- Mine Production - not surprised to see low variability here, given mines are generally consistent producers and GFMS can also access mine company reporting to analysts and refiner surveys for cross checking.
- Recycled & Jewellery - a bit more variability here as we have a large number of businesses involved that can't all be surveyed, or would want to report.
- Retail Bar & Coin - I am surprised by the variability here, possibly there was some methodology change in later years, but again with many manufacturers across the globe it is going to be hard to get this right within a month of quarter end.
- ETFs - I suspect these variances are due to GMFS expanding the limited list of ETFs they were using in early years and recalculating the figures accordingly.
- Official Sector - this is not surprising given that official reserves reporting is unlikely for many countries to be done within a month of each quarter so I expect there is a fair bit of estimation in these figures to start with.
27 November 2014
Lies, damned lies, and supply & demand figures
Warning: this post is wonkish, those who get annoyed at nit-picking or ambiguity should stop reading now.
Thanks to the beneficence of 19 gold miners, every quarter the World Gold Council (WGC) provides free of charge its Gold Demand Trends report. Despite the inclusion of "manager" in my highfalutin title, I don't actually manage any data monkey lackey staff so for years I've keyed in the Thomson Reuters GFMS sourced supply and demand figures from the report into a spreadsheet myself.
As part of their report, the WGC provides a table of supply/demand figures not just for the current quarter, but also for 2 years worth of prior quarters, so one can see the trends in the figures. What I have noticed is that with each report the figures of the prior quarters change. To see what I mean consider the image below.
Now you may think that I have cherry picked a particularly bad example but this sort of variance is not unusual. Below is a table that compares the originally reported figures with the latest figures the WGC reports, showing how much in percentage terms the original figures were under/over to the more accurate later figure (I have focused here on those categories which are more significant from a tonnage point of view).
Some additional comments (keep in mind these figures are global, so getting numbers across the entire world isn't easy):