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Methods for Measuring Expectations and Uncertainty in Markov-Switching Models

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  • Bianchi, Francesco

Abstract

I develop a toolbox to analyze the properties of multivariate Markov-switching models. I first derive analytical formulas for the evolution of first and second moments, taking into account the possibility of regime changes. The formulas are then used to characterize the evolution of expectations and uncertainty, the propagation of the shocks, the contribution of the shocks to the overall volatility, and the welfare implications of regime changes in general equilibrium models. Then, I show how the methods can be used to capture the link between uncertainty and the state of the economy. Finally, I generalize Campbell's VAR implementation of Campbell and Shiller's present value decomposition to allow for parameter instability. The applications reveal the importance of taking into account the effects of regime changes on agents' expectations, welfare, and uncertainty. All results are derived analytically, do not require numerical integration, and are therefore suitable for structural estimation.

Suggested Citation

  • Bianchi, Francesco, 2013. "Methods for Measuring Expectations and Uncertainty in Markov-Switching Models," CEPR Discussion Papers 9705, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:9705
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    Citations

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    Cited by:

    1. Francesco Bianchi & Leonardo Melosi, 2017. "Escaping the Great Recession," American Economic Review, American Economic Association, vol. 107(4), pages 1030-1058, April.
    2. Bianchi, Francesco & Melosi, Leonardo, 2019. "The dire effects of the lack of monetary and fiscal coordination," Journal of Monetary Economics, Elsevier, vol. 104(C), pages 1-22.
    3. Alexander Karalis Isaac, 2014. "Higher moments of MSVARs and the business cycle," BCAM Working Papers 1405, Birkbeck Centre for Applied Macroeconomics.
    4. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    5. repec:eee:dyncon:v:93:y:2018:i:c:p:277-296 is not listed on IDEAS
    6. Castelnuovo, Efrem & Pellegrino, Giovanni, 2018. "Uncertainty-dependent effects of monetary policy shocks: A new-Keynesian interpretation," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 277-296.
    7. Francesco Bianchi & Howard Kung & Mikhail Tirskikh, 2019. "The Origins and Effects of Macroeconomic Uncertainty," 2019 Meeting Papers 245, Society for Economic Dynamics.
    8. Bianchi, Francesco & Kung, Howard & Tirskikh, Mikhail, 2019. "The Origins and Effects of Macroeconomic Uncertainty," CEPR Discussion Papers 13450, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Bayesian Methods; DSGE; Impulse responses; Markov-switching; Uncertainty; VAR; Welfare;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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