Prediction and Causality in Econometrics and Related Topics

This book provides the ultimate goal of economic studies to predict how the economy develops-and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques-including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

Inhalt

Prediction intervals for the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) via the LUBE method.- Analysis and Modeling of Information Security Information Security Systems in Industry 4.0.- Using Non-linear Integral Models in Automatic Control and Measurement Systems for Sensors' Input Signals' Recovery.- Neural Network Method and Algorithm for Document Detection Based on Signaling Analysis.- Using fuzzy probabilistic implication in Z-set based inference.- Accounting experience between fuzzy integral and Z-numbers.- The Impact of In-Store Environment on Purchase Intention in Supermarkets.- A recurrent method for structural-parametric identification of fuzzy neural networks.- Voltage Control System for Electrical Networks Based on Fuzzy Sets.- Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers.