The ONS announced today that the real-terms change in quarterly GDP for Q3 (July to September 2019) was +0.3%, a turnaround from the contraction of -0.2% seen in Q2.
The #icaewchartoftheweek looks instead at the seasonally adjusted monthly changes in GDP over the last year. This is a view that the ONS tends not to focus on because it highlights one of the issues with GDP, which is the inherent difficultly in estimating it accurately. It prefers to remove the rockiness in the monthly numbers by averaging the results over longer periods, such as its headline three-month rolling estimates reported in the media today; a number that is still subject to revision, but to a lesser extent than that for individual months.
The monthly contraction of -0.07% in September may therefore not make the headlines, but it is the principal reason why expectations of 0.4% for quarterly growth were 0.1% too high. Most economists expected the economy to be flat this month, rather than the small contraction in the statistics released this morning.
Revisions may have a significant impact on the October monthly GDP estimates scheduled to be released two days before the general election on 10 December 2019. A flat October with no revisions would see the three-month rolling GDP number fall to 0.0%, while a further contraction could see quarterly growth turn negative, a potentially significant contributor to the public debate in the couple of days before the polling booths open.
Perhaps the main conclusion that can be drawn is not about the specific monthly changes themselves, but rather how the economy is so weak that a very small change either in actual economic activity, or in statistical data collection, can easily move the numbers from positive to negative or vice-versa.
A rather dismal perspective to hold onto as the debate rages and claim and counterclaim are made.
Office for National Statistics, First quarterly estimate, Q3 2019.
Thanks for the latest updates on our GDP data. Coming from a data background myself, I especially enjoyed the last perspective you shared of how a stronger economy could better withstand the minute swings that always exist in data collection