No abstract

Risk aversion, Experiments, Elicitation methods, Heterogeneity, C90, C81,

No abstract

We examine the bank lending channel (BLC) of monetary transmission in a factor‐augmented vector autoregression (FAVAR). A FAVAR exploits large numbers of macro‐economic indicators and allows us to consider an alternative identification of monetary shocks and analyze the lending response of banks at the aggregate and individual levels. We find that the existence of the BLC is more prevalent than previously thought using aggregated lending data, while the lending response of individual banks are driven more by specific innovations than monetary shocks. Nonetheless, the average individual bank response to a monetary shock is consistent with the existence of a BLC.

We examine the role of generalized constant gain stochastic gradient (SGCG) learning in generating large deviations of an endogenous variable from its rational expectations value. We show analytically that these large deviations can occur with a frequency associated with a fat tailed distribution even though the model is driven by thin tailed exogenous stochastic processes. We characterize these large deviations that are driven by sequences of consistently low or consistently high shocks. We then apply our model to the canonical asset-pricing model. We demonstrate that the tails of the stationary distribution of the price-dividend ratio will follow a power law.