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Forecasting the spot spices of various coffee types using linear and non-linear error correction models
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Autores
Milas C.
Otero Cardona, Jesús Gilberto
Panagiotidis T.
Fecha
2004
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John Wiley and Sons Ltd
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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. © 2004 John Wiley and Sons, Ltd.
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Keywords
Coffee , Commodity market , Estimation method , Forecasting method , Price dynamics , Asymmetric and polynomial error models , Coffee prices , Forecasting
