Latest Articles for Economics

A look at how fractional maps help analyze complex systems influenced by memory.

Explore the dynamics of delay differential equations with unimodal functions and their applications.

A look into how the GDID method enhances causal analysis in research.

Learn how to address discounted control problems affected by time delays.

Learn how quantile regression and MM algorithms improve data analysis across various fields.

A look into optimal transport and its applications across various fields.

This study explores market crashes as phase transitions, offering fresh insights for investors.

This article examines the comparison results of Hamilton-Jacobi equations and their importance.

NIRVAR analyzes complex time series as networks, enhancing predictive accuracy across various fields.

A new approach leverages firm expectations to improve production function estimates.

A study on wealth estimation models across Sub-Saharan Africa.

Investigating additive martingales to reveal population dynamics over time.

This article discusses a new model for analyzing spatio-temporal data.

A deep dive into how players make choices in games.

An overview of key mathematical ideas and their practical uses.

Learn how causal discovery reveals relationships between variables in social sciences.

Examining the trends and impacts of market concentration in Europe's agricultural sector.

A model highlighting Zipf's law in agent interactions across various systems.

This article examines the MIDAS and Lag-Llama models for predicting Eurozone inflation.

Characteristic Interventional Sum-Product Networks improve causal inference in mixed data.

Learn how visualization atlases make complex topics accessible and engaging.

New methods improve variable selection in high-dimensional data analysis.

Research reveals connections between optimal transport and diffusion in porous mediums.

Peer-to-peer energy trading offers new opportunities for consumers and producers.

Learn how time series analysis aids in predicting future trends.

A clear overview of factor models and their applications in various fields.

A fresh approach to modeling how clusters exchange and grow.

A method to identify significant shifts in data over time.

Enhancing asset return predictions through causal feature selection in unstable markets.

A look at estimating conduct parameters for market behavior analysis.

Investigating how diagonal elements influence system stability.

Deep-MacroFin utilizes deep learning to solve complex economic equations effectively.

A look at how linear regression can help estimate causal effects in research.

New approach improves counterfactual generation using causal representation and diffusion models.

Introducing a statistical model for better analysis of bounded data.

This article examines advanced models for predicting stock prices using deep learning techniques.

Explore ways to effectively communicate uncertainty in data predictions.

A new model reveals how urban areas evolve through worker and company interactions.

This study improves economic predictions using Bayesian methods and a stochastic block model.

Self-organization shapes systems, enhancing efficiency through energy flow and interactions.