TY - BOOK ID - 7913413 TI - Causal Inference in Econometrics AU - Huynh, Van-Nam. AU - Kreinovich, Vladik. AU - Sriboonchitta, Songsak. PY - 2016 SN - 3319272837 3319272845 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Computer Science KW - Engineering & Applied Sciences KW - Engineering. KW - Economics, Mathematical. KW - Computational intelligence. KW - Quality control. KW - Reliability. KW - Industrial safety. KW - Computational Intelligence. KW - Quantitative Finance. KW - Quality Control, Reliability, Safety and Risk. KW - Industrial accidents KW - Industries KW - Job safety KW - Occupational hazards, Prevention of KW - Occupational health and safety KW - Occupational safety and health KW - Prevention of industrial accidents KW - Prevention of occupational hazards KW - Safety, Industrial KW - Safety engineering KW - Safety measures KW - Safety of workers KW - Accidents KW - System safety KW - Dependability KW - Trustworthiness KW - Conduct of life KW - Factory management KW - Industrial engineering KW - Reliability (Engineering) KW - Sampling (Statistics) KW - Standardization KW - Quality assurance KW - Quality of products KW - Intelligence, Computational KW - Artificial intelligence KW - Soft computing KW - Economics KW - Mathematical economics KW - Econometrics KW - Mathematics KW - Construction KW - Industrial arts KW - Technology KW - Prevention KW - Methodology KW - Finance. KW - System safety. KW - Safety, System KW - Safety of systems KW - Systems safety KW - Industrial safety KW - Systems engineering KW - Funding KW - Funds KW - Currency question KW - Economics, Mathematical . KW - Econometrics. KW - Economics, Mathematical KW - Statistics UR - https://www.unicat.be/uniCat?func=search&query=sysid:7913413 AB - This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies. ER -