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The Impact of Steel Price on Ship Demolition Prices: Evidence from Heterogeneous Panel of Developing Countries

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  • Mehtap TUNÇ
  • Abdullah AÇI

Abstract

In this study, the causal relationship between global steel prices and demolition prices in five developing countries (Bangladesh, China, India, Pakistan, and Turkey) that host five main ship scrap centers in the world are examined. The bootstrap panel Granger causality analysis is employed to take heterogeneity and cross-sectional dependence into account. The data set used in this study consists of 289 weekly observations from January 8, 2013 to July 16, 2018. As a result of the study, a collective causality relationship from steel price to demolition prices is determined and individual causality relationships for all countries except Bangladesh are identified.

Suggested Citation

  • Mehtap TUNÇ & Abdullah AÇI, 2019. "The Impact of Steel Price on Ship Demolition Prices: Evidence from Heterogeneous Panel of Developing Countries," Sosyoekonomi Journal, Sosyoekonomi Society, issue 27(42).
    • Handle: RePEc:sos:sosjrn:190412
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    1. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    2. Mohammed Umar & Jauhari Dahalan, 2016. "An Application of Asymmetric Toda Yamamoto Causality on Exchange Rate-inflation Differentials in Emerging Economies," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 420-426.
    3. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    4. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    5. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, March.
    6. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    7. Kar, Muhsin & NazlIoglu, Saban & AgIr, Hüseyin, 2011. "Financial development and economic growth nexus in the MENA countries: Bootstrap panel granger causality analysis," Economic Modelling, Elsevier, vol. 28(1-2), pages 685-693, January.
    8. Nikos D. Kagkarakis & Andreas G. Merikas & Anna Merika, 2016. "Modelling and forecasting the demolition market in shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(8), pages 1021-1035, November.
    9. Dogan, Eyup & Aslan, Alper, 2017. "Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional depen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 239-245.
    10. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    11. Giuliodori, David & Rodriguez, Alejandro, 2015. "Analysis of the stainless steel market in the EU, China and US using co-integration and VECM," Resources Policy, Elsevier, vol. 44(C), pages 12-24.
    12. L. Vanessa Smith & Stephen Leybourne & Tae-Hwan Kim & Paul Newbold, 2004. "More powerful panel data unit root tests with an application to mean reversion in real exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 147-170.
    13. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    14. Xie, Zixiong & Chen, Shyh-Wei, 2014. "Untangling the causal relationship between government budget and current account deficits in OECD countries: Evidence from bootstrap panel Granger causality," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 95-104.
    15. Menyah, Kojo & Nazlioglu, Saban & Wolde-Rufael, Yemane, 2014. "Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach," Economic Modelling, Elsevier, vol. 37(C), pages 386-394.
    16. Emirmahmutoglu, Furkan & Kose, Nezir, 2011. "Testing for Granger causality in heterogeneous mixed panels," Economic Modelling, Elsevier, vol. 28(3), pages 870-876, May.
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure

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