Financial stability, competitiveness and banks' innovation capacity: Evidence from the Global Financial Crisis

Degl’Innocenti, Marta; Grant, Kevin; Šević, Aleksandar; Tzeremes, Nickolaos

doi:10.1016/j.irfa.2018.07.009

Cited by 35 publications

(11 citation statements)

References 82 publications

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“…Recent developments in nonparametric efficiency analyses have motivated the use of the conditional efficiency framework (Daraio and Simar, 2005; Simar and Wilson, 2013, 2015). Meanwhile, several pieces of empirical research have transposed the conditional efficiency framework into the banking sector (e.g., Halkos and Tzeremes, 2011; Badin et al., 2012; Tzeremes, 2015; Matousek and Tzeremes, 2016; Degl'Innocenti et al., 2017, 2018; Daraio et al., 2018). Indeed, Halkos and Tzeremes (2011) argue that conditional efficiency may be of great interest to cross‐country bank efficiency studies since it allows efficiency measurements toward capturing environmental influences to be adjusted.…”

Section: Related Literaturementioning

confidence: 99%

Technical and managerial efficiency assessment of European banks using a conditional nonparametric approach

Minviel

Bouheni

2020

Int Trans Operational Res

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This paper investigates the conditional technical and managerial efficiency of European banks through the lending channel using a robust nonparametric frontier approach. We select the largest commercial banks in France, Germany, the United Kingdom, Italy, Spain, and Greece over the period 2005-2013 for our study. The estimates show significant technical inefficiency in the use of available resources for banks in our sample. The overall measure of managerial efficiency suggests sound managerial performance. However, at a detailed level, we find that, for each country examined, banks exhibit large proportions of poor managerial performance. This may explain why some banks could not resist the 2008 financial crisis. Regarding institutional factors, we find capital requirements and bank size are associated with bank efficiency in a nonlinear manner. These findings provide support for contextual factors in determining bank efficiency and rethinking financial reforms.

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Section: Related Literaturementioning

confidence: 99%

Technical and managerial efficiency assessment of European banks using a conditional nonparametric approach

Minviel

Bouheni

2020

Int Trans Operational Res

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“…These results are identical to our previous findings. Tzeremes, 2018;Demirgüç-Kunt, Peria, & Tressel, 2020;Temin, 2010;Yuan, Liu, & Xie, 2010 In this section, we discuss whether our proposed models containing GEPU and regime switching could have different forecasting performances during the GFC crisis period. The results are presented in Table 10.…”

Section: Different Horizonsmentioning

confidence: 99%

Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models

Wang

et al. 2021

Journal of Forecasting

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This paper explores the effects of global economic policy uncertainty (GEPU) on conditional volatility in the gold futures market using Markov regimeswitching GARCH-MIDAS models. The in-sample empirical results suggest that GEPU indeed contains predictive information for the gold futures market, and higher GEPU leads to higher volatility within the gold futures market.Moreover, the novel model, which adds Markov regime switching with timevarying transition probabilities and the GEPU index, achieves relatively better performance than those of the other competing models from a statistical point of view. Furthermore, we discuss the asymmetric effects of different changes in GEPU on the gold futures market and the models' performances with different horizons, and we find that our new model has better predictive performance under negative changes in GEPU than under positive changes in GEPU. Further discussion also confirms that our previous findings are robust during two special cases, the global financial crisis and European debt crisis, during which the market suffered from fierce fluctuations and was fraught with considerable uncertainty. K E Y W O R D SGARCH-MIDAS model, GEPU, gold futures market volatility, Markov regime switching, volatility forecasting | INTRODUCTIONDifferent from financial assets, gold, as a real asset, is always regarded as an effective buffer to slow down economic and political shocks (

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“…The second period, characterized by decline in the number of granted building permits was between 2009 and 2013. The change in the developmental tendency for the number of granted building permits in 2009 was dictated by the global economic crisis that originated from the American real estate market in 2008 (Coombs and Laufer, 2018;Degl'Innocenti, Grant, Šević, and Tzeremes, 2018;Gallegati and Delli Gatti, 2018;Makin, 2019;Manjunath, Baghel, and Kumar, 2019). Starting from 2013, one can note the period of time when the phenomenon under discussion saw growth again.…”

Section: A Time-frequency Analysis Of Housing Construction Time In Pomentioning

confidence: 99%

A time-frequency analysis of the housing construction time as the basis for making decisions on the construction market (the case study of Poland)

Mach¹,

Zmarzły²,

Dąbrowski³

et al. 2020

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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Due to the increasingly complex market situation characterized by the growing variability of its determinants, making accurate decisions is riddled with an increasing risk of error. Widely used economic methods for analyzing market phenomena with a trajectory of time series has proved insufficient in many cases. Hence, it becomes necessary to seek more precise analytic methods, based on which it is be possible to obtain more precise mapping and relations in real-life activities. The goal of the present study is to apply the time-frequency analysis in the domain of real estate. Based on the application of, among others, Savitzky-Golay filtering, spectral density analysis, or cross-correlation, the time-frequency analysis will render it possible to precisely identify the parameters that selectively determine the housing market. The obtained results will make it possible to decrease the informational gap in the investment decision-making process in the housing market

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Financial stability, competitiveness and banks' innovation capacity: Evidence from the Global Financial Crisis

Cited by 35 publications

References 82 publications

Technical and managerial efficiency assessment of European banks using a conditional nonparametric approach

Technical and managerial efficiency assessment of European banks using a conditional nonparametric approach

Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models

A time-frequency analysis of the housing construction time as the basis for making decisions on the construction market (the case study of Poland)

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