Econometric modeling and sales forecasts of ginger rhizome in Ecuador
Econometric and stochastic modeling are highly relevant tools for forecasting. The main objective of this research was the study of econometric and stochastic modeling in ginger sales forecasts in Ecuador. Considering endogenous and exogenous variables of a continuous random nature. The financial da...
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| Format: | Online |
| Language: | spa |
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Universidad Pedagógica y Tecnológica de Colombia - UPTC
2022
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| Online Access: | https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/14453 |
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| author | Sabando García, Ángel Ramón Ugando Peñate, Mikel Armas Herrera, Reinaldo Higuerey Gómez, Ángel Alexander Espín Estrella, Grace Margarita Villalón Peñate, Antonio |
| author_facet | Sabando García, Ángel Ramón Ugando Peñate, Mikel Armas Herrera, Reinaldo Higuerey Gómez, Ángel Alexander Espín Estrella, Grace Margarita Villalón Peñate, Antonio |
| author_sort | Sabando García, Ángel Ramón |
| collection | OJS |
| description | Econometric and stochastic modeling are highly relevant tools for forecasting. The main objective of this research was the study of econometric and stochastic modeling in ginger sales forecasts in Ecuador. Considering endogenous and exogenous variables of a continuous random nature. The financial data was recorded monthly from the company Nature Product Gingerdale Cía. Ltda., from the province of Santo Domingo de los Tsáchilas, Ecuador. For which the econometric variables were considered such as: price/kg., Quantity exported/kg and sales levels/thousands of dollars. In particular, this study wasfocused on the financial dynamics that these accounts have had from 2016 to 2019. From these data, a projection was made until 2021. Statistical techniques were used for the mathematical, statistical and graphic analysis of simple linear regression and time series using SPSS version 25 software. The results show a high covariance, exerted by the price/kg number whose prediction fits an ARIMA (0,1,0) (0,0,0), with respect to exports/kg ARIMA (2,0,0) (1,0,0) is adjusted andbased on sales/thousands of dollars to an ARIMA (0,0,0) (0,0,0). As a consequence, in conclusion, it was obtained that thestochastic model represents a better forecast of sales, price and exported kilograms of ginger, by presenting significantcoefficients and lower prediction errors and, by default, the simulation is encouraging for the production and export ofginger to Ecuador. |
| format | Online |
| id | oai:oai.revistas.uptc.edu.co:article-14453 |
| institution | Revista Ingeniería, Investigación y Desarrollo |
| language | spa |
| publishDate | 2022 |
| publisher | Universidad Pedagógica y Tecnológica de Colombia - UPTC |
| record_format | ojs |
| spelling | oai:oai.revistas.uptc.edu.co:article-144532022-07-05T21:13:03Z Econometric modeling and sales forecasts of ginger rhizome in Ecuador MODELACIÓN ECONOMÉTRICA Y ESTOCÁSTICA EN LOS PRONÓSTICOS DE VENTAS DE JENGIBRE EN ECUADOR Sabando García, Ángel Ramón Ugando Peñate, Mikel Armas Herrera, Reinaldo Higuerey Gómez, Ángel Alexander Espín Estrella, Grace Margarita Villalón Peñate, Antonio Econometrics Scientific statistics Prediction Production Time series Econometría Estadísticas científicas Previsión Producción Series temporales Econometric and stochastic modeling are highly relevant tools for forecasting. The main objective of this research was the study of econometric and stochastic modeling in ginger sales forecasts in Ecuador. Considering endogenous and exogenous variables of a continuous random nature. The financial data was recorded monthly from the company Nature Product Gingerdale Cía. Ltda., from the province of Santo Domingo de los Tsáchilas, Ecuador. For which the econometric variables were considered such as: price/kg., Quantity exported/kg and sales levels/thousands of dollars. In particular, this study wasfocused on the financial dynamics that these accounts have had from 2016 to 2019. From these data, a projection was made until 2021. Statistical techniques were used for the mathematical, statistical and graphic analysis of simple linear regression and time series using SPSS version 25 software. The results show a high covariance, exerted by the price/kg number whose prediction fits an ARIMA (0,1,0) (0,0,0), with respect to exports/kg ARIMA (2,0,0) (1,0,0) is adjusted andbased on sales/thousands of dollars to an ARIMA (0,0,0) (0,0,0). As a consequence, in conclusion, it was obtained that thestochastic model represents a better forecast of sales, price and exported kilograms of ginger, by presenting significantcoefficients and lower prediction errors and, by default, the simulation is encouraging for the production and export ofginger to Ecuador. La modelación econométrica y estocástica son herramientas relevantes para la realización de pronósticos. Esta investigación tuvo como objetivo principal el estudio de la modelación econométrica y estocástica en los pronósticos de ventas de jengibre en Ecuador. Considerando variables endógenas y exógenas de carácter aleatorio continuo. Los datos financieros se registraron mensualmente por la empresa Nature Product Gingerdale Cía. Ltda., de la provincia de Santo Domingo de los Tsáchilas, Ecuador. Para los cuales se consideraron las variables econométricas como: precio/kg., Cantidad exportada/kg y niveles de ventas/miles de dólares. Particularmente, este estudio se enfocó en la dinámica financiera que han tenido estas cuentas desde el año 2016 hasta el año 2019. A partir de estos datos se realizó una proyección hasta el año 2021. Para el análisis matemático, estadístico y gráfico se utilizó las técnicas estadísticas de la regresión lineal simple y series de tiempo mediante el software SPSS versión 25. Los resultados muestran una alta covarianza, ejercida por el número el precio/kg cuya predicción se ajusta a un modelo ARIMA (0,1,0) (0,0,0), con respecto a la exportación/kg se ajusta ARIMA(2,0,0)(1,0,0) y en función a las ventas/miles de dólares a un modelo ARIMA(0,0,0)(0,0,0). En consecuencia, como conclusión, se obtuvo que el modelo estocástico representa un mejor pronóstico de las ventas, precio y kilogramos exportados de jengibre, al presentar los coeficientes significativos y menores errores de predicción y, por defecto, la simulación es alentadora para laproducción y exportación de jengibre para el Ecuador. Universidad Pedagógica y Tecnológica de Colombia - UPTC 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/14453 10.19053/1900771X.v22.n1.2022.14453 Ingeniería Investigación y Desarrollo; Vol. 22 No. 1 (2022): Enero - Junio; 25-43 Ingeniería Investigación y Desarrollo; Vol. 22 Núm. 1 (2022): Enero - Junio; 25-43 2422-4324 1900-771X spa https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/14453/11789 |
| spellingShingle | Econometrics Scientific statistics Prediction Production Time series Econometría Estadísticas científicas Previsión Producción Series temporales Sabando García, Ángel Ramón Ugando Peñate, Mikel Armas Herrera, Reinaldo Higuerey Gómez, Ángel Alexander Espín Estrella, Grace Margarita Villalón Peñate, Antonio Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title | Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title_alt | MODELACIÓN ECONOMÉTRICA Y ESTOCÁSTICA EN LOS PRONÓSTICOS DE VENTAS DE JENGIBRE EN ECUADOR |
| title_full | Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title_fullStr | Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title_full_unstemmed | Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title_short | Econometric modeling and sales forecasts of ginger rhizome in Ecuador |
| title_sort | econometric modeling and sales forecasts of ginger rhizome in ecuador |
| topic | Econometrics Scientific statistics Prediction Production Time series Econometría Estadísticas científicas Previsión Producción Series temporales |
| topic_facet | Econometrics Scientific statistics Prediction Production Time series Econometría Estadísticas científicas Previsión Producción Series temporales |
| url | https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/14453 |
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