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Measuring monetary policy with empirically grounded identifying restrictions

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  • Piyachart Phiromswad

Abstract

This article reevaluates the impulse response functions (IRFs) to a monetary policy shock of the structural vector autoregression (SVAR). Identifying restrictions are specified and justified based on empirical evidence,i.e., conditional independence relations of variables, which is an important dimension that a good model must be able to mimic. The empirical-based approach is able to significant narrow down the set of admissible causal orders to identify the IRFs to a monetary policy shock (from 2,482 to 8). I find that most of the qualitative “stylized” features reported in the literature remain intact. However, the quantitative predictions are much less certain than what is commonly perceived. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Piyachart Phiromswad, 2014. "Measuring monetary policy with empirically grounded identifying restrictions," Empirical Economics, Springer, vol. 46(2), pages 681-699, March.
  • Handle: RePEc:spr:empeco:v:46:y:2014:i:2:p:681-699
    DOI: 10.1007/s00181-013-0692-7
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    Cited by:

    1. Phiromswad, Piyachart, 2015. "Measuring monetary policy with empirically grounded restrictions: An application to Thailand," Journal of Asian Economics, Elsevier, vol. 38(C), pages 104-113.
    2. Nikolay Arefiev, 2016. "Graphical Interpretations of Rank Conditions For Identification of Linear Gaussian Models," HSE Working papers WP BRP 124/EC/2016, National Research University Higher School of Economics.
    3. Wongboonsin, Kua & Phiromswad, Piyachart, 2017. "Searching for empirical linkages between demographic structure and economic growth," Economic Modelling, Elsevier, vol. 60(C), pages 364-379.
    4. Piyachart Phiromswad & Takeshi Yagihashi, 2016. "Empirical identification of factor models," Empirical Economics, Springer, vol. 51(2), pages 621-658, September.
    5. Nikolay Arefiev, 2016. "Identification of Monetary Policy Shocks within a Svar Using Restrictions Consistent with a DSGE Model," HSE Working papers WP BRP 125/EC/2016, National Research University Higher School of Economics.

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    More about this item

    Keywords

    Monetary policy; Monetary policy shock; Graph theory; Causality; Causal search; PC algorithm; CPC algorithm; SVAR; Recursiveness assumption; C30; C32; C51;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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