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

Costas Milas, Jesús Otero, Theodore Panagiotidis

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)277-288
Number of pages12
JournalInternational Journal of Finance and Economics
Volume9
Issue number3
DOIs
StatePublished - Jul 2004

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics

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