A robust least square approach for forecasting models: an application to Brazil’s natural gas demand

2019 ◽  
Vol 11 (4) ◽  
pp. 1111-1135
Author(s):  
Oswaldo L. V. Costa ◽  
Celma de Oliveira Ribeiro ◽  
Linda Lee Ho ◽  
Erik Eduardo Rego ◽  
Virginia Parente ◽  
...  
2020 ◽  
Vol 8 (08) ◽  
pp. 423-438
Author(s):  
E. Stathakis ◽  
E. Stambologlou

The modeling of Natural Gas (NG) demand differs significantly from the demand for electricity in terms of the determinants that affect it, as all fields of economic activities in a modern economy are directly related to electricity but not to NG. But NG is the second energy type after electricity used in all countries in percentages greater than 10% in average terms. NG is going to be installed in the Region of East Macedonia-Thrace (REMTH) the next years. So, we consider it is worth to predict the NG demand in REMTH using eight deterministic forecasting models. In order to do it we used a dataset of 20 years concerning two Greek regions to which the NG is used that period and through them we built the eight forecasting models aiming to find the NG demand in the REMTH. In order to evaluate the reliability and accuracy of them we used four types of statistical errors, Mean Error (ME), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Scale Error (MASE). These are the most widely used measures of evaluating the accuracy of deterministic predictive models, due to their advantages of scale-independency and interpretability. When  each of them is used alone has the significant disadvantage to produce infinite or undefined values for zero or close-to-zero actual values. In order to address this disadvantage, we propose a way to use the same time all of them measuring the accuracy of a model used to forecast the demand of Natural Gas in the Greek region EMTH. The innovation of this paper is that for NG demand forecasting were used seven different models and they are evaluated regarding their reliability /accuracy using five types of residuals or statistical errors


Author(s):  
Evgenia Christoforou ◽  
Alessandro Nordio ◽  
Alberto Tarable ◽  
Emilio Leonardi

2021 ◽  
Vol 99 ◽  
pp. 105301
Author(s):  
Ioannis Kostakis ◽  
Sarantis Lolos ◽  
Eleni Sardianou

Author(s):  
Omar Avalos ◽  
Erik Cuevas ◽  
Héctor G. Becerra ◽  
Jorge Gálvez ◽  
Salvador Hinojosa ◽  
...  

Author(s):  
Tomiwa Sunday Adebayo ◽  
Abraham Ayobamiji Awosusi ◽  
Seun Damola Oladipupo ◽  
Ephraim Bonah Agyekum ◽  
Arunkumar Jayakumar ◽  
...  

Despite the drive for increased environmental protection and the achievement of the Sustainable Development Goals (SDGs), coal, oil, and natural gas use continues to dominate Japan’s energy mix. In light of this issue, this research assessed the position of natural gas, oil, and coal energy use in Japan’s environmental mitigation efforts from the perspective of sustainable development with respect to economic growth between 1965 and 2019. In this regard, the study employs Bayer and Hanck cointegration, fully modified Ordinary Least Square (FMOLS), and dynamic ordinary least square (DOLS) to investigate these interconnections. The empirical findings from this study revealed that the utilization of natural gas, oil, and coal energy reduces the sustainability of the environment with oil consumption having the most significant impact. Furthermore, the study validates the environmental Kuznets curve (EKC) hypothesis in Japan. The outcomes of the Gradual shift causality showed that CO2 emissions can predict economic growth, while oil, coal, and energy consumption can predict CO2 emissions in Japan. Given Japan’s ongoing energy crisis, this innovative analysis provides valuable policy insights