Game theory experiments

Game-theoretic experiments embed an interactive economic game inside a survey. Respondents make decisions with real (or hypothetical) monetary consequences, and the researcher observes how individuals behave under controlled strategic incentives. Game-theoretic experiments are a core method in experimental economics, behavioural science, environmental and resource economics, and any field that studies cooperation, trust, risk-taking, fairness or coordination.

tickStat implements interactive games on top of a real-time engine that synchronises respondents in the same session via WebSockets, tracks rounds and periods, and computes payoffs at the end of the game.

When to use it

Use a game-theoretic experiment when you want to observe behaviour rather than self-reported attitudes — that is, when the research question is "what would a person do in this strategic situation" rather than "what do they say they would do". Typical applications include:

  • Cooperation and free-riding in environmental governance and common-pool resource management.
  • Trust, reciprocity and reputation in transactions and institutions.
  • Coordination problems where the social outcome depends on players matching their effort.
  • Pro-social behaviour, fairness norms, inequality aversion.

Supported game

The platform currently exposes the Weakest-Value (Minimum Effort) Coordination Game as a standard question type. In this game — based on the classic minimum-effort coordination paradigm — each player selects an effort level from 1 to N. The payoff for every player in the group depends on the minimum effort chosen across the group, minus a private cost proportional to that player's own effort. The game has multiple Pareto-ranked Nash equilibria, which makes it a natural laboratory for studying coordination failure, strategic uncertainty and the dynamics of effort under repeated interaction.

Additional game types — Trust Game, Dictator Game, Public Goods Game — are implemented on the same engine and can be activated for a research project on request.

How it works in tickStat

Configuration options for a game-theoretic question include:

  • Effort levels (1..N) and the payoff matrix — the per-effort cost and the group payoff function.
  • Number of rounds the game is played.
  • Maximum number of concurrent sessions — caps how many independent groups play in parallel.
  • Target number of completed sessions — the data-collection goal for the experiment.
  • Initial information screen — instructions explaining the game, the payoff structure and a worked example.

At runtime, respondents are assembled into game sessions and synchronised in real time. Each round, the engine collects every player's decision, computes the round payoff according to the game rules, and broadcasts the updated state back to all players.

Captured data

For every play, tickStat records:

  • The session identifier and the round/period number.
  • The decision made by each player.
  • The realised payoff for that round.
  • The cumulative payoff at the end of the game (used to determine the final monetary incentive, when applicable).

Data exports in the standard SPSS-format report at the player–round level, which is the natural unit of analysis for panel-style estimation of learning, convergence and treatment effects.

Practical tips

  • Run a soft launch with a small number of sessions to verify that respondents understand the payoff structure before opening the game to the full sample.
  • For coordination games, group size matters — larger groups make convergence to the efficient equilibrium harder. Pre-register your group size as a design parameter.
  • If your design requires real monetary incentives, configure the payoff scale so that the expected payment is consistent with your panel provider's per-respondent budget.