Duopoly with Differentiated Demand and Capacity Constraints (B. Çelen & S. Feldmann)

We are adding a new competition game, by Bogaçhan Çelen and Sven Feldmann (Melbourne Business School).

Players are randomly and anonymously paired with another participant, and play 6 rounds of an airline duopoly game with capacity constraints and differentiated demand.

The airlines simultaneously choose capacity and prices with which they compete. The system of demand is linear and symmetric (model of demand).


The rules can be found here and and we also included a simulation “outside” of the game, to help players determine their best choice: simulation

The game is the last game in the list in the industrial organization section.

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Monopoly version of the Price/Production game with Quotas, Taxes…

If you are an instructor running the market game with quotas, taxes… (rules), you may find it easier to start by inviting your students to play the simulation as a monopoly, before introducing competition.




This is now possible with one click in the mono-player simulation section (“Play as a monopoly” button, third simulation, https://simu.io).

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The Carbon Game is in open access until the end of August

The complete version of the game about CO2 emissions and environmental policies (on which the final of the 2017 tournament was partly based) is in open access on the site, until the end of August.

To create the game, click on the button in the blue well on the home page of the commercial site: https://lud.io/

The companion document can be downloaded here: https://lud.io/resources/site/manual/carbon-game-manual.pdf


During the final, out of the 12 teams to qualify, the winner, HEC Montréal,  scored 2 296 587. The second team (Toulouse School of Economics) scored 2 287 370 and the 3rd (Cardiff Metropolitan University) 2 105 320. Can you do better?

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[Video] Model of Demand for the Airline Game

Complements for instructors about the model of demand of the Airline Economics Simulation

You must be familiar with the simulation before watching this video: https://lud.io/transport or https://economics-games.com/industrial-organization.

1 – General Considerations and Customers’ Characteristics: 1:07
2 – Dynamics of sales inside a phase: 4:11
3 – Comparing customers’ characteristics between phases: 7:42
4 – Why the effect of frequencies on sales exhibit decreasing returns: 11:19
5 – When can a cheaper firm sell less than its competitor? Example 1 (because of different frequencies or comfort): 14:22
6 – When can a cheaper firm sell less than its competitor? Example 2 (because of seat quotas): 18:04
7 – When can a cheaper firm sell less than its competitor? Example 3 (because of the random component of individual choices): 22:54

The video is maybe not polished enough to show to your students, but should be quite useful to the instructors who run the Airline Game in their courses.


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The Bubble Game, An Extension


Jieying Hong, Sophie Moinas, and Sébastien Pouget have written a very interesting experimental and theoretical extension to the Bubble Game, studying learning in speculative bubbles. A great extension to direct your students to, after running the bubble game on our site.




Abstract of the paper:

“Does traders’ experience reduce their propensity to participate in speculate bubbles? This paper studies this issue from a theoretical and an experimental viewpoint. We focus on a game in which bubbles, if they arise, are irrational, as in the Smith, Suchanek, and Williams (1988)’s set up. Our theoretical results are based on Camerer and Ho (1999)’s Experience-Weighted Attraction learning model. Adaptive traders are assumed to adjust their behavior according to actions’ past performance. In the long run, learning induces the market to converge to the unique no bubble equilibrium. However, learning initially increases traders’ propensity to speculate. In the short run, more experienced traders thus create more bubbles. An experiment shows that bubbles are very pervasive despite the fact that subjects have become experienced. Our estimation of the EWA model also indicates that learning is at work.”

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“A Classroom Inflation Uncertainty Experiment”

We have just added a new experiment: “A Classroom Inflation Uncertainty Experiment” by Denise Hazlett (IREE 2007).

The paper is available on the site of the journal, and the game is in the “macro section” on our site.




Abstract of the paper:

This classroom experiment uses a double oral auction credit market to demonstrate how inflation uncertainty causes a wealth transfer between borrowers and lenders. The experiment also shows the social cost of inflation uncertainty when borrowers and lenders cannot agree on a nominal interest rate that compensates each for their risk. In this case, the credit market fails to allocate funds to the highest-valued investment projects. The experiment provides hands-on experience with the effects of anticipated and unanticipated inflation, giving students a common background for a discussion of the economic costs of inflation. It can be used in principles, intermediate macroeconomics,money and banking, or financial economics courses, with 8–60 students…”

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“Contracting under Incomplete Information and Social Preferences”

We have just added a new experiment: “Contracting under Incomplete Information and Social Preferences: An Experimental Study” by Eva Hoppe and Patrick Schmitz (RES 2013).

The paper is available on the site of the journal, and the game is in the “information asymmetry section” on our site.




Abstract of the paper:

Principal-agent models in which the agent has access to private information before a contract is signed are a cornerstone of contract theory. We have conducted an experiment with 720 participants to explore whether the theoretical insights are rejected by the behavior of subjects in the laboratory and to what extent deviations from standard theory can be explained by social preferences. Investigating settings with both exogenous and endogenous information structures, we find that agency theory is indeed useful to qualitatively predict how variations in the degree of uncertainty affect subjects’ behavior. Regarding the quantitative deviations from standard predictions, our analysis based on several control treatments and quantal response estimations shows that agents’ behavior can be explained by social preferences that are less pronounced than in conventional ultimatum games. Principalsíown social preferences are not an important determinant of their behavior. However, when the principals make contract offers, they anticipate that social preferences affect agents’ behavior.”

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An extension to help running experiments with oTree on mTurk

For those of you who design research experiments with the oTree software (http://www.otree.org/) and want to run them on Amazon mTurk.

During the WZB oTree hackathon, we worked, with Essi Kujansuu and Philipp Chapkovski on developing special pages intended to help doing this, when the experiment involves interactions between the participants. Most of the features deal with the dropout/”participant synchronization” problems:

1 – Participants can be offered to do a specific task while waiting for other players to arrive (to ensure that they remain “available” and ready to start the experiment while they wait).

2 – You can offer participants to finish part of the experiment (or just a part of it) if they have been waiting for too long.

3 – It is possible to pay participants for their tasks or for the time they spent on the wait page.


The project, mturk-oTree-utils, runs on oTree 1.4, and you can find it, along with more details (in the readme file), here: https://github.com/chapkovski/custom-waiting-page-for-mturk

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