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Online Gaming - An Economic Analysis

Subject Area Economic Policy, Applied Economics
Term from 2015 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 273826972
 
Online gaming on the internet has become a multi-billion dollar industry. The size of the industry clearly justifies a careful investigation of the regulatory, economic, and legal issues that come with it. In the last 18 months, we focused our attention on two important aspects of online gaming. The first aspect was the question what distinguishes games of skill from games of chance. This question has important legal and regulatory implications since in many jurisdictions games of chance are prohibited or tightly regulated. Legislators or courts often consider a game as legal if the skill content is more than 50%. However, no generally accepted measure exists that would allow to measure the content of skill versus chance. We were successful in creating a new measure, the best-fit ELO rating, which is applicable to all games. We have obtained large data sets from leading providers of various online games and use them to compare the degree of skill and chance of different games empirically. Our approach attempts to capture the heterogeneity of players' abilities. First results indicate that poker fails to pass the 50% reference point for skill and is therefore closer to a game of chance. In the proposed extension period we will build on these foundations and finish this work (and PhD student Marco Lambrecht his dissertation) by classifying other games, extending the analysis to multi-player games and sports, and performing various robustness checks.The second aspect dealt with dynamic aspects of gaming, including problem gambling and rational choice. Our focus is specifically on the hot hand fallacy and chasing after losses. We have formulated corresponding hypothesis, cleaned the data set and performed preliminary analyses on the continuation behavior of online players. During the requested extension, we intend to investigate on changes in risk taking behavior and categorize players by individual indicators in order to establish markers of addiction. In addition, we will run a laboratory experiment, which should help us to distinguish the phenomena of chasing after losses from the gambler's fallacy. From empirical data, this difference cannot be observed.
DFG Programme Research Grants
Co-Investigator Professor Dr. Ingo Fiedler
 
 

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