Spatial heterogeneity in non-parametric efficiency: An application to Italian hospitals

Identification of spatially constrained homogeneous clusters of COVID‐19 transmission in Italy

“…The issue of the potential mismatch between the administrative boundaries of the government and the management of healthcare services and the spatial differentiation of health needs and demand, revealed by our analysis of the COVID-19 epidemic, is probably more general. As shown, for instance, by (Auteri et al, 2019), who deal with the issue of defining spatial regimes for the estimation of the efficiency of hospital services in Italy, clusters differentiated by the relevant production boundary generally overlap with different regions. Even if we are aware that the definition of the boundaries of jurisdictions is not a short-term decision and must correspond to a wider spectrum of interests than those related to the provision of a specific service, there is a need to seek institutional coordination mechanisms that are flexible enough to guarantee more homogeneous policy interventions in specific circumstances, such as that faced within the current epidemic, as also recommended by (World Health Organization, 2020b; 2020a).…”

“…This is a problem connected with the partitioning of spatial data with respect to the trends of the epidemic curves. While several attempts have already been made to deal with spatial aspects in the health field, from spatial dependence (Baltagi, Moscone, & Santos, 2018) to spatial heterogeneity (Auteri, Guccio, Pammolli, Pignataro, & Vidoli, 2019; Baltagi, Lagravinese, Moscone, & Tosetti, 2017; Billé, Benedetti & Postiglione, 2017; 2018), a specific, systematic and complete approach to such a grouping problem is not yet available and remains the focus of scientific debate (see e.g. Zhou et al, 2020 and Chasco, Le Gallo, & López, 2018).…”

Exploring hospital efficiency within and between Italian regions: new empirical evidence

“…With the aim of measuring the impact of environmental characteristics on hospitals’ technical efficiency, the conditional-efficiency approach (Cordero et al, 2015 , Halkos and Tzeremes, 2011 , Mastromarco et al, 2019 , Varabyova et al, 2017 ) as well as a two-stage semiparametric bootstrap-based approach are applied (Cavalieri et al, 2018 , Chowdhury and Zelenyuk, 2016 ). The importance of the spatial dependent heterogeneity in hospital technical efficiency is also underlined, through a spatial stochastic frontier, to separate spatial issues from the effects of geographical institutional factors (Auteri et al, 2019 , Cavalieri et al, 2020 ). Stochastic input and output distance functions are also employed (Daidone and D’Amico, 2009 , Jiang and Andrews, 2020 ) to model multiple input and output technologies.…”

Effects of Regional Innovation Capability on the Green Technology Efficiency of China’s Manufacturing Industry: Evidence from Listed Companies

“…Can changes in the above factors indirectly affect the green technology efficiency of manufacturing? Differences in resource endowments in various regions will cause differences in innovation capability and technical efficiency [16]. As such, it is necessary to explore the heterogeneity of the impact of different regions' innovation capabilities on their green technology manufacturing efficiency.…”