Algorithmic Writing Assistance on Jobseekers’ Resumes Increases Hires

Emma Wiles, Zanele T. Munyikwa and John J. Horton

No 30886, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: There is a strong association between writing quality in resumes for new labor market entrants and whether they are ultimately hired. We show this relationship is, at least partially, causal: in a field experiment in an online labor market with nearly half a million jobseekers, treated jobseekers received algorithmic writing assistance on their resumes. Treated jobseekers were hired 8% more often. Contrary to concerns that the assistance takes away a valuable signal, we find no evidence that employers were less satisfied. We present a model where better writing does not signal ability but helps employers ascertain ability, rationalizing our findings.

JEL-codes: J0 J64 M5 (search for similar items in EconPapers)
Date: 2023-01
New Economics Papers: this item is included in nep-exp and nep-lab
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