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Faiz Oranının Kuru Dökme Yük Navlun Piyasasına Etkisinin Zamanla Değişen Nedensellik Yöntemiyle Analizi

Year 2021, Volume: 6 Issue: 2, 403 - 417, 27.08.2021
https://doi.org/10.30784/epfad.798092

Abstract

Faiz oranları hem gemi yatırımlarındaki maliyeti belirleyici rolü hem de dünya ekonomisindeki mallara olan talebi belirleyici rolü ile denizcilik piyasalarını da önemli ölçüde etkilemektedir. Biz bu çalışmamızda diğer denizcilik piyasalarının temeli olan ve onlara göre çok daha dinamik yapıda olan navlun piyasasına olan etkisini incelemeyi amaçladık. Faiz oranlarındaki değişimin dünya ekonomisini etkileyeceğini ancak bu etkinin tüm dönem boyunca varlığını sürdüremeyeceğinden yola çıkarak, önce doğrusal bir yaklaşımla, daha sonra ise zamana göre değişen bir yaklaşımla analizleri uyguladık. Analizlerde küresel faiz oranlarının göstergesi olarak Federal Fon Oranı, kuru dökme yük navlunlarının göstergesi olarak ise Baltık Kuru Yük Endeksi (BKYE) kullanılmıştır. 1995 ve 2020 yılları arasını kapsayan aylık 302 gözlemden oluşan veri seti kullanılarak zamana göre değişen yaklaşım ile yapılan analizler sonucunda, anlamlı ilişkinin tüm örneklem boyunca var olmadığı, sadece belli zamanlarda görüldüğü ve anlamlı ilişkinin görüldüğü dönemlerin BKYE’nin artış ve düşüş eğilimine girdiği dönemler olduğu tespit edilmiştir. Böylece faiz oranlarındaki değişimlerin yalnızca küresel ekonomiyi etkilemekle kalmayıp, kuru dökme yük navlun piyasasının eğilimini de etkilediği belirlenmiştir.

