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...

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...

Can workers from social groups of comparable productivities obtain comparable employment opportunities in the long run? We model dynamic hiring and employer learning via a general Poisson multi-armed bandit framework. Breakdown environments that reveal on-the-job mistakes rather than successes...

Using administrative records from a large national US retailer, we find managers learn to discriminate "on the job" as they gain experience hiring workers of different races. First, we find that negative and positive experiences with black hires seed the race of future hires, consistent with...

Technological know-how is necessary to make effectively use of new machinery and capital goods. Firms and employees accumulate technology-specific knowledge when working with specific machinery. Radical innovation differs by technology type and pre-existing knowledge may be imperfectly...

We analyse strategic experimentation in which information arrives through fully revealing, publicly observable “breakdowns.” With hidden actions, there exists a unique equilibrium that involves randomization over stopping times. This randomization induces belief disagreement on the...

In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in...

We develop a tractable model of Bitcoin adoption with network effects and social learning, which we then connect to unique data from the Bank of Canada's Bitcoin Omnibus Survey for the years 2017 and 2018. The model determines how the probability of Bitcoin adoption depends on (1) network...

In this paper I propose a novel abstract mechanism for the creation and diffusion of knowledge and use an agent based modelling approach to explore it. The mechanism takes into account the relation between the phenomena that agents attempt to explain and the stocks of knowledge available in a...