Interdependency Pattern Recognition in Econometrics: A Penalized Regularization Antidote

When it comes to variable interpretation, multicollinearity is among the biggest issues that must be surmounted, especially in this new era of Big Data Analytics. Since even moderate size can prevent proper special diagnostics recommended and implemented for identification purposes. Nonetheless, areas econometrics statistics, other fields, these are controversial concerning their “successfulness”. It has been remarked they frequently fail do model assessment due information complexity, resulting misspecification. This work proposes investigates a robust easily interpretable methodology, termed Elastic Information Criterion, capable capturing rather accurately effectively thus providing assessment. The performance investigated via simulated real data.