MATHEMATICAL MODELING FOR FORECASTING THE GROSS DOMESTIC PRODUCT OF MEXICO

摘要

This paper presents three mathematical models for forecasting of the Mexico's gross domestic product using regressions. Three mathematical models are: 1) linear regression; 2) exponential regression; 3) parabolic regression. The regression models have been developed through the data analysis of 82 years from 1935 until 2016. Starting from the idea that in economics, as well as in other sciences, anything has the tendency to depend on anything else and in this paper three models are developed to observe which of the three is capable of expressing the relation between the years and the gross domestic product of Mexico. According to the figures shown, it is clearly observed that the parabolic regression model is more accurate with respect to the linear and exponential regression models. Then, the parabolic regression model is the most appropriate, since it is adjusted to real conditions of the Mexico's gross domestic product, which is the main contribution of this paper.