Using the Growth-at-Risk (GaR) framework, this study investigated the connection between economic vulnerability and climate change in emerging and developing economies. The growing understanding that climate shocks present asymmetric risks and disproportionately impact the lower tail of the GDP growth distribution instead of the average outcomes served as the impetus for the study. Variables like temperature anomalies, precipitation volatility, and the frequency of natural disasters were all included in the analysis of a panel dataset that covered several developing economies. The impact of climate-related factors on growth across quantiles was evaluated using simulation-based GaR models and quantile regression. The findings showed that while natural disasters increased the likelihood of a negative outcome, higher temperature anomalies and increased precipitation variability significantly decreased economic performance at the 5th and 25th percentiles. The median while upper quantiles of GDP growth, on the other hand, stayed largely unchanged, highlighting the fact that climate change primarily increased the probability of severe downturns. These results underlined the need for risk-focused approaches to economic modeling and the shortcomings of traditional mean-based forecasting techniques. According to the study's findings, climate change made financial and macroeconomic fragility worse, especially in areas that are already at risk. It also suggested policy solutions like better disaster management, resilient infrastructure, and climate-sensitive financial regulations. Future research directions included integrating institutional quality, conducting sector-specific analyses, and utilizing technological advancements like artificial intelligence to improve predictive capacity.
Zeb et al. (Sun,) studied this question.