Abstract. I provide an economic interpretation to the entropy-based probabilistic models of network formation used in statistical physics. Specifically, I show how these models are nested in a wider class of network formation models where agents are rationally inattentive about the characteristics of other agents. I develop conditions for estimating these models and provide an application about the formation of R&D alliance networks.
Abstract. Borrowing tools from the practice of neural networks, I design an empirical framework for the analysis of “hierarchical networks:” socio-economic settings featuring multiple, layered networks, whose nodes are linked across layers. I use this framework to revisit questions involving networks of workers and fi rms.
Joint work with Francesco del Prato.
Abstract. In local labor markets, workers often move at early stages of their careers from lower-paying firms that provide them training, to better-paying, specialized fi rms. We call this mechanism “human capital value chain” and we document its implications on both workers’ page paths and local agglomeration externalities.