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Princeton University Library Catalog
Algorithmic Writing Assistance on Jobseekers' Resumes Increases Hires / Emma Wiles, Zanele T. Munyikwa, John J. Horton.
Cambridge, Mass. National Bureau of Economic Research 2023.
1 online resource: illustrations (black and white);
National Bureau of Economic Research
Munyikwa, Zanele T.
Horton, John J.
Working Paper Series (National Bureau of Economic Research) no. w30886.
[More in this series]
NBER working paper series no. w30886
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.
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