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The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach

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  • ANDREA CARRIERO
  • HAROON MUMTAZ
  • KONSTANTINOS THEODORIDIS
  • ANGELIKI THEOPHILOPOULOU

Abstract

A growing literature considers the impact of uncertainty using SVAR models that include proxies for uncertainty shocks as endogenous variables. In this paper, we consider the impact of measurement error in these proxies on the estimated impulse responses. We show via a Monte Carlo experiment that measurement error can result in attenuation bias in impulse responses. In contrast, the proxy SVAR that uses the uncertainty shock proxy as an instrument does not suffer from this bias. Applying this latter method to the Bloom (2009) data set results in impulse responses to uncertainty shocks that are larger in magnitude and more persistent than those obtained from a recursive SVAR.

Suggested Citation

  • Andrea Carriero & Haroon Mumtaz & Konstantinos Theodoridis & Angeliki Theophilopoulou, 2015. "The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(6), pages 1223-1238, September.
    • Handle: RePEc:wly:jmoncb:v:47:y:2015:i:6:p:1223-1238
    DOI: 10.1111/jmcb.12243
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    References listed on IDEAS

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    1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    2. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    3. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
    4. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    5. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    6. Rotemberg, Julio J, 1982. "Sticky Prices in the United States," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1187-1211, December.
    7. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
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    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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