escape clause" model. The model is calibrated to produce three rational expectations equilibria. Two of these equilibria are E-stable and one is unstable. Dynamics are introduced by assuming that agents must learn about the government's decision rule. It is assumed they do this using a stochastic approximation algorithm. It turns out that as a certain parameter describing the sensitivity of beliefs to new information gets small, the algorithm converges to a small noise diffusion process. The dynamics of exchange rate changes are then characterized using large deviation techniques from Freidlin and Wentzell (Random Perturbations of Dynamical Systems, Second Edition, Berlin: Springer-Verlag, 1998). These methods describe the sense in which the limiting distribution of exchange rate changes is approximated by a two-state Markov-Switching process, where the two states correspond to the two E-stable equilibria. The model is calibrated to the exchange rate histories of Argentina, Brazil, and Mexico. Currency crises in these countries resemble the predicted "escape routes" of the model. A key feature of these escape routes is that expectations of a devaluation erupt suddenly, without large contemporaneous shocks. This is consistent with evidence showing that crises are often poorly anticipated by financial markets.
A decision maker doubts the stationarity of his environment. In response, he uses two models, one with time-varying parameters, and another with constant parameters. Forecasts are then based on a Bayesian model averaging strategy, which mixes forecasts from the two models. In reality, structural parameters are constant, but the (unknown) true model features expectational feedback, which the reduced-form models neglect. This feedback permits fears of parameter instability to become self-confirming. Within the context of a standard asset-pricing model, we use the tools of large deviations theory to show that even though the constant parameter model would converge to the rational expectations equilibrium if considered in isolation, the mere presence of an unstable alternative drives it out of consideration. (JEL C63, D83, D84)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.