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First Look at Measuring a Server’s GDP

Author: Roboticus

Now that my Auction House data exporter is working, I wanted to give a few glimpses of what sort of information is being captured.  Currently, I am only working with data from one server (Stormreaver) at one time (11/9/2008), but expect future analyses that look across time and across different servers.

First let me present an aggregate of all items listed on the Auction House, sorted by type of item. Note that all figures are represented in Gold, with the decimal places representing remainder Silver and Copper.

Sum of Buyout Prices by Item Type
Type Sum of Buyout in Gold
Armor 70039.8719
Consumable 23358.8791
Container 2445.3044
Gem 47931.1272
Glyph 10725.5583
Miscellaneous 2130.7305
Projectile 408.8389
Quest 32137.6646
Quiver 369.96
Recipe 30138.5143
Trade Goods 69960.0365
Weapon 31296.9946
Grand Total 320943.4803

Nothing surprising here, except that we can now see the sum of all buyouts on all items in the Auction House is 320,943 Gold, 48 Silver, and 3 Copper at this particular point in time.

I expect that the calculation of this value, while uninteresting by itself, will become very useful for identifying changes in a server’s economy over time, tracking inflation, and comparing one server’s economy to another.  And more to the point of todays article, finding this figure is the first step towards measuring a server’s GDP.

In addition to overall GPD, I expect to be able to find sector-by-sector values.  The following table is a derivative of the table above, but breaks down the items into subgroups.

Type and Subtype of Item with Sum of Buyout
Type and subtype Sum of Buyout
Armor 70039.8719
Cloth 21045.4729
Idols 210.2952
Leather 16843.0403
Mail 8509.3164
Miscellaneous 14734.6428
Plate 6892.2313
Shields 1804.873
Consumable 23358.8791
Bandage 63.1764
Consumable 72.7867
Elixir 1618.017
Flask 35.5407
Food & Drink 2414.4204
Item Enhancement 15449.8228
Other 733.3774
Potion 2293.5101
Scroll 678.2276
Container 2445.3044
Bag 1583.0437
Engineering Bag 155.31
Gem Bag 61.5
Herb Bag 519.99
Inscription Bag 3.7635
Leatherworking Bag 50
Mining Bag 71.6972
Gem 47931.1272
Blue 5146.0353
Green 4301.6676
Meta 6222.8292
Orange 6509.88
Prismatic 31.1744
Purple 8543.6341
Red 9199.1135
Simple 2634.9168
Yellow 5341.8763
Glyph 10725.5583
Death Knight 496.199
Druid 2214.0928
Mage 1546.2229
Paladin 1148.2079
Priest 627.5763
Rogue 900.8655
Shaman 1524.7049
Warlock 1586.4794
Warrior 681.2096
Miscellaneous 2130.7305
Holiday 53.45
Junk 316.3309
Other 1593.4134
Pet 76.8958
Reagent 90.6404
Projectile 408.8389
Arrow 80.04
Bullet 328.7989
Quest 32137.6646
Quest 32137.6646
Quiver 369.96
Ammo Pouch 363.75
Quiver 6.21
Recipe 30138.5143
Alchemy 1428.9197
Blacksmithing 6867.7532
Book 1073.8336
Cooking 995.0474
Enchanting 4541.3618
Engineering 2370.0679
First Aid 114.2065
Fishing 27.225
Jewelcrafting 6779.6602
Leatherworking 3453.8882
Tailoring 2486.5508
Trade Goods 69960.0365
Armor Enchantment 3.6054
Cloth 5979.1744
Devices 767.5765
Elemental 10910.8582
Enchanting 18010.4966
Explosives 29.882
Herb 5710.5765
Jewelcrafting 46.8442
Leather 4728.083
Materials 1014.5043
Meat 384.4169
Metal & Stone 8897.0247
Other 10742.7059
Parts 2734.2879
Weapon 31296.9946
Bows 739.6056
Crossbows 191.5898
Daggers 3099.9228
Fist Weapons 145.68
Guns 4130.3708
Miscellaneous 3
One-Handed Axes 1097.4225
One-Handed Maces 3938.9103
One-Handed Swords 2354.3544
Polearms 1000.0112
Staves 4327.5878
Thrown 107.799
Two-Handed Axes 7155.0013
Two-Handed Maces 843.2646
Two-Handed Swords 1651.6771
Wands 510.7974
Grand Total 320943.4803

While that may have been more information than most people need on the issue, I wanted to show the level of granularity that total-market scans can unveil.

Even just in presenting these numbers, I already can see the many difficulties that must be addressed before a firm methodology for establishing server GDP.  In these numbers, I found two outliers that more than doubled the overall value of the economy.  These items were simple Copper Bullets, selling for 180,000 Gold — an item that normally sells for 15 Silver.  A clear method for identifying these outliers must be found, preferably one that does not require looking at data sets one by one. Other factors that need to be identified is how to determine what items successfully sell, which items are re-listings from previous scans, and what time frame to use for measuring GDP.

But before we get on to that, I wanted to share some more types of information that can be gleaned from these data.  Below is a table that compares total value of buyouts for goods, sorted by the level of quality of the item.  For the non-WoW players here, Common items are generally items found by gathering professions and drops off of minor mobs while Epic items are those that drop off the most difficult raid bosses and from high end crafting professions.

Sum of Buyout Price by Quality of Item
Row Labels Sum of Buyout
Common (white) 77006.9874
Uncommon (green) 64049.214
Rare (blue) 96213.0551
Epic (purple) 83674.2238
Grand Total 320943.4803

The surprising find here is that each of the four gradients are relatively near each other in sum of buyout values.  I would have expected that epic items would have represented a great majority of the Auction House’s value.

If you have any questions, or want more details about these data, please feel free to leave a comment and I will get back to you!

Tags: data collection, GDP

This entry was posted on Wednesday, November 12th, 2008 at 4:16 pm and is filed under Econometrics. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.

2 Responses to “First Look at Measuring a Server’s GDP”

December 19th, 2008 at 11:42 am

Isaac Knowles says:

A method for detecting an auction ending before its scheduled time (suggesting a buyout) would be a matter of just taking frequent scans, assigning items on the AH a unique identifier, and then watching whether or not they disappear before they are scheduled to do so.

What I wonder is how, if at all, you plan to deal with auctions ending due to cancellations by sellers.

December 19th, 2008 at 12:12 pm

Roboticus says:

I’ve already looked into that approach and have been doing scans as frequently as possible. The limiting factor to this approach is that a full Auction House scan takes 8 to 12 minutes (depending on the amount of postings) and 2-3 minutes of processing time to parse the data. Unless I create a second account, this means that I can’t be playing the game while taking scans. Perhaps if I did have a second account, I could write an addon to the game that automates the process of scanning, parsing, saving, deleting old auction data and then repeating so I could just leave the second account constantly running. Unfortunately, I am limited by both time and money, given that I am currently applying to Ph.D. programs in Economics. (hence the shortage of new posts at the moment)

Nice blog of your own by the way. I’ve read your RMT paper before, which was one of my first glances at analyzing MMOs.

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