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Sensitivity to Calibrated Parameters

Author

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  • Thomas H. Jørgensen

    (CEBI, Department of Economics, University of Copenhagen)

Abstract

A common approach to estimation of dynamic economic models is to calibrate a subset of model parameters and keep them fixed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model, but estimation time often makes a systematic investigation of the sensitivity to calibrated parameters infeasible. I propose a simple and computationally low-cost measure of the sensitivity of parameters and other objects of interest to the calibrated parameters. In the main empirical application, I revisit the analysis of life-cycle savings motives in Gourinchas and Parker (

Suggested Citation

  • Thomas H. Jørgensen, 2023. "Sensitivity to Calibrated Parameters," The Review of Economics and Statistics, MIT Press, vol. 105(2), pages 474-481, March.
  • Handle: RePEc:tpr:restat:v:105:y:2023:i:2:p:474-481
    DOI: 10.1162/rest_a_01054
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    Cited by:

    1. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
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    3. Eisenhauer, Philipp & Gabler, Janos & Janys, Lena, 2021. "Structural Models for Policy-Making: Coping with Parametric Uncertainty," IZA Discussion Papers 14317, Institute of Labor Economics (IZA).
    4. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust Decision-Making Under Risk and Ambiguity," ECONtribute Discussion Papers Series 104, University of Bonn and University of Cologne, Germany.

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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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