The Untapped Potential of Complex Agent Based Models in Economics

When it comes to understanding and predicting economic phenomena, traditional models often fall short. The emergence of complex agent-based models (ABMs) has opened new windows of opportunity for economists to gain a deeper understanding of complex economic systems. In this article, we delve into the world of ABMs and explore how they can offer fresh insights into the intricacies of the economy.

What are Complex Agent-Based Models?

Complex agent-based models are computational models that simulate the actions and interactions of multiple autonomous agents within a given environment. Each agent has its own set of rules and behavior that governs its decision-making process. By observing how these individual agents interact, economists can gain a better understanding of how collective macroeconomic patterns emerge.

Breaking Away from Simplistic Assumptions

Traditional economic models often rely on simplifying assumptions and mathematical equations to analyze complex phenomena. However, these models tend to overlook the heterogeneity and adaptive nature of individuals in economic systems. Complex ABMs provide a more realistic representation of human behavior by considering individual agents as decision-makers who adapt and learn over time.

Complex Agent-Based Models (New Economic Windows)

by Douglas Fisher (1st ed. 2018 Edition, Kindle Edition)

4.6 out of 5

Language	:	English
File size	:	507 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	159 pages

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Unlocking Emergent Phenomena

One of the key advantages of ABMs is their ability to simulate emergent phenomena. Emergence refers to the phenomenon where complex macro-level behavior arises from the interactions of individual agents, without being explicitly programmed into the model. By simulating a wide range of interactions between agents, ABMs can reveal emergent patterns and phenomena that are often difficult to observe using traditional economic models.

Applications of Complex ABMs in Economics

Complex agent-based models have found applications in various areas of economics, including financial markets, labor markets, and economic policy-making. For example, ABMs have been used to study financial contagion and the systemic risk that arises from interconnected markets. They have also been employed to understand the dynamics of job markets, and how labor market policies can affect unemployment rates.

Challenges and Limitations

While complex ABMs offer exciting possibilities, they also come with challenges and limitations. Developing a reliable ABM requires meticulous data collection, parameter calibration, and validation against real-world observations. Furthermore, the complexity of ABMs often leads to high computational costs, making them less accessible to researchers with limited resources.

The Future of Complex Agent-Based Models

Despite the challenges, the potential of complex ABMs in economics is immense. These models have the capability to capture the nuances and dynamics of real-world economic systems, enabling economists to better understand, predict, and develop policies to address complex economic issues. With advancements in computing technology, ABMs are becoming more accessible, allowing researchers to explore new economic windows.

Complex agent-based models offer a promising paradigm for economists seeking to uncover the intricate workings of economic systems. By simulating interactions between autonomous agents, ABMs provide insights into emergent phenomena and challenge traditional economic assumptions. While they come with challenges, the potential benefits of ABMs in economics are vast. It's time for economists to embrace the power of complexity and unlock new economic windows.

Complex Agent-Based Models (New Economic Windows)

by Douglas Fisher (1st ed. 2018 Edition, Kindle Edition)

4.6 out of 5

Language	:	English
File size	:	507 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	159 pages

FREE

This book offers a thorough to the highly promising complex agent-based approach to economics, in which agent-based models (ABMs) are used to represent economic systems as complex and evolving systems composed of heterogeneous agents of limited rationality who interact with each other, generating the system’s emergent properties in the process. 

This approach represents a response to the limitations of the dominant theory in economics, which does not consider the possibility of a major crisis, and to the inability of dynamic stochastic general equilibrium theory to generate empirically falsifiable propositions. In the new perspective, the focus is on identifying the elements of instability rather than the triggering event. As the theory of complexity demonstrates, the interactions of heterogeneous agents produce non-linearity: this puts an end to the age of certainties. 

With ABMs, the methodology is “from the bottom up”. The individual parameters and their distribution are estimated, and then evaluated to verify whether aggregate regularities emerge on the whole. In short, not only micro, but also meso and macro empirical validation are employed. Moreover, it shows that the mantra of growth should be supplanted by the concept of a growth​.
Given its depth of coverage, the book will enable students at the undergraduate and Master’s level to gain a firm grasp of this important emerging approach.

“This book is flower blossomed by one of the two greatest Italian economists.”

Bruce Greenwald, Columbia University

“The author’s - the ABM prophet’s - thoughts on economics have been at the forefront of the world. Without a firm belief in and dedication to human society, it is impossible to write such a book. This is a work of high academic value, which can help readers quickly understand the history and current situation of complex economic theory. In particular, we can understand the basic viewpoints, academic status, advantages and shortcomings of various schools of economic theory.”

Jie Wu, Guangzhou Milestone Software Co., China