Abstract
Bu çalışmanın
amacı kuru dökme ve tanker piyasalarındaki navlun seviyelerinin korsan
saldırılarına etkisinin olup olmadığının tespit edilmesidir. Çalışmadaki
örneklem 2008 ve 2018 dönemleri arasını kapsayan aylık dökme ve tanker navlun
endekslerinden ve yıllık korsan saldırısı değerlerinden oluşmaktadır. Korsan
saldırısı değişkeni analizleri daha isabetli şekilde yürütebilmek için kübik
dönüşüm ile aylık veriye dönüştürülmüştür. Sonuçlar navlun oranlarının korsan
saldırılarının nedeni olduğunu, navlun seviyelerindeki değişmelerin hem dökme
gemilerinde hem de tanker gemilerindeki korsan saldırılarını anlamlı bir
şekilde pozitif yönde etkilediğini ve dökme piyasasındaki navlun değişimlerinin
korsan saldırılarını daha fazla açıkladığını göstermektedir. Bu sonuçlar, artan
navlun gelirlerinin korsanları saldırmaları için daha fazla motive ettiğine
işaret etmektedir.
References
- Allen, M. P. (2004). Understanding Regression Analysis, New York, Springer Science & Business Media.
- Archdeacon, T. J. (1994). Correlation and Regression Analysis: A Historian's Guide, Univ of Wisconsin Press.
- Chatterjee, S., Hadi, A. S. (2015). Regression Analysis by Example, John Wiley & Sons.
- Dickey, D. A., Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of The American Statistical Association, 74(366a): 427-431.
- Dura, Y. C., Beser, M. K., Acaroglu, H. (2017). Econometric analysis of Turkey's export-led growth. Ege Akademik Bakis, 17(2): 295.
- Esquerdo, P. J. R., Welc, J. (2018). Applied Regression Analysis for Business, Switzerland, Springer International Publishing
- Gordon, R. (2015). Regression Analysis for the Social Sciences, New York, Routledge
- Granger, C.W.J. (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 36: 424-438.
- Hallwood, C., Miceli, T. (2015). Maritime Piracy and Its Control: An Economic Analysis, New York, Springer.
- ICC (2019). Piracy and Armed Robbery against Ships Report, obtained from https://www.icc-ccs.org/reports/2019Q2IMB-Piracy-Report.pdf.
- Investing (2019). Baltic Dry Index and Baltic Dirty Tanker Index, obtained from https://tr.investing.com/.
- Mejia, M. Q., Kojima, C., Sawyer, M. (2013). The Malmö Declaration: Calling for a multi-sectoral response to piracy. In “Piracy at Sea”, Springer, pp. 1-15, Berlin, Heidelberg.
- Menard, S. (2002). Applied Logistic Regression Analysis (Vol. 106), Sage.
- Murphy, M. N. (2013). Contemporary Piracy and Maritime Terrorism: The Threat to International Security, New York, Routledge.
- Pagan, A. R., Hall, A.D. (1983). Diagnostic tests as residual analysis. Econometric Reviews, 2(2): 159-218.
- Yu, L., Li, J., Tang, L., Wang, S. (2015). Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach, Energy Economics, 51: 300-311.
Abstract
The aim of this study is to determine whether freight levels in dry bulk and tanker markets have an impact on pirate attacks. The sample included in the study consists of monthly bulk and tanker freight indices and annual attack values between 2008 and 2018 periods. Annual attack values due to data constraint have been converted to monthly data by cubic transformation in order to carry out the analyzes more accurately. The results reveal that freight rates are the causes of pirate attacks, freight rates significantly affect pirate attacks on both bulk ships and tanker ships in a positive way, and freight rate changes in the bulk market explain the attacks more. This results indicate that increased freight revenues are more motivating for pirates to attack.
References
- Allen, M. P. (2004). Understanding Regression Analysis, New York, Springer Science & Business Media.
- Archdeacon, T. J. (1994). Correlation and Regression Analysis: A Historian's Guide, Univ of Wisconsin Press.
- Chatterjee, S., Hadi, A. S. (2015). Regression Analysis by Example, John Wiley & Sons.
- Dickey, D. A., Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of The American Statistical Association, 74(366a): 427-431.
- Dura, Y. C., Beser, M. K., Acaroglu, H. (2017). Econometric analysis of Turkey's export-led growth. Ege Akademik Bakis, 17(2): 295.
- Esquerdo, P. J. R., Welc, J. (2018). Applied Regression Analysis for Business, Switzerland, Springer International Publishing
- Gordon, R. (2015). Regression Analysis for the Social Sciences, New York, Routledge
- Granger, C.W.J. (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 36: 424-438.
- Hallwood, C., Miceli, T. (2015). Maritime Piracy and Its Control: An Economic Analysis, New York, Springer.
- ICC (2019). Piracy and Armed Robbery against Ships Report, obtained from https://www.icc-ccs.org/reports/2019Q2IMB-Piracy-Report.pdf.
- Investing (2019). Baltic Dry Index and Baltic Dirty Tanker Index, obtained from https://tr.investing.com/.
- Mejia, M. Q., Kojima, C., Sawyer, M. (2013). The Malmö Declaration: Calling for a multi-sectoral response to piracy. In “Piracy at Sea”, Springer, pp. 1-15, Berlin, Heidelberg.
- Menard, S. (2002). Applied Logistic Regression Analysis (Vol. 106), Sage.
- Murphy, M. N. (2013). Contemporary Piracy and Maritime Terrorism: The Threat to International Security, New York, Routledge.
- Pagan, A. R., Hall, A.D. (1983). Diagnostic tests as residual analysis. Econometric Reviews, 2(2): 159-218.
- Yu, L., Li, J., Tang, L., Wang, S. (2015). Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach, Energy Economics, 51: 300-311.
Details
| Primary Language | English |
|---|---|
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 17, 2019 |
| Submission Date | July 25, 2019 |
| Acceptance Date | October 11, 2019 |
| Published in Issue | Year 2019 Volume: 5 Issue: 2 |
This Journal is licensed with Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND 4.0).