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- W2139185886 abstract "This note discusses the (dis-)similarities between automated inference and computer-aided decisions, at the interface of econometrics and economics. It is argued that computer-aided decisions are best suited for scientific communication. For the future, the topic of learning is singled out as one of the most promising areas of integration of econometric techniques and economics. It is a pleasure to participate in the discussion on Automated Inference and the Future of Econometrics at the 20th anniversary mark of Econometric Theory. Many factors appear to be fueling the growth of computer-intensive inferential rules; some of these lie with theoretical advances and with the current and predictable increases in computing power and in availability of large data sets. Among the many possible aspects, I wish to comment on three issues related to this theme, with a view toward possible developments. These comments are not intended to highlight some published work of mine, and they are mostly nontechnical; I hope none of these features will be seen as a liability by the reader. The three issues, listed in increasing degree of importance, concern the distinction between automation and computer aided decisions (Section 1), model selection (Section 2), and learning (Section 3). Conclusions are reported in" @default.
- W2139185886 created "2016-06-24" @default.
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- W2139185886 date "2005-02-01" @default.
- W2139185886 modified "2023-09-25" @default.
- W2139185886 title "AUTOMATED INFERENCE AND THE FUTURE OF ECONOMETRICS: A COMMENT" @default.
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- W2139185886 doi "https://doi.org/10.1017/s0266466605050061" @default.
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