Estimating the causal impact of the Paris agreement on the ESG market: A Bayesian structural time-series approach

This study uses a Bayesian structural time-series model to examine the causal impact of the Paris Agreement on Environmental, Social, and Governance (ESG) markets across 18 countries. The research addresses key gaps in understanding the long-term effects of international climate agreements on sustainable finance. By analyzing MSCI ESG Leaders indices from 2013 to 2022, the study reveals significant variations in the agreement's impact across different economies. Countries like China and Indonesia experienced substantial increases in their ESG indices (31.01 %), while others like the UK saw decreases (−2.63 %). A structural break analysis serves as a robustness test, confirming significant shifts in ESG indices coinciding with the Paris Agreement's adoption in 2015. The study also highlights subsequent structural breaks in 2017, 2019, and 2021, reflecting ongoing regulatory changes and global events affecting ESG markets. This research contributes to a more nuanced understanding of how international climate policies shape sustainable investment practices, offering valuable insights for policymakers and investors navigating the evolving landscape of climate finance.