The impact of central bank transparency on systemic risk—Evidence from Central and Eastern Europe

Andrieş, Alin Marius; Nistor, Simona; Sprincean, Nicu

doi:10.1016/j.ribaf.2018.06.002

Cited by 19 publications

(10 citation statements)

References 44 publications

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“…The findings of the study are in line with Bruyckere et al (2013). Finally, regulatory quality is insignificant in explaining variations in MES (Andrieş et al, 2018).…”

Section: Country Level Determinants Analysis Of ∆Covar Based On System Gmmsupporting

confidence: 77%

“…The first step in controlling systemic instability is to correctly and comprehensively identify systemically important financial institutions followed by identification of factors that influence systemic risk (Andrieş et al, 2018;Huang et al, 2019). Recent studies try to shed light on the drivers and mechanisms of systemic risk.…”

Section: Determinants Of Systemic Riskmentioning

confidence: 99%

“…In addition to that, Brownlees and Engle (2012) set the daily loss to be minus two percent. Moreover, Andries et al (Andrieş et al, 2018) used weekly frequency of data and aggregated within a year to match the frequency of independent variables. Consistent with Brownlees and Engle (2012), the threshold event is set at −2% and daily frequency of data is used.…”

Section: Marginal Expected Shortfallmentioning

confidence: 99%

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MES vs ∆CoVaR: Empirical evidence from Pakistan

Hanif

Yousaf

Waheed

et al. 2021

Cogent Business & Management

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The global financial crisis unveiled that inadequate analysis of risk can annihilate the financial system and repercussions can encompass the whole economy. Pakistan is one of the developing economies that has experienced robust growth in the banking sector. This hard earned growth can only be sustained by adequately examining the risk exposure of the financial system. Consistent with this purview, this study attempts to comprehensively analyse for the first time, the systemic importance of financial institutions of Pakistan using ∆CoVaR and MES. Moreover, the study employs System GMM to analyze the bank, sector and country level determinants of systemic risk measures. The findings of the study signify that MES and ∆CoVaR measures identify different institutions as systemically important. Similarly, the influence of variables also changes with change in the systemic measure. The estimation of determinants of systemic risk outline that non-interst income is insignificant when MES is used as measure of systemic risk but the same turns significant for ∆CoVaR. The impact of deposit ratio also changes across the measures of systemic risk. Concentration has positive impact on MES but negatively influences ∆CoVaR. Finally, the impact of bank claims also varies across the measures of systemic risk. The study contributes to the literature by highlighting the complementary nature of systemic risk measures for the first time in a developing economy like Pakistan. The study also identifies important relationships necessary ABOUT THE AUTHORS

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“…The findings of the study are in line with Bruyckere et al (2013). Finally, regulatory quality is insignificant in explaining variations in MES (Andrieş et al, 2018).…”

Section: Country Level Determinants Analysis Of ∆Covar Based On System Gmmsupporting

confidence: 77%

Section: Determinants Of Systemic Riskmentioning

confidence: 99%

Section: Marginal Expected Shortfallmentioning

confidence: 99%

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MES vs ∆CoVaR: Empirical evidence from Pakistan

Hanif

Yousaf

Waheed

et al. 2021

Cogent Business & Management

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“…They were the most aggressively economically developing countries in the sample with the least stable flow of funds from abroad. In addition, for these countries, several domestic crisis-like events may be enumerated (see Kubinschi and Barnea 2016;Andrieş et al 2018;Barkauskaite et al 2018;and Karaś and Szczepaniak 2019). It was for these countries that we observed the largest volatility of the SIN measure.…”

Section: Data and Empirical Resultsmentioning

confidence: 99%

Systemic Illiquidity Noise-Based Measure—A Solution for Systemic Liquidity Monitoring in Frontier and Emerging Markets

Dziwok

Karaś

2021

Risks

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The paper presents an alternative approach to measuring systemic illiquidity applicable to countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize the curve-fitting error as an indicator of financial system illiquidity. We empirically apply our method to a set of 10 divergent Central and Eastern Europe countries—Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia—in the period of 2006–2020. The results show three periods of increased risk in the sample period: the global financial crisis, the European public debt crisis, and the COVID-19 pandemic. They also allow us to identify three divergent sets of countries with different systemic liquidity risk characteristics. The analysis also illustrates the impact of the introduction of the euro on systemic illiquidity risk. The proposed methodology may be of consequence for financial system regulators and macroprudential bodies: it allows for contemporaneous monitoring of discussed risk at a minimal cost using well-known models and easily accessible data.

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“…The fragility of financial system can be avoided by adequately analyzing the risk exposure of the financial institutions (Andrieş et al, 2018). The risks faced by the organizations are broadly categorized as systematic and idiosyncratic risk along with the comparatively novel manifestation of systemic risk.…”

Section: Introductionmentioning

confidence: 99%