Modeling of multivariate time series in an agnostic manner without assumptions about underlying theoretical structure is traditionally conducted using Vector Auto-Regressions. They are well suited for linear and state-independent evolution. A more general methodology of Multivariate Recurrent...

The modeling of multivariate time series in an agnostic manner, without assumptions about underlying theoretical structure is traditionally conducted using Vector Auto-Regressions. They are well suited for linear and state-independent evolution. A more general methodology of Multivariate...

These supplemental materials contain additional plots of empirical and model-implied CEs as well as posterior mean and probability weighting functions. They present statistical analysis of detected regime changes. They include additional bibliographical and technical details on the themes...

Economic agents live in a perpetually changing environment. The ensuing scarcity of information is tackled with invariant ignorance priors, forcing them to overweight the chances of less probable events. Beliefs are updated from directly sampled, described, or ambiguous sources, which may...

These supplemental materials include technical details on the algorithm for decision-making under risk utilized in the main text, as well as a concise review of neural foundations underlying the main text's theoretical framework. Several peripheral extensions to the main work are also placed here

These supplemental materials include extensions and details on the model used in the main text, as well as on its solution. An abbreviated overview of the related literature is also offered. Proofs for the propositions stated in the main text are collected here too

This paper studies the problem of decision-making under risk by agents whose information processing abilities may be limited. The constructed theoretical framework grounds on findings from economic laboratory experiments, incorporates existing neuroscience knowledge, and is implemented using...

This paper considers the problem of learning and decision-making in a dynamic stochastic economic environment by agents subject to information processing constraints. An agent endogenously chooses to operate in terms of a simplified model of the economy, which implies: a delayed, if at all,...