Renewable Electricity and CO2 Emissions in Tajikistan: Evidence from an ARDL–STIRPAT Framework

Tajikistan relies heavily on hydropower for electricity generation, but increasing energy demand, winter electricity shortages, rising coal consumption, and climate-related changes in water availability pose significant challenges to the country’s energy system and environment. In this study, we examined the relationship between renewable electricity generation and per capita CO2 emissions in Tajikistan from 1991 to 2023. We conducted the analysis within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework using an autoregressive distributed lag (ARDL) approach. Our model incorporates population growth, gross domestic product (GDP) per capita, industry value added, renewable electricity generation, and globalisation. The diagnostic and stability tests employed did not detect major specification problems in the selected model. We found that the share of renewable electricity has a statistically significant negative contemporaneous association with per capita CO2 emissions. GDP per capita is positively associated with emissions, whereas globalisation has a negative association in both the current and subsequent years. We also found a positive coefficient for lagged population growth and a negative coefficient for lagged industry value added. On the basis of these results, we conclude that renewable electricity can play an important role in addressing Tajikistan’s energy and environmental challenges. Our findings also provide country-specific evidence that may support the development of energy, environmental, and economic policies aimed at strengthening energy security while limiting carbon emissions.