Outside of more understandable factors like this, we have also seen statistical agencies such as the ONS and US Bureau of Labor Statistics (BLS), reporting issues regarding the inherent quality of their data. Just this week, the ONS announced that the July retail sales data will be delayed from publication until early September.
Although there was no indication of the reason, we’ve certainly seen that many economic data series have experienced material declines in the number of survey respondents where the survey data is used to infer the equivalent statistics at the national level. In the US, the commonly followed JOLTS data (Job Openings and Labor Turnover Statistics) is particularly poor, with response rates moving from around 60% in 2015 to roughly 30% today. Clearly, as we approach these levels of response rates, it is prudent to reduce our confidence in the numbers.
If the statistical quirks weren’t enough, there’s also been speculation about political interference with economic data in the US. This culminated in President Trump firing the BLS commissioner after claiming the data was ‘RIGGED’. It’s unlikely that President Trump would be calling for BLS staffers to literally change the numbers to support his desired outcomes, but political views can certainly drive changes in calculation methodology, which could lead to more subtle shifts in data.
Ultimately, while the minutiae of how these economic data points are calculated can seem irrelevant, each of the factors highlighted has the potential to increase volatility around data releases. This emphasises why we consider multiple factors when coming to an investment decision rather than blindly following the numbers, and it does seem this approach will help navigate markets in the months ahead.
