Journal Article
Convergence to Rational Expectations in Learning Models: A Note of Caution
Chien, YiLi; Cho, In-Koo; Ravikumar, B. (2021-07-01)
We show in a simple monetary model that the learning dynamics do not converge to the rational expectations monetary steady state. We then show it is necessary to restrict the learning rule to obtain convergence. We derive an upper bound on the gain parameter in the learning rule, based on economic fundamentals in the monetary model, such that gain parameters above the upper bound would imply that the learning dynamics would diverge from the rational expectations monetary steady state.
Review , Volume 103 , Issue 3 , Pages 351-366

Journal Article
Stability and Equilibrium Selection in Learning Models: A Note of Caution
Chien, YiLi; Cho, In-Koo; Ravikumar, B. (2021-10-18)
Relative to rational expectations models, learning models provide a theory of expectation formation where agents use observed data and a learning rule. Given the possibility of multiple equilibria under rational expectations, the learning literature often uses stability as a criterion to select an equilibrium. This article uses a monetary economy to illustrate that equilibrium selection based on stability is sensitive to specifications of the learning rule. The stability criterion selects qualitatively different equilibria even when the differences in learning specifications are small.
Review , Volume 103 , Issue 4 , Pages 477-488