Predicting Legal Systems: An Artificial Neural Network Approach with Statistical Analysis for Comparative Study of Civil Law and Common Law Countries

Abstract

This study compares countries with common law with countries with civil law systems and investigates the possibility of predicting legal systems using artificial neural networks (ANNs). The OLS model, ANOVA, ANN, and Tensor Flow are used in the research to analyze the data. The goal is to find out how board characteristics and country legislative frameworks affect how European corporations disclose their social performance. The performance of a hidden layer with five nodes is best, according to the ANN model. The model’s accuracy throughout testing and validation is 0.750. The confusion matrix shows that, of the four observations in the test set, three were correctly categorized as “Civil law” and one was incorrectly categorized as “Common law.”

Keywords

• common law
• civil law
• artificial neural networks
• ols model
• anova
• ann
• tensor-flow
• board attributes
• national regulatory framework
• social performance disclosure