Peer Effects in Central Banking

Roman Horvath

No 2020/24, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

Abstract: We provide a new explanation for why central banks have become transparent over the last three decades. We apply recently developed social interaction panel regression models for the observational data, which allow the identification of peer effects. The identification is based on variations in the past monetary policy regime exogenously determined with respect to transparency. Previous literature has argued that domestic factors such as macroeconomic stability were behind the trend toward greater transparency. In contrast, our results indicate that transparency primarily increased because of a favorable global environment and, importantly, because of the peer effects among central bankers. Central bankers thus learned from each other's experiences regarding transparency. To our knowledge, our paper is the first econometric analysis of peer effects among public institutions or in the macroeconomic literature.

Keywords: peer effects; central banks; transparency (search for similar items in EconPapers)
JEL-codes: C31 D83 E58 (search for similar items in EconPapers)
Pages: 57 pages
Date: 2020-08, Revised 2020-08
New Economics Papers: this item is included in nep-cba, nep-mac, nep-mon and nep-net
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ies.fsv.cuni.cz/en/veda-vyzkum/working-papers/6270 (application/pdf)

Related works:
Journal Article: Peer Effects in Central Banking (2020)
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:fau:wpaper:wp2020_24

Access Statistics for this paper

More papers in Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies Contact information at EDIRC.
Bibliographic data for series maintained by Natalie Svarcova ().