Every time the statistical authority releases new data there is a surge in economic commentary. Not analysis, but commentary. A thoughtful analysis would usually say that a single new data point doesn’t provide enough information to change anything we thought previously. There’s just too much randomness and error in point estimates to be able to tell much from them. Commentary is different because it creates a narrative and fits the data into that narrative.

A good example is the narrative about double and triple-dips in the UK. Commentators made much of the ONS’ revisions to the GDP series that ‘revised away’ the triple-dip, ‘vindicating Osborne’. The revisions may have eliminated a slight dip in GDP but they didn’t change anyone’s understanding of what had happened in the macroeconomy. That data was important for commentary but not for analysis. In fairness to commentators, distinguishing genuine trends from randomness is not easy. Our eyes are drawn to ‘streaks’, whether in football games or economic time series, even when the series is essentially random. Economists are always looking for techniques to separate the streaks from the randomness. The problem we face is that many of the tools are fairly impenetrable to casual observers and hard to explain.

Edward Tufte has suggested using randomised sparklines to visually distinguish genuine trends from deceptive streaks, so I thought I’d give it a go with the last four years of UK unemployment data. Here is the monthly change in the UK unemployment rate since June 2009: . We think that a recovery has begun so the recent years’ falling unemployment looks good. Now let’s try randomising the values and see if the ‘streak’ disappears. Read more