oTree - An Open-Source Platform for Laboratory, Online, and Field Experiments

Chen, Daniel L.; Schonger, Martin; Wickens, Chris

doi:10.2139/ssrn.2806713

Cited by 19 publications

(13 citation statements)

References 27 publications

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“…We administered the experiment online using oTree (Chen et al, 2016) in nine countries: Brazil, China, Germany, India, Japan, Russia, Great Britain, the United States, and South Africa. 1…”

Section: Participant Recruitment and Data Collectionmentioning

confidence: 99%

What Drives Risk Perception? A Global Survey with Financial Professionals and Lay People

Holzmeister¹,

Huber²,

Kirchler³

et al. 2019

Preprint

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Risk is an integral part of many economic decisions, and is vitally important in finance. Despite extensive research on decision-making under risk, little is known about how risks are actually perceived by financial professionals, the key players in global financial markets. In a large-scale survey experiment with 2,213 finance professionals and 4,559 lay people in nine countries representing ∼50% of the world's population and more than 60% of the world's gross domestic product, we expose participants to return distributions with equal expected return and we systematically vary the distributions' next three higher moments. Of these, skewness is the only moment that systematically affects financial professionals' perception of financial risk. Strikingly, variance does not influence risk perception, even though return volatility is the most common risk measure in finance in both academia and the industry. When testing other, compound risk measures, the probability to experience losses is the strongest predictor of what is perceived as being risky. Analyzing professionals' propensity to invest, skewness and loss probability also have strong predictive power, while volatility and kurtosis have some additional effect. Our results are very similar for lay people, and they are robust across and within countries with different cultural backgrounds as well as for different job fields of professionals.

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“…We administered the experiment online using oTree (Chen et al, 2016) in nine countries: Brazil, China, Germany, India, Japan, Russia, Great Britain, the United States, and South Africa. 1…”

Section: Participant Recruitment and Data Collectionmentioning

confidence: 99%

What Drives Risk Perception? A Global Survey with Financial Professionals and Lay People

Holzmeister¹,

Huber²,

Kirchler³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The original experiment was conducted at the ExCEN experimental laboratory at Georgia State University, and was programmed using O-Tree (Chen et al, 2016). As specified in the preregistration at the AEA RCT registry and in the original working paper, we conducted a total of three independent replications of the original experiment.…”

Section: Replication Detailsmentioning

confidence: 99%

A New Mechanism to Alleviate the Crises of Confidence in Science-With An Application to the Public Goods Game

Butera¹,

Grossman²,

Houser³

et al. 2020

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Creation of empirical knowledge in economics has taken a dramatic turn in the past few decades. One feature of the new research landscape is the nature and extent to which scholars generate data. Today, in nearly every field the experimental approach plays an increasingly crucial role in testing theories and informing organizational decisions. Whereas there is much to appreciate about this revolution, recently a credibility crisis has taken hold across the social sciences, arguing that an important component of Fischer (1935)'s tripod has not been fully embraced: replication. Indeed, while the importance of replications is not debatable scientifically, current incentives are not sufficient to encourage replications from the individual researcher's perspective. We propose a novel mechanism that promotes replications by leveraging mutually beneficial gains between scholars and editors. We develop a model capturing the trade-offs involved in seeking independent replications before submission of a paper to journals. * Acknowledgements: For useful comments we are grateful to

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“…The interface and engine of this online game was implemented using the oTree framework ( Fig. 2) [26]. Subjects' view of other workstations was restricted and all communication during the games was forbidden.…”

Section: B Experimental Settingmentioning

confidence: 99%

Group formation on a small-world: experiment and modelling

Bhattacharya

Takko

Monsivais

et al. 2019

J. R. Soc. Interface.

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As a step towards studying human-agent collectives we conduct an online game with human participants cooperating on a network. The game is presented in the context of achieving group formation through local coordination. The players set initially to a small world network with limited information on the location of other players, coordinate their movements to arrange themselves into groups. To understand the decision making process we construct a data-driven model of agents based on probability matching. The model allows us to gather insight into the nature and degree of rationality employed by the human players. By varying the parameters in agent based simulations we are able to benchmark the human behaviour. We observe that while the players utilize the neighbourhood information in limited capacity, the perception of risk is optimal. We also find that for certain parameter ranges the agents are able to act more efficiently when compared to the human players. This approach would allow us to simulate the collective dynamics in games with agents having varying strategies playing alongside human proxies.

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oTree - An Open-Source Platform for Laboratory, Online, and Field Experiments

Cited by 19 publications

References 27 publications

What Drives Risk Perception? A Global Survey with Financial Professionals and Lay People

What Drives Risk Perception? A Global Survey with Financial Professionals and Lay People

A New Mechanism to Alleviate the Crises of Confidence in Science-With An Application to the Public Goods Game

Group formation on a small-world: experiment and modelling

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