A Presentation given at the AVEA Virtual Economy Seminar in Helsinki (8.6.2010) on the possibilities of using data from virtual worlds to study the validity of mircroeconomic models.

1. AVEA virtual economy seminar 8.6.2010 Juha Tolvanen juha.tolvanen@hiit.fi

2. Experimentation in virtual worlds Contents Some words on my work in AVEA Virtual words as a source for natural experiments A quick example

3. My work on game theory What is game theory? You and me, we both have to make a choice. What you choose affects my decision and vice versa. I’ve been studying large games, i.e. games where the number of agents is large

4. Large games In general, the larger the game, the harder it is to analyze. I’ve been working on finding theoretically sound ways to tackle this problem and testing the findings using data from virtual worlds.

5. Large games This is rather technical stuff, so let’s do something else today to demonstrate how the data from VWs can be used in social sciences. Some virtual world oriented examples can be found from the final report.

6. Virtual worlds are rich of natural experiments Natural experiments are situations where naturally isolated changes in some variables allow us to control our “other things equal” assumptions. In VWs the environment changes often and creates a rich source of possible natural experiments.

7. The credit crunch and natural experiments Let’s take a look at one of them: After the credit crunch, many economists have criticized the so called efficient market hypothesis (EMH).

8. The credit crunch and natural experiments EMH: Prices reflect all available public information on assets (Fama, 1970). Many have argued that the collateral for the subprime loans was highly overvalued and risk premiums were systematically too low prior to 2007. A free hair cut with a loan!

9. How to test the EMH? EMH implies that changing production from one good to any other shouldn’t yield any profits if one does not have any private information. Testing the hypothesis above can be hard: Changing production from good A to good B can be very costly . How can we control private information?

10. But how about Virtual Worlds? Let’s see if we can test the EMH in virtual worlds using data from EVE Online, an online role-playing game set in space! The following data and graphs are from two sources: CCP’s Quarterly Economic News Letter 3/2009 www.eve-markets.net – a website using huge quantities of user submitted data to monitor market trends.

11. The setting We shall compare the factor prices of Bane Torpedoes (BT) and Wrath Cruise Missiles (WCM). BT WCM Both are ammunition for space warfare sold in high quantities in the ingame market.

12. The setting for the experiment On June 2009 CCP Launched a massive campaign called The Unholy Rage against real money traders. Approx. 2% of player accounts were banned. Nice source of exogenous variation, since Wrath Cruise Missiles are popular among farmers

13. UnholyRage

14. An example of a natural experiment On July alone the price of a WCM dropped slightly less than 20% (from little over 150k isk to about 125k isk). During the same time the price of a BT dropped about 9% (from 320k to 290k). Is this in line with the EMH?

15. An example of a natural experiment Both products take the same time to produce, require the same skills and their inputs are readily available in the market. Thus changing from producing one to another shouldn’t cost the producer anything.

16. An example of a natural experiment Economic theory predicts that the price of a product should be the sum of the prices of its factor inputs. =>The price of a torpedo should be the cost of the materials used plus some compensation for the skills, time and effort the player has put into producing it.

17. An example of a natural experiment As the skill requirements, building time and other manufacturing requirements for both BTs and WCMs are equal, the EMH should imply that any difference in their price should be completely due to differences in material costs. 15.6.2010: See also the last slide of this presentation

18. The timeline Unholy rage on July. On both May and August the price development of both items was again relatively stable – an indication of markets clearing. Were the markets able to correctly adjust to Unholy rage?

19. Calculations for the two warheads Wrath Cruise Missile Bane Torpedo

20. Results In May the difference in mark-ups is tolerable (2,5%) But still after one month from the sudden drop in Wrath Cruise Missile prices Bane Torpedoes earned a mark-up that is over 22% smaller compared to the WMC mark-up.

21. Results We also calculated that compared to building Bane Torpedoes, disassembling them and turning them into Wrath Cruise Missiles would have paid more in both periods. However, arbitrage is not possible: the latter still pays less than building Wrath Cruise Missiles straight from raw materials.

22. Summa summarum The markets at EVE do not seem to react efficiently to second order shocks (i.e. the way how the price of WCMs affects the price of BTs). Does this generalize to real markets? Hard to say. The opposite result would have generalized better.

23. What else can be done with natural experiments? There is no ready-made formula. You just have to keep your eyes open. For business purposes, estimating the demand curve for some product is one classic example. Another possibly profitable application how good substitutes or complements two goods are

24. What else can be done with natural experiments? Testing scientific models and estimating model parameters that are otherwise hard to pin down. Especially instrumental variable regression has become popular in economics. A good first read: Angrist & Krueger (2001)

25. Relevant literature On large games: Al-Najjar, N. 2008: Large games and the law of large numbers. Games Econ. Behav., 1-34. Tolvanen, J. 2010: Approximating Competitive Games with a Large Number of Players. Master’s thesis, University of Helsinki. Tolvanen, J. & Soultanis, E. 2010: Corrigendum and some further notes on “Large games and the law of large numbers” [Games Econ. Behav. 64 (2008), 1-34], Games Econ. Behav., in review.

26. Relevant literature Efficient market hypothesis: Fama, E. 1970: Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance 2, 383-417. Natural experiments: Angrist, J. & Krueger, A. 2001: Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments. Journal of Economic Perspectives 4, 69-85.

27. A Correction After my talk I got an insightful comment from a member of the audience regarding my example: Assuming that the manufacturers maximize the money earned per unit of time and that they are credit constrained, then the fact that manufacturing a BT costs more than 2 times the cost of a WCM should imply that the markup on a BT should be more than 2 times the markup on a WCM, since producing one BT ties 2 times the amount of capital compared to a WCM. This of course turns the setting up side down – the manufacturers are still using public information inefficiently but now they are producing too many WCMs which is opposite to the previous case where they were producing too few.