2020
DOI: 10.1016/j.ejor.2019.12.036
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Spatial scale and product mix economies in U.S. banking with simultaneous spillover regimes

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Cited by 6 publications
(28 citation statements)
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“…The proxy for revenue diversification partially confirms evidence presented by earlier studies. Indeed, Income div presents only a direct effect on bank efficiency and the associated spillover effects is almost never significant, which confirms that small banks are not affected by noninterest activities of neighboring banks (Glass et al, 2020). To a large extent, this would imply that Italian small cooperative banks can diversify their services with respect to the rival mutual banks of the same area.…”
Section: Resultsmentioning
confidence: 88%
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“…The proxy for revenue diversification partially confirms evidence presented by earlier studies. Indeed, Income div presents only a direct effect on bank efficiency and the associated spillover effects is almost never significant, which confirms that small banks are not affected by noninterest activities of neighboring banks (Glass et al, 2020). To a large extent, this would imply that Italian small cooperative banks can diversify their services with respect to the rival mutual banks of the same area.…”
Section: Resultsmentioning
confidence: 88%
“…The effect of direct and indirect allocative efficiency spillovers is captured in their spatial Durbin specification, which integrates the regressors' spatial lags. Glass et al (2020) show a geographical return to scale in medium and large US banks through a spatial cost function analysis, in which the spatial lags of the dependent and independent variables are related to the bank's indirect elasticity of output. Zhao et al (2020) apply a spatial Durbin production frontier analysis to urban commercial Chinese banks, considering both spatial dependence and regional market environment effects on bank efficiency.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…Because location is an important factor affecting firm performance, previous empirical studies heavily rely on spatial econometrics to examine the locational/spatial effects on production. Oftentimes, spatially‐weighted averages of other firms' outputs and inputs are included as additional regressors in spatial autoregressive (SAR) production‐function models (e.g., Glass et al, 2016b, 2020,b; Glass & Kenjegalieva, 2019; Hou et al, 2020; Kutlu et al, 2020; Serpa & Krishnan, 2018; Vidoli & Canello, 2016). The appropriateness of such a conceptualization of firm‐level production functions in the presence of locational influences however remains unclear because these SAR specifications are difficult to reconcile with the theory of firm.…”
Section: Introductionmentioning
confidence: 99%