Overview

Anomaly detection plays a critical role in econometrics by identifying unusual patterns and data irregularities that can distort inference and lead to misleading conclusions. Economic data is often noisy and affected by reporting errors and rare but impactful events, making traditional detection methods insufficient. Robust methods for anomaly detection seek to address these challenges by remaining reliable while preserving interpretability and statistical validity. Developing and applying such methods is essential for improving the accuracy of econometric analysis and supporting sound economic policy and decision-making. Robust Methods for Anomaly Detection in Econometrics explores innovations surrounding anomalous observations in modern quantitative research. It examines influential observations in complex, high-volume, and high-velocity data settings. Covering topics such as econometrics, robust methods, and research, this book is an excellent resource for academicians, researchers, policy makers, software engineering, and graduate students.

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9798337382975

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Dr. Mohieddine Rahmouni is an Associate Professor of Economics and Quantitative Methods at King Faisal University and the University of Tunis (Higher School of Economic and Commercial Sciences of Tunis). He earned his Ph.D. through a joint program between the University of Montesquieu Bordeaux-IV and the University of Tunis. Dr. Rahmouni's research spans the economics and econometrics of innovation, applied econometrics, productivity, technology, and industrial dynamics, with a focus on the intersections of these fields in driving economic development and industrial transformation.

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