Social Network Extraction of Unobservable Productivity
RCTClinical Trial
Standard formal recruitment tools like resumes, education credentials, and standardized testing miss key dimensions of job productivity, leaving employers with residual asymmetric information.
Picture this
Consider a candidate who looks average on a written resume but possesses exceptional real-world problem-solving speed under stress. A coworker who has worked alongside them in high-pressure situations knows this hidden strength firsthand, making peer networks an effective telescope for observing qualities invisible on paper.
What the evidence says
Adding controls for resume-observable variables and formal testing metrics did not reduce the productivity premium of referrals chosen by incentivized high-ability participants (coefficient remained 0.383 standard deviations versus 0.370 standard deviations in the baseline specification).
- Who was studied
- N = 561 original male labor market participants in urban Kolkata, India.
- How
- Econometric regression modeling controlling for resume-observable variables (age groups, education levels, occupational categories, Raven's matrices, digit span, income) on referral cognitive task performance.
What to do
Incorporate peer referral pipelines alongside traditional resume screening to evaluate non-standard worker competencies that formal screening mechanisms fail to detect.
From the source
"That is, highly skilled, incentivized OPs are bringing in referrals who are highly skilled in ways that are hard to predict by the covariates in our data, even though some of those covariates are highly correlated with puzzle task performance."
468 Job Referrals in India AER Dec12.pdf