Log-Ergodic Dynamics in Stochastic Monetary Velocity: Theoretical Insights and Economic Implications

TL;DR

This paper introduces a log-ergodic model for simulating the velocity of money, providing new theoretical insights and practical tools for understanding economic stability and improving policy predictions.

Contribution

It develops a novel log-ergodic approach to model money velocity, bridging theory and empirical analysis for better economic forecasting.

Findings

The model captures long-term stability of money velocity.

It outperforms traditional models in predictive accuracy.

Empirical analysis confirms effectiveness with U.S. data.

Abstract

We suggest employing log-ergodic processes to simulate the velocity of money in an ergodic manner. Our approach sheds light on economic behavior, policy implications, and financial dynamics by maintaining long-term stability. By bridging theory and practice, the partially ergodic model helps analysts and policymakers comprehend and forecast velocity of money. The empirical analysis, using historical U.S. GDP and money supply data, demonstrates the model's effectiveness in capturing the long-term stability of the velocity of money. Key findings indicate that the log-ergodic model offers superior predictive power compared to traditional models, making it a valuable tool for policymakers to control economic factors in vital situations.