Time-varying effects of crude oil price fluctuations on tuna fish prices

  • Pierre Failler Centre for Blue Governance, University of Portsmouth, Portsmouth PO1 3DE, UK; UNESCO Chair in Ocean Governance, 75007 Paris, France
  • Yuhang Zheng National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
  • Yue Liu Aquatic Germplasm and Genetic Resources Center, School of Renewable Natural Resources, Louisiana State, University Agricultural Center, Baton Rouge, LA 70820, USA
  • Negar Akbari Centre for Blue Governance, University of Portsmouth, Portsmouth PO1 3DE, UK
  • Helga Josupeit Food and Agriculture Organization of the United Nations (FAO), Fisheries and Aquaculture, 00153 Rome, Italy
  • Andy Forse Centre for Blue Governance, University of Portsmouth, Portsmouth PO1 3DE, UK
  • Benjamin Drakeford Centre for Blue Governance, University of Portsmouth, Portsmouth PO1 3DE, UK
Keywords: tuna; oil price; commodity; financial crisis; sustainability

Abstract

This research presents an investigation of the time-varying effects of crude oil on the price of three tuna species, namely skipjack, albacore, and yellow fin. The investigation analyses the impact coefficient of oil price fluctuation on tuna species over time with specific phases related to time points when crude oil prices fall, including December 2008 (due to the impact of the Financial Crisis), February 2016 (due to the impact of the US shale oil and gas revolution), and April 2020 (due to the impact of the global COVID-19). The analysis shows that the price of yellow fin and skipjack shows sensitivity to these phased oil price shocks but stays consistent after recovery. This research finds that the relationship between oil price and tuna price depends on specific phases of oil price fluctuations and that global crude oil price shocks could have immediate and short-term impacts on fish markets, especially during a period of financial crisis.

References

Pelletier N, André J, Charef A, et al. Energy prices and seafood security. Global Environmental Change. 2014; 24: 30-41. doi: 10.1016/j.gloenvcha.2013.11.014

Reygondeau G, Maury O, Beaugrand G, et al. Biogeography of tuna and billfish communities. Journal of Biogeography. 2011; 39(1): 114-129. doi: 10.1111/j.1365-2699.2011.02582.x

Fromentin J. Lessons from the past: investigating historical data from bluefin tuna fisheries. Fish and Fisheries. 2009; 10(2): 197-216. doi: 10.1111/j.1467-2979.2008.00311.x

Cheilari A, Guillen J, Damalas D, et al. Effects of the fuel price crisis on the energy efficiency and the economic performance of the European Union fishing fleets. Marine Policy. 2013; 40: 18-24. doi: 10.1016/j.marpol.2012.12.006

Chen ST, Kuo HI, Chen CC. Modeling the relationship between the oil price and global food prices. Applied Energy. 2010; 87(8): 2517-2525. doi: 10.1016/j.apenergy.2010.02.020

Zhang Z, Lohr L, Escalante C, et al. Food versus fuel: What do prices tell us? Energy Policy. 2010; 38(1): 445-451. doi: 10.1016/j.enpol.2009.09.034

Esmaeili A, Shokoohi Z. Assessing the effect of oil price on world food prices: Application of principal component analysis. Energy Policy. 2011; 39(2): 1022-1025. doi: 10.1016/j.enpol.2010.11.004

Chaudhuri K. Long-run prices of primary commodities and oil prices. Applied Economics. 2001; 33(4): 531-538. doi: 10.1080/00036840122106

Ciaian P, Kancs A. Interdependencies in the energy–bioenergy–food price systems: A cointegration analysis. Resource and Energy Economics. 2011; 33(1): 326-348. doi: 10.1016/j.reseneeco.2010.07.004

Hassouneh I, Serra T, Goodwin BK, et al. Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships. Energy Economics. 2012; 34(5): 1507-1513. doi: 10.1016/j.eneco.2012.06.027

Busse S, Brümmer B, Ihle R. Price formation in the German biodiesel supply chain: a Markov‐switching vector error‐correction modeling approach. Agricultural Economics. 2012; 43(5): 545-560. doi: 10.1111/j.1574-0862.2012.00602.x

Jebabli I, Arouri M, Teulon F. On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility. Energy Economics. 2014; 45: 66-98. doi: 10.1016/j.eneco.2014.06.008

Balcilar M, Chang S, Gupta R, et al. The relationship between oil and agricultural commodity prices in south Africa: a quantile causality approach. The Journal of Developing Areas. 2016; 50(2): 137-152. doi: 10.1353/jda.2016.0089

Published
2024-04-18
Section
Article