Forecasting the spot spices of various coffee types using linear and non-linear error correction models
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 th...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2004
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/24355
- Acceso en línea:
- https://doi.org/10.1002/ijfe.245
https://repository.urosario.edu.co/handle/10336/24355
- Palabra clave:
- Coffee
Commodity market
Estimation method
Forecasting method
Price dynamics
Asymmetric and polynomial error models
Coffee prices
Forecasting
- Rights
- License
- Abierto (Texto Completo)
| Summary: | 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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