IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v62y2017icp230-239.html
   My bibliography  Save this article

Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis

Author

Listed:
  • Pal, Debdatta
  • Mitra, Subrata K.

Abstract

This paper evaluates the association between crude oil prices and world food price indices, first within general space and time, and then within the combined time-frequency sphere. Monthly price data spanning from January 1990 to February 2016 were used for the analysis. The Johansen cointegration test conducted within the time domain confirmed the statistically significant cointegrated relationship between crude oil prices and the price indices of food and its sub-categories, such as dairy, cereals, vegetable oil, and sugar; however, frequency information was not accounted for. To incorporate both the time and frequency features of the data, we used a wavelet method that has shown that the world food prices, along with the prices of cereals, vegetable oils, and sugar, co-move with and are led by crude oil prices, results that remain relevant from the short-run policy perspective. The outcome of Toda–Yamamoto causality confirmed the spillover of crude oil price changes to the world food price index also in the long run. The paper ends with the policy implications of these results.

Suggested Citation

  • Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
  • Handle: RePEc:eee:eneeco:v:62:y:2017:i:c:p:230-239
    DOI: 10.1016/j.eneco.2016.12.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988317300075
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rafiq, Shuddhasattwa & Bloch, Harry, 2016. "Explaining commodity prices through asymmetric oil shocks: Evidence from nonlinear models," Resources Policy, Elsevier, vol. 50(C), pages 34-48.
    2. Saghaian, Sayed H., 2010. "The Impact of the Oil Sector on Commodity Prices: Correlation or Causation?," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 42(03), pages 477-485, August.
    3. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
    4. Vacha, Lukas & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2013. "Time–frequency dynamics of biofuel–fuel–food system," Energy Economics, Elsevier, vol. 40(C), pages 233-241.
    5. Natanelov, Valeri & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2013. "Crude oil–corn–ethanol – nexus: A contextual approach," Energy Policy, Elsevier, vol. 63(C), pages 504-513.
    6. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "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, Elsevier, vol. 45(C), pages 66-98.
    7. Abdelradi, Fadi & Serra, Teresa, 2015. "Food–energy nexus in Europe: Price volatility approach," Energy Economics, Elsevier, vol. 48(C), pages 157-167.
    8. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425.
    9. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    10. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    11. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    12. Maros Ivanic & Will Martin, 2008. "Implications of higher global food prices for poverty in low-income countries-super-1," Agricultural Economics, International Association of Agricultural Economists, vol. 39(s1), pages 405-416, November.
    13. Power, Gabriel J. & Turvey, Calum G., 2010. "Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 79-90.
    14. Lucotte, Yannick, 2016. "Co-movements between crude oil and food prices: A post-commodity boom perspective," Economics Letters, Elsevier, vol. 147(C), pages 142-147.
    15. repec:dau:papers:123456789/14980 is not listed on IDEAS
    16. Chris Brooks & Marcel Prokopczuk, 2013. "The dynamics of commodity prices," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 527-542, March.
    17. Manimaran, P. & Panigrahi, Prasanta K. & Parikh, Jitendra C., 2009. "Multiresolution analysis of fluctuations in non-stationary time series through discrete wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2306-2314.
    18. Geman, Hélyette & Kharoubi, Cécile, 2008. "WTI crude oil Futures in portfolio diversification: The time-to-maturity effect," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2553-2559, December.
    19. Nazlioglu, Saban & Soytas, Ugur, 2011. "World oil prices and agricultural commodity prices: Evidence from an emerging market," Energy Economics, Elsevier, vol. 33(3), pages 488-496, May.
    20. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
    21. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    22. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    23. Soytas, Ugur & Sari, Ramazan, 2006. "Can China contribute more to the fight against global warming?," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 837-846, November.
    24. Bazilian, Morgan & Rogner, Holger & Howells, Mark & Hermann, Sebastian & Arent, Douglas & Gielen, Dolf & Steduto, Pasquale & Mueller, Alexander & Komor, Paul & Tol, Richard S.J. & Yumkella, Kandeh K., 2011. "Considering the energy, water and food nexus: Towards an integrated modelling approach," Energy Policy, Elsevier, vol. 39(12), pages 7896-7906.
