Turning a Weakness within Game Theory into a Strength: A Review of 'Testing' Game Theory by Daniel Hausman (2005)

Summary: 

         In Hausman’s article on testing game theory, the author identifies the primary difficulty in empirically testing the axioms of the analytic technique. In order to conduct an experiment on game theory a scientist must impose experimental conditions prior to testing. The scientist determines who the players are, what strategies are available to the players, and the payoffs for each strategy. For example, an economist may present a game theory test in which the players are two business professionals choosing a strategy based on monetary payoffs (make money or lose money). On the other hand, an evolutionary biologist may present a game theory scenario in which the players are two animals choosing a strategy based on evolutionary payoffs (survival or death). After imposing these conditions, the emergent test of game theory is what Hausman describes as a “Human Premeditated Game Theory” (HP game theory). Since every discipline produces a different game theory test, Hausman argues that the economist and evolutionary biologist are conducting their own tests of HP game theory and not tests of game theory itself. 

         Since pre-determined conditions are necessary to apply a test of game theory and since those same conditions inherently turn a test of game theory into a test of HP game theory, there is no way to test game theory itself. Thus, Hausman concludes, attempting to test the axioms of game theory is a futile effort. Instead, Hausman emphasizes the value of using game theory to test claims about people’s preferences.

         Hausman explains the varying levels of control a scientist has in determining conditions for a test of game theory. At the lowest level of difficulty is determining how many players there are and what strategies are available to those players. With slightly greater difficulty, scientists can control the beliefs players have concerning permissible strategies, the physical outcomes of strategy combinations, and the knowledge available to other players (including their beliefs about the beliefs of each other). The greatest difficulties for the scientist are determining the payoffs and the preferences of the participants. Determining the payoffs in a game theory experiment are critical because they are used "to make any substantial predictions concerning laboratory behavior". Furthermore, the payoffs are built on the assumption that the participant’s preference is to choose the strategy that offers the most favorable payoff, or the dominant strategy. 

      Yet when applied in experimental tests of game theory, there are times when individual preferences lead participants to choose the non-dominant strategy. Rather than consider this anomaly as disconfirming the effectiveness of game theory in predicting behavior, Hausman suggests that scientists should use game theoretic anomalies to study the factors influencing preferences. In an economist’s HP game theory, the economist assumes that the participant will prefer to maximize the monetary payoff by choosing the dominant strategy. However, other unknown factors (what Hausman calls preferences) may influence the participants to choose the non-dominant strategy with the lesser monetary payoff. For example, participants may care about the monetary payoffs other participants receive, what other participants trust them to do, whether the outcome is fair, etc. Hausman concludes that the true value in applying game theory is this opportunity to understand how those personal preferences are affecting decision-making.

Critique:

     The seemingly fatal flaw of applying game theory, in my opinion, is the assumption that the participant will choose to maximize personal payoff with the dominant strategy. As analysts we are taught to identify our assumptions and reconsider how those assumptions are affecting our analysis. Here, Hausman identifies the assumption that is misleading scientists and leaving them surprised when participants choose the non-dominant strategy.

   Although this assumption is a weakness, I agree with Hausman that we can turn this weakness into a strength by using game theory to understand how personal preferences affect a participant’s decision regarding the payoffs. An opportunity to expand on empirical tests of game theory is to conduct a survey of the participants alongside the experiment. These surveys should attempt to reveal the preferences, or personality characteristics, of the target population. How important are the values of fairness, generosity, or selfishness to these participants? With a large enough sample, this survey/game theory experiment can reveal two things: the target population’s beliefs regarding these factors and what factors tend carry the most influence in decision-making for very specific, HP game theory situations.

Although this combined experiment could provide a more wholistic understanding of the target population’s preferences and the decision-making process for participants, challenges remain because a scientist is limiting participants to two strategies and payoffs to only four mutual outcomes. Thus, it will be difficult to generalize results from a wide-scale study of this kind because real-world “HP game theory” situations will typically present decision-makers with more possible strategies and far more potential outcomes.

Source: Hausman, D. M., (2005). ‘Testing’ game theory. Journal of Economic Methodology. 12(2), 211-223.