Mathiness in the Theory of Economic Growth
By Paul M. Romer. 2015
209 citations recorded by the source corpus.
Mathiness lets academic politics masquerade as science. Like mathematical theory, mathiness uses a mixture of words and symbols, but instead of making tight links, it leaves ample room for slippage between statements in the languages of words as opposed to symbols, and between statements with theoretical as opposed to empirical content. Because it is difficult to distinguish machines from mathematical theory, the market for lemons tells us that the market for mathematical theory might collapse, leaving only machines as entertainment that is worth little but cheap to produce.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/7a077a927fab57b93caa5fdf11725368f324fb3e
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In Economics and Econometrics
Citations in the corpus
- Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2017, background): “One can also note that signals of distress as to the quality of mathematical modelling are heard from different disciplines: from economics (Reinert, 2000; Romer, 2015) to natural sciences (Oreskes, 2000; Oreskes et al.”
- Troubling Trends in Machine Learning Scholarship (2018, background): “What sort of papers best serve their readers? We can enumerate desirable characteristics: these papers should (i) provide intuition to aid the reader’s understanding, but clearly distinguish it from stronger conclusions supported by evidence; (ii) describe empirical investigations that consider and ”