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Total-factor spillovers, similarities, and competitions in the petroleum industry

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  • Gong, Binlei

Abstract

This article investigates multi-dimensional spillovers, similarities, and competitions in the petroleum industry. Spatial techniques are applied first in production function in order to observe the cross-sectional dependence in each of the four dimensions (product-, technology-, segment-, and region-wide). These four single-dimensional spatial models are then aggregated by a model averaging method that assigns weights to different models based on their ability to explain data. Taking all dependences into consideration, this article estimates the total-factor spillovers, similarities, and competitions in the spirit of total-factor productivity. Negative spillover effects are observed in all the four dimensions. Moreover, segment-wide competition has negative effect on productivity. Some policy implications concerning human capital, globalization, and development strategies are also discussed.

Suggested Citation

  • Gong, Binlei, 2018. "Total-factor spillovers, similarities, and competitions in the petroleum industry," Energy Economics, Elsevier, vol. 73(C), pages 228-238.
    • Handle: RePEc:eee:eneeco:v:73:y:2018:i:c:p:228-238
    DOI: 10.1016/j.eneco.2018.04.036
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    Citations

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    Cited by:

    1. Eungchan Kim & Young Seok Ock & Seung-Jun Shin & Wonchul Seo, 2018. "An Approach to Generating Reference Information for Technology Evaluation," Sustainability, MDPI, vol. 10(9), pages 1-19, September.
    2. Gong, Binlei, 2018. "Interstate competition in agriculture: Cheer or fear? Evidence from the United States and China," Food Policy, Elsevier, vol. 81(C), pages 37-47.
    3. Wang, Junqi & Cao, Hongjun, 2022. "Improving competitive strategic decisions of Chinese coal companies toward green transformation: A hybrid multi-criteria decision-making model," Resources Policy, Elsevier, vol. 75(C).
    4. Li, Cunfang & Li, Danping & Dong, Mei, 2019. "The spillage effect of the transfer behavior of coal resource-exhausted enterprises and science and technology projects," Resources Policy, Elsevier, vol. 62(C), pages 385-396.
    5. Hyun-Jee Kim & Bongsuk Sung, 2020. "How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    6. Sung, Bongsuk & Soh, Jin Young & Park, Chun Gun, 2022. "Comparing government support, firm heterogeneity, and inter-firm spillovers for productivity enhancement: Evidence from the Korean solar energy technology industry," Energy, Elsevier, vol. 246(C).
    7. Uddin, Gazi Salah & Luo, Tianqi & Yahya, Muhammad & Jayasekera, Ranadeva & Rahman, Md Lutfur & Okhrin, Yarema, 2023. "Risk network of global energy markets," Energy Economics, Elsevier, vol. 125(C).

    More about this item

    Keywords

    Petroleum industry; Spatial econometric model; Multi-dimensional dependence; Spillovers; similarities; and competitions;
    All these keywords.

    JEL classification:

    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

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