The Driving Factors of Italy’s CO 2 Emissions Based on the STIRPAT Model: ARDL, FMOLS, DOLS, and CCR Approaches

Dulal Chandra Pattak, Farian Tahrim, Mahdi Salehi, Liton Chandra Voumik (), Salma Akter, Mohammad Ridwan, Beata Sadowska and Grzegorz Zimon ()
Additional contact information
Dulal Chandra Pattak: Department of Banking & Insurance, Faculty of Business Studies, University of Dhaka, Dhaka 1205, Bangladesh
Farian Tahrim: Department of Economics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
Mahdi Salehi: Department of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
Liton Chandra Voumik: Department of Economics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
Salma Akter: Department of Economics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
Mohammad Ridwan: Department of Economics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
Grzegorz Zimon: Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland

Energies, 2023, vol. 16, issue 15, 1-21

Abstract: As the sustainability of the environment is a very much concerning issue for developed countries, the drive of the paper is to reveal the effects of nuclear, environment-friendly, and non-friendly energy, population, and GDP on CO 2 emission for Italy, a developed country. Using the extended Stochastic Regression on Population, Affluence, and Technology (STIRPAT) framework, the yearly data from 1972 to 2021 are analyzed in this paper through an Autoregressive Distributed Lag (ARDL) framework. The reliability of the study is also examined by employing Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS), and Canonical Cointegration Regression (CCR) estimators and also the Granger causality method which is used to see the directional relationship among the indicators. The investigation confirms the findings of previous studies by showing that in the longer period, rising Italian GDP and non-green energy by 1% can lead to higher CO 2 emissions by 8.08% and 1.505%, respectively, while rising alternative and nuclear energy by 1% can lead to falling in CO 2 emission by 0.624%. Although population and green energy adversely influence the upsurge of CO 2 , they seem insignificant. Robustness tests confirm these longer-period impacts. This analysis may be helpful in planning and developing strategies for future financial funding in the energy sector in Italy, which is essential if the country is to achieve its goals of sustainable development.

Keywords: ARDL; CO 2 emission; renewable energy; fossil fuels; STIRPAT model; Italy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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