A New Way to Quantify the Effect of Uncertainty

43 Pages Posted: 18 May 2017 Last revised: 29 Apr 2020

Date Written: May, 2017


This paper develops a new way to quantify the effect of uncertainty and other higher-order moments. First, we estimate a nonlinear model using Bayesian methods with data on uncertainty, in addition to common macro time series. This key step allows us to decompose the exogenous and endogenous sources of uncertainty, calculate the effect of volatility following the cost of business cycles literature, and generate data-driven policy functions for any higherorder moment. Second, we use the Euler equation to analytically decompose consumption into several terms--expected consumption, the ex-ante real interest rate, and the ex-ante variance and skewness of future consumption, technology growth, and inflation--and then use the policy functions to filter the data and create a time series for the effect of each term. We apply our method to a familiar New Keynesian model with a zero lower bound constraint on the nominal interest rate and two stochastic volatility shocks, but it is adaptable to a broad class of models.

Keywords: Endogenous uncertainty, stochastic volatility, particle filter, zero lower bound

JEL Classification: C11, D81, E32, E58

Suggested Citation

Richter, Alexander W. and Throckmorton, Nathaniel A., A New Way to Quantify the Effect of Uncertainty (May, 2017). FRB of Dallas Working Paper No. 1705, Available at SSRN: https://ssrn.com/abstract=2970281 or http://dx.doi.org/10.24149/wp1705r1

Alexander W. Richter (Contact Author)

Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States
214-922-5360 (Phone)

HOME PAGE: http://alexrichterecon.com

Nathaniel A. Throckmorton

William & Mary ( email )

Economics Department
P.O. Box 8795
Williamsburg, VA 23187
United States

HOME PAGE: http://nathrockmorton.people.wm.edu/

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