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Springer Behavioral Predictive Modeling in Economics 897

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Description

Traditional economic models often rely on the assumption that individuals make perfectly rational decisions based on complete information. However, real-world behavior frequently differs from these theoretical ideals. This book, part of the Studies in Computational Intelligence series, addresses this gap by exploring how human behavior impacts economic forecasts. Through a combination of methodological papers and practical examples, this text demonstrates how to integrate behavioral insights into predictive models. It moves beyond the concept of the perfectly rational actor to account for the reality that people have limited information processing abilities. By understanding these behavioral nuances, researchers and economists can develop more accurate models that reflect how decisions are actually made in the real world. This resource is designed for those looking to bridge the gap between classical economic theory and the practical complexities of human decision-making. It provides the tools necessary to adjust economic predictions to better account for non-optimal human choices, making it a valuable addition to your library of computational intelligence and econometrics studies.

Key Features

Explores methodological approaches to building behavioral predictive models for complex economic problems.

Provides real-world examples of applying behavioral models to improve the accuracy of economic predictions.

Addresses the limitations of traditional economic models that assume perfect rationality in decision-making.

Integrates Nobel Prize-winning research regarding how limited information processing affects human choices.

Offers a specialized perspective within the Studies in Computational Intelligence series for advanced study.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
07 August 2021
Listed Since
10 July 2021

Barcode

No barcode data available

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