Understanding the Social Network Premium in Hiring Low Wage Workers

This project uses experimental methods to study how an individual’s social connectedness affects the likelihood of that person securing employment. The project is conducted in partnership with several large construction worksites and seeks to unpack the reasons why less socially connected individuals tend to have a harder time finding work. The project focuses on testing several potential channels that have been proposed as important drivers of this difference: (i) less socially connected workers have a harder time signaling their ability to employers, (ii) employers may prefer to spend the workday with employees for whom they have a social connection already, (iii) employers may be better able to hold socially connected workers accountable in the long run, (iv) employers may prefer to provide the benefits of employment to those they are connected to, or (v) social connectedness is actually an accurate predictor of underlying productivity. The results of this project will provide inputs into policies to promote equal access to employment and increase the efficiency of the labor market. This will improve labor allocation, labor productivity, and economic growth. Five hypotheses have been put forth to explain why employers hire from their social networks and how this affects group productivity: (i) signal ability to employers; (ii) employer preference for people in their network, (iii) accountability and better monitoring, (iv) personal favor, and (v) social network may be an indicator of worker productivity. This research tests each of these potential mechanisms by varying the information employers have about worker’s productivity, financial incentives associated with employee productivity, and the extent of monitoring capability employers have over employees. The research measures worker productivity before treatment and then again during and after the treatment. The PIs will construct a measure productivity that captures detailed information about the tasks completed by the worker each day. Finally, the PIs will track workers over time to see how hiring patterns change for workers depending on the treatment they received during the experimental phase. Combined, these pieces of information allow the PIs to disentangle which of these channels explains the cross-sectional variation in employment rates. The results of this project will provide inputs into policies to promote equal access to employment and increase the efficiency of the labor market, improve labor allocation, labor productivity, and economic growth. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.