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Calibration and the estimation of macroeconomic models

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  • Nikolay Iskrev

Abstract

We propose two measures of the impact of calibration on the estimation of macroeconomic models.The first quantifies the amount of information introduced with respect to each estimated parameter as a result of fixing the value of one or more calibrated parameters.The second is a measure of the sensitivity of parameter estimates to perturbations in the calibration values.The purpose of the measures is to show researchers how much and in what way calibration affects their estimation results – by shifting the location and reducing the spread of the marginal posterior distributions of the estimated parameters.This type of analysis is often appropriate since macroeconomists do not always agree on whether and how to calibrate structural parameters in macroeconomic models. The methodology is illustrated using the models estimated in Smets and Wouters (2007) and Schmitt-Grohé and Uribe (2012).

Suggested Citation

  • Nikolay Iskrev, 2018. "Calibration and the estimation of macroeconomic models," Working Papers REM 2018/34, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    • Handle: RePEc:ise:remwps:wp0342018
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    References listed on IDEAS

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    1. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    2. Jae-Young Kim, 1998. "Large Sample Properties of Posterior Densities, Bayesian Information Criterion and the Likelihood Principle in Nonstationary Time Series Models," Econometrica, Econometric Society, vol. 66(2), pages 359-380, March.
    3. 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.
    4. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
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    Cited by:

    1. Dong, Xue & Minford, Patrick & Meenagh, David, 2019. "How important are the international financial market imperfections for the foreign exchange rate dynamics: A study of the sterling exchange rate," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 62-80.

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    More about this item

    Keywords

    DSGE models; information content; calibration;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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