Week 1 - Introduction

Why do some individuals open their wallets to help others, while some hold back?

Introduction:

The complexities of altruistic behavior in financial decisions offer a rich field for exploration. I am doing this project out of a desire to dissect these complexities, to understand what drives altruism in financial contexts, and how these decisions can be influenced by various factors.

This project investigates the complexities of financial decision-making, focusing on how individuals make choices regarding donations. The intrigue lies in the observable gap between theoretical economic models and the actual, often unpredictable, financial behaviors of individuals. I’m driven by a desire to understand and predict these behaviors, using the combined forces of game theory and machine learning, aiming to bridge the gap between economic theories and real-world applications.

Question/Plan/Hypothesis:

The central question of this project is, “What factors drive individuals to make altruistic financial decisions, and how can game theory and machine learning uncover these underlying motivations?” This inquiry aims to dissect the complex motivations behind altruistic behavior, focusing on financial donations as a primary context.

To explore the nuanced landscape of altruism in financial decision-making, this project will employ a methodical approach combining theoretical exploration with empirical analysis. Initially, literature review will establish a foundational understanding of the existing theories and findings related to altruism, game theory, and machine learning applications in financial decisions. Following this, a survey of various participants will gather data on individual financial behaviors, attitudes towards risk, saving tendencies, and impulse buying habits, alongside demographic information for a nuanced analysis. Game theory-based scenarios will specifically probe the altruistic inclinations in financial contexts. Utilizing machine learning algorithms, the project aims to discern patterns and correlations within the collected data, shedding light on the factors influencing altruistic financial decisions. 

I hypothesize that through the application of game theory and machine learning, I will identify specific patterns that indicate the presence of altruistic behavior in financial decisions. These patterns will likely reveal that a combination of demographic, psychological, and situational factors are key drivers of altruism. The expectation is that this approach will not only provide insights into the mechanisms of altruistic decision-making but also offer predictive power in understanding and encouraging such behavior in financial contexts.