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Un análisis de series de tiempo mediante modelos SARIMAX para la proyección de demanda de carga en el puerto del Callao

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  • Victor Chang Rojas

Abstract

El objetivo principal de este artículo es estimar y proporcionar modelos de pronóstico para predecir el rendimiento de carga para el Puerto del Callao del 2019 al 2023. Estos resultados podrían servir para hacer un análisis prospectivo, mejorar las decisiones de inversión y determinar las tarifas del puerto. Para este propósito, los modelos de series temporales SARIMAX se utilizan con la inclusión de entradas exógenas que son representativas del rendimiento de carga de las tres terminales del Puerto del Callao: APMTC, DPWC y TC. Los resultados del pronóstico indican que para el año 2023 se alcanzará un total de 17 millones de TM y 3.4 millones de TEU’s, activando los gatillos de inversión para APMTC y DPWC.

Suggested Citation

  • Victor Chang Rojas, 2019. "Un análisis de series de tiempo mediante modelos SARIMAX para la proyección de demanda de carga en el puerto del Callao," Revista de Análisis Económico y Financiero, Universidad de San Martín de Porres, vol. 1(03), pages 15-31.
    • Handle: RePEc:alp:revaef:03-01
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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