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So now it’s official: it’s not what you know, it’s who you know:

Among currently employed workers, those who found their job through a referral from their network had an average weekly salary of $772.20, or roughly $40,000 per year. Those who did not find their job via a referral had an average weekly salary of $725.84, or nearly $38,000 per year. On average, salaries were 6 percent higher if workers found their job through their networks.

Further, their earnings are even more positively skewed. One way to interpret this is that network searchers have more “upside” risk: They can potentially draw a variety of wages, but there are more very high potential outcomes through the network, To quantify this, Kelley’s statistic is 0.6 for network-finders and 0.44 for others, meaning that 80 percent rather than 74 percent of the dispersion between 90th and 10th percentile is accounted for by the top half (from 90th percentile to 50th).

The distribution of wage offers should typically be different from the distribution of wages among employed workers. Not all offers are accepted, and workers at lower wages tend to make more over time through selective job mobility and pay increases on the job. Still, even among the distribution of wage offers, we see a premium associated with those who found jobs through their network. Workers who were searching while unemployed received offers through their networks that averaged 62 percent more than those found through direct contact. Workers searching while employed received network offers that were 12 percent higher, on average.

This is based on a working paper by Marcelo Arbex, Dennis O’Dea, and David Wiczer titled Network Search: Climbing the Job Ladder Faster:

We introduce an irregular network structure into a model of frictional, on-the-job search in which workers find jobs through their network connections or directly from firms. We show that jobs found through network search have wages that stochastically dominate those found through direct contact. Because we consider irregular networks, heterogeneity in the worker’s position within the network leads to heterogeneity in wage and employment dynamics: better connected workers climb the job ladder faster and do not fall off it as far. These workers also pass along higher quality referrals, which benefits their connections. Despite this rich heterogeneity from the network structure, the mean-field approach allows the problem of our workers to be formulated tractably and recursively. We then calibrate and study the wage and employment dynamics coming from our job ladder with network heterogeneity. This quantitative version of our mechanism is consistent with several features of empirical studies on networks and labor markets: jobs found through networks have higher wages and last longer.

This entry was posted on Thursday, July 21st, 2016 at 11:52 pm and is filed under Market Action. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.