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Measuring monetary policy with empirically grounded identifying restrictions

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  • Piyachart Phiromswad

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    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

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    File URL: http://hdl.handle.net/10.1007/s00181-013-0692-7
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    Bibliographic Info

    Article provided by Springer in its journal Empirical Economics.

    Volume (Year): 46 (2014)
    Issue (Month): 2 (March)
    Pages: 681-699

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    Handle: RePEc:spr:empeco:v:46:y:2014:i:2:p:681-699

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    Related research

    Keywords: Monetary policy; Monetary policy shock; Graph theory; Causality; Causal search; PC algorithm; CPC algorithm; SVAR; Recursiveness assumption; C30; C32; C51;

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