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Identification of prior information via moment-matching


  • Sacht, Stephen


In this paper we apply a sensitivity analysis regarding two types of prior information considered within the Bayesian estimation of a standard hybrid New-Keynesian model. In particular, we shed a light on the impact of micro- and macropriors on the estimation outcome. First, we investigate the impact of the transformation of those model parameters which are bounded to the unit interval, in order to allow for a more diffuse prior distribution. Second, we combine the Moment-Matching (MM, Franke et al. (2012)) and Bayesian technique in order to evaluate macropriors. In this respect we define a two-stage estimation procedure - the so-called Moment-Matching based Bayesian (MoMBay) estimation approach - where we take the point estimates evaluated via MM and consider them as prior mean values of the parameters within Bayesian estimation. We show that while (transformed) micropriors are often used in the literature, applying macropriors evaluated via the MoMBay approach leads to a better fit of the structural model to the data. Furthermore, there is evidence for intrinsic (degree of price indexation) rather than extrinsic (autocorrelation in the shock process) persistence - an observation which stands in contradiction to the results documented in the recent literature.

Suggested Citation

  • Sacht, Stephen, 2014. "Identification of prior information via moment-matching," Economics Working Papers 2014-04, Christian-Albrechts-University of Kiel, Department of Economics.
  • Handle: RePEc:zbw:cauewp:201404

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    References listed on IDEAS

    1. Franke, Reiner & Jang, Tae-Seok & Sacht, Stephen, 2015. "Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 126-154.
    2. Sacht, Stephen, 2014. "Analysis of Various Shocks within the High-Frequency Versions of the Baseline New-Keynesian Model," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100372, Verein für Socialpolitik / German Economic Association.
    3. Lombardi, Marco J. & Nicoletti, Giulio, 2012. "Bayesian prior elicitation in DSGE models: Macro- vs micropriors," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 294-313.
    4. Sacht, Stephen, 2014. "Optimal monetary policy responses and welfare analysis within the highfrequency New-Keynesian framework," Economics Working Papers 2014-03, Christian-Albrechts-University of Kiel, Department of Economics.
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    Cited by:

    1. Franke, Reiner & Jang, Tae-Seok & Sacht, Stephen, 2015. "Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 126-154.

    More about this item


    Bayesian estimation; moment-matching estimation; mombay estimation; New-Keynesian model; micropriors; macropriors;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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