Application of time series methodology the estimation of the levels of exports of Colombia’s coffee period 1958 - 2011
DOI:
https://doi.org/10.15649/2346075X.210Keywords:
Time series models, Box Jenkins methodology, exports of coffee, ARIMA models.Abstract
A fundamental element for the coffee Colombian sector, is to know to short, medium and long term, the behavior of the exports
of soft coffee of Colombia, to know his relation in the processes of sales and production. In conformity with the previous
thing, the present work was elaborated realizing an evaluation of the levels of exports of coffee, in monthly form from beginnings
of 1958 until ends of 2008. With the aim to develop a model who allows to characterize and to obtain forecasts on the behavior
of the exports of coffee realized in the country, the methodology used Box Jenkins, following the phases for the models ARIMA
(Autoregressive Integrated of Mobile Average).
The information was taken of the web page of the National Federation of Coffee Growers of Colombia. In the series under
study a seasonal behavior was observed, where the first quarters present the minor levels of the year, particularly in February,
month that registers the lowest levels of exports of the year, these levels quarterly go increasing of gradual form up to reaching
the major level of exports in the quarter IV, specifically between November and December. Finally the forecasts were obtained
between the year 2009 and 2011, following a stable behavior with regard to the period of validation of the sample of the series.
The information was analyzed using the language R.
References
(1) Federación Colombiana De Cafeteros. Comportamiento de la industria cafetera en Colombia 2011. Disponible en http:// www.federaciondecafeteros.org/static/files/2010_Comportamiento.pdf. Recuperado el 01 de Febrero 2011.
(2) Garcia I.Análisis y predicción de la serie de tiempo del precio externo del café colombiano usando redes neuronales. Revista Universitas Scientiarum. (2003). Universidad Pontificia Javeriana. Vol 8,45-50.
(3) Box G.e.p., G.m. Jenkins Time Series Analysis, Forecasting and Control.3ra Edición, Prentice Hall Hispanoamericana, s.a.México, (1995)
(4) Méndez J. Análisis de series temporales. Volumen I: Modelos Univariantes. Instituto de Estadística Aplicada y Computación. Universidad de Los Andes, Mérida. Venezuela.(2007).
(5) Development Core Team (2011). R: A Language and Environment for Statistical Computing.URL: http://www.R-project.org/
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