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

journal

  • International Journal of Finance and Economics

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.

publication date

  • 2004-7-1

edition

  • 9

keywords

  • Coffee
  • Deviation
  • Economics
  • Error Correction Model
  • Forecasting Performance
  • Nonlinear Error Correction Model
  • Polynomials
  • Random Walk Model
  • Short-run
  • Spot Price

International Standard Serial Number (ISSN)

  • 1076-9307

number of pages

  • 12

start page

  • 277

end page

  • 288