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The State Level Impact of Uncertainty Shocks

Author

Listed:
  • Haroon Mumtaz

    (Queen Mary University of London)

  • Laura Sunder-Plassmann

    (University of Copenhagen)

  • Angeliki Theophilopoulou

    (University of Westminster)

Abstract

This paper uses a FAVAR model with stochastic volatility to estimate the impact of uncertainty shocks on real income growth in US states. The results suggest that there is a large degree of heterogeneity in the magnitude and the persistence of the response to uncertainty shocks across states. The response is largest in Michigan, Indiana and Arkansas while the real income in New York, Alaska and New Mexico seems least sensitive to uncertainty. We relate the cross section of responses to state-level characteristics and find that the magnitude of the decline in income is largest in states with a large share of manufacturing, agriculture and construction industries, a high fiscal deficit and a more volatile housing market. In contrast, a higher share of mining industries and larger inter-governmental fiscal transfers ameliorate the impact of uncertainty.

Suggested Citation

  • Haroon Mumtaz & Laura Sunder-Plassmann & Angeliki Theophilopoulou, 2016. "The State Level Impact of Uncertainty Shocks," Working Papers 793, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:793
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    References listed on IDEAS

    as
    1. Haroon Mumtaz & Konstantinos Theodoridis, 2014. "The Changing Transmission of Uncertainty shocks in the US: An Empirical Analysis," Working Papers 735, Queen Mary University of London, School of Economics and Finance.
    2. Shoag, Daniel & Veuger, Stan, 2016. "Uncertainty and the geography of the great recession," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 84-93.
    3. 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.
    4. Haroon Mumtaz & Francesco Zanetti, 2013. "The Impact of the Volatility of Monetary Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 535-558, June.
    5. Haroon Mumtaz & Konstantinos Theodoridis, 2015. "The International Transmission Of Volatility Shocks: An Empirical Analysis," Journal of the European Economic Association, European Economic Association, vol. 13(3), pages 512-533, June.
    6. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
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    9. Gerald A. Carlino & Robert H. DeFina, 1997. "The differential regional effects of monetary policy: evidence from the U.S. States," Working Papers 97-12, Federal Reserve Bank of Philadelphia.
    10. 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.
    11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    FAVAR; Stochastic volatility; Uncertainty shocks; Regional effects;
    All these keywords.

    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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