Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/194798 
Year of Publication: 
2019
Publisher: 
ZBW – Leibniz Information Centre for Economics, Kiel, Hamburg
Abstract: 
This paper questions the conventional wisdom that publication bias must result from the biased preferences of researchers. When readers only compare the number of positive and negative results of papers to make their decisions, even unbiased researchers will omit noisy null results and inflate some marginally insignificant estimates. Nonetheless, the equilibrium with such publication bias is socially optimal. The model predicts that published non-positive results are either precise null results or noisy but extreme negative results. This paper shows this prediction holds with some data, and proposes a new stem-based bias correction method that is robust to this and other publication selection processes.
Subjects: 
publication bias
information aggregation
meta-analysis
bias correction method
JEL: 
C13
C18
D71
D82
D83
Document Type: 
Working Paper

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