Algorithmic Writing Assistance on Jobseekers' Resumes Increases Hires / Emma Wiles, Zanele T. Munyikwa, John J. Horton.

Format:

Book

Author/Creator:

Wiles, Emma.

Contributor:

National Bureau of Economic Research.

Munyikwa, Zanele T.

Horton, John J.

Series:

Working Paper Series (National Bureau of Economic Research) no. w30886.

NBER working paper series no. w30886

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2023.

Summary:

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.

Notes:

Print version record

January 2023.