Resolving a Replication That Failed

The paper at hand aimes at identifying the assumptions that lead to the results presented in an article by Michael Macy and Yoshimichi Sato published in PNAS. In answer to a failed replication, the authors provided the source code of their model and here the results of carefully studying that code are presented. The main finding is that the simulation program implements an assumption that is most probably an unwilling, unintended, and unwanted implication of the code. This implied assumption is never mentioned in Macy and Sato's article and if the authors wanted to program what they describe in their article then it is due to a programming error. After introducing the reader to the discussion, data that stem from a new replication based on the assumptions extracted from the source code is compared with the results published in Macy and Sato's original article. The replicated results are sufficiently similar to serve as a strong indicator that this new replication implements the same relevant assumptions as the original model. Afterwards it is shown that a removal of the dubious assumption leads to results that are dramatically different from those published in Macy and Sato's PNAS article. Replication, Social Dilemma Situations, Trust, Simulation Methodology, Cooperation Introduction In Will and Hegselmann (2008a) we reported to JASSS on how we failed to replicate the results presented in Macy and Sato (2002). We considered several aspects of the model as causes of our failure. The most plausible explanation we could find, was that we had missed the way in which transaction costs were implemented. Lacking the opportunity to analyse the source code of the model, we were not able to verify this conjecture. Shortly after the publication of our paper, the authors' reply appeared in the same journal (Macy and Sato (2008)). No clear answer on why our replication might have failed was given in this text (Will and Hegselmann 2008b) but Macy and Sato published their source code in answer to our article. In the present text, I am presenting the insights I gained from studying the code carefully, trying to uncover those assumptions of the original model that we got wrong in our replication. Macy and Sato's model is quite appealing. It implements a social structure that distinguishes between interactions in (a) more or less small groups of people that know each other comparatively well and (b) usually larger groups of strangers. This is a structural scenario that corresponds well to real-world interactions of people. The model predicts that social mobility, as long as it is not extremely high, has a large positive effect on trust among strangers. In a world with probably increasing social mobility this is an interesting finding. Thus Macy and