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Forecasting the spot prices of various coffee types using linear and non-linear error correction models

Author

Listed:
  • Costas Milas

    (Department of Economics, City University, UK)

  • Jesús Otero

    (Facultad de Economía, Universidad del Rosario, Colombia)

  • Theodore Panagiotidis

    (Department of Economics, Loughborough University, UK)

Abstract

This paper estimates linear and non-linear error correction models for the spot prices of four different coffee types. In line with economic priors, we find some evidence that when prices are too high, they move back to equilibrium more slowly than when they are too low. This may reflect the fact that, in the short run, it is easier for countries to restrict the supply of coffee in order to raise prices, rather than increase supply in order to reduce them. Further, there is some evidence that adjustment is faster when deviations from the equilibrium level get larger. Our forecasting analysis suggests that asymmetric and polynomial error correction models offer weak evidence of improved forecasting performance relative to the random walk model. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Costas Milas & Jesús Otero & Theodore Panagiotidis, 2004. "Forecasting the spot prices of various coffee types using linear and non-linear error correction models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 277-288.
    • Handle: RePEc:ijf:ijfiec:v:9:y:2004:i:3:p:277-288
    DOI: 10.1002/ijfe.245
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    References listed on IDEAS

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    Cited by:

    1. David Ubilava, 2012. "El Niño, La Niña, and world coffee price dynamics," Agricultural Economics, International Association of Agricultural Economists, vol. 43(1), pages 17-26, January.
    2. Fousekis, Panos & Grigoriadis, Vasilis, 2022. "Conditional tail price risk spillovers in coffee markets across quality, physical space, and time: Empirical analysis with penalized quantile regressions," Economic Modelling, Elsevier, vol. 106(C).
    3. Andrea Bastianin & Alessandro Lanza & Matteo Manera, 2018. "Economic impacts of El Niño southern oscillation: evidence from the Colombian coffee market," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 623-633, September.
    4. Coronado Ramírez Semei Leopoldo & Porras Serrano Jesús & Sandoval Bravo Salvador, 2013. "Aplicación de bicorrelación cruzada al rendimiento diario del precio del café," Contaduría y Administración, Accounting and Management, vol. 58(1), pages 117-129, enero-mar.
    5. Li, Xi-Le & Saghaian, Sayed, 2014. "The Presence Of Market Power In The Coffee Market: The Case Of Colombian Milds," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170348, Agricultural and Applied Economics Association.
    6. Atanu Ghoshray, 2010. "The Extent Of The World Coffee Market," Bulletin of Economic Research, Wiley Blackwell, vol. 62(1), pages 97-107, January.
    7. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    8. Atanu Ghoshray, 2009. "On Price Dynamics for Different Qualities of Coffee," Review of Market Integration, India Development Foundation, vol. 1(1), pages 103-118, April.
    9. Benedicto Lukanima & Raymond Swaray, 2014. "Market Reforms and Commodity Price Volatility: The Case of East African Coffee Market," The World Economy, Wiley Blackwell, vol. 37(8), pages 1152-1185, August.
    10. Angelos Kanas, 2008. "Modeling regime transition in stock index futures markets and forecasting implications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 649-669.
    11. John M. Fry & Baoying Lai & Mark Rhodes, 2011. "The interdependence of Coffee spot and futures market," Working Papers 2011.1, International Network for Economic Research - INFER.
    12. Man Wang & Kun Chen & Qin Luo & Chao Cheng, 2018. "Multi-Step Inflation Prediction with Functional Coefficient Autoregressive Model," Sustainability, MDPI, vol. 10(6), pages 1-16, May.

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    More about this item

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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