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Forecasting crop yields through climate variables using mixed frequency data. The case of Argentine soybeans

Author

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  • Magdalena Cornejo

    (Escuela de Gobierno, Universidad Torcuato Di Tella, Argentina y Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina)

Abstract

Este artículo evalúa el valor de utilizar información sobre variables climáticas publicadas con anticipación y con una frecuencia superior a la variable objetivo de interés -los rendimientos de los cultivos- con el fin de obtener pronósticos a corto plazo. Se utilizan datos climáticos agregados y desagregados, esquemas de ponderación alternativos y diferentes esquemas de actualización para evaluar el desempeño de las predicciones. Este estudio se centra en el caso de los rendimientos de la soja en Argentina. Los resultados muestran que los modelos que incluyen datos meteorológicos de alta frecuencia obtuvieron mejores resultados, particularmente durante las tres campañas consecutivas después de 2008/09, cuando el rendimiento de la soja disminuyó en casi un 50%. A su vez, las combinaciones de pronóstico mostraron un mejor desempeño que los modelos de pronóstico individuales.

Suggested Citation

  • Magdalena Cornejo, 2021. "Forecasting crop yields through climate variables using mixed frequency data. The case of Argentine soybeans," Económica, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 67, pages 93-106, January-D.
    • Handle: RePEc:akh:journl:633
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    File URL: https://revistas.unlp.edu.ar/Economica/article/view/10621/12171
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    Keywords

    Rendimiento; pronósticos; clima; frecuencias mixtas; soja;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

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