We study social learning in a social network setting where agents receive independent noisy signals about the truth. Agents naïvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. The weights are fixed in the sense of representing average frequency and intensity of...

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents are connected according to an undirected graph, the social network, and have the choice between two actions: either to adopt a new behavior or technology or stay with the default...

We study the impact of bots on social learning in a social network setting. Regular agents receive independent noisy signals about the true value of a variable and then communicate in a network. They na¨ıvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. Bots...

We present a multi-country theory of economic growth and R&D-driven technological progress in which countries are connected by a network of knowledge exchange. Technological progress in any country depends on the state of technology in the countries it exchanges knowledge with. The diffusion of...

We present a multi-country theory of economic growth in which countries are connected by a network of mutual knowledge exchange. Growth is generated through human capital accumulation and knowledge externalities. The available knowledge in any country depends on its connections to the rest of...