Author:
R.M. Alsayed Ahmed,Kun Sek Siok,Halil Ariç Kivanç,Isa Zaidi
Abstract
Climate change and global warming during the recent decades are posing formidable chal- lenges to ecosystems. Nevertheless, changing the climate system due to extreme weather events such as cold spells, high temperatures, droughts, and heat waves have been recorded all over the world. Particularly, it has become less accurate to predict the weather in some European regions using a short time series without considering the extreme values events in the estimated model. Thus, forecasting the behaviour of climate needs more accurate statisti- cal techniques to be used. The main objective of this experimental study is to detect the best robust scale or robust location estimator to model the relationship between CO2 emissions, fossil fuel consumption and gross domestic product by considering the influence of different types of extreme weather events in the panel data of Mediterranean Europe countries over the period 1960-2020. The findings show that the MM-estimator is the best robust estimator han- dling data with high efficiency and high breakdown point with the existence of different types of extreme weather events. In conclusion, the robust MM-estimator could be used to provide an innovative integrated climate-economic approach for the accurate prediction of carbon emissions.
Subject
Management, Monitoring, Policy and Law,Economics and Econometrics,Renewable Energy, Sustainability and the Environment
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