(untitled) (LACCEI, 2024)
The objective of the article was to demonstrate the construction of a simple linear regression model of liquidity (dependent variable) with asset turnover for the agricultural sector. Also, to verify if the regression model works, taking into account that there must be a causal relationship, not only random, between the variables. The methodology had a quantitative approach of non-experimental design at a causal and longitudinal correlational level. For these purposes, simple linear regression was used to find a predictive model. This study had as population and sample all the companies of the Peruvian agricultural sector, listed in the Lima Stock Exchange. The result shows an acceptable goodness of fit. The standard error of the estimation is low, showing a better fit. The model is feasible, since there is a significant relationship between the variables. The regression model obtained is: Liquidity = 1.490 + 3.696 Asset turnover. The conclusion indicates that the regression model works because there is a causal relationship between the variables. For future research it is convenient to incorporate other economic sectors, a larger geographic space, or more analyzed periods. Different variables could be included to build a multiple regression model, logistic or structural equations.