Big data forecasting and the conundrum of unknown unknowns

19 Feb, 2014 at 17:54 | Posted in Economics | 1 Comment

Short-term weather forecasting is possible because most of the factors that determine tomorrow’s weather are, in a sense, already there … But when you look further ahead you encounter the intractable problem that, in non-linear systems, small changes in initial conditions can lead to cumulatively larger and larger changes in outcomes over time. In these circumstances imperfect knowledge may be no more useful than no knowledge at all.

Much the same is true in economics and business. What gross domestic product will be tomorrow is, like tomorrow’s rain or the 1987 hurricane, more or less already there: tomorrow’s output is already in production, tomorrow’s sales are already on the shelves, tomorrow’s business appointments already made. Big data will help us analyse this. We will know more accurately and more quickly what GDP is, we will be more successful in predicting output in the next quarter, and our estimates will be subject to fewer revisions …

Big data can help us understand the past and the present but it can help us understand the future only to the extent that the future is, in some relevant way, contained in the present. That requires a constancy of underlying structure that is true of some physical processes but can never be true of a world that contains Hitler and Napoleon, Henry Ford and Steve Jobs; a world in which important decisions or discoveries are made by processes that are inherently unpredictable and not susceptible to quantitative description.

John Kay