{'fraction_non_alphanumeric': 0.02526906878802059, 'fraction_numerical': 0.009358914365933552, 'mean_word_length': 5.126074498567335, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Mathematical speciﬁcation of an agend-based model of exchange

Agent-based computer models are becoming increasingly popular in economics, both as a toolbox for theoreticians [12] and for policy advise [7]. All science nowadays relies on computer models. For an interesting analysis of just how much, see ”Simulation and its Discontents” [13]. But a distinguishing feature is that, in computational economics, computer models are often the only kind of models we have. The situation is completely different from physics and engineering where computer models are secondary to mathematical ones. It is the latter which embody the theories and serve as object of discussion between scientists: computer code rarely makes its way in scientific publications. In physics and engineering a computer model is judged to be correct if it faithfully implements its mathematical counterpart. Prominent computer model failures – from 1996 Ariane 5 flight 501 [1] to 2010 “flash crash” at the New York Stock Exchange – remind us that, sometimes, it is difficult to formulate exactly what counts as “faithful”. But, at least in principle, mathematical models provide a “golden standard” for the correctness of computer models in physics and engineering. But what is “golden standard” against which to judge the correctness of agent-based models for computational economics ? When can we trust the outcome of multi-agent simulations designed to study viable decarbonization options or to inform politicians on the effect of green building subsidies on unemployment ? Such models are usually accompanied by a narrative, an informal description of the ideas behind their development. But a narrative is too blunt an instrument to help us decide whether a computer implementation of it is correct or not, whether the results of a simulation are trustworthy or flawed by programming errors. In a nutshell, the current state of affairs in computational economics can be summed up as follows: we can limit ourselves to informal narratives, or we can use simulations of computer models which we do not understand [10] and whose correctness we cannot guarantee.