Edited by John B. Davis and D. Wade Hands
K. Vela Velupillai and Stefano Zambelli 12.1 A PREAMBLE Computing is integral to science – not just as a tool for analyzing data, but as an agent of thought and discovery. (Denning, 2010, p. 369, italics added) No one economist – although he was more than just an economist – considered, modelled and implemented the idea of ‘computing . . . as an agent of thought and discovery’ better or more systematically, in human problem solving, organization theory, decision making in economics, models of discovery, evolutionary dynamics, and much else of core relevance to economic theory, than Herbert Simon.1 In these two senses computing is clearly an epistemic and epistemological agent. On the other hand, the computer is undoubtedly also a ‘tool for analyzing data’, an aspect precisely and perceptively characterized by Richard Stone and Alan Brown in their pioneering work on A Computable Model of Growth:2 Our approach is quantitative because economic life is largely concerned with quantities. We use computers because they are the best means that exist for answering the questions we ask. It is our responsibility to formulate the questions and get together the data which the computer needs to answer them. (Stone and Brown, 1962, p.viii; italics in original) Remarkably – though not unexpectedly, at least to us3 – 34 years later, we find two of the undisputed pioneers of real business cycle (RBC) theory, the core constituent of the stochastic dynamic general equilibrium4 (SDGE) model, considered one of the two dominant, frontier, ‘schools’ of macroeconomics, defining and asserting the meaning of...
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