Forecasting weekly Canary tomato exports from annual surface data

  1. Carmen Gloria Martín Rodríguez 1
  2. José Juan Cáceres Hernández 1
  1. 1 Universidad de La Laguna

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    GRID grid.10041.34

International Association of Agricultural Economists Conference ( 28º. 2012. Foz do Iguacu, Brazil)

Publisher: International Association of Agricultural Economists

Year of publication: 2012

Type: Conference paper

Export: RIS


Sea shipping is the main transport mode used by Canary farmers to export tomatoes to the European markets. Provincial associations of Canary growers negotiate charter fees with the shipping companies for the whole exporting period and, therefore, provide a unified sea transport service. When such a negotiation takes place each year, the individual growers’ decisions about planting surface are usually known. However, the forecasting of the distribution of tomato exports over the whole harvesting period would help Canary associations make more timely and effective decisions. In this paper, a model is proposed to forecast weekly Canary tomato exports conditioned on a given total planting surface. A seasonal model is formulated to deal with the weekly seasonal pattern of Canary tomato yields per hectare by means of evolving splines. Such a model is a useful tool to forecast weekly yields. From these forecasts, weekly tomato exports beyond the end of the sample are also forecast by taking the total planting surface into account. To illustrate the aptness of this framework, the proposed methodology is applied to a weekly series of tomatoes exported to the European markets from 1995/1996 to 2010/2011 harvests.

Bibliographic References

  • Cabrero, A., Camba-Méndez, G., Hirsch, A. and Nieto, F., 2009. Modelling the daily bank notes in circulation in the context of the liquidity management of the European Central Bank. Journal of Forecasting 28, 194-217.
  • Cáceres-Hernández, J.J., 2000. La Exportación de Tomate en Canarias. Elementos para una Estrategia Competitiva. Ediciones Canarias, La Laguna.
  • Cáceres-Hernández, J.J., 2001. Optimalidad del patrón estacional de las exportaciones canarias de tomate. Estudios de Economía Aplicada 18, 41-66.
  • Eubank, R.L., 1988. Spline Smoothing and Nonparametric Regression. M. Dekker, New York.
  • Harvey, A.C., 1989. Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press, Cambridge.
  • Harvey, A.C., Koopman, S.J., 1993. Forecasting hourly electricity demand using time varying splines. Journal of the American Statistical Association 88, 1228-1236.
  • Harvey, A.C., Koopman, S.J., Riani, M., 1997. The modelling and seasonal adjustment of weekly observations. Journal of Business and Economic Statistics 15, 354-368.
  • Jumah, A., Kunst, R.M., 2008. Seasonal prediction of European cereal prices: good forecasts using bad models? Journal of Forecasting 27, 391-406.
  • Koopman, S.J., 1992. Diagnostic Checking and Intra-Daily Effects in Time Series Models. Thesis Publishers Tinbergen Institute Research Series 27, Amsterdam.
  • Martín-Rodríguez, G., Cáceres-Hernández, J.J., 2005. Modelling weekly Canary tomato exports. Agricultural Economics 33, 255-267.
  • Martín-Rodríguez, G., Cáceres-Hernández, J.J., 2010. Spline and the proportion of the seasonal period as a season index. Economic Modelling 27, 83-88.
  • Poirier, D.J., 1976. The Econometric of Structural Change with Special Emphasis on Spline Functions. North Holland Publishing Company, Amsterdam.