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Empirical Analysis of Agricultural Commodity Prices, Crude Oil Prices and US Dollar Exchange Rates using Panel Data Econometric Methods

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  • Anthony N. Rezitis

    (Department of Economics and Management, University of Helsinki, P.O. Box 27, Latokartanokaari 9, FI-00014, Finland.)

Abstract

This study examines the long-run relationship between crude oil prices, US dollar exchange rates (EXCR) and the prices of 30 selected international agricultural prices and five international fertilizer prices using panel econometric methods with and without unobserved heterogeneous effects on data sets of the period from June 1983 to June 2013. The empirical results indicate that in the long-run the impact of crude oil price changes on agricultural prices is positive and statistically significant, while the impact of US dollar EXCR changes is negative and statistically significant. Furthermore, the effect of US dollar EXCR changes on commodity prices is stronger than that of crude oil price changes. The present study estimates the speed of adjustment of agricultural commodity prices (AGCP) towards the long-run equilibrium and the empirical results indicate that AGCP adjust slowly towards the long-run equilibrium. Furthermore, the results of this study indicate that when unobserved heterogeneous effects with common factors are considered, the effects of oil prices and US dollar EXCRs on AGCP are much weaker than in the case in which such effects are not considered. Finally, the persistent movements of agricultural prices are mostly attributed to the first common factor, which is closely related to the US dollar EXCR, while the short-lived deviations of AGCP away from their long-run equilibrium level might be due to the remaining four stationary common factors, which are capturing factors affecting the world supply and demand conditions of the international agricultural prices

Suggested Citation

  • Anthony N. Rezitis, 2015. "Empirical Analysis of Agricultural Commodity Prices, Crude Oil Prices and US Dollar Exchange Rates using Panel Data Econometric Methods," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 851-868.
    • Handle: RePEc:eco:journ2:2015-03-28
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    as
    1. 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(3), pages 477-485, August.
    2. Robles, Miguel & Torero, Maximo & von Braun, Joachim, 2009. "When speculation matters:," Issue briefs 57, International Food Policy Research Institute (IFPRI).
    3. Brian D. Wright, 2012. "International Grain Reserves And Other Instruments to Address Volatility in Grain Markets," The World Bank Research Observer, World Bank, vol. 27(2), pages 222-260, August.
    4. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Hansen, Bruce E., 1992. "Efficient estimation and testing of cointegrating vectors in the presence of deterministic trends," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 87-121.
    7. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    8. Shu-Ling Chen & John D. Jackson & Hyeongwoo Kim & Pramesti Resiandini, 2014. "What Drives Commodity Prices?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(5), pages 1455-1468.
    9. Derek Headey & Shenggen Fan, 2008. "Anatomy of a crisis: the causes and consequences of surging food prices," Agricultural Economics, International Association of Agricultural Economists, vol. 39(s1), pages 375-391, November.
    10. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    11. Trostle, Ronald, 2008. "Fluctuating Food Commodity Prices: A Complex Issue With No Easy Answers," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-8, November.
    12. Kneip, Alois & Sickles, Robin C. & Song, Wonho, 2012. "A New Panel Data Treatment For Heterogeneity In Time Trends," Econometric Theory, Cambridge University Press, vol. 28(3), pages 590-628, June.
    13. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Department of Economics Working Papers 2000-02, Department of Economics, Williams College.
    14. Kellard, Neil & Wohar, Mark E., 2006. "On the prevalence of trends in primary commodity prices," Journal of Development Economics, Elsevier, vol. 79(1), pages 146-167, February.
    15. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    16. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    17. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    18. Anthony N. Rezitis, 2015. "The relationship between agricultural commodity prices, crude oil prices and US dollar exchange rates: a panel VAR approach and causality analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 29(3), pages 403-434, May.
    19. Anindya Banerjee & Martin Wagner, 2009. "Panel Methods to Test for Unit Roots and Cointegration," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 13, pages 632-726, Palgrave Macmillan.
    20. Cooke, Bryce & Robles, Miguel, 2009. "Recent food prices movements: A time series analysis," IFPRI discussion papers 942, International Food Policy Research Institute (IFPRI).
    21. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    22. 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.
    23. 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.
    24. Peter Pedroni, 2007. "Social capital, barriers to production and capital shares: implications for the importance of parameter heterogeneity from a nonstationary panel approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 429-451.
    25. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    26. repec:bla:obuest:v:61:y:1999:i:0:p:653-70 is not listed on IDEAS
    27. Aynur Pala, 2013. "Structural Breaks, Cointegration, and Causality by VECM Analysis of Crude Oil and Food Price," International Journal of Energy Economics and Policy, Econjournals, vol. 3(3), pages 238-246.
    28. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
    29. Dabin Wang & William G. Tomek, 2007. "Commodity Prices and Unit Root Tests," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(4), pages 873-889.
    30. Peter Pedroni, 2001. "Purchasing Power Parity Tests In Cointegrated Panels," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 727-731, November.
    31. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    32. Ciaian, Pavel & Kancs, d'Artis, 2011. "Interdependencies in the energy-bioenergy-food price systems: A cointegration analysis," Resource and Energy Economics, Elsevier, vol. 33(1), pages 326-348, January.
    33. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
    34. Harri, Ardian & Nalley, Lanier & Hudson, Darren, 2009. "The Relationship between Oil, Exchange Rates, and Commodity Prices," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(2), pages 501-510, August.
    35. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    36. Brian D. Wright, 2011. "The Economics of Grain Price Volatility," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 32-58.
    37. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    38. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    39. C. Peter Timmer, 2009. "Did Speculation Affect World Rice Prices?," Working Papers 09-07, Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA).
    40. Nazlioglu, Saban & Soytas, Ugur, 2012. "Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis," Energy Economics, Elsevier, vol. 34(4), pages 1098-1104.
    41. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    42. Bada, Oualid & Liebl, Dominik, 2014. "phtt: Panel Data Analysis with Heterogeneous Time Trends in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i06).
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    More about this item

    Keywords

    Agricultural Commodity Prices; Oil Prices; Exchange Rates; Panel Cointegration; Panel Error Correction; Unobserved Heterogeneity; Common Factors;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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