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ã¯ãæè¿ãã®ãã¼ãã«é¢ããè«æãRoger Backhouseï¼ãã¼ãã³ã¬ã 大ï¼ã¨共著したBeatrice Cherrierï¼ã«ã¼ã³å¤§ï¼ã
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Though this bears unmistakable element of truth, the idea that computerization fostered the rise of applied economics seems somewhat simplistic. While macroeconometricians like Modigliani had yearned for more computational power, better storage, convenient software, the leap done by the computer industry at the turn of the 1980s did not prevent the marginalization of Keynesian type of econometrics in the wake of the Lucas critique, nor that of the other computationally-intensive field of the 1970s, computational general equilibrium. The former was replaced with calibration, often viewed as a second best. And paradoxically, the hot methodological debate pervading microeconometrics in the early 1980s ended up in the rise of quasi-experiments, a method minimally demanding in terms of computational power.
Tying the purported rise of economics with the spread of computers also overlooks the possible transformative effects of computers on theory. In mathematics, physics and biology, automated-theorem proving, numerical or algorithmic proofs, and simulations have become well-accepted scientific practices. In economics, by contrast, that proofs are demonstrated with the help of a computer is carefully concealed in published papers. In spite of a long tradition dating back to Guy Orcutt and Jay Forrester, simulation is merely acceptable as an empirical illustration, or when analytical proofs are impossible to reach. Complaints that economists have been unable to change their idea of what a âproofâ should be, that they had stick to the Hilbertian paradigm instead of jumping on the algorithmic bandwagon, or shun numerical methods in their most prestigious publications abound. If a few computer-based approaches, like mechanism design and experimental economics, have become mainstream, a galaxy of new approaches, from agent-based modeling to automated theorem proving, computational game theory or computational social choice have hitherto wandered on the margins of the discipline, though there are hints that the situation is slowing evolving.
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The history of computerization in economics has been riven with giant leaps, but also utopian hopes and over-optimistic predictions. In 1948, Wassily Leontief, the brain behind input-ouput analysis, thought the ENIAC could soon âtell you what kind and amount of public works were needed to pump-prime your way out of a depression.â In 1962, econometrician Daniel Suit wrote that with the aid of the IBM 1920, âwe can use models of indefinite size, limited only by the available data.â In 1971, RAND alumni Charles Wolf and John Enns explained that âcomputers have provided the bridge between [â¦] formal theory and [â¦] databases.â The next challenge, they argued, was to use computer not merely for âhypothesis-testing,â but also for âhypothesis-formulation.â And Francis Diebold has recently unearthed 1989 lecture notes in which Jerome Friedman claimed that statisticians are âsubstituting computer power for unverifiable assumptions about the data.â All thing that have either not happened, or much more slowly than predicted
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