We propose a model of learning when experimentation is possible, but unawareness and ambiguity matter. In this model, complete lack of information regarding the underlying data generating process is expressed as a (maximal) family of priors. These priors yield posterior inferences that become...

We analyze the Bitcoin protocol for electronic peer-to-peer payments and the operations that support the “blockchain” that underpins it. It is shown that that protocol maps formally into a dynamic game that is an extension of standard models of R&D racing. The model provides a technical...

Leveraging county-level exogenous variation in the agricultural origins of time preferences, identified by Galor and Ozak (2016), we measure the causal effects of long-term orientation traits on mobility behavior and COVID-19 infection rates from 22 January 2020 to 30 November 2020 in the United...

We define and discuss Savage games, which are ordinal games of incomplete information set in L. J. Savage's framework of purely subjective uncertainty. Every Bayesian game is ordinally equivalent to a Savage game. However, Savage games are free of priors, probabilities and payoffs. Players'...

We define and discuss Savage games, which are ordinal games of incomplete information set in L. J. Savage's framework of purely subjective uncertainty. Every Bayesian game is ordinally equivalent to a Savage game. However, Savage games are free of priors, probabilities and payoffs. Players'...