Role of Interest Rates on Fleet Capacity Adjustment Decisions of Shipowners

Öz

The aim of this study is to empirically examine the impact of real interest rate on global fleet adjustment processes by modelling new orders and demolitions. The data set used consists of 34 annual observations and covers the years between 1985 and 2018. According to the results, the freight rate has a positive impact on amount of new ship orders and a negative impact on amount of ships scrapped, while the real interest rate has a negative impact on both amount of new ship orders and ships scrapped. The impact of freight rate on new ship orders and demolitions is clear whereas the impact of the real interest rate may be explained by two reasons. Increasing capital costs due to increasing interest rates may cause decrease in both new orders and demolitions as ordering new ships becomes more expensive. The second one may be related to expectations of ship investors to gain more revenue by evaluating their capitals on higher interest rates instead of ordering new ships. Therefore, it is important to limit negative impact of high interest rates by various policies so that maritime transport sector can contribute to economic growth by facilitating trade with sustainable costs.

Anahtar Kelimeler

• Interest Rate,Ship Investment,Demolition

Gemi Sahiplerinin Filo Kapasitesi Ayarlama Kararlarında Faiz Oranlarının Rolü

Öz

Bu çalışmanın amacı reel faiz oranının küresel filo ayarlama sürecine olan etkisini yeni siparişleri ve hurdaya gönderimleri modelleyerek ampirik olarak test etmektir. Kullanılan veri seti 1985 ve 2018 yılları arasını kapsamaktadır ve yıllık bazda 34 gözlemden oluşmaktadır. Elde edilen sonuçlara göre navlun oranı yeni gemi sipariş miktarını pozitif ve söküme gönderilen gemi miktarını negatif etkilerken reel faiz oranı hem yeni sipariş miktarını hem de söküme gönderilen gemi miktarını negatif olarak etkilemektedir. Navlun oranının yeni siparişlerde ve söküme gönderimlerde etkisi açık iken faiz oranının negatif etkisi iki şekilde açıklanabilir. Yükselen faiz oranı nedeniyle artan sermaye maliyetleri yeni gemi siparişlerinin daha pahalı olmasına neden olduğu için yeni siparişlerde ve söküme gönderimlerde azalışa neden oluyor olabilir. İkinci nedeni ise gemi yatırımcılarının sermayelerini daha fazla gelir elde etmek için yeni gemi sipariş etmek yerine yüksek faiz oranlarında değerlendirmeleriyle ilgili olabilir. Bu nedenle, deniz taşımacılığı sektörünün sürdürülebilir maliyetlerle ticareti kolaylaştırarak ekonomik büyümeye katkı sunabilmesi için yüksek faiz oranlarının negatif etkisinin çeşitli politikalarla sınırlandırılması önem arz etmektedir. 

Anahtar Kelimeler

• Faiz Oranı,Gemi Yatırımı,Gemi Hurdası

Kaynakça

1. Açık, A. and Baran, E. (2019). The reflection of ship demolition prices to construction costs in Turkey. Marine Science and Technology Bulletin, 8(1), 23-29. doi: 10.33714/masteb.547103
2. Açık, A. and Başer, S. Ö. (2017). The relationship between freight revenues and vessel disposal decisions. Journal of Research in Economics, Politics & Finance, 2(2), 96-112. doi: 10.30784/epfad.363721
3. Açık, A. and Başer, S. Ö. (2018a). Navlun oranlarıyla gemi söküm fiyatları arasındaki ilişki. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 2(1), 16-32. doi: 10.30711/utead.358662
4. Açık, A. and Başer, S. Ö. (2018b, June). Market efficiency in ship demolition prices. Paper presented at the International Conference on Empirical Economics and Social Sciences. Bandirma, Turkey. Retrieved from https://www.researchgate.net/publication/327976775_MARKET_ EFFICIENCY_IN_SHIP_DEMOLITION_PRICES
5. Açık, A. and S. Başer (2019). Price volatility spillover in ship demolition markets. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 6(2), 311-322. doi: 10.17541/optimum.531561
6. Adland, R. and Cullinane, K. (2006). The non-linear dynamics of spot freight rates in tanker markets. Transportation Research Part E: Logistics and Transportation Review, 42(3), 211-224. doi: 10.1016/j.tre.2004.12.001
7. Alizadeh, A. H., Strandenes, S. P. and Thanopoulou, H. (2016). Capacity retirement in the dry bulk market: A vessel-based logit model. Transportation Research Part E: Logistics and Transportation Review, 92, 28-42. doi: 10.1016/j.tre.2016.03.005
8. Allen, M. P. (2004). Understanding regression analysis. New York: Springer Science & Business Media.

9. Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61, 821–856. doi: 10.2307/2951764
10. Andrews, D. and Ploberger, W. (1994). Optimal tests when a nuisance parameter is present only under the alternative. Econometrica, 62, 1383–1414. doi: 10.2307/2951753
11. Archdeacon, T. J. (1994). Correlation and regression analysis: A historian's guide. Madison: The University of Wisconsin Press.
12. Arnold, R.A. (2010). Economics. USA: South-Western CENGAGE Learning.
13. Athenian Shipbrokers SA (2019). Weekly demolition reports. Retrieved from http://www.atheniansa.gr.
14. Başer, S. Ö. and Açık, A. (2018). The response of shipbuilding activities to freight market. International Journal of Economics and Administrative Sciences, 4(1), 120-136. doi: 10.29131/uiibd.415303
15. Bloomberg Data Platform (2019), Baltic Dry Index. Retrieved from https://www.bloomberg.com/professional/
16. Branch, A. E. (2012). Economics of shipping practice and management. USA: Springer Science & Business Media.
17. Buxton, I. L. (1991). The market for ship demolition. Maritime Policy & Management, 18(2), 105–112. doi:10.1080/03088839100000034
18. Chatterjee, S. and Hadi, A. S. (2015). Regression analysis by example. New Jersey: John Wiley & Sons.
19. Choi, J. K., Kelley, D., Murphy, S. and Thangamani, D. (2016). Economic and environmental perspectives of end-of-life ship management. Resources, Conservation and Recycling, 107, 82-91. doi: 10.1016/j.resconrec.2015.12.007
20. Dai, L., Hu, H., Chen, F. and Zheng, J. (2015). The dynamics between newbuilding ship price volatility and freight volatility in dry bulk shipping market. International Journal of Shipping and Transport Logistics, 7(4), 393-406. doi: 10.1504/IJSTL.2015.069666
21. Dickey, D. A. and 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. doi: 10.2307/2286348
22. Erol, E. and Dursun, A. (2016). Düzensiz hat denizyolu taşımacılığının piyasa yapısı ve değerlendirilmesi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 16, 153-170. Retrieved from https://dergipark.org.tr/ulikidince
23. Eryüzlü, H. (2019). Dünya deniz ticareti ve Türkiye diş ticareti ilişkileri: Ekonometrik bir analiz. The Journal of Social Science, 3(5), 152-162. doi: 10.30520/tjsosci.524826
24. Esquerdo, P. J. R. and Welc, J. (2018). Applied regression analysis for business. Switzerland: Springer International Publishing.
25. FED (2019). Inflation and Interest Rates. Retrieved from https://fred.stlouisfed.org/series/ FEDFUNDS
26. Gaurav, K. (2011). Multiple regression analysis: Key to social science research. Germany: GRIN Verlag.
27. Geman, H. (2008). Risk management in commodity markets: From shipping to agricultures and energy. UK: Wiley
28. Glen, D. and Christy, S. (2010). Tanker market: Current structure and economic analysis. In C. Grammenos (Ed.), The handbook of maritime economics and business (pp. 355-390). Great Britain: MPG Books
29. Gordon, R. (2015). Regression analysis for the social sciences. New York: Routledge.
30. Hossain, M. S., Fakhruddin, A. N. M., Chowdhury, M. A. Z. and Gan, S. H. (2016). Impact of ship-breaking activities on the coastal environment of Bangladesh and a management system for its sustainability. Environmental Science & Policy, 60, 84-94. doi: 10.1016/j.envsci.2016.03.005
31. Kagkarakis, N. D., Merikas, A. G. and Merika, A. (2016). Modelling and forecasting the demolition market in shipping. Maritime Policy & Management, 43(8), 1021-1035. doi: 10.1080/03088839.2016.1185181
32. Karakitsos, E. and Varnavides, L. (2014). Maritime economics: A macroeconomic approach. New York: Palgrave Macmillan.
