kaüi̇i̇bfd Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 1309-4289 2149-9136 Kafkas Üniversitesi 10.36543/kauiibfd.2021.033 FORECASTING OF CO2 WITH THE EFFECT OF RENEWABLE ENERGY, NON-RENEWABLE ENERGY, GDP AND POPULATION FOR TURKEY: FORECASTING WITH NMGM (1,N) GRAY FORECASTING MODEL FORECASTING OF CO2 WITH THE EFFECT OF RENEWABLE ENERGY, NON-RENEWABLE ENERGY, GDP AND POPULATION FOR TURKEY: FORECASTING WITH NMGM (1,N) GRAY FORECASTING MODEL https://orcid.org/0000-0003-0832-0490 Karadağ Albayrak Özlem KAFKAS UNIVERSITY 12 21 2021 12 24 810 828 09 08 2021 11 21 2021 Copyright © 2010, Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 2010 Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi

Karbondioksit salınımı çevre üzerinde olumsuz etkisi olan önemli faktörlerden birisidir. Politika yapıcıların yenilenebilir enerji konusunda teşvik politikaları üretmelerinin nedenlerinden biri de CO2 emisyonlarını azaltmayı istemeleridir. Bu noktadan hareketle CO2 emisyonlarının farklı faktörlere bağlı olarak tahmini yapılmalı ve tahmin sonuçlarına göre yeni politikalar geliştirilip uygulanmalıdır. Bu makalede, yenilenebilir enerji tüketimi, yenilenemeyen enerji tüketimi, GSMH ve Nüfus faktörlerinin zaman içinde CO2 emisyonu üzerindeki etkisini ölçmek için gri tahmin modellerinden yeni bir yaklaşım olan NMGM (1, N) tahmin modeli kullanılmıştır. Bu çalışmada 2006-2015 verisi similasyon seti, 2016-2019 verileri test seti olarak kullanılmıştır. Bu yönteme ek olarak GM (1, N) ve çok değişkenli gri tahmin yöntemi olan ekonometrik model ile tahmin yapılmış ve sonuçlar karşılaştırılmıştır. Sonuç olarak NMGM (1, N) tahmin modeli çok düşük sapma değerleri ile oldukça etkili bir tahmin sunmuştur.

Carbon dioxide emission is one of the important factors that have a negative impact on the environment. One of the reasons why policy makers produce incentive policies on renewable energy is that they want to reduce CO2 emissions. From this point of view, prediction of CO2 emissions must be made depending on different factors, and new policies can be developed and implemented according to the prediction results. In this article, a new approach from gray estimation models, NMGM (1, N) forecasting model, is used to measure the impact of renewable energy consumption, non-renewable energy consumption, GDP and Population factors on CO2 emission over time. 2006-2015 data was simulation set and 2016-2019 data was used as a test set. In addition to this method, estimation was made with GM (1, N) and econometric model, which is the multivariate gray estimation method, and the results were compared. As a result, NMGM (1, N) model has become a very effective estimation method with very low deviation values.

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