ISTFIX Balonlarını Ne Tetikler?
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?
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.
Keywords:
Price bubbles, maritime, GSADF, logit regression, freight index,
___
- 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.
- ISSN: 2149-6838
- Yayın Aralığı: Yılda 2 Sayı
- Başlangıç: 2015
- Yayıncı: Seyfettin Artan
Sayıdaki Diğer Makaleler
Kamu Borç Yönetimi ve Vade Yapısına İlişkin Teorik Yaklaşımlar
Okul Öncesi Çocuklarda Reklâmın Satın Alma Davranışı Üzerindeki Etkileri
SERNUR KARAOĞLU, ÇİĞDEM ŞAHİN BAŞFIRINCI
Türkiye Elektrik Türev Piyasalarının Gelişimi
ISTFIX Balonlarını Ne Tetikler?
ABDULLAH AÇIK, SADIK ÖZLEN BAŞER, Egemen ERTÜRK