Six Blind Men and the Economics-Elephant: Why Computational Power Cannot Cure Methodological Blindness

Tomasz Kopczewski, Iana Okhrimenko () and Jan Lisicki ()
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Iana Okhrimenko: Lazarski University in Warsaw, Department of Econometrics
Jan Lisicki: University of Warsaw, Faculty of Economic Sciences

No 2026-39, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: Economics rewards precision, but precision within a model does not establish what a result means, whether the represented object is economically admissible, or whether the conclusion travels to the world. This methodological essay builds a classroom prank on the Indian parable of the blind men and the elephant. Students solve slightly different calibrations of a two-sector Leontief model, reduce the answers to policy signs and vote; every system is solvable, yet thirty of the hundred coefficient pairs fail the Hawkins–Simon productivity condition. Six blind men extend the lesson to calculation, point equilibrium, binary inference, identification, aggregation and computational dynamics. In each case the well-behaved statistic is not the one that answers the economic question, and its good behaviour is what makes it persuasive. Artificial intelligence lowers the cost of building alternative models towards zero; the scarce input is the disposition to ask what a successful result is not showing.

Keywords: economic methodology; model instability; Hawkins–Simon condition; statistical significance; classroom demonstration (search for similar items in EconPapers)
JEL-codes: A22 B41 C12 C63 C67 D51 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2026
New Economics Papers: this item is included in nep-hme, nep-hpe and nep-inv
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