    25. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    26. Drabik, Dušan & Ciaian, Pavel & Pokrivčák, Ján, 2016. "The effect of ethanol policies on the vertical price transmission in corn and food markets," Energy Economics, Elsevier, vol. 55(C), pages 189-199.
    27. Wallace E. Tyner, 2010. "The integration of energy and agricultural markets," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 193-201, November.
    28. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
    29. Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2010. "Modeling the relationship between the oil price and global food prices," Applied Energy, Elsevier, vol. 87(8), pages 2517-2525, August.
    30. Liu, Li & Ma, Guofeng, 2014. "Cross-correlation between crude oil and refined product prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 284-293.
    31. Le, Thai-Ha & Chang, Youngho, 2015. "Effects of oil price shocks on the stock market performance: Do nature of shocks and economies matter?," Energy Economics, Elsevier, vol. 51(C), pages 261-274.
    32. Zhang, Zibin & Lohr, Luanne & Escalante, Cesar & Wetzstein, Michael, 2010. "Food versus fuel: What do prices tell us?," Energy Policy, Elsevier, vol. 38(1), pages 445-451, January.
    33. Han, Liyan & Zhou, Yimin & Yin, Libo, 2015. "Exogenous impacts on the links between energy and agricultural commodity markets," Energy Economics, Elsevier, vol. 49(C), pages 350-358.
    34. Olson, Eric & J. Vivian, Andrew & Wohar, Mark E., 2014. "The relationship between energy and equity markets: Evidence from volatility impulse response functions," Energy Economics, Elsevier, vol. 43(C), pages 297-305.
    35. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    36. Ivanic, Maros & Martin, Will, 2008. "Implications of higher global food prices for poverty in low-income countries," Policy Research Working Paper Series 4594, The World Bank.
    37. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    38. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    39. Mitchell, Donald, 2008. "A note on rising food prices," Policy Research Working Paper Series 4682, The World Bank.
    40. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    41. Adams, Zeno & Glueck, Thorsten, 2014. "Financialization in Commodity Markets: A Passing Trend or the New Normal?," Working Papers on Finance 1413, University of St. Gallen, School of Finance, revised Aug 2015.
    42. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    43. Rua, António & Nunes, Luís C., 2009. "International comovement of stock market returns: A wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 632-639, September.
    44. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    45. Nagayev, Ruslan & Disli, Mustafa & Inghelbrecht, Koen & Ng, Adam, 2016. "On the dynamic links between commodities and Islamic equity," Energy Economics, Elsevier, vol. 58(C), pages 125-140.
    46. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    47. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    48. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
    49. Robert J. Myers & Stanley R. Johnson & Michael Helmar & Harry Baumes, 2014. "Long-run and Short-run Co-movements in Energy Prices and the Prices of Agricultural Feedstocks for Biofuel," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(4), pages 991-1008.
    50. Doran, James S. & Ronn, Ehud I., 2008. "Computing the market price of volatility risk in the energy commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2541-2552, December.
    51. Teresa Serra & David Zilberman & José M. Gil & Barry K. Goodwin, 2011. "Nonlinearities in the U.S. corn‐ethanol‐oil‐gasoline price system," Agricultural Economics, International Association of Agricultural Economists, vol. 42(1), pages 35-45, January.
    52. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2016. "Time–frequency featured co-movement between the stock and prices of crude oil and gold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 985-995.
    53. Kelvin Balcombe & George Rapsomanikis, 2008. "Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 658-668.
    54. Minot, Nicholas, 2010. "Transmission of World Food Price Changes to African Markets and its Effect on Household Welfare," Food Security Collaborative Working Papers 58563, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    55. Hanson, Kenneth & Robinson, Sherman & Schluter, Gerald E., 1993. "Sectoral Effects Of A World Oil Price Shock: Economywide Linkages To The Agricultural Sector," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-21, July.
    56. Cha, Kyung Soo & Bae, Jeong Hwan, 2011. "Dynamic impacts of high oil prices on the bioethanol and feedstock markets," Energy Policy, Elsevier, vol. 39(2), pages 753-760, February.
    57. repec:dau:papers:123456789/607 is not listed on IDEAS
    58. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:eco:journ2:2018-04-16 is not listed on IDEAS

    More about this item

    Keywords

    Co-movement; Food price; Crude oil price; Time series; Wavelet;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:62:y:2017:i:c:p:230-239. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eneco .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.