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Posterior Distribution of Nondifferentiable Functions

Author

Listed:
  • Toru Kitagawa

    (University College London)

  • José Luis Montiel Olea

    (Columbia University)

  • Jonathan Payne

    (New York University)

  • Amilcar Velez

    (Central Bank of Peru)

Abstract

This paper examines the asymptotic behavior of the posterior distribution of a possibly nondifferentiable function g(θ), where θ is a finite-dimensional parameter of either a parametric or semiparametric model. The main assumption is that the distribution of a suitable estimator θ̂n, its bootstrap approximation, and the Bayesian posterior for θ all agree asymptotically.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Toru Kitagawa & José Luis Montiel Olea & Jonathan Payne & Amilcar Velez, 2019. "Posterior Distribution of Nondifferentiable Functions," Working Papers 147, Peruvian Economic Association.
    • Handle: RePEc:apc:wpaper:147
    as

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    References listed on IDEAS

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    3. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
    4. Christopher D. Walker, 2024. "Semiparametric Bayesian Inference for a Conditional Moment Equality Model," Papers 2410.16017, arXiv.org.

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