A simultaneous system of dynamic spatial stochastic frontier models with dependent error components and inefficiency determinants

In this paper, we develop a system of simultaneous stochastic frontier models with inefficiency determinants, spatio-temporal effects and correlated inefficiency as well as correlated random errors among frontiers. The dependence among the errors of the different equations can stem from either shocks external to the system, interrelated inefficiency mechanisms, or a combination of both. Estimation is performed using a copula-based quasi-maximum likelihood approach. Simulation results confirm the good finite sample properties of the proposed estimator. To demonstrate the effectiveness of the proposed model and estimation technique in empirical settings, we analyze the key role of some sustainability-related factors in determining the efficiency level of Italian cultural and creative sectors. • We propose a system of spatial stochastic frontiers with inefficiency determinants. • We consider both correlated inefficiency and correlated random errors among frontiers. • Copula functions are used to handle dependence. • The application to Italian cultural sectors reveals cross-sectoral efficiency effects. • Findings highlight sustainability’s role in improving regional efficiency.

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Publication Details

Journal
Spatial Statistics
Published
2025-11-29
DOI
https://doi.org/10.1016/j.spasta.2025.100947
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

A simultaneous system of dynamic spatial stochastic frontier models with dependent error components and inefficiency determinants

Federica Galli, Silvia Emili
Spatial Statistics
Efficiency Analysis Using DEA
article

A simultaneous system of dynamic spatial stochastic frontier models with dependent error components and inefficiency determinants

Federica Galli, Silvia Emili
article en

Abstract

In this paper, we develop a system of simultaneous stochastic frontier models with inefficiency determinants, spatio-temporal effects and correlated inefficiency as well as correlated random errors among frontiers. The dependence among the errors of the different equations can stem from either shocks external to the system, interrelated inefficiency mechanisms, or a combination of both. Estimation is performed using a copula-based quasi-maximum likelihood approach. Simulation results confirm the good finite sample properties of the proposed estimator. To demonstrate the effectiveness of the proposed model and estimation technique in empirical settings, we analyze the key role of some sustainability-related factors in determining the efficiency level of Italian cultural and creative sectors. • We propose a system of spatial stochastic frontiers with inefficiency determinants. • We consider both correlated inefficiency and correlated random errors among frontiers. • Copula functions are used to handle dependence. • The application to Italian cultural sectors reveals cross-sectoral efficiency effects. • Findings highlight sustainability’s role in improving regional efficiency.

Spatial StatisticsVol. 71
University of Bologna (IT)
Openalex Percentile: Top 57%
Efficiency Analysis Using DEA
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