking, like a crossword the answer must fit the letters of previously identified clues. An economic model does not admit anarchy.
None of Wells, Bradbury or Adams quite got our present, as their future, quite right. Equally forecasters prior to the Great Recession did not either. And they would not have expected to be quite right. But elements of truth are there and those elements are useful. Wells’ vision of a society dominated by the young, Bradbury’s point about small events in the past having large effects in future and Adams’ guide for hitchhikers is really a smartphone. And in some cases it is too early to tell how inaccurate they are and so it is the same with any recent economic forecast.