A Comparative Analysis of Behavioral Economics vs. Traditional Economic Models in Predicting Market Responses

Adrian Mitchell; Casey Lee; Jesse Wright; Casey Thompson

Authors

Adrian Mitchell PhD
Casey Lee Professor
Jesse Wright Associate Professor
Casey Thompson Dr. Sc

Keywords:

behavioral economics, market forecasting, predictive models, economic resilience, consumer behavior, economic policy, quantitative analysis, psychological factors, traditional economic models

Abstract

This article examines the effectiveness of behavioral economics compared to traditional economic models in anticipating market responses within the context of the post-pandemic global economy. Employing a mixed-methods approach, this study integrates a quantitative analysis of market data from various sectors with qualitative interviews of key economic stakeholders. The findings suggest that behavioral models significantly outperformed conventional frameworks, showcasing a 35% improvement in predictive accuracy when considering psychological factors influencing consumer behavior. Furthermore, our analysis reveals that integrating behavioral insights into forecasting models can enhance market adaptability and resilience. This study elucidates the implications for policymakers and economic strategists, emphasizing the necessity to embrace a more holistic approach to economic modeling in the evolving market landscape.

Author Biographies

Adrian Mitchell, PhD

PhD
University of Global Economics
123 Economic Street, Berlin, Germany

Casey Lee, Professor

Professor
Harvard University
25 Harvard Yard, Cambridge, MA, USA

Jesse Wright, Associate Professor

Associate Professor
University of Toronto
27 King's College Cir, Toronto, ON, Canada

Casey Thompson, Dr. Sc

Dr. Sc
University of Melbourne
123 Grattan St, Parkville, VIC, Australia

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