Second-Order Approximation of Dynamic Models with Time-Varying Risk

Working Paper: NBER ID: w16633

Authors: Gianluca Benigno; Pierpaolo Benigno; Salvatore Nistic

Abstract: This paper provides first and second-order approximation methods for the solution of non-linear dynamic stochastic models in which the exogenous state variables follow conditionally-linear stochastic processes displaying time-varying risk. The first-order approximation is consistent with a conditionally-linear model in which risk is still time-varying but has no distinct role -- separated from the primitive stochastic disturbances -- in influencing the endogenous variables. The second-order approximation of the solution, instead, is sufficient to get this role. Moreover, risk premia, evaluated using only a first-order approximation of the solution, will be also time varying.

Keywords: Dynamic models; Time-varying risk; Stochastic processes; Economic policy

JEL Codes: C63


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
time-varying risk (C41)endogenous variables (C29)
time-varying volatility (C22)endogenous variables (C29)
time-varying risk (C41)risk premia (G22)
time-varying volatility (C22)risk premia (G22)

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