# AI-Carbon-Energy: Spillover effects and drivers in interconnected markets

## TL;DR

This paper examines how risks and effects spread between AI, carbon, and energy markets, finding that AI progress can reduce these spillovers.

## Contribution

The study introduces a novel analysis of interconnected market spillovers using advanced statistical models.

## Key findings

- Significant spillover effects exist among AI, carbon, and energy markets.
- The carbon market consistently receives risk from other markets.
- AI technological progress helps reduce spillover intensity.

## Abstract

This study explores the spillover effects between the AI market, international carbon market, and energy markets based on a time-varying parameter vector autoregression model. Further, the study uses a multivariate quantile-to-quantile regression model to identify the macro and micro factors influencing spillover effects. The results show that there are significant spillover effects among the three markets. The AI and new energy markets are the main risk-transmitting markets with respect to the return and volatility spillovers. For skewness and kurtosis, all traditional energy markets except the gas market become risk transmitters. Across all moments, the carbon market consistently is a net recipient of risk. The spillover effects clearly vary with time. Short-term dynamics drive returns and skewness connections, and long-term effects primarily drive volatility and kurtosis connections. In addition, geopolitical risk, economic policy uncertainty, climate risk, AI technological progress, and investor attention may exert differentiated impacts on various spillover effects.

•Significant spillover effects exist across AI, carbon, and energy markets•Carbon market is a consistent net recipient of risk across all moments•Spillover effects vary clearly over time across different market dynamics•AI technological progress generally helps to restrain spillover intensity

Significant spillover effects exist across AI, carbon, and energy markets

Carbon market is a consistent net recipient of risk across all moments

Spillover effects vary clearly over time across different market dynamics

AI technological progress generally helps to restrain spillover intensity

Artificial intelligence applications; Computer modeling; Energy management