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Sensitivity to Calibrated Parameters

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  • Thomas H. J{o}rgensen

Abstract

A common approach to estimation of economic models is to calibrate a sub-set 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 (2002) and show that some estimates are sensitive to calibrations.

Suggested Citation

  • Thomas H. J{o}rgensen, 2020. "Sensitivity to Calibrated Parameters," Papers 2004.12100, arXiv.org, revised Mar 2021.
    • Handle: RePEc:arx:papers:2004.12100
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    References listed on IDEAS

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    10. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
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    Cited by:

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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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