Optimal Post-Hoc Theorizing
Andrew Y. Chen
Papers from arXiv.org
Abstract:
For many economic questions, the empirical results are not interesting unless they are strong. For these questions, theorizing before the results are known is not always optimal. Instead, the optimal sequencing of theory and empirics trades off a ``Darwinian Learning'' effect from theorizing first with a ``Statistical Learning'' effect from examining the data first. This short paper formalizes the tradeoff in a Bayesian model. In the modern era of mature economic theory and enormous datasets, I argue that post hoc theorizing is typically optimal.
Date: 2025-05
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://arxiv.org/pdf/2505.10370 Latest version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2505.10370
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().