Series de tiempo para el pronóstico de la producción de mandarina en el Perú, periodo 2017-2022
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Date
2023
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Universidad Nacional de Trujillo
Abstract
Este estudio es de tipo descriptivo observacional longitudinal, con tendencia, teniendo como objetivo principal determinar un modelo de pronóstico que mejor explique el comportamiento de la producción mensual de mandarina, utilizando información del Banco Central de Reserva del Perú (BRCP) desde el periodo enero 2017 - diciembre 2022, siendo esta una investigación aplicada. La metodología estadística aplicada fue la Box Jenkins y la serie se dividió en : enero 2017 a junio 2022 para la estimación del modelo y de julio 2022 a diciembre 2022 para la validación del pronóstico, esta técnica estadística se encarga de describir las características de la serie, en términos de sus componentes de interés como su tendencia y estacionariedad además de predecir futuros valores de la variable, el procesamiento de los mismos se efectuó con el programa estadístico Eviews 12 y el programa Microsoft Excel 2021 para contrastar los resultados. Finalmente se concluyó que el modelo identificado fue una serie de tendencia estacionaria y el modelo pronosticado fue un SARIMA ar(1) sar(12) ma(1), siendo probada la adecuacidad del modelo
ABSTRACT This study is of a longitudinal observational descriptive type, with a trend, with the main objective being to determine a forecast model that best explains the behavior of monthly mandarin production, using information from the Central Reserve Bank of Peru (BRCP) since the period January 2017. - December 2022, this being applied research. The statistical methodology applied was Box Jenkins and the series was divided into: January 2017 to June 2022 for the estimation of the model and from July 2022 to December 2022 for the validation of the forecast. This statistical technique is responsible for describing the characteristics of the series. , in terms of its components of interest such as its trend and stationarity, in addition to predicting future values of the variable, their processing was carried out with the Eviews 12 statistical program and the Microsoft Excel 2021 program to contrast the results. Finally, it was concluded that the identified model was a stationary trend series and the predicted model was a SARIMA ar(1) sar(12) ma(1), the adequacy of the model being tested
ABSTRACT This study is of a longitudinal observational descriptive type, with a trend, with the main objective being to determine a forecast model that best explains the behavior of monthly mandarin production, using information from the Central Reserve Bank of Peru (BRCP) since the period January 2017. - December 2022, this being applied research. The statistical methodology applied was Box Jenkins and the series was divided into: January 2017 to June 2022 for the estimation of the model and from July 2022 to December 2022 for the validation of the forecast. This statistical technique is responsible for describing the characteristics of the series. , in terms of its components of interest such as its trend and stationarity, in addition to predicting future values of the variable, their processing was carried out with the Eviews 12 statistical program and the Microsoft Excel 2021 program to contrast the results. Finally, it was concluded that the identified model was a stationary trend series and the predicted model was a SARIMA ar(1) sar(12) ma(1), the adequacy of the model being tested
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Keywords
Metodología Box-Jenkins, Producción, Mandarina, SARIM