33. Karlis, T. and Polemis, D. (2016). Ship demolition activity: A monetary flow process approach. Pomorstvo, 30(2), 128-132. doi: 10.31217/p.30.2.5
34. Karlis, T., Polemis, D. and Georgakis, A. (2016). Ship demolition activity. An evaluation of the effect of currency exchange rates on ship scrap values. SPOUDAI-Journal of Economics and Business, 66(3), 53-70. Retrieved from https://spoudai.unipi.gr/index.php/spoudai
35. Kim, C. Y. and Park, K. (2017). An analysis on the causal relationship between freight rate and newbuilding orders: Implications for Korean trade and shipbuilding companies. Journal of Korea Trade, 21(1), 22-37. doi: 10.1108/JKT-11-2016-0039
36. Knapp, S., Kumar, S. N. and Remijn, A. B. (2008). Econometric analysis of the ship demolition market. Maritime Policy & Management, 32(6), 1023–1036. doi: 10.1016/j.marpol.2008.02.004
37. Koopmans, T. C. (1939). Tanker freight rates and tankship building. Holland: Haarlem.
38. Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. and Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54, 159-178. doi: 10.1016/0304-4076(92)90104-Y
39. Menard, S. (2002). Applied logistic regression analysis (Vol. 106). London: Sage.
40. Neşer, G., Ünsalan, D., Tekoğul, N. and Stuer-Lauridsen, F. (2008). The shipbreaking industry in Turkey: Environmental, safety and health issues. Journal of Cleaner Production, 16(3), 350-358. doi: 10.1016/j.jclepro.2006.08.018
41. Pagan, A. R. and Hall, A. D. (1983). Diagnostic tests as residual analysis. Econometric Reviews, 2(2), 159-218. doi: 10.1080/07311768308800039
42. Quandt, R. E. (1960). Tests of the hypothesis that a linear regression system obeys two separate regimes. Journal of the American Statistical Association, 55, 324–330. doi: 10.2307/2281745
43. SAJ (2019). Shipbuilding Statistics. Retrieved from https://www.sajn.or.jp/e (15.09.2019).
44. Shahbaz, M., Van Hoang, T. H., Mahalik, M. K. and Roubaud, D. (2017). Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis. Energy Economics, 63, 199-212. doi: 10.1016/j.eneco.2017.01.023.
45. Stopford, M. (2009). Maritime economics (3rd ed.). London: Routledge.
46. Stopford, M. (2010). Shipping Market Cycles. In Grammenos, C. (Ed.), The handbook of maritime economics and business (pp. 235-257). Great Britain: MPG Books
47. Taylor, A. J. (1974). The dynamics of supply and demand in shipping. Dynamica, 2(2): 62-71. Retrieved from https://www.systemdynamics.org.
48. Tunç, M. and Açik, A. (2019). The impact of steel price on ship demolition prices: Evidence from heterogeneous panel of developing countries. Sosyoekonomi, 27(42), 227-240. doi: 10.17233/sosyoekonomi.2019.04.12
49. Xiarchos, I. M. and Fletcher, J. J. (2009). Price and volatility transmission between primary and scrap metal markets. Resources, Conservation and Recycling, 53(12), 664-673. doi: 10.1016/j.resconrec.2009.04.020
50. Xu, J. J., Yip, T. L. and Liu, L. (2011). A directional relationship between freight and newbuilding markets: A panel analysis. Maritime Economics & Logistics, 13(1), 44-60. doi: 10.1057/mel.2010.20
51. Yin, J. and Fan, L. (2018). Survival analysis of the world ship demolition market. Transport Policy, 63, 141-156. doi: 10.1016/j.tranpol.2017.12.019
52. Zeren, F. and Kahramaner, H. (2019). Baltık Kuru Yük Endeksi ile İstanbul Navlun Endeksi arasındaki etkileşimin incelenmesi: Ekonometrik bir uygulama. Uluslararası Yönetim Eğitim ve Ekonomik Perspektifler Dergisi, 7(1), 68-79. Erişim adresi: https://dergipark.org.tr/jimeep