… economic forecasting, has died.
… Granger realised that not all long-term associations between non-stationary time series are nonsense. Suppose, as the American academic Kevin D Hoover explained, that the randomly-walking drunk has a faithful (and sober) friend who follows him down the street from a safe distance to make sure he does not injure himself.
“Because he is following the drunk, the friend, viewed in isolation, also appears to follow a random walk, yet his path is not aimless; it is largely predictable, conditional on knowing where the drunk is,” Hoover noted. Granger and Engle coined the term “co-integration” to describe the genuine relationship between two non-stationary time series. Time series are “co-integrated” when the difference between them is itself stationary – the friend never gets too far away from the drunk, but, on average, stays a constant distance behind.
Granger’s discovery had an enormous impact, leading, as one of his students put it, to “chaos for a few years”. In order to forecast non-stationary variables, new techniques had to be developed to replace the ones Granger had debunked. …
Granger once wrote: “A teacher told my mother that ‘I would never become successful’, which illustrates the difficulty of long-run forecasting on inadequate data.”