Networks Webinar - Georgios Angelis

Paper Abstract:

The matching function is a “black box” whose satisfactory microfoundation has proven
elusive for nearly forty years now. In this paper we propose a network variant of
the classic balls-in-bins model that allows us to address the problem at significant
generality. The matching function that emerges endogenously depends on the whole
network of connections between unemployed and firms, yet it is captured by a compact
expression. We show how in special cases matching depends only on the number
of unemployed and vacancies as typically assumed in the literature, and we recover
existing functional forms. We analyze how matching efficiency depends on the network
structure with two main themes emerging: (a) applicant-side heterogeneity in search
intensity is harmful for matching efficiency, and (b) increasing search intensity for
everyone has an ambiguous effect on matching efficiency. Finally, we find “scaling,”
i.e. how search intensity of applicants varies with changes in the sizes of unemployed
and vacancies, to play a critical role for the properties of the aggregate matching
function. We characterize the conditions under which an Erd¨os-Renyi version of our
model is consistent with the Cobb-Douglas and CES forms.