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 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.

• Tipo de recurso: http://purl.org/coar/resource_type/c_6557
• Fecha de publicación: 2022
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/12353
• Acceso en línea: https://revistas.uptc.edu.co/index.php/ingenieria_sogamoso/article/view/14453; https://repositorio.uptc.edu.co/handle/001/12353
• Palabra clave: Econometrics; Scientific statistics; Prediction; Production; Time series; Econometría; Estadísticas científicas; Previsión; Producción; Series temporales
• License: http://purl.org/coar/access_right/c_abf58