Distributional effects of hiring through networks

How would a policy that bans the use of networks in hiring (e.g., anti-old boy network laws) affect welfare? To answer this question, we examine a variant of Galenianos (2013), a version of a random search model with two matching technologies: a standard matching function and worker networks. Our model has two types of workers, networked workers and non-networked workers. It is shown that the effects of such a policy on non-networked workers can be either positive or negative, depending on model parameters. In our calibration such a policy would make non-networked workers slightly worse off and networked workers substantially worse off.