Central banks' voting contest

Wojciech Charemza

MPRA Paper from University Library of Munich, Germany

Abstract: This paper compares how effective different voting algorithms are for the decisions taken by monetary policy councils. A voting activity index is proposed and computed as the ratio of the number of all possible decisions to the total number of different combinations of decisions available to a given composition of an MPC. The voting systems considered are these used by the US Federal Reserve Board and the central banks of the UK, Australia, Canada, Sweden and Poland. In the dynamic simulation model, which emulates voting decisions, the heterogeneous agents act upon individual forecast signals and optimise a Taylor-like decision function. The selection criterion is based on the simulated probability of staying within the bounds that define the inflationary target. The general conclusion is that the voting algorithm used by the Bank of Sweden is the best given the criteria applied, especially when inflation is initially outside the target bounds. It is observed that a decrease in inflation forecast uncertainty, which is inversely proportional to the correlation between the forecast signals delivered to members of the monetary policy board, makes the voting less effective.

Keywords: voting algorithms; monetary policy; inflation targeting; forecast uncertainty (search for similar items in EconPapers)
JEL-codes: D72 E4 E47 E58 (search for similar items in EconPapers)
Date: 2020-05-31
New Economics Papers: this item is included in nep-cba, nep-mac, nep-mon and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/101205/1/MPRA_paper_101205.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:101205

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().