Statistical evaluations of the agricultural input price index in relation to monthly precipitation levels in Colombian territory

Abstract

The objective of this research was to determine if there is a significant linear variation between the total receipt recorded each month in Colombia and the changes in the agricultural input price index recorded each month. Using information obtained from secondary sources, such as the official pages of the National Open Data Platform of Colombia, the monthly accumulated rainfall levels and the inter-monthly changes in the agricultural input price index values across Colombia from January to October 2024 were examined, running a classification analysis through R Studio. Using the Shapiro-Wilks normality test, it was verified that the data obtained for the variables "Total precipitation" and "Variation in agricultural input prices" fit a normal distribution, so the Pearson weighting test was used to determine the level of evaluation between both variables. The p-value of the statistic obtained is 0.01353, which is significantly lower than the significance level of 0.05, confirming that there is a significant linear evaluation between the monthly accumulated rainfall in the country and the fluctuations in the price index of Colombian agricultural inputs. The calculated correlation coefficient is 0.7444429, which indicates that there is a considerable positive correlation between the variables. These results show that it is plausible to state that monthly fluctuations in the agricultural commodity price index tend to be positive as monthly accumulated precipitation increases, while they tend to be negative as accumulated precipitation decreases. This does not mean that there is a causal relationship between the two, since many factors can influence this dynamic. Therefore, it has been concluded that more research is needed to better understand the causes of changes in the agricultural commodity price index in Colombia and how climatic conditions influence this process.