A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992–2015

The effect of monetary policy on bank competition using the Boone index

“…Spatial / network analysis of bank e¢ciency using speci…cally designed spatial / network methods like we employ (i.e., those that are based on the network linkage matrix L N ) is very much in its infancy. This is evident as there is just one other study that applies this type of method to banks to estimate a cost frontier (Glass and Kenjegalieva, 2019), whereas we consider a pro…t frontier. Given the paucity of banking studies that use the type of methods we employ, we remain consistent with the early evolution of the banking production literature as we base our choice of inputs and outputs on the intermediation approach (Sealey and Lindley, 1977).…”

A spatial production analysis of Chinese regional banks: case of urban commercial banks

“…Then we compute gross inefficiency (GVI) by combining these two inefficiencies, . The resulting inefficiency measure, GVI, is the time‐variant inefficiency (Glass and Kenjegalieva, ). By dividing inefficiency into NVI and NII components, we can observe any effects based on market restructure to short‐run and persistent efficiency.…”

Does risk aversion affect bank output loss? The case of the Eurozone

“…To this date, there is no universally accepted way of conceptualizing bank risk (Diamond & Dybvig (1983); Santomero (1997)), let alone of measuring it (Diamond & Rajan (2005); Brunnermeier (2009); Acharya, Schnabl, & Suarez (2013); Acharya & Mora (2015)); Dong, Firth, Hou, & Yang (2016); Delis, Iosifidi, & Tsionas (2017); Quaranta, Raffoni, & Visani (2018); Tsionas (2017); Glass and Kenjegalieva, (2019) and Badunenko & Kumbhakar (2017).4 This lack of consensus and understanding may be further compounded because 'traditional approaches have difficulty analyzing how risks can accumulate gradually and then suddenly erupt in a full blown crisis' (Gray, Merton, & Bodie (2007)).…”

“…The production technology is described by a general transformation function Following Appelbaum & Ullah (1997), our basic stochastic assumption about bank 8 Another strand of the literature examines the relationship between bank risk, as measured by nonperforming loans, and bank performance (e.g., Havrylchyk (2006); Koutsomanoli-Filippaki & Mamatzakis (2009); Mamatzakis, Tsionas, Kumbhakar, & Koutsomanoli-Filippaki (2015)). Atkinson & Dorfman (2005) highlight the importance of including indicators of output quality, i.e., nonperforming loans, in the cost function suggesting that otherwise the bank performance estimates are likely to be biased (see also Glass & Kenjegalieva (2019)). Fiordelisi, Marques-Ibanez, & Molyneux (2011) assess the intertemporal relationship between bank efficiency, capital and risk in a sample of European commercial banks employing several definitions of efficiency, capital and risk and using the Granger causality methodology in a panel data framework.…”

“…Stiglitz & Greenwald (2003) for example argue that banks due to information asymmetry and competition imperfections may follow risk adverse practices. The degree of bank risk aversion may crucially depend upon a bank`s net worth (see also Rajan (2006); Borio & Zhu (2012); Delis, Iosifidi, & Tsionas (2017) and Quaranta, Raffoni, & Visani (2018); Glass and Kenjegalieva, (2019)). Following from this idea, we explore whether uncertainty around these three bank output prices, that in turn would impact upon bank net worth, would also affect bank risk aversion.…”