Modeling business cycles via collective risk fluctuations in economic agents' risk space.
problem Understanding and predicting business cycles through economic agents' risk dynamics.
method Continuous numerical risk grades for economic agents, modeling collective economic variables and flows as functions of risk coordinates, deriving equations for their evolution.
result Business and credit cycles are explained as fluctuations of collective economic variables and their mean risks in the risk space of economic agents.
Second-order economic theory considers new variables to improve price volatility predictions.
problem Current economic models focus on first-order variables, missing second-order variables that affect price volatility.
method Introduces second-order economic theory with new variables composed of sums of squares of agents' transactions.
result Second-order economic theory complements first-order variables and introduces new macroeconomic variables.
Developing an AI economist agent using RAG, knowledge graphs, and LLMs for economic scenario analysis.
problem Economic scenario analysis using large language models and knowledge graphs.
method Proposing an RAG-based AI economist framework that utilizes knowledge graphs and LLMs.
result Improves economic coherence and traceability in generated reports.
We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each ot…
AI agents improve forecast combination in empirical economics.
problem Hidden researcher degrees of freedom in AI-generated code.
method Adapted agent-loop architecture to empirical economics, added holdout evaluation.
result Independent agent searches find better forecast methods than benchmarks.
We consider a heterogeneous agent-based economic model where economic agents have strictly bounded rationality and where income allocation strategies evolve through selective imitation. Income is calculated by a Cobb-Douglas type production function, and selection of strategies for imitation depends on the income growt…
This essay discusses the advantages of a probabilistic agent-based approach to questions in theoretical economics, from the nature of economic agents, to the nature of the equilibria supported by their interactions. One idea we propose is that "agents" are meta-individual, hierarchically structured objects, that includ…
We present an overview of some representative Agent-Based Models in Economics. We discuss why and how agent-based models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a schematic analysis of several m…
AI agents improve forecast combination but require transparency.
problem AI coding agents increase flexibility in empirical economics, leading to hidden degrees of freedom.
method Adapted open-source agent-loop architecture to empirical economics workflow, adding post-search holdout evaluation.
result Multiple agent runs outperform standard benchmarks in rolling evaluation but not all on post-search holdout.
Tax dynamics affects wealth distribution in a linearly growing socio-economic model.
problem Analyzing how tax policies impact wealth distribution in a stochastic resetting system.
method Analytical and numerical study of a system of agents with linear wealth growth, stochastic resetting, and tax redistribution.
result Optimal taxation leads to economic equality, while excessive taxation results in reverse disparity.
This work explains crises in markets without external news using bounded rational agents.
problem Inability to model out-of-equilibrium dynamics in economic markets.
method Modeling bounded rational strategic reasoning in multi-agent market games.
result Bounded rational strategic reasoning can lead to endogenously emerging crises.
We review some statistical many-agent models of economic and social systems inspired by microscopic molecular models and discuss their stochastic interpretation. We apply these models to wealth exchange in economics and study how the relaxation process depends on the parameters of the system, in particular on the savin…
We consider a simple model of a closed economic system where the total money is conserved and the number of economic agents is fixed. In analogy to statistical systems in equilibrium, money and the average money per economic agent are equivalent to energy and temperature, respectively. We investigate the effect of the …
We revisit a recently introduced agent model[ACS {\bf 11}, 99 (2008)], where economic growth is a consequence of education (human capital formation) and innovation, and investigate the influence of the agents' social network, both on an agent's decision to pursue education and on the output of new ideas. Regular and ra…
We study the effect of the social stratification on the wealth distribution on a system of interacting economic agents that are constrained to interact only within their own economic class. The economical mobility of the agents is related to its success in exchange transactions. Different wealth distributions are obtai…
We present a model in which we investigate the structure and evolution of a random network that connects agents capable of exchanging wealth. Economic interactions between neighbors can occur only if the difference between their wealth is less than a threshold value that defines the width of the economic classes. If th…
Market equilibrium price proven in a large-agent model.
problem Proving market equilibrium in a large-agent setting.
method Proved existence of equilibrium price in a complete, continuous time market with infinite agents.
result The equilibrium price dynamics decouple as the number of agents increases.
We study the qualitative and quantitative appearance of stylized facts in several agent-based computational economic market (ABCEM) models. We perform our simulations with the SABCEMM (Simulator for Agent-Based Computational Economic Market Models) tool recently introduced by the authors (Trimborn et al. 2019). Further…
Study examines how governance, corruption, and R&D affect economic development.
problem The impact of corruption and governance on economic development.
method General equilibrium model with heterogeneous agents and a government, including corruption as a fraction of tax revenues.
result Redistribution and innovation-led strategies can mitigate the negative effects of corruption on economic development.
Boltzmann-Gibbs distribution arises as the statistical equilibrium probability distribution of money among the agents of a closed economic system where random and undirected exchanges are allowed. When considering a model with uniform savings in the exchanges, the final distribution is close to the gamma family. In thi…
A new platform models how narratives influence financial markets.
problem Explaining irrational market behaviors through narratives.
method Integrated opinion dynamics and agent-based modeling.
result Initial results show how narratives shape financial outcomes.
The current economic crisis has provoked an active response from the interdisciplinary scientific community. As a result many papers suggesting what can be improved in understanding of the complex socio-economics systems were published. Some of the most prominent papers on the topic include (Bouchaud, 2009; Farmer and …
In science and especially in economics, agent-based modeling has become a widely used modeling approach. These models are often formulated as a large system of difference equations. In this study, we discuss two aspects, numerical modeling and the probabilistic description for two agent-based computational economic mar…
In this article, we address the question of how non-knowledge about future events that influence economic agents' decisions in choice settings has been formally represented in economic theory up to date. To position our discussion within the ongoing debate on uncertainty, we provide a brief review of historical develop…
Collective behavior of the complex socio-economic systems is heavily influenced by the herding, group, behavior of individuals. The importance of the herding behavior may enable the control of the collective behavior of the individuals. In this contribution we consider a simple agent-based herding model modified to inc…
Inequality persists as wealth concentrates in a few agents.
problem Widening wealth gap in society.
method Modeling wealth exchanges and proposing regulatory policies.
result Simple policies can redistribute wealth and prevent inequality.
Paper forecasts commodity price spikes using AI and economic news.
problem Accurate forecasting of commodity price spikes for economic stability.
method Hybrid framework combining historical data and semantic signals from economic news.
result Model achieves high AUC and accuracy in detecting price shocks.
We analyze a conservative market model for the competition among economic agents in a close society. A minimum dynamics ensures that the poorest agent has a chance to improve its economic welfare. After a transient, the system self-organizes into a critical state where the wealth distribution have a minimum threshold, …
One 'problem' with the 21st century world, particularly the economic and business worlds, is the phenomenal and increasing number of interconnections between economic agents (consumers, firms, banks, markets, national economies). This implies that such agents are all interacting and consequently giving raise to enormou…
We present examples of agent-based and stochastic models of competition and business processes in economics and finance. We start from as simple as possible models, which have microscopic, agent-based, versions and macroscopic treatment in behavior. Microscopic and macroscopic versions of herding model proposed by Kirm…
We introduce the simulation tool SABCEMM (Simulator for Agent-Based Computational Economic Market Models) for agent-based computational economic market (ABCEM) models. Our simulation tool is implemented in C++ and we can easily run ABCEM models with several million agents. The object-oriented software design enables th…
The existence of stylized facts in financial data has been documented in many studies. In the past decade the modeling of financial markets by agent-based computational economic market models has become a frequently used modeling approach. The main purpose of these models is to replicate stylized facts and to identify …
Agent-based model uses SAM to create realistic economic system.
problem Lack of tools to understand and predict economic crises.
method Agent-based modeling (ABM) with Social Accounting Matrix (SAM) calibration.
result ABM can produce economic systems close to real-world data.
We introduce a simple model for addressing the controversy in the study of financial systems, sometimes taken as brownian-like processes and other as critical systems with fluctuations of arbitrary magnitude. The model considers a collection of economical agents which establish trade connections among them according to…
Reinforcement learning aids decision-making in economics and finance.
problem Optimal decision-making in dynamic, uncertain environments.
method Reinforcement learning algorithms to learn optimal policies.
result Deep learning enhances solving complex behavioral problems.
Deep RL solves complex economic models with heterogeneous agents.
problem Solving models with heterogeneous economic actors is difficult.
method Reinforcement Learning techniques for solving general equilibrium models.
result Successfully captures economic behaviors induced by age-based health risks.
The paper gives picture of enrichment to economic and financial system analysis using agent-based models as a form of advanced study for financial economic data post-statistical-data analysis and micro-simulation analysis. Theoretical exploration is carried out by using comparisons of some usual financial economy syste…
Introduces a new price measure and a second-order economic theory for volatility forecasting.
problem Forecasting price volatility in financial markets.
method Develops a new price measure and a second-order economic theory to model price volatility.
result Shows that second-order economic theory improves forecasting of price volatility.
We use the maximum entropy principle for pricing the non-life insurance and recover the Bühlmann results for the economic premium principle. The concept of economic equilibrium is revised in this respect.
AI-driven tax policies improve economic equality and productivity.
problem Lack of appropriate economic data and limited opportunity to experiment.
method Two-level deep reinforcement learning approach to learn dynamic tax policies from observational data.
result AI-driven tax policies improve the trade-off between equality and productivity by 16%.
As we show using the notion of equilibrium in the theory of infinite sequential games, bubbles and escalations are rational for economic and environmental agents, who believe in an infinite world. This goes against a vision of a self regulating, wise and pacific economy in equilibrium. In other words, in this context, …
SIMPOL solves complex economic models using numerical methods.
problem Optimizing consumption and savings under uncertainty.
method SIMPOL uses a modular numerical framework combining policy iteration and finite difference schemes.
result SIMPOL produces solutions consistent with economic and mathematical theory.
We present and analyze a model for the evolution of the wealth distribution within a heterogeneous economic environment. The model considers a system of rational agents interacting in a game theoretical framework, through fairly general assumptions on the cost function. This evolution drives the dynamic of the agents i…
ESOP uses Bayesian optimization to find optimal lock-down schedules.
problem Finding optimal lock-down schedules balancing health and economy.
method Bayesian optimization interacting with epidemiological models.
result ESOP schedules balance public health and economic impacts.
The paper develops an economic foundation for multi-agent learning in markets.
problem Learning dynamics in markets with strategic externalities.
method A two-phase incentive mechanism that estimates and uses implementable transfers to steer long-run dynamics.
result The mechanism achieves sublinear social-welfare regret and asymptotically optimal welfare under mild rationality and exploration conditions.
Exponential distribution is ubiquitous in the framework of multi-agent systems. An alternative approach with an economic motivation to derive the exponential distribution in the framework of iterations in the space of distributions is disclosed.
A dynamic agent model is introduced with an annual random wealth multiplicative process followed by taxes paid according to a linear wealth-dependent tax rate. If poor agents pay higher tax rates than rich agents, eventually all wealth becomes concentrated in the hands of a single agent. By contrast, if poor agents are…
We study two kinds of economic exchange, additive and multiplicative, in a system of N agents. The work is divided in two parts, in the first one, the agents are free to interact with each other. The system evolves to a Boltzmann-Gibbs distribution with additive exchange and condenses with a multiplicative one. If bank…