Online Gaming - An Economic Analysis
Final Report Abstract
Online gaming on the internet has become a multi-billion dollar industry. Yet, the question what distinguishes games of skill from games of chance has not been answered sufficiently. The question has important legal and regulatory implications since in many jurisdictions games of chance are prohibited or tightly regulated. Furthermore, there is little evidence on problem gambling and its potential link to the amount of skill within a game. We proposed a method that measures the amount of skill and chance within games empirically, both for the special case of two-player games, as well as multiplayer games. This method, to the best of our knowledge, is the first empirical approach which incorporates the strength of opponents instead of only considering outcomes. While empirical approaches crucially depend on the data used for analysis, we are confident that the abundance of available observations from online gaming approximates sufficiently. We acquired millions of these observations and applied our measure. While the computational effort was extensive, we managed to compare the heterogeneity of playing strengths of players for a variety of games such as chess, poker and Go. We also set up reference points by creating artificial datasets (x%-chess), which facilitate to set up a threshold for distinction. We found that poker has a similar heterogeneity of playing strengths as 25%-chess. This result holds regardless of the number of players, i.e. is similar for two-player, six-player and nine-player versions of poker. The heterogeneity of playing strengths for games like Go or sports like Tennis turned out to be similar to that of chess, while those of card games like Crazy 8s or dice games like Yahtzee are even lower than for poker. Our contribution to classify poker might seem the most relevant, due to the fact that there were extended debates (including courtrooms) whether it should be regarded as a game of skill or a game of chance. Furthermore, the method itself is widely applicable and could be used to analyze future games which might be questionable in this regard. The second subproject which was set out to investigate the behavior of players and potentially reveal fallacies turned out to produce uninformative results. Instead, we wrote a paper that suggests that the regulation of online gambling in general might need more attention. This could be inferred from the fact that countries around the world have remarkably different approaches of how to regulate online gambling. In another paper, we propose to consider GINI coefficients of gambling expenditures as an indicator of problem gambling. We find strong positive relationships between the GINI coefficient and the share of revenue derived from problem gamblers, as well as excessive spending of problem gamblers. Since the problem gambling status of players is often unknown, policy makers and gambling operators could use the GINI coefficient as an indicator to monitor social risk in gambling activities. Furthermore, we tried to contribute to understand the behavior of investors at online trading platforms. By conducting a lab experiment, we found that the information on success of other traders resulted in a higher likelihood to adopt more risky investment strategies. This finding seems relevant, as it shows that public information on individual earnings may lead to excessive risk taking and individually and socially suboptimal outcomes. In another lab experiment, we sought to investigate the behavior of participants in cryptocurrency markets. It turned out that our stylized version of the proof-of-work algorithm, which is part of the design of many cryptocurrencies, fuels overpricing – both in environments with and without entry barriers. This finding seems to be especially informative to researchers and central banks who are working on the development of future cryptocurrencies, as price stability could be an important aspect.
Publications
- (2020) Copy Trading. Management Science 66 (12) 5608–5622
Apesteguia, Jose; Oechssler, Jörg; Weidenholzer, Simon
(See online at https://doi.org/10.1287/mnsc.2019.3508) - “Measuring skill and chance in games.” Discussion Paper 643 (2017), AWI Heidelberg
Duersch, P., Lambrecht, M., and Oechssler, J.
(See online at https://doi.org/10.11588/heidok.00023867) - (2018), Regulation of Online Gambling, Economics and Business Letters, 7(4), 162-168
Fiedler, I.
(See online at https://doi.org/10.17811/ebl.7.4.2018.162-168) - (2019), “Gambling spending and its concentration on problem gamblers”, Journal of Business Research 98, 82-91
Fiedler, I., Kairouz, S., Costes, J.-M., and Weißmüller, K.
(See online at https://doi.org/10.1016/j.jbusres.2019.01.040)
