On Spatio-Temporal Stochastic Frontier Models

Elisa Fusco (), Giuseppe Arbia (), Francesco Vidoli () and Vincenzo Nardelli ()
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Elisa Fusco: Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze, https://cercachi.unifi.it/p-doc2-0-0-A-3f2c372d362c2c.html
Giuseppe Arbia: Dipartimento di Scienze Statistiche, Università Cattolica del Sacro Cuore, Roma, https://docenti.unicatt.it/ppd2/it/docenti/35215/giuseppe-arbia/profilo
Francesco Vidoli: Dipartimento di Economia, Società , Politica (DESP), Università degli Studi di Urbino Carlo Bo, https://www.uniurb.it/persone/francesco-vidoli
Vincenzo Nardelli: Università Cattolica del Sacro Cuore, Roma, https://docenti.unicatt.it/ppd2/it/docenti/80554/vincenzo-nardelli/profilo

No 2024_09, Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"

Abstract: In the literature on stochastic frontier models until the early 2000s, the joint consideration of spatial and temporal dimensions was often inadequately addressed, if not completely neglected. However, from an evolutionary economics perspective, the production process of the decision-making units constantly changes over both dimensions: it is not stable over time due to managerial enhancements and/or internal or external shocks, and is influenced by the nearest territorial neighbours. This paper proposes an extension of the Fusco and Vidoli (2013) SEM-like approach, which globally accounts for spatial and temporal effects in the term of inefficiency. In particular, coherently with the stochastic panel frontier literature, two different versions of the model are proposed: the time-invariant and the time-varying spatial stochastic frontier models. In order to evaluate the inferential properties of the proposed es- timators, we first run Monte Carlo experiments and then present the results of an application to a set of commonly referenced data, demonstrating robustness and stability of estimates across all scenarios.

Keywords: Stochastic frontier analysis; Spatio-temporal effects; Productive efficiency (search for similar items in EconPapers)
JEL-codes: C21 D24 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2024-10
New Economics Papers: this item is included in nep-ecm and nep-eff
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