Green bubbles: a four-stage paradigm for detection and propagation

TL;DR

This paper introduces a four-stage paradigm utilizing SPC and econometric models to detect green investment bubbles, emphasizing their role in facilitating sustainable energy transitions amid market dynamics.

Contribution

It presents a novel framework combining SPC and social factors to identify green bubbles in renewable energy markets, linking them to economic and social implications.

Findings

Green bubbles can be detected using SPC methodologies.

Social factors influence green bubble dynamics.

Green bubbles play a role in sustainable energy transition.

Abstract

Climate change has emerged as a significant global concern, attracting increasing attention worldwide. While green bubbles may be examined through a social bubble hypothesis, it is essential not to neglect a Climate Minsky moment triggered by sudden asset price changes. The significant increase in green investments highlights the urgent need for a comprehensive understanding of these market dynamics. Therefore, the current paper introduces a novel paradigm for studying such phenomena. Focusing on the renewable energy sector, Statistical Process Control (SPC) methodologies are employed to identify green bubbles within time series data. Furthermore, search volume indexes and social factors are incorporated into established econometric models to reveal potential implications for the financial system. Inspired by Joseph Schumpeter's perspectives on business cycles, this study recognizes green bubbles as a necessary evil for facilitating a successful transition towards a more sustainable future.