References

  • Açık, A. and Ayaz, İ. S. (2018). Time varying causality between cost and price: An empirical analysis on dry bulk shipping market. Journal of Business Research-Turk, 10(4), 136-147. https://doi.org/10.20491/isarder.2018.516
  • Açık, A. and Başer, S. Ö. (2018). An analytical study on the likely causes of the minor bubbles in the Baltic Dry Index. International Journal of Logistics Economics and Globalisation, 7(4), 353-365. https://doi.org/10.1504/IJLEG.2018.097478
  • Açık, A. and İnce, M. R. (2019). Income and asset value relationship: A nonlinear approach to Capesize shipping market. In S. Koc, S. Yilmaz Genc and V. H Benli (Eds.), Economic issues: Global and local perspectives (pp. 35-43). UK: Cambridge International Academics.
  • Açık, A., Kesiktaş, H. H. İ. and Başer, S. Ö. (2020). Role of interest rates on fleet capacity adjustment decisions of shipowners. Ekonomi, Politika & Finans Araştırmaları Dergisi, 5(1), 66-80. https://doi.org/10.30784/epfad.642061
  • Açık, A., Sağlam, B. B. and Tepe, R. (2019). Time-varying causality between exchange rate and container handling volume in Turkish ports. Transport & Logistics: The International Journal, 19(46), 1-11. Retrieved from http://ulpad.fberg.tuke.sk/transportlogistics/
  • Agarwal, V. (2010). Macroeconomics: Theory and policy. India: Pearson.
  • Balcilar, M. and Ozdemir, Z. A. (2013a). Asymmetric and time‐varying causality between inflation and inflation uncertainty in G-7 countries. Scottish Journal of Political Economy, 60(1), 1-42. https://doi.org/10.1111/sjpe.12000
  • Balcilar, M. and Ozdemir, Z. A. (2013b). The export-output growth nexus in Japan: A bootstrap rolling window approach. Empirical Economics, 44(2), 639-660. https://doi.org/10.1007/s00181-012-0562-8
  • Bampinas, G. and Panagiotidis, T. (2015). On the relationship between oil and gold before and after financial crisis: Linear, nonlinear and time-varying causality testing. Studies in Nonlinear Dynamics & Econometrics, 19(5), 657-668. https://doi.org/10.1515/snde-2014-0060
  • Başer, S. Ö. and Açık, A. (2019). The effects of global economic growth on dry bulk freight rates. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 3(1), 1-17. https://doi.org/10.30711/utead.507566
  • Beenstock, M. (1985). A theory of ship prices. Maritime Policy & Management: The Flagship Journal of International Shipping and Port Research, 12(3), 215-225. https://doi.org/10.1080/03088838500000028
  • Bildirici, M. E. and Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46, 202-211. https://doi.org/10.1016/j.resourpol.2015.09.002
  • Bloomberg. (2020). Baltic dry index [Dataset]. Retrieved from https://www.bloomberg.com/professional/
  • Branch, A. E. (2007). Elements of shipping. New York: Routledge.
  • Broock, W. A., Scheinkman, J. A., Dechert, W. D. and LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3), 197-235. https://doi.org/10.1080/07474939608800353
  • Fabozzi, F. J, Modigliani, F. and Jones, F.J. (2014). Foundation of financial markets and institutions (4. Edition). USA: Pearson.
  • FED. (2019). Inflation and interest rates [Dataset]. Retrieved from https://fred.stlouisfed.org/series/FEDFUNDS
  • Geman, H. (2009). Risk management in commodity markets: From shipping to agriculturals and energy (Vol. 445). USA: John Wiley & Sons.
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral method. Econometrica: Journal of the Econometric Society, 424-438. https://doi.org/10.2307/1912791
  • Inglesi-Lotz, R., Balcilar, M. and Gupta, R. (2014). Time-varying causality between research output and economic growth in US. Scientometrics, 100(1), 203-216. https://doi.org/10.1007/s11192-014-1257-z
  • Karakitsos, E. and Varnavides, L. (2014). Maritime economics: A macroeconomic approach. New York: Springer.
  • Kavussanos, M. G. and Visvikis, I. D. (2006). Shipping freight derivatives: A survey of recent evidence. Maritime Policy & Management, 33(3), 233–255. https://doi.org/10.1080/03088830600783152
  • Langdana, F. K. (2009). Macroeconomic policy: Demystifying monetary and fiscal policy. USA: Springer.
  • Lawson, M. (2008). If not now, when? Three actions the G20 must take now to protect the World’s poor from the economic crisis and build a new political and economic governance system. USA: Oxfam.
  • Lee, J. and Strazicich, M. C. (2003). Minimum lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics, 85(4), 1082-1089. https://doi.org/10.1162/003465303772815961
  • Lee, J. and Strazicich, M. C. (2013). Minimum LM unit root test with one structural break. Economics Bulletin, 33(4), 2483-2492. Retrieved from http://www.accessecon.com/
  • Li, X. L., Balcilar, M., Gupta, R. and Chang, T. (2016). The causal relationship between economic policy uncertainty and stock returns in China and India: Evidence from a bootstrap rolling window approach. Emerging Markets Finance and Trade, 52(3), 674-689. https://doi.org/10.1080/1540496X.2014.998564
  • Ma, S. (2020). Economics of maritime business. New York: Routledge.
  • Narayan, P. K. and Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37(9), 1425-1438. https://doi.org/ 10.1080/02664760903039883
  • Poulakidas, A. and Joutz, F. (2009). Exploring the link between oil prices and tanker rates. Maritime Policy & Management, 36(3), 215-233. https://doi.org/10.1080/03088830902861094
  • Shen, C. W. and Chou, C. C. (2015, August). Temporal causality between dry bulk freight and crude oil price. Paper presented at the International Association of Maritime Economists (IAME) conference, Kuala Lumpur, Malaysia.
  • Strandenes, S. P. (1984). Price determination in the time charter and second hand markets (Center for Applied Research, Norwegian School of Economics and Business Administration, Working Paper MU, 6). Retrieved from https://www.econbiz.de/
  • Şahin, B., Gürgen, S., Ünver, B. and Altin, I. (2018). Forecasting the Baltic Dry Index by using an artificial neural network approach. Turkish Journal of Electrical Engineering & Computer Sciences, 26(3), 1673-1684. Retrieved from https://dergipark.org.tr/tr/pub/tbtkelektrik
  • UNCTAD. (2018). Review of maritime transport 2018. Retrieved from https://unctad.org/system/files/official-document/rmt2018_en.pdf
  • United Nations. (2009). World economic situation and prospects 2009 (World economic and social survey supplement). Retrieved from https://www.un.org/es/file/71089/download?toke n=TbJO7hmb
  • Vermeulen, K. J. (2010). Framing a canvas for shipping strategy. In C. Grammenos (Ed.), The handbook of maritime economics and business (pp. 851-888). London: Lloyd’s List.
  • Yin, J., M. Luo and L. Fan. (2017). Dynamics and interactions between spot and forward freights in the dry bulk shipping market. Maritime Policy & Management, 44(2), 271–288. https://doi.org/10.1080/03088839.2016.1253884
  • Youngjae, C. and Hyunsok, K. (2016). The spillover from asset determinants to ship price. The Korea Port Economic Association, 32(2), 59-71. Retrieved from https://www.koreascience.or.kr/
  • Zannetos, Z. S. (1966). The theory of oil tankship rates. USA: Massachusetts Institute of Technology.
  • Zivot, E. and Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 20(1), 25-44. https://doi.org/ 10.2307/1391541

Analyzing the Impact of Interest Rate on Dry Bulk Freight Market with Time-Varying Causality Method

Year 2021, Volume: 6 Issue: 2, 403 - 417, 27.08.2021
https://doi.org/10.30784/epfad.798092

Abstract

The interest rates significantly affect maritime markets, both with their role in determining the cost of ship investments and their role in determining the demand for goods in the world economy. We examined the impact on the freight market, which is the fundamental of other maritime markets and is much more dynamic than them. Considering that change in interest rates affects the world economy, but this effect may not survive throughout the period, we applied the analysis first with a linear approach and then with a time-varying approach. The federal funds rate is used as an indicator of global interest rates, and the Baltic Dry Index (BDI) is used as an indicator of the dry bulk freight market. As a result of analysis performed using a data set consisting of 302 monthly observations covering the period between 1995 and 2020, it was determined that the significant relationship does not exist throughout the whole sample, it exists only at certain periods, and the significant effect occurs when BDI tends to increase and decrease. Thus, it was determined that changes in interest rates not only affect the global economy but also the trend of the dry bulk freight market.

References

  • Açık, A. and Ayaz, İ. S. (2018). Time varying causality between cost and price: An empirical analysis on dry bulk shipping market. Journal of Business Research-Turk, 10(4), 136-147. https://doi.org/10.20491/isarder.2018.516
  • Açık, A. and Başer, S. Ö. (2018). An analytical study on the likely causes of the minor bubbles in the Baltic Dry Index. International Journal of Logistics Economics and Globalisation, 7(4), 353-365. https://doi.org/10.1504/IJLEG.2018.097478
  • Açık, A. and İnce, M. R. (2019). Income and asset value relationship: A nonlinear approach to Capesize shipping market. In S. Koc, S. Yilmaz Genc and V. H Benli (Eds.), Economic issues: Global and local perspectives (pp. 35-43). UK: Cambridge International Academics.
  • Açık, A., Kesiktaş, H. H. İ. and Başer, S. Ö. (2020). Role of interest rates on fleet capacity adjustment decisions of shipowners. Ekonomi, Politika & Finans Araştırmaları Dergisi, 5(1), 66-80. https://doi.org/10.30784/epfad.642061
  • Açık, A., Sağlam, B. B. and Tepe, R. (2019). Time-varying causality between exchange rate and container handling volume in Turkish ports. Transport & Logistics: The International Journal, 19(46), 1-11. Retrieved from http://ulpad.fberg.tuke.sk/transportlogistics/
  • Agarwal, V. (2010). Macroeconomics: Theory and policy. India: Pearson.
  • Balcilar, M. and Ozdemir, Z. A. (2013a). Asymmetric and time‐varying causality between inflation and inflation uncertainty in G-7 countries. Scottish Journal of Political Economy, 60(1), 1-42. https://doi.org/10.1111/sjpe.12000
  • Balcilar, M. and Ozdemir, Z. A. (2013b). The export-output growth nexus in Japan: A bootstrap rolling window approach. Empirical Economics, 44(2), 639-660. https://doi.org/10.1007/s00181-012-0562-8
  • Bampinas, G. and Panagiotidis, T. (2015). On the relationship between oil and gold before and after financial crisis: Linear, nonlinear and time-varying causality testing. Studies in Nonlinear Dynamics & Econometrics, 19(5), 657-668. https://doi.org/10.1515/snde-2014-0060
  • Başer, S. Ö. and Açık, A. (2019). The effects of global economic growth on dry bulk freight rates. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 3(1), 1-17. https://doi.org/10.30711/utead.507566
  • Beenstock, M. (1985). A theory of ship prices. Maritime Policy & Management: The Flagship Journal of International Shipping and Port Research, 12(3), 215-225. https://doi.org/10.1080/03088838500000028
  • Bildirici, M. E. and Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46, 202-211. https://doi.org/10.1016/j.resourpol.2015.09.002
  • Bloomberg. (2020). Baltic dry index [Dataset]. Retrieved from https://www.bloomberg.com/professional/
  • Branch, A. E. (2007). Elements of shipping. New York: Routledge.
  • Broock, W. A., Scheinkman, J. A., Dechert, W. D. and LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3), 197-235. https://doi.org/10.1080/07474939608800353
  • Fabozzi, F. J, Modigliani, F. and Jones, F.J. (2014). Foundation of financial markets and institutions (4. Edition). USA: Pearson.
  • FED. (2019). Inflation and interest rates [Dataset]. Retrieved from https://fred.stlouisfed.org/series/FEDFUNDS
  • Geman, H. (2009). Risk management in commodity markets: From shipping to agriculturals and energy (Vol. 445). USA: John Wiley & Sons.
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral method. Econometrica: Journal of the Econometric Society, 424-438. https://doi.org/10.2307/1912791
  • Inglesi-Lotz, R., Balcilar, M. and Gupta, R. (2014). Time-varying causality between research output and economic growth in US. Scientometrics, 100(1), 203-216. https://doi.org/10.1007/s11192-014-1257-z
  • Karakitsos, E. and Varnavides, L. (2014). Maritime economics: A macroeconomic approach. New York: Springer.
  • Kavussanos, M. G. and Visvikis, I. D. (2006). Shipping freight derivatives: A survey of recent evidence. Maritime Policy & Management, 33(3), 233–255. https://doi.org/10.1080/03088830600783152
  • Langdana, F. K. (2009). Macroeconomic policy: Demystifying monetary and fiscal policy. USA: Springer.
  • Lawson, M. (2008). If not now, when? Three actions the G20 must take now to protect the World’s poor from the economic crisis and build a new political and economic governance system. USA: Oxfam.
  • Lee, J. and Strazicich, M. C. (2003). Minimum lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics, 85(4), 1082-1089. https://doi.org/10.1162/003465303772815961
  • Lee, J. and Strazicich, M. C. (2013). Minimum LM unit root test with one structural break. Economics Bulletin, 33(4), 2483-2492. Retrieved from http://www.accessecon.com/
  • Li, X. L., Balcilar, M., Gupta, R. and Chang, T. (2016). The causal relationship between economic policy uncertainty and stock returns in China and India: Evidence from a bootstrap rolling window approach. Emerging Markets Finance and Trade, 52(3), 674-689. https://doi.org/10.1080/1540496X.2014.998564
  • Ma, S. (2020). Economics of maritime business. New York: Routledge.
  • Narayan, P. K. and Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37(9), 1425-1438. https://doi.org/ 10.1080/02664760903039883
  • Poulakidas, A. and Joutz, F. (2009). Exploring the link between oil prices and tanker rates. Maritime Policy & Management, 36(3), 215-233. https://doi.org/10.1080/03088830902861094
  • Shen, C. W. and Chou, C. C. (2015, August). Temporal causality between dry bulk freight and crude oil price. Paper presented at the International Association of Maritime Economists (IAME) conference, Kuala Lumpur, Malaysia.
  • Strandenes, S. P. (1984). Price determination in the time charter and second hand markets (Center for Applied Research, Norwegian School of Economics and Business Administration, Working Paper MU, 6). Retrieved from https://www.econbiz.de/
  • Şahin, B., Gürgen, S., Ünver, B. and Altin, I. (2018). Forecasting the Baltic Dry Index by using an artificial neural network approach. Turkish Journal of Electrical Engineering & Computer Sciences, 26(3), 1673-1684. Retrieved from https://dergipark.org.tr/tr/pub/tbtkelektrik
  • UNCTAD. (2018). Review of maritime transport 2018. Retrieved from https://unctad.org/system/files/official-document/rmt2018_en.pdf
  • United Nations. (2009). World economic situation and prospects 2009 (World economic and social survey supplement). Retrieved from https://www.un.org/es/file/71089/download?toke n=TbJO7hmb
  • Vermeulen, K. J. (2010). Framing a canvas for shipping strategy. In C. Grammenos (Ed.), The handbook of maritime economics and business (pp. 851-888). London: Lloyd’s List.
  • Yin, J., M. Luo and L. Fan. (2017). Dynamics and interactions between spot and forward freights in the dry bulk shipping market. Maritime Policy & Management, 44(2), 271–288. https://doi.org/10.1080/03088839.2016.1253884
  • Youngjae, C. and Hyunsok, K. (2016). The spillover from asset determinants to ship price. The Korea Port Economic Association, 32(2), 59-71. Retrieved from https://www.koreascience.or.kr/
  • Zannetos, Z. S. (1966). The theory of oil tankship rates. USA: Massachusetts Institute of Technology.
  • Zivot, E. and Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 20(1), 25-44. https://doi.org/ 10.2307/1391541
There are 40 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Makaleler
Authors

Abdullah Açık 0000-0003-4542-9831

Özhan Okutucu This is me 0000-0003-0880-5383

Kamil Özden Efes 0000-0001-7087-5337

Sadık Özlen Başer 0000-0001-6632-2617

Publication Date August 27, 2021
Acceptance Date June 13, 2021
Published in Issue Year 2021 Volume: 6 Issue: 2

Cite

APA Açık, A., Okutucu, Ö., Efes, K. Ö., Başer, S. Ö. (2021). Analyzing the Impact of Interest Rate on Dry Bulk Freight Market with Time-Varying Causality Method. Ekonomi Politika Ve Finans Araştırmaları Dergisi, 6(2), 403-417. https://doi.org/10.30784/epfad.798092