The Driving Factors of Italy’s CO2 Emissions Based on the STIRPAT Model: ARDL, FMOLS, DOLS, and CCR Approaches

As the sustainability of environment is a very much concerning issue for developed countries, drive paper to reveal effects nuclear, environment-friendly, and non-friendly energy, population, GDP on CO2 emission Italy, country. Using extended Stochastic Regression Population, Affluence, Technology (STIRPAT) framework, yearly data from 1972 2021 are analyzed in this through an Autoregressive Distributed Lag (ARDL) framework. The reliability study also examined by employing Fully Modified Ordinary Least Square (FMOLS), Dynamic (DOLS), Canonical Cointegration (CCR) estimators Granger causality method which used see directional relationship among indicators. investigation confirms findings previous studies showing that longer period, rising Italian non-green energy 1% can lead higher emissions 8.08% 1.505%, respectively, while alternative nuclear falling 0.624%. Although population green adversely influence upsurge CO2, they seem insignificant. Robustness tests confirm these longer-period impacts. This analysis may be helpful planning developing strategies future financial funding sector essential if country achieve its goals sustainable development.