Heuristics and Biases
MobLab Survey: Availability Bias
Key Teaching Points:
- People estimate the frequency of an event based on the ease with which an event comes to mind.
MobLab Survey: Represent v. Likelihood (Steve)
Key Teaching Points:
- Show that individuals develop categories to understand the world around them. Each category has a prototype. Representativeness occurs when individuals assess the probability of something belonging to a category based on how well the thing conforms to the prototype.
MobLab Survey: Conjunction Fallacy (Linda)
Key Teaching Points:
- Following a representative heuristic can lead individuals to make errors that violate laws of probability.
MobLab Survey: Anchoring Bias
Key Teaching Points:
- Show that when individuals have experienced different numerical anchors, when asked the same numerical question there is insufficient adjustment from those anchors.
MobLab Survey: Mental Accounting (Sunk Costs)
Key Teaching Points:
- Show that individuals develop different mental accounts when dealing with money. This leads to individuals framing economic activities has belonging to different accounts and that leads to departures from economic theory.
There are a number of other pre-built survey-based experiments on heuristics and biases. Also, use our Blank Survey to generate your own survey-based experiments.
Individual Choice Experiments
MobLab Game: Bomb Risk Game
Key Teaching Points:
- Individuals differ in their risk tolerance. Risk preferences displayed in one environment can carry over to other environments.
- Individuals who open fewer than 50 boxes can be said to be risk averse. Those who open more can be said to be risk seeking.
Additional Risk Preference Surveys: Risk Preferences: Holt Laury and Risk Preferences: Binswanger
MobLab Survey: Allais Paradox
Key Teaching Points:
- People overweight small probability events and this leads to violation of predictions from Expected Utility Theory.
MobLab Survey: Ambiguity Aversion
Key Teaching Points:
- Show that individuals exhibit a preference for known rather than unknown risks.
MobLab Surveys: Time Preferences: Binary Choice (and Budget Sets)
Key Teaching Points:
- Time inconsistent preferences. Individuals exhibit different willingness to tradeoff between present and future at different points in time.
MobLab Game: Monty Hall
Key Teaching Points:
- Through repeated iterations of the Monty Hall game, students learn the intuition behind Bayes' Rule.
Social Preferences
MobLab Game: Dictator Game
Key Teaching Points:
- Individuals may have altruistic (other-regarding) preferences.
- Social norms and other-regarding preferences may alter strategic responses.
MobLab Game: Ultimatum
Key Teaching Points:
- Demonstrates how social norms such as fairness and altruism may result in behaviors that deviate from game theoretic predictions.
- In conjunction with the Dictator Game, helps distinguish between strategic and non-strategic altruism
MobLab Game: Ultimatum: Strategy Method
- The successful bargainer accounts for a wide variation in others’ preferences for fairness.
- Many players make offers that they themselves would not accept, which may be evidence of a lack of strategic thought.
MobLab Game: Trust Game
Key Teaching Points:
- Explore and test backward induction and sub-game perfect Nash Equilibrium.
- Preferences for trustworthiness (positive reciprocity) or fairness may lead a Responder to return positive amounts. Anticipating this, and perhaps also motivated by altruism or fairness, Investors may choose to invest.
MobLab Game: Public Good: Linear
Key Teaching Points:
- Show how individual profit maximization leads to the free-rider problem, but, that individuals do not begin playing their dominant strategy.
- Demonstrates the distinction between private and social benefits of public goods.
MobLab Game: Public Good: Punishment and Reward
Key Teaching Points:
- Show the strength of norms for fairness. In this game students can incur a cost to punish free-riders or reward contributors.
- Show how incurring these costs results in preserving norms for cooperation.
- Reporting each individual’s contribution likely increases voluntary contributions to a public good
MobLab Game: Public Good: (Discrete) Threshold
Key Teaching Points:
- Highlights the features of public goods: non-rival and non-excludable.
- Highlights the coordination aspect of the free-rider problem.
- Allow players to explore the collective action problem, where more diffuse benefits lead to lower overall contributions.
Behavioral Finance
MobLab Game: Asset Market (Bubbles and Crashes)
Key Teaching Points:
- Shows how asset bubbles may develop even with common knowledge about an asset's terminal value and the distribution of dividends.
MobLab Game: Keynesian Beauty Contest
Key Teaching Points:
- Strategic thought requires making conjectures about the reasoning and choices of others whose actions affect the payoffs of my choices.
- Test the solution concept of iterated dominance and lead into a discussion of bounded rationality and theory of the greater fool.
MobLab Game: Herding (Information Cascades)
Key Teaching Points:
- In a social learning environment, it is often rational for an individual to ignore her private information and follow the herd (i.e., imitate the choice of her predecessors).
- While players will generally weigh private and public information appropriately, it is not uncommon for players to place too much weight on private information.
MobLab has a number of other games: matrix form games, different auction formats, voting, and more. If we do not have a game you're looking for, please consider suggesting a game by writing to support@moblab.com.