Economic theories have for long been considered for real world application given the widespread application of theories in academics and research to advance political or social theories that require economic references. Theories are widely applauded for providing a bridge between the analytics and the process of human decision making especially in economics (Azar and Bar-Eli, 2011). Game theory was established to aid in the prediction of decision making of firms and companies in the market based on the existing payoffs together with the consideration for the move that will be made by the other player during the game.
Game theory has successfully been applied in the prediction of the behavior of monopolies, oligopolies, entrant firms, incumbent firms, together with a myriad of other competing firms of diverse natures and sizes within the market (Azar and Bar-Eli, 2011). Game theory can either be behavioral or analytic based on the principles that underlie the basis through which the games predict the outcomes and payoffs of the game together with the strategies of the players in the game, in this case, firms in the market (Azar and Bar-Eli, 2011). Behavioral game theory has conclusively demonstrated that human-decision making in the context of strategic interaction is at odds with the prediction of analytical game theory.
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Research findings point to the fact that game theory was initially almost entirely theoretical which led to the realization that theories often fail to give unique predictions of equilibrium. For instance, in experimental games conducted by researchers, the outcomes of the experiment revealed a Nash equilibrium that significantly deviated from the theoretical Nash equilibrium in the game (Azar and Bar-Eli, 2011). Furthermore, theories are based on assumptions and the accuracy of the outcomes is largely dependent upon the strength of the assumptions. The assumptions made about the theories and the populations that the economic theories often rely upon predictor factors and variables that have been considered by the study.
The latent self-interest is one predictor that is used to establish assumptions on the expected behavior of the players in a game. Latent self-interest pertains to the rationality of firs to prioritize their interests with the belief that the interests of all other stakeholders and players of the firms shall also be optimized (Huerta, 2002). It is often applied in the prediction of the probability of cooperative behavior among first with regard to the strategies adopted to achieve the Nash equilibrium for the individual firms. Moreover, a similar predictor for the cooperative behavior of firms is the proxy political affiliation of the firms and the decisions that are made with this consideration. The predictions of the outcome of the game with regard to the consideration for cooperative behavior together with the probable moves to be made by players often have to be standardized and sensitized to suit the assumptions that were made prior to the beginning of the games.
To this extent, most individuals question the validity of analytical game theory as compared to experimental game theory given the deviations in the outcomes that are predicted by the two games (Huerta, 2002). Experimental game theory was first delved into during the mid-20 th century by the exploration into theories such as the prisoner’s dilemma together with the oligopoly games established during the same period. However, the aspect of game theory has witnessed immense growth gaining the name behavioral game theory. Research findings have delineated the difference between behavioral game theory and analytical game theory pointing to the former as being a positive theory focusing on the reasons for the decisions made by players and firms and the rationality of the decisions (Huerta, 2002). On the other hand, the analytic game theory focuses on the identification of the optimal decisions that should be made by the players in a game given the payoffs and possible outcomes.
With regard to experimental and behavioral game theory, arguments often arise over the most effective strategy to apply in the experimentation of the explanation as to why individual firms choose the strategies that they adopt. The adoption of real experiment situations has been criticized for exhibiting results that veer far from the Nash equilibrium exhibited by analytical game theory (Huerta, 2002). However, real life natural experiments are limited in number citing limited or imperfect data which is speculated to be countered by the use of lab experiments in place of the real life experiments. Lab experiments have been identified as being more efficient given the fact that they give the game the attribute of flexibility with regard to the rules and payoffs of the game and strategies that have been adopted.
Additionally, lab experiments enable the individuals conducting the experiments to be able to control the experiment given the fact that’s the samples are appropriately selected. This is together with the control over the exogenous and endogenous variables which is a critical component in the increment of the ability of individuals to identify the causal factors within the experiments (Huerta, 2002). To this extent therefore, laboratory experiments can allow for the researchers and scholars to observe and measure items and objects that may be difficult to measure within the real world. From the research findings, a majority of the analytical game theory prediction deviate from behavioral game theory predictions for instance in the games of the traveler’s dilemma, centipede and the beauty contest game.
Delving into the efficacy of experimental games as compared to real-life games exposes the fact that for the theoretical framework to suffice in providing accurate predictions in games of chance, then the experiments have to meet specific criteria for results to be valid (Palacios‐Huerta and Volij, 2008). The problem must be simplified for the subjects coupled with the provision of adequate incentives. Moreover, more time has to be allowed for the adjustment of predictors and other measurements (Palacios‐Huerta and Volij, 2008). Researchers identify that the inability of experiments to sufficiently align with these criteria leads to the differences between the results and prediction of a behavioral game as compared to the analytical game theory predictions that would have been derived.
Scholarly findings continuously point to the difference in the predictor variables for behavior of consumers and market players in general that arises between traditional game theory and behavioral or experimental game theory. individuals and firms alike have been found to often exhibit social preference in the selection of strategies and moves to take in a sequential game rather than acting out of pure self-interest (Palacios‐Huerta and Volij, 2008). This points to the recognition of the fact that aside from being interested in their own payoffs to make their decisions, players also consider the payoffs and other strategies that are likely to be adopted by their competitor firm during a game, in this case a market.
To this extent therefore, the dependence of the decisions of players in the game on the moves and strategies that have been adopted by other players in the market points to the consideration of the utility functions of the individuals when determining the payoffs in games. It is therefore key to note that the deviation between the results and predictions of behavioral and experimental games and those of traditional and analytical games theory arises as a result of a myriad of factors that ae considered with regard to the purposed decision making of the players (Palacios‐Huerta and Volij, 2008). While analytical games are not completely disregarded, researchers indicate that the use of behavioral game theory is more likely to align with more applicable strategies and results as coppered to analytical game theory.
References
Azar, O.H. and Bar-Eli, M., 2011. Do soccer players play the mixed-strategy Nash equilibrium?. Applied Economics , 43 (25), pp.3591-3601.
Huerta, I.P., 2002. Professionals Play Minimax. In Abstracts of the Fifth Spanish Meeting on Game Theory and Applications (p. 89). Universidad de Sevilla.
Palacios‐Huerta, I. and Volij, O., 2008. Experientia docet: Professionals play minimax in laboratory experiments. Econometrica , 76 (1), pp.71-115.
