This paper argues that changes in the propagation of idiosyncratic shocks along firm networks are important to understanding variations in asset returns. When calibrated to match key features of supplier-customer networks in the United States, an equilibrium model in which investors have...

This paper provides a closed-form solution for the price-dividend ratio in a standard asset pricing model with stochastic volatility. The solution is useful in allowing comparisons among numerical methods used to approximate the non-trivial closed-form

This paper provides a closed-form solution for the price-dividend ratio in a standard asset pricing model with stochastic volatility. The solution is useful in allowing comparisons among numerical methods used to approximate the non-trivial closed-form

This paper illustrates two types of pitfalls in using linearization methods. First, if constraints are linearized before deriving optimality conditions, the derived conditions are not correct up to first order. Second, even when the behavior of the economy is correct to the first order, applying...

This paper explores Knightian model uncertainty as a possible explanation of the considerable difference between estimated interest rate rules and optimal feedback descriptions of monetary policy. We focus on two types of uncertainty: (i) unstructured model uncertainty reflected in additive...

I study the problem of regulating a network of interdependent financial institutions that is prone to contagion when there is uncertainty regarding its precise structure. I show that such uncertainty reduces the scope for welfare-improving interventions. While improving network transparency...

I study 46 vintages of FRB/US, the principal macro model used by Federal Reserve Board staff for forecasting and policy analysis, as measures of real-time model uncertainty. I also study the implications of model uncertainty for the robustness of commonly applied, simple monetary policy rules. I...

This paper provides a new technique for representing discrete time nonlinear dynamic stochastic time invariant maps. Using this new series representation, the paper augments the usual solution strategy with an additional set of constraints thereby enhancing algorithm reliability. The paper also...

We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The...

This paper compares the functionality, accuracy, computational efficiency, and practicalities of alternative approaches to solving linear rational expectations models, including the procedures of (Sims, 1996), (Anderson and Moore, 1983), (Binder and Pesaran, 1994), (King and Watson, 1998),...