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A New Way to Quantify the Effect of Uncertainty

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Abstract

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.

Suggested Citation

  • Richter, Alexander & Throckmorton, Nathaniel, 2017. "A New Way to Quantify the Effect of Uncertainty," Working Papers 1705, Federal Reserve Bank of Dallas, revised 23 Feb 2018.
  • Handle: RePEc:fip:feddwp:1705
    DOI: 10.24149/wp1705r1
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    References listed on IDEAS

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    1. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    2. Edward P. Herbst & Frank Schorfheide, 2016. "Bayesian Estimation of DSGE Models," Economics Books, Princeton University Press, edition 1, number 10612.
    3. Zhiguo He & Arvind Krishnamurthy, 2014. "A Macroeconomic Framework for Quantifying Systemic Risk," NBER Working Papers 19885, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    Endogenous uncertainty; stochastic volatility; particle filter; zero lower bound;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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