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Striated Metropolis–Hastings sampler for high-dimensional models

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  • Waggoner, Daniel F.
  • Wu, Hongwei
  • Zha, Tao

Abstract

Having efficient and accurate samplers for simulating the posterior distribution is crucial for Bayesian analysis. We develop a generic posterior simulator called the “dynamic striated Metropolis–Hastings (DSMH)” sampler. Grounded in the Metropolis–Hastings algorithm, it pools the strengths from the equi-energy and sequential Monte Carlo samplers while avoiding the weaknesses of the standard Metropolis–Hastings algorithm and those of importance sampling. In particular, the DSMH sampler possesses the capacity to cope with extremely irregular distributions that contain winding ridges and multiple peaks; and it is robust to how the sampling procedure progresses across stages. The high-dimensional application studied in this paper provides a natural platform for testing any generic sampler.

Suggested Citation

  • Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
  • Handle: RePEc:eee:econom:v:192:y:2016:i:2:p:406-420
    DOI: 10.1016/j.jeconom.2016.02.007
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    Cited by:

    1. Hee Soo (test record) Kim & Christian Matthes & Toan Phan, 2011. "Extreme Weather and the Macroeconomy," Working Paper 21-14, Federal Reserve Bank of Richmond.
    2. Kirstin Hubrich & Daniel F. Waggoner, 2022. "The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework," FRB Atlanta Working Paper 2022-5, Federal Reserve Bank of Atlanta.
    3. Kaiji Chen & Patrick Higgins & Tao Zha, 2021. "Cyclical Lending Standards: A Structural Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 283-306, October.
    4. Kaiji Chen & Patrick Higgins & Tao Zha, 2021. "Cyclical Lending Standards: A Structural Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 283-306, October.
    5. Andrle, Michal & Plašil, Miroslav, 2018. "Econometrics with system priors," Economics Letters, Elsevier, vol. 172(C), pages 134-137.
    6. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.

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    More about this item

    Keywords

    Dynamic striation adjustments; Simultaneous equations; Monetary policy; Inflation coefficient; Winding ridges; Multiple peaks; Independent striated draws; Irregular posterior distribution; Importance weights; Tempered likelihood; Effective sample size;
    All these keywords.

    JEL classification:

    • 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
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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