IDEAS home Printed from https://ideas.repec.org/p/kud/kucebi/2014.html
   My bibliography  Save this paper

Sensitivity to Calibrated Parameters

Author

Listed:
  • Thomas H. Jørgensen

    (CEBI, Department of Economics, University of Copenhagen)

Abstract

A common approach to estimation of dynamic 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. Jørgensen, 2021. "Sensitivity to Calibrated Parameters," CEBI working paper series 20-14, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    • Handle: RePEc:kud:kucebi:2014
    as

    Download full text from publisher

    File URL: https://www.econ.ku.dk/cebi/publikationer/working-papers/CEBI_WP_14-20.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Richard Blundell & Monica Costa Dias & Costas Meghir & Jonathan Shaw, 2016. "Female Labor Supply, Human Capital, and Welfare Reform," Econometrica, Econometric Society, vol. 84, pages 1705-1753, September.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Mr. Christopher Carroll & Mr. Martin Sommer & Mr. Jiri Slacalek, 2012. "Dissecting Saving Dynamics: Measuring Wealth, Precautionary, and Credit Effects," IMF Working Papers 2012/219, International Monetary Fund.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Mariacristina De Nardi & Eric French & John B. Jones, 2010. "Why Do the Elderly Save? The Role of Medical Expenses," Journal of Political Economy, University of Chicago Press, vol. 118(1), pages 39-75, February.
    6. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 63-84, Suppl. De.
    7. Iskrev, Nikolay, 2019. "What to expect when you're calibrating: Measuring the effect of calibration on the estimation of macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 99(C), pages 54-81.
    8. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
    9. John Karl Scholz & Ananth Seshadri & Surachai Khitatrakun, 2006. "Are Americans Saving "Optimally" for Retirement?," Journal of Political Economy, University of Chicago Press, vol. 114(4), pages 607-643, August.
    10. Marco Cagetti & Mariacristina De Nardi, 2006. "Entrepreneurship, Frictions, and Wealth," Journal of Political Economy, University of Chicago Press, vol. 114(5), pages 835-870, October.
    11. Florian Oswald, 2019. "The effect of homeownership on the option value of regional migration," Quantitative Economics, Econometric Society, vol. 10(4), pages 1453-1493, November.
    12. Pierre-Olivier Gourinchas & Jonathan A. Parker, 2002. "Consumption Over the Life Cycle," Econometrica, Econometric Society, vol. 70(1), pages 47-89, January.
    13. Jørgensen, Thomas H., 2013. "Structural estimation of continuous choice models: Evaluating the EGM and MPEC," Economics Letters, Elsevier, vol. 119(3), pages 287-290.
    14. Christopher D. Carroll, 1992. "The Buffer-Stock Theory of Saving: Some Macroeconomic Evidence," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(2), pages 61-156.
    15. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2017. "Measuring the Sensitivity of Parameter Estimates to Estimation Moments," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1553-1592.
    16. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    17. Yuichi Kitamura & Taisuke Otsu & Kirill Evdokimov, 2013. "Robustness, Infinitesimal Neighborhoods, and Moment Restrictions," Econometrica, Econometric Society, vol. 81(3), pages 1185-1201, May.
    18. Daniel Harenberg & Stefano Marelli & Bruno Sudret & Viktor Winschel, 2019. "Uncertainty quantification and global sensitivity analysis for economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 1-41, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
    2. Philipp Eisenhauer & Janos Gabler & Lena Janys, 2021. "Structural Models for Policy-Making: Coping with Parametric Uncertainty," ECONtribute Discussion Papers Series 082, University of Bonn and University of Cologne, Germany.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
    2. 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.
    3. Thomas H. Jørgensen, 2017. "Life-Cycle Consumption and Children: Evidence from a Structural Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 717-746, October.
    4. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2017. "Measuring the Sensitivity of Parameter Estimates to Estimation Moments," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1553-1592.
    5. Bo Honoré & Thomas Jørgensen & Áureo de Paula, 2020. "The informativeness of estimation moments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 797-813, November.
    6. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2020. "Transparency in Structural Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 711-722, October.
    7. Hui Chen & Michael Michaux & Nikolai Roussanov, 2020. "Houses as ATMs: Mortgage Refinancing and Macroeconomic Uncertainty," Journal of Finance, American Finance Association, vol. 75(1), pages 323-375, February.
    8. Lorenzo Pozzi, 2015. "The Time‐Varying Volatility of Earnings and Aggregate Consumption Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(4), pages 551-580, June.
    9. Philipp Eisenhauer & Lena Janys & Christopher Walsh & Janós Gabler, 2023. "Structural Models for Policy-Making," CRC TR 224 Discussion Paper Series crctr224_2023_484, University of Bonn and University of Mannheim, Germany.
    10. Marco Angrisani & Michael D. Hurd & Erik Meijer, 2012. "Investment Decisions in Retirement: The Role of Subjective Expectations," Working Papers wp274, University of Michigan, Michigan Retirement Research Center.
    11. Naoya Sueishi, 2022. "A Misuse of Specification Tests," Papers 2211.11915, arXiv.org.
    12. Hwang, Jungbin & Kang, Byunghoon & Lee, Seojeong, 2022. "A doubly corrected robust variance estimator for linear GMM," Journal of Econometrics, Elsevier, vol. 229(2), pages 276-298.
    13. Ivan Vidangos, 2009. "Household welfare, precautionary saving, and social insurance under multiple sources of risk," Finance and Economics Discussion Series 2009-14, Board of Governors of the Federal Reserve System (U.S.).
    14. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    15. Hero Ashman & Seth Neumuller, 2020. "Can Income Differences Explain the Racial Wealth Gap: A Quantitative Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 220-239, January.
    16. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
    17. Thomas H. Jørgensen, 2016. "Euler equation estimation: Children and credit constraints," Quantitative Economics, Econometric Society, vol. 7(3), pages 935-968, November.
    18. Chiara Dal Bianco, 2023. "Disability Insurance and the Effects of Return-to-work Policies," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 351-373, July.
    19. Krueger, D. & Mitman, K. & Perri, F., 2016. "Macroeconomics and Household Heterogeneity," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 843-921, Elsevier.
    20. Mariacristina De Nardi & Eric French & John Bailey Jones, 2016. "Savings After Retirement: A Survey," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 177-204, October.

    More about this item

    Keywords

    sensitivity; transparency; structural estimation; calibration; savings motives;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kud:kucebi:2014. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/cebkudk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.