Volume 56, Number 3, May-June 2022
|Page(s)||2015 - 2035|
|Published online||30 June 2022|
Towards a framework to combine multiobjective optimization and econometrics and an application in economics of education
Department of Applied Economics (Mathematics), Universidad de Málaga, C/ Ejido S/N, Málaga 29071, Spain
2 Department of Applied Economics (Statistics and Econometrics), Universidad de Málaga, C/ Ejido S/N, Málaga 29071, Spain
3 Department of Quantitative Methods for Business and Economics, Universidad de Granada, P.º de Cartuja, 7, Granada 18011, Spain
* Corresponding author: email@example.com
Accepted: 24 May 2022
In this paper, we propose a theoretical framework that combines econometric and multiobjective programming methodologies to help researchers to identify and achieve optimal solutions to socio-economic and management problems. Sometimes, it is important to analyse which combination of values of the explanatory variables -in an econometric model- would imply the simultaneous achievement of the best values of the response variables. In such situations, if certain degree of conflict is observed among the response variables, we propose to formulate a multiobjective optimization problem based on the conclusions obtained from a regression analysis. Subsequently, the application of multiobjective optimization techniques allows gaining a better insight about the conflicting relation between the response variables, and how a balanced “optimal” situation among them could be achieved. This piece of information can be hardly extracted just by econometric techniques. An application in the field of economics of education, related to the analysis of the students’ well-being as a way to improve their academic performance, demonstrates the potential of our proposal.
Mathematics Subject Classification: 90C29 / 62P20 / 62P25
Key words: Multiple objective decision-making / econometrics / multiobjective optimization / economics of education
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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