ISTFIX Balonlarını Ne Tetikler?

Yıl 2018, Cilt: 4 Sayı: 2, 119 - 135, 21.10.2018

Abdullah Açık Sadık Özlen Başer Egemen Ertürk

https://doi.org/10.20979/ueyd.434031

Öz

Denizcilik piyasasında arzın talebe olan tepkisindeki
gecikmelerden dolayı büyük veya küçük sürekli konjonktürel dalgalanmalar
gözlemlenmektedir. Bazı durumlarda gelirler gemi sahiplerine yaşam fırsatı
vermeyecek kadar düşerken, bazı durumlarda onlara sıfırdan çok büyük kazançlara
uzanma fırsatı sağlamaktadır. Tüm bu risklere rağmen denizcilik piyasası
özellikle Türkiye gibi gelişmekte olan ülkeler için çok önemlidir. Bu
çalışmanın amacı İstanbul Navlun Endeksi’nde (ISTFIX) fiyat balonları oluşma
olasılığına etki eden faktörleri tespit etmektir. Bu doğrultuda ilk olarak
genelleştirilmiş eküs Augmented-Dickey-Fuller (GSADF) testi ile fiyat balonları
tespit edilmiştir. GSADF testini takiben de balonların görüldüğü tarihlerden
kukla değişken oluşturularak lojistik regresyon modeli kurulmuştur ve balon
oluşumunu etkileyen faktörler tespit edilmeye çalışılmıştır. Veri seti
18.03.2011 ve 31.12.2017 tarihleri arasını kapsayan 354 gözlemden oluşmaktadır.
Sonuçlara göre uzunlukları 6 ila 12 hafta arasında değişen 4 balon dönemi
tespit edilmiştir. Lojistik regresyonda ise “avro” ve “yakıt fiyatı”
değişkenlerinin balon oluşma olasılığını arttırdıkları ve “avro” değişkeninin
marjinal etkisinin çok daha yüksek olduğu tespit edilmiştir. 

Anahtar Kelimeler

Fiyat balonları, denizcilik, GSADF, lojistik regresyon, navlun endeksi.

What Triggers the ISTFIX Bubbles?

Öz

Business cycles are constantly observed,
whether small or large, due to delays in response of supply to demand in the
maritime market. In some cases, the incomes are so low that it does not give
the shipowners a chance to live, and in some cases they go from rags to riches.
Despite these risks, the maritime market is vital especially for developing
countries such as Turkey. The aim of this study is to determine the factors
that influence the probability of price bubble formation in the İstanbul
Freight Index (ISTFIX). In this direction, firstly the price bubbles were
determined by generalized sup augmented Dickey-Fuller (GSADF) test. Following
the GSADF test, a logit regression model was established by creating dummy
variables from bubble dates and it was tried to determine the factors affecting
bubble formation. The dataset consists of 354 weekly observations and covers the
dates between 18.03.2011 and 31.12.2017. According to the results, 4 bubble
periods with lengths ranging from 6 to 12 weeks were detected. In the logit
model, it was found that “euro” and “fuel price” variables increase the
probability of bubble formation and the marginal effect of “euro” is much
higher. 

Anahtar Kelimeler

Price bubbles, maritime, GSADF, logit regression, freight index

Kaynakça

• Alexander, S. S. (1952), “Effects of Devaluation on a Trade Balance”, IMF Staff Paper, 2(2), 263-78.
• Asteriou, D., Masatci, K.and Pılbeam, K. (2016), “Exchange Rate Volatility and International Trade: International Evidence from The MINT Countries”, Economic Modelling, 58, 133-140.
• Baker, F. B. and Kim, S. H. (Eds.). (2004), Item Response Theory: Parameter Estimation Techniques, United States: CRC Press.
• Caspi, I., Katzke, N. and Gupta, R. (2015), "Date Stamping Historical Periods of Oil Price Explosivity: 1876–2014", Energy Economics, 70(C), 582-587.
• Chaudhary, G. M., Hashmi, S. H. and Khan, M. A. (2016), “Exchange Rate and Foreign Trade: A Comparative Study of Major South Asian and South-East Asian Countries”, Procedia-Social and Behavioral Sciences, 230, 85-93.
• Chen, S., Meersman, H., Van de Voorde, E., and Frouws, K. (2014), Modelling and Forecasting in Dry Bulk Shipping, London: Informa Law from Routledge.
• Chi, J. and Cheng, S. K. (2016), “Do Exchange Rate Volatility and Income Affect Australia’s Maritime Export Flows to Asia?”, Transport Policy, 47, 13-21.
• Cowie, J. (2009), The Economics of Transport: A Theoretical and Applied Perspective, New York: Routledge.
• Evans, G.W. (1991), “Pitfalls in Testing for Explosive Bubbles in Asset Prices”, The American Economic Review, 81(4), 922–930.
• Gujrati, D.N. (2004), Basic Econometric (4th Ed.), NewYork:.The McGraw-Hill Companies.
• ISTFIX (İstanbul Freight Index), “About Us”, http://www.istfix.com/Content.php?ContentID=145 (Accessed: 20.05.2018)
• Krishnan, R. (2016), Univariate Time-Series Analysis and Forecasting: Theory and Practice, Decision Sciences: Theory and Practice, 523-627.
• Odeke, A. (1984), Protectionism and the Future of International Shipping: The Nature, Development, and Role of Flag Discriminations and Preferences, Cargo Reservations and Cabotage Restrictions, State Intervention and Maritime Subsidies, Dordrecht: Martinus Nijhoff.
• Phillips, P.C.B., S. Shi, and J. Yu, (2012), “Testing for Multiple Bubbles”, Cowles Foundation Discussion Paper, No. 1843, Yale University, New Haven, Connecticut, USA.
• Phillips, P.C.B., Y. Wu, and J. Yu, (2011), “Explosive behavior in the 1990s NASDAQ: When did exuberance escalate asset values?”, International Economic Review, 52, 201–226.
• Sekmen, F. and Saribas, H. (2007), “Cointegration and Causality Among Exchange Rate, Export, and Import: Empirical Evidence from Turkey”, Applied Econometrics and International Development, 7(2), 71-78.
• Senadza, B. and Diaba, D. D. (2017), “Effect of Exchange Rate Volatility On Trade in Sub-Saharan Africa”, Journal of African Trade, 4(1-2), 20-36.
• Serenis, D. and Tsounis, N. (2014), “Does Exchange Rate Variation Effect African Trade Flows?”, Procedia Economics and Finance, 14, 565-574.
• Sharma, C. and Pal, D. (2018), “Exchange Rate Volatility and India's Cross-Border Trade: A Pooled Mean Group and Nonlinear Cointegration Approach”, Economic Modelling, xx, 1-17.
• Shenkar, O. and Luo, Y. (2008), International Business (2nd Ed), London: Sage Publications.
• Šimáková, J. (2014), “The Impact of Exchange Rate Development on Czech Trade Flows”, Procedia Economics and Finance, 15, 129-136.
• Su, C. W., Li, Z. Z., Chang, H. L. and Lobonţ, O. R. (2017), “When Will Occur the Crude Oil Bubbles?”, Energy Policy, 102, 1-6.
• Su-Ling, T. S. A. I. and Hsien-Hung, K. U. N. G. (2015), “Testing for Multiple Bubbles in the 35 Large and Medium Cities of Real Estate Price in China”, Theoretical & Applied Economics, 22(4), 275-290.
• CBRT (Central Bank of the Republic of Turkey), “Exchange Rates”, http://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Statistics/Exchange+Rates/ (Accessed: 15.05.2018)
• TSI (Turkish Statistical Institute), “Export Statistics of Turkey”, http://www.tuik.gov.tr/PreTablo.do?alt_id=1046 (Accessed: 13.05.2018)
• Verbeek, M. (2017), A Guide to Modern Econometrics (5th Ed), Australia: John Wiley & Sons.
• Wijnolst, N. and Wergeland, T. (2009), Shipping Innovation, Amsterdam: IOS Press.