An Analysis on the Connection between Sustainable Development and Per Capita Greenhouse Gas Emissions, PM2.5 Exposure, and Renewable Energy Consumption in Kazakhstan Using the Nonlinear Cointegration (NARDL) Method

This study analyzes the relationships between sustainable development and environmental sustainability indicators in Kazakhstan, specifically focusing on greenhouse gas emissions per capita, PM2.5 exposure, and renewable energy consumption. The Nonlinear Autoregressive Distributed Lag (NARDL) method was employed, which offers distinct advantages by evaluating the separate effects of positive and negative changes and accommodating variables that are stationary at different levels. Using annual data from 1995 to 2022, the analysis revealed that greenhouse gas emissions and PM2.5 exposure have asymmetric and statistically significant effects on sustainable development. Although these effects were found to progress towards equilibrium over the long term, both variables are found to produce significant short-term impacts. However, no significant effect of renewable energy consumption on sustainable development was identified. The study's findings emphasize the need for policymakers to consider the impact of environmental sustainability components on sustainable development. To enhance sustainable development performance, particularly given its low level since 2016, it is vital to implement environmental policies aimed at reducing greenhouse gas emissions and minimizing air pollution from PM2.5. Furthermore, it is suggested that the relationships between environmental sustainability and sustainable development should be examined more deeply, particularly concerning causal structures. Additionally, incorporating the stationarity properties of time series along with structural breaks could provide methodological insights.