Measuring monetary policy with empirically grounded identifying restrictions

Piyachart Phiromswad ()

Empirical Economics, 2014, vol. 46, issue 2, 699 pages

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

Keywords: Monetary policy; Monetary policy shock; Graph theory; Causality; Causal search; PC algorithm; CPC algorithm; SVAR; Recursiveness assumption; C30; C32; C51 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:empeco:v:46:y:2014:i:2:p:681-699

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DOI: 10.1007/s00181-013-0692-7

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