The Effect of Aging on Ship Values: An Econometric Analysis on Major Ship Types

Ships are investments that require significant capital and therefore the factors affecting their value must be analyzed carefully. The study in the paper is determined to what extent the effect of age, which is one of the most influential factors in sales value, differs in terms of ship type. The reports including the ship sale activities cover the period between January 2013 and December 2019 and consist of 84 monthly reports. Regression analysis was performed as the sales price as the dependent variable, age, freight, and size as independent variables. According to the results, it was determined that the ship types whose value decreases the most due to the age change are those used in gas transportation, while the least affected ship type by age is those used in bulk transportation. In addition, it has been determined that the ship type most affected by freight is those used in gas transportation and that the ship type most affected by the size is those used in container transportation. It can also be said that the ship type with the lowest risk of investment is bulk ships and the ship type with the greatest risk is gas ships. It is hoped that these results provide important information especially for players conducting their commercial activities upon sale & purchase transactions in the market.


Açık, A, Kesi̇ktaş, H. H. İ., & Başer, S. Ö. (2020). Role of interest rates on fleet capacity adjustment decisions of shipowners. Ekonomi Politika ve Finans Araştırmaları Dergisi, 5(1), 66-80.

Açık, A., & Başer, S. Ö. (2018). The impact of freight rates on the second-hand ship price bubbles: An application on the Panamax market. Proceedings of İzmir International Congress on Economics and Administrative Sciences, Turkey, pp. 629-643.

Alizadeh, A. H., & Nomikos, N. K. (2003). The price-volume relationship in the sale and purchase market for dry bulk vessels. Maritime Policy & Management, 30(4), 321-337.

Alizadeh, A. H., Thanopoulou, H., & Yip, T. L. (2017). Investors’ behavior and dynamics of ship prices: A heterogeneous agent model. Transportation Research Part E: Logistics and Transportation Review, 106, 98-114.

Allen, M. P. (2004). Understanding Regression Analysis. Springer Science & Business Media.

Archdeacon, T. J. (1994). Correlation and Regression Analysis: A Historian’s Guide. University of Wisconsin Press.

Athenian, S. A. (2020). Sale & purchase market reports. Retrieved on April 15, 2020, from

Başer, S. Ö., & Açık, A., (2018). Efficiency in dirty tanker market. Journal of ETA Maritime Science, 6(3), 275-287.

Başer, S. Ö., & Açık, A. (2019a). The effects of global economic growth on dry bulk freight rates. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 3(1), 1-17.

Başer, S. Ö., & Açık, A. (2019b). Do commodity prices matter for second hand values? An empirical research on Capesize market. Turkish Journal of Maritime and Marine Sciences, 5(1), 44–52.

Branch, A. E. (2007). Elements of Shipping. Routledge.

Capital Link (2020). Freight indices. Retrieved on April 15, 2020, from

Chatterjee, S., & Hadi, A. S. (2015). Regression Analysis by Example. John Wiley & Sons.

Dickie, W. J. (2014). Reeds 21st century ship management. Bloomsbury Publishing.

Esquerdo, P. J. R., & Welc, J. (2018). Applied Regression Analysis for Business. Springer International Publishing.

Gaurav, K. (2011). Multiple Regression Analysis: Key to Social Science Research. GRIN Verlag.

Gordon, R. (2015). Regression Analysis for the Social Sciences. Routledge.

Kavussanos, M. G. (1997). The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector. Applied Economics, 29(4), 433-443.

Kavussanos, M. G., & Alizadeh, A. H. (2002). Efficient pricing of ships in the dry bulk sector of the shipping industry. Maritime Policy & Management, 29(3), 303-330.

Kou, Y., Liu, L., & Luo, M. (2014). Lead–lag relationship between new-building and second-hand ship prices. Maritime Policy & Management, 41(4), 303-327.

Ma, S. (2020). Economics of Maritime Business. Routledge.

Menard, S. (2002). Applied Logistic Regression Analysis. Sage.

Merika, A., Merikas, A., Tsionas, M., & Andrikopoulos, A. (2019). Exploring vessel-price dynamics: The case of the dry bulk market. Maritime Policy & Management, 46(3), 309-329.

Newey, W., & West, K. (1987). A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55, 703–708.

Pagan, A. R., & Hall, A. D. (1983). Diagnostic tests as residual analysis. Econometric Reviews, 2(2), 159-218.

Pehli̇vanoğlu, F., & İnce, M. R. (2018). Batık maliyet, potansiyel rekabet ve yarışılabilirlik: denizyolu taşımacılığı piyasası örneği [Sunk cost, potential competition and contestability: The sample of maritime transport market]. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 5(3), 665-686.

Pruyn, J. F. J., Van de Voorde, E., & Meersman, H. (2011). Second hand vessel value estimation in maritime economics: a review of the past 20 years and the proposal of an elementary method. Maritime Economics & Logistics, 13(2), 213-236.

Rodrigue, J. P. (2013). Transport and globalization. In Rodrigue, J. P., Notteboom, T., & Shaw, J. (Eds.), The SAGE Handbook of Transport Studies (pp. 17-30). Sage.

Stopford, M. (2009). Maritime Economics. Routledge.

Syriopoulos, T., & Roumpis, E. (2006). Price and volume dynamics in second-hand dry bulk and tanker shipping markets. Maritime Policy & Management, 33(5), 497-518.

Tarı, R., & İnce, M. R. (2019). Denizyolu taşımacılığı piyasası kapsamında küresel ticaret hacminin analizi: Markov rejim değişim modeli [Analysis of global trade volume within the scope of maritime transport market: Markov regime switching model]. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 37, 1-20.

White, H. (1980). A heteroskedasticity-consistent covariance matrix and a direct test for heteroskedasticity. Econometrica, 48, 817–838.

Vermeulen, K. J. (2010). Framing a canvas for shipping strategy. In Grammenos, C. (Ed.), The Handbook of Maritime Economics and Business (pp. 851-888). Lloyd’s List.

Yan, X., & Su, X. (2009). Linear Regression Analysis: Theory and Computing. World Scientific.

Kaynak Göster

  • ISSN: 2147-9666
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 2012
  • Yayıncı: Adem Yavuz Sönmez

763 144

Sayıdaki Diğer Makaleler

Extraction and Characterization of Polyhydroxybutyrate (PHB) From Bacillus flexus MHO57386.1 Isolated From Marine Sponge Oceanopia arenosa (Rao, 1941)

Aryaraj D, Pramitha V V S

Investigation of the Use of Zeolite (Clinoptilolite) As Aquarium Filtration Material for Electric Blue Hap (Sciaenochromis ahli)

Meryem ÖZ, Dilek ŞAHİN, Zafer KARSLI, Orhan ARAL, Mehmet BAHTİYAR

Emission Analysis of LNG Fuelled Molten Carbonate Fuel Cell System for a Chemical Tanker Ship: A Case Study

Ömer Berkehan İNAL, Cengiz DENİZ

Adverse Effects of Ruditapes decussatus (Linnaeus, 1758) Diet on Stomach Tissues in Rats

Latife Ceyda İRKİN, Şamil ÖZTÜRK

Investigations on Endohelmint Fauna of Teleost Fishes of Aras and Murat Rivers in Turkey

Burçak ASLAN ÇELİK, Mehmet Cemal OĞUZ

Influence of Heat Shock Protein (HSP-70) Enhancing Compound From Red Alga (Porphyridium cruentum) for Augmenting Egg Production in Copepod Culture – A New In Silico Report


The Effect of Aging on Ship Values: An Econometric Analysis on Major Ship Types

Ozan Hasret GÜLTEKİN, ABDULLAH AÇIK, Sadık Özlen BAŞER, Kamil Özden EFES

Age, Growth and Reproduction of Neogobius melanostomus (Pallas 1814) (Perciformes: Gobiidae) in the Southern Black Sea

Mehmet AYDIN

Determination of Some Biological Characteristics and Population Parameters of the Blotched Picarel (Spicara flexuosa Rafinesque, 1810) Distributed in the Eastern Black Sea (Rize - Hopa)


Purification of Glutathione Reductase From Some Tissues of Capoeta umbla and the Inhibitory Effects of Some Metal Ions on Enzyme Activity

Muammer KIRICI, Mahinur KIRICI, Muhammed ATAMANALP, Şükrü BEYDEMİR