Causal Inference in Econometrics
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This bookis devoted to the analysis of causal inference which is one of the most difficult tasks in dataanalysis: when two phenomena are observed to be related, it is often difficultto decide whether one of them causally influences the other one, or whetherthese two phenomena have a common cause. This analysis is the main focus ofthis volume.To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models a...
This bookis devoted to the analysis of causal inference which is one of the most difficult tasks in dataanalysis: when two phenomena are observed to be related, it is often difficultto decide whether one of them causally influences the other one, or whetherthese two phenomena have a common cause. This analysis is the main focus ofthis volume.
To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models and models obtained by using neural networks and data miningtechniques. It also contains papers that apply different econometric models toanalyze real-life economic dependencies.
To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models and models obtained by using neural networks and data miningtechniques. It also contains papers that apply different econometric models toanalyze real-life economic dependencies.
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