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Letter from the editor

Markov Switching

"Markov switching models are a family of models that introduces time variation in the parameters in the form of their state, or regime-specific values. This time variation is governed by a latent discrete-valued stochastic process with limited memory. ..." – By Yong Song and Tomasz Woźniak

Agent-Level Adaptive Learning

"The introduction of adaptive learning at the agent level requires the specification of the learning implementation’s behavioral primitives, equilibrium notions, and stability concepts. The cognitive consistency principle—that the sophistication of a model’s agents should be comparable to the sophistication of the modeler—guides the behavioral assumptions. ..." – By George W. Evans and Bruce McGough

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