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.
Paper proposes a framework for token economy simulation and wealth distribution.
problem Simulation and regulation of token economies.
method Formal analysis framework for tokenomics, defining mechanisms for wealth distribution and stability.
result Algorithmic regulatory controls for token economies to achieve desired wealth distribution.
Proposes a machine learning framework for more efficient economic dispatch.
problem Temporal and spatial correlations between system cost and load prediction errors.
method End-to-end machine learning approach with task-specific learning criteria and an efficient optimization kernel.
result Demonstrates the effectiveness and efficiency of the proposed learning framework.
This paper provides an attempt to formalize Hayek's notion of spontaneous order within the framework of the Arrow-Debreu economy. Our study shows that if a competitive economy is enough fair and free, then a spontaneous economic order shall emerge in long-run competitive equilibria so that social members together occup…
New framework for interpretable firm characteristics factors.
problem Creating statistically efficient and economically interpretable factors from firm characteristics.
method Grouping related characteristics and deriving one factor per group, combining economic intuition with data-driven clustering.
result Parsimonious, transparent factors outperform benchmarks in out-of-sample tests.
Money analyzed as a multidimensional tensor for better economic policy.
problem Economic complexity and policy responsiveness.
method Tensor analysis of money dynamics.
result Enhanced economic policy design and resilience.
Our study shows that many firms would accumulate at zero output level (namely, Bankruptcy status) if a perfectly competitive market reaches full employment (namely, those people who should obtain employment have obtained employment). As a result, appearance of economic crisis is determined by two points; that is, (a). …
Deep-MacroFin uses neural networks to solve complex economic models efficiently.
problem Solving high-dimensional partial differential equations in continuous time economics.
method Leverages deep learning, specifically Multi-Layer Perceptrons and Kolmogorov-Arnold Networks, optimized with HJB equations.
result Offers a more efficient solution (5imes less memory, 40imes fewer FLOPs) for 50D economic models. 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.
New framework detects time-varying economic persistence.
problem Time-varying persistence in economic shocks.
method Localized regression techniques to identify evolving heterogeneity.
result Substantial persistence variations align with macroeconomic events.
Proposes a taxonomy for economic policies.
problem Lack of a standardized list of economic policies.
method Develops a tree taxonomy to categorize economic policies.
result Constructs an exhaustive list of economic policies.
Study adds memory effect to Solow-Swan model for more accurate economic growth modeling.
problem Inaccuracies in classical Solow-Swan model in capturing long-term dynamics.
method Introduced fractional calculus with Caputo derivative into Solow-Swan framework.
result Fractional-order model shows significant impact on capital accumulation and stability.
Novel framework analyzes economic shifts in data-poor economies.
problem Data scarcity and unreliability in LMICs hinder accurate assessment of structural transformation.
method Bayesian hierarchical modeling, machine learning, data imputation, factor analysis.
result Framework predicts structural changes even with up to 60% missing data.
FinML-Chain integrates blockchain data for financial machine learning.
problem Challenges in financial machine learning, including missing data, lack of transparency, and incompatible data sources.
method Blockchain technology integrated with machine learning techniques to address financial market challenges.
result Framework generates datasets for analyzing economic mechanisms, advancing financial research.
Paper introduces a new method for calibrating ESGs to both historical and forward-looking data.
problem Lack of a generally accepted methodology for calibrating ESGs to forward-looking information.
method Conditional Scenario Simulator framework for consistent calibration of economic and financial variables.
result Framework can embed various financial and macroeconomic models and demonstrate practical examples in frequentist and Bayesian settings.
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%.
Develops a framework to analyze financial structures.
problem Difficulty in systematic analysis, comparison, and verification of financial structures.
method Formalizes financial structures as structured allocation systems with explicit allocation operators.
result Specifies inputs, structural requirements, and feasibility restrictions for financial structures.
Develops a framework to assess infrastructure reliability under natural and malicious events.
problem Assessing reliability and costs of infrastructure under various hazards.
method Coupling mechanical reliability analyses with economical reliability analyses using probabilistic considerations.
result Indicators of probable cost of failure for infrastructure, aiding safety investments.
Study uses geometric algebra to analyze credit cycles, revealing dangerous feedback loops.
problem Understanding and predicting dangerous feedback loops in credit cycles.
method Represent economic states as multi-vectors in Clifford algebra, focusing on bivector elements for rotational coupling.
result Geometric relationship between unemployment and credit contraction shifts from simple correlation to dangerous rotational dynamics during crises.
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.
AI framework for automated policy-making connects with econometrics and social choice.
problem Improving government and economic policy-making through AI.
method Social Environment Design framework integrating Reinforcement Learning, EconCS, and Computational Social Choice.
result Promotes ethical and responsible decision making by solving open problems.
Although not a formal pricing consideration, gap risk or hedging errors are the norm of derivatives businesses. Starting with the gap risk during a margin period of risk of a repurchase agreement (repo), this article extends the Black-Scholes-Merton option pricing framework by introducing a reserve capital approach to …
This paper argues that the fundamental principle of contemporary financial economics is balanced reciprocity, not the principle of utility maximisation that is important in economics more generally. The argument is developed by analysing the mathematical Fundamental Theory of Asset Pricing with reference to the emergen…
In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among economic and financial entities are crucial to understand and networks provide a natural framework for representing and studying such systems.…
Quantum approach models economic decisions with probabilistic and dynamic probabilities.
problem Traditional economic models fail to explain recent financial crises.
method Develops a quantum probabilistic framework for economics.
result Quantum circuits can model cognitive phenomena like preference reversal.
The green area of economy is the key of healthy living. It is necessary to convene economic and ecologic framework to establish a market attentive to drastic reduction of emissions damaging our climate and landscapes in rural areas, to the protection of biological diversity of the planet, to stop producing nuclear wast…
In this article, we briefly review the different aspects and applications of kinetic exchange models in economics and sociology. Our main aim is to show in what manner the kinetic exchange models for closed economic systems were inspired by the kinetic theory of gas molecules. The simple yet powerful framework of kinet…
Economic factors significantly influence stock returns, as shown by attribution analysis.
problem The influence of economic factors on stock returns.
method Attribution model using five classic factors and new factors like Market Indices, Consumptions, and Oil Prices.
result Stock returns are exposed to economic news and priced based on risk exposure.
The paper analyzes tech specialization and diversification at various scales.
problem Trade-offs between specialization and diversification in economic development.
method Patent data and Economic Complexity framework.
result Technological Coherence positively impacts growth at metropolitan areas but negatively at larger scales.
The paper proposes a new model for predicting and analyzing economic variables.
problem Predicting and analyzing economic variables in developed regions.
method Time-varying parameter global vector autoregressive (TVP-GVAR) framework combined with machine learning models.
result The proposed model provides high precision out-of-sample predictions and novel insights into economic variable connectedness.
The present paper analyses the formal parallelism existing between the laws of thermodynamics and some economic principles. Based on previous works, we shall show how the existence in Economics of principles analogous to those in thermodynamics involves the occurrence of economic events that remind of well-known phenom…
Model credit ratings using economic states with Markov chains.
problem Credit rating migration influenced by economic state changes.
method Developed a Markov chain model for credit ratings conditional on economic states.
result Derived asymptotic behavior of the rating process using Markov theory.
Unified framework for DRO and DTA using Bayesian nonparametrics.
problem Combining DRO and DTA under ambiguity.
method Unified framework using DP and HDPs, with outlier robustness.
result Favorable performance in prediction accuracy and stability.
The study examines tail dependence between global economic uncertainty and BRICS currencies using high-frequency data.
problem Understanding the tail dependence between exchange rates and economic uncertainty.
method Daily Twitter Uncertainty Index and BRICS exchange rates analyzed using time-varying copula framework.
result Indian, Russian, and South African currencies exhibit elliptical copulas, while Brazilian and Chinese currencies show upward trending tail dependence.
Recent research in economic theory attempts to study optimal economic growth and spatial location of economic activity in a unified framework. So far, the key result of this literature - asymptotic convergence, even in the absence of decreasing returns to capital - relies on specific assumptions about the objective of …
ARTEMIS combines deep learning and symbolic reasoning for financial predictions.
problem Lack of interpretability and economic principles in deep learning models in finance.
method Neuro-symbolic framework combining neural operators, stochastic differential equations, and symbolic distillation.
result ARTEMIS achieves state-of-the-art directional accuracy, outperforming all baselines on synthetic crash regime.
The economic equities maximization criterion (MFPE) leads to the choice of financial portfolio, which maximizes the ratio of the expected value of the insurance company on the capital. This criterion is presented in the framework of a non-life insurance company and is applied within the framework of the French legislat…
IntraLayer connects digital finance platforms efficiently.
problem Inefficient interconnectivity in digital finance.
method Core infrastructure and adaptive fiscal policy.
result Optimised transactional efficiency for various agents.
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 propose in this work a kinetic wealth-exchange model of economic growth by introducing saving as a non consumed fraction of production. In this new model, which starts also from microeconomic arguments, it is found that economic transactions between pairs of agents leads the system to a macroscopic behavior where to…
Machine learning models predict US economic recessions using Treasury term spreads.
problem Predicting US economic recessions using Treasury term spreads.
method Gradient Boosting and Random Forest methods trained with SHapley Additive exPlanations (SHAP) framework.
result 3 month to 6 month Treasury term spread is the most relevant for predicting US economic recession.
Peru's abundant natural resources and friendly trade policies has made the country a major economic player in both South America and the global community. Consequently, exports are playing an increasingly important role in Peru's national economy. Indeed, growing from 13.1% as of 1994, exports now contribute approximat…
The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance has produced valuable results. The principal movement which has steered this research direction is known under the name of `econophysics'. In this paper, we illustrate and advance some of the…
Over the last decades, the distribution of income and wealth has been deteriorating in many countries, leading to increased inequalities within and between societies. This tendency has revived the interest in the subject greatly, yet it still receives very little attention within the realm of mainstream economic thinki…
Paper uses bipartite graph to forecast cross-market returns, revealing asymmetry.
problem Cross-market return predictability and asymmetry between U.S. and Chinese markets.
method Directed bipartite graph capturing time-ordered linkages, hypothesis testing for edge selection, regularized and ensemble machine learning models.
result U.S. returns predict Chinese intraday returns, but not vice versa, revealing asymmetry.
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.
This paper presents an assessment of global economic energy potentials for all major natural energy resources. This work is based on both an extensive literature review and calculations using natural resource assessment data. Economic potentials are presented in the form of cost-supply curves, in terms of energy flows …
Unified framework for risk evaluation under uncertainty.
problem Risk assessment under multiple economic scenarios.
method Axiomatic framework for generalized risk measures.
result Characterization of worst-case, coherent, and robust risk measures.