A New Computational Method for Estimating Simultaneous Equations Models Using Entropy as a Parameter Criteria

Abstract

Simultaneous Equations Models (SEM) is a statistical technique widely used in economic science to model the simultaneity relationship between variables. In the past years, this technique has also been used in other fields such as psychology or medicine. Thus, the development of new estimating methods is an important line of research. In fact, if we want to apply the SEM to medical problems with the main goal being to obtain the best approximation between the parameters of model and their estimations. This paper shows a computational study between different methods for estimating simultaneous equations models as well as a new method which allows the estimation of those parameters based on the optimization of the Bayesian Method of Moments and minimizing the Akaike Information Criteria. In addition, an entropy measure has been calculated as a parameter criteria to compare the estimation methods studied. The comparison between those methods is performed through an experimental study using randomly generated models. The experimental study compares the estimations obtained by the different methods as well as the efficiency when comparing solutions by Akaike Information Criteria and Entropy Measure. The study shows that the proposed estimation method offered better approximations and the entropy measured results more efficiently than the rest.

The paradox of human resource investment in smoking households

“…This study has more than one equation and uses variables that influence each other (income and expend iture on education and health). Therefore, the use of simultaneous equation estimation analysis is important to determine the relationship of dependence between one independent variable and another (Pérez-Sánchez, González, Perea, & López-Espín, 2021). The use of the simultaneous equation analysis method has several advantages over other methods, such as: 1) overcoming the problem of endogeneity, which is a situation where the variables being observed influence each other (income variable and expenditure on education and health); 2) the simultaneous equation estimation method can estimate parameters by equation from a model consisting of several equations; as known in this study, several equations will be analyzed simultaneously; 3) approaching the true value or more precise; 4) the simultaneous equation analysis method is specifically designed to analyze the simultaneous relationship between variables in a system of equations (Gujarati, 2012).…”