A model of the Eurosystem's operational framework and the euro overnight interbank market

Hauck, Achim; Neyer, Ulrike

doi:10.1016/j.ejpoleco.2013.06.010

Cited by 10 publications

(6 citation statements)

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“…Furthermore, according to Go Tamakoshi and Shigeyuki Hamori (2014), the Eonia rate plays a crucial role in signalling the target of monetary policy, while the Euribor rate provides outstanding interest rates for various financial products, i.e., the 3-month Euribor rate is used because it has been a focus in recent studies of interbank money markets. Finally, Achim Hauck and Ulrike Neyer (2014) explain how the Eurosystem's liquidity measures to reactivate the interbank market could conflict with aims from the monetary policy perspective and financial stability perspective. Our empirical setup for the analysis of the dynamics in the relationship between the overnight rate and the shortterm interest rates is given.…”

Section: Literature Reviewmentioning

confidence: 99%

The role of Eonia in the dynamics of short-term interbank rates

2020

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To signal monetary policies and market expectations, we apply a fractionally cointegrated vector autoregressive (FCVAR) model, aiming to analyse the expectations hypothesis of term structure (EHTS), persistence in the Euro OverNight Index Average (Eonia) spread and permanent-transitory decomposition using a novel approach. We use a monthly frequency sample for the 3month Euribor rate and Eonia rate, covering the period from January 1999 to February 2019. The results obtained confirm the EHTS and show evidence of a high persistence of the spread, which means that shocks may impede effectiveness in monetary policy and that the European Central Bank (ECB) loses control over interest rates. Additionally, according to permanent-transitory decomposition, we determine that the Eonia rate has a permanent component and thus dominates the common trend in the cointegration system. In sum, if the ECB wants to keep the interbank market interest rates under control, it must contemplate the evolution of the Eonia rate.

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Section: Literature Reviewmentioning

confidence: 99%

The role of Eonia in the dynamics of short-term interbank rates

2020

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“…Hence, an increase in the marginal lending rate decreases the liquidity supply at interbank markets. 7 Some studies introduce other kinds of frictions such as aggregate liquidity shocks (Allen et al 2009), Knightian uncertainty (Pritsker 2013), or participation costs at the interbank market (Hauck and Neyer 2014). Peiris and Vardoulakis (2013) allow for the possibility that agents can choose to default on their loan repayments and show that trade fails if the level of reserves is too low.…”

Section: Introductionmentioning

confidence: 99%

The effect of the central bank’s standing facilities on interbank lending and bank liquidity holding

Näther

2018

Econ Theory

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How does the central bank influence interbank lending? The central bank's policy rates determine the attractiveness of the standing facilities compared with the interbank market. Therefore, by choosing the policy rates the central bank affects the number of banks using the standing facilities and the number of banks using the interbank market. There is also a second channel. The policy rates may influence bank liquidity holding and thus the chances that interbank lending occurs. To address both channels, bank liquidity holding is endogenous in the presented model. The results show that liquidity is not held to insure against idiosyncratic risk but to lend to the interbank market in case counterparty risk is not too high. If banks expect interbank lending to be sufficiently likely and profitable, a smooth liquidity transfer at the interbank market is guaranteed. The central bank can create such a situation under the constraint that counterparty risk is moderate and counterparty risk perceptions are not too distorted. If, however, counterparty risk is perceived to be too large, this may result in liquidity hoarding. KeywordsInterbank market • Liquidity holding • Standing facilities JEL Classification E43 • E58 • G21 The author would like to thank an anonymous referee, Diemo Dietrich, Uwe Vollmer, Harald Wiese, and the participants of the 8th RGS Doctoral Conference in Economics, the Doctoral Seminars at IWH and Leipzig University, and the Annual Congress 2015 of the Swiss Society of Economics and Statistics for helpful comments and suggestions, while retaining responsibility for all errors..

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“…Wetherilt [2003] Hassler and Nautz [2008] studied the spread of EONIA analysing the integration and long memory in time series. The papers by Schianchi and Verga [2006], as well as by Hauck and Neyer [2014] provided the theoretical background for the analysis of factors determining the spread. Würtz [2003] pointed out the role of liquidity expectations in forming interbank rates.…”

Section: Polonia Rate and Monetary Policymentioning

confidence: 99%

Determinants of the Spread Between Polonia Rate and the Reference Rate – Dynamic Model Averaging Approach

Kliber¹

2017

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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Summary:In the paper, we consider the factors that determine the overnight interest rates in the Polish interbank market. Since 2008 the Polish central bank has been trying to place the POLONIA rate around the NBP reference rate, mainly by influencing the liquidity conditions through open market operations. We identify a set of factors that determine the overnight rates, namely: liquidity, expectations, confidence in the banking sector and central bank operations. To this end we have used dynamic model averaging method, which allows to identify the set of variables that provide the best description of the explanatory variable. The results reveal that before the outbreak of financial crisis in 2008 the spread between POLONIA rate and reference rate could be explained mainly by liquidity conditions. After the crisis had begun, the importance of liquidity factor decreased and the expectations played a more important role in determining the spread.Keywords: monetary policy, POLONIA rate, interbank rates, dynamic model averaging, liquidity in the interbank market.Streszczenie: W artykule rozważane są czynniki determinujące stopy overnight na polskim rynku międzybankowym, przy czym jako miernik ich wysokości przyjmuje się stawkę PO-LONIA. Od 2008 roku celem operacyjnym NBP jest ustalanie stawki POLONIA na poziomie zbliżonym do stopy referencyjnej NBP. Wskazano zbiór czynników wpływających na stopy overnight, a mianowicie płynność, oczekiwania i zaufanie na rynku międzybankowym. Starano się ustalić, w jakim stopniu każdy z tych czynników wpływał na stawkę POLONIA w latach 2006-2016. Wykorzystano w tym celu metodę dynamicznego uśredniania modeli (dynamic model averaging), która pozwala ustalić, jaki zbiór zmiennych niezależnych w najlepszym stopniu objaśnia zmienną objaśnianą. Wyniki pokazują, że przed wybuchem kryzysu finansowego w 2008 roku spread między stawką POLONIA i stopą referencyjną najlepiej 108Paweł Kliber wyjaśniała sytuacja płynnościowa. Po rozpoczęciu kryzysu wzrosło znaczenie oczekiwań dotyczących przyszłych stóp procentowych.Słowa kluczowe: polityka monetarna, stawka POLONIA, stopy międzybankowe, dynamiczne uśrednianie modeli, płynność na rynku międzybankowym.

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A model of the Eurosystem's operational framework and the euro overnight interbank market

Cited by 10 publications

References 67 publications

The role of Eonia in the dynamics of short-term interbank rates

The role of Eonia in the dynamics of short-term interbank rates

The effect of the central bank’s standing facilities on interbank lending and bank liquidity holding

Determinants of the Spread Between Polonia Rate and the Reference Rate – Dynamic Model Averaging Approach

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