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An assessment of energy production efficiency activity: a spatial analysis

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  • Luigi Aldieri

    (University of Salerno)

  • Concetto Paolo Vinci

    (University of Salerno)

Abstract

The aim of this paper is to investigate the extent to which the environmental technological spillover effects on firms’ productivity are affected by the spatial dimension. To this end, we introduce a spatial Durbin model with additional endogenous variables for the energy production efficiency activity of large R&D-intensive firms located in three economic areas: the USA, Japan and Europe. To identify the technological proximity between the firms, we construct an original Mahalanobis environmental industry weight matrix, based on the construction of technological vectors for each firm, with European environmental patents distributed across more technology classes. The findings show a statistically negative impact of spatially distributed environmental spillovers on firms’ productivity in all the economic areas.

Suggested Citation

  • Luigi Aldieri & Concetto Paolo Vinci, 2018. "An assessment of energy production efficiency activity: a spatial analysis," Letters in Spatial and Resource Sciences, Springer, vol. 11(3), pages 233-243, October.
    • Handle: RePEc:spr:lsprsc:v:11:y:2018:i:3:d:10.1007_s12076-017-0196-8
    DOI: 10.1007/s12076-017-0196-8
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    2. Aldieri, Luigi & Kotsemir, Maxim & Vinci, Concetto Paolo, 2017. "Jacobian spillovers in environmental technological proximity: the role of Mahalanobis index on European patents within the Triad," MPRA Paper 77274, University Library of Munich, Germany.
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    10. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
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    Cited by:

    1. Aldieri, Luigi & Makkonen, Teemu & Paolo Vinci, Concetto, 2020. "Environmental knowledge spillovers and productivity: A patent analysis for large international firms in the energy, water and land resources fields," Resources Policy, Elsevier, vol. 69(C).
    2. Gatto, Andrea & Drago, Carlo & Panarello, Demetrio & Aldieri, Luigi, 2023. "Energy transition in China: Assessing progress in sustainable development and resilience directions," International Economics, Elsevier, vol. 176(C).
    3. Xiaoli Shi & Ying Chen & Qianju Cheng, 2022. "Environmental Regulation, Environmental Knowledge Spillover, and Regional Economic Growth in China: An Empirical Test Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 14(21), pages 1-23, November.

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    More about this item

    Keywords

    Innovation; Technological spillovers; Spatial models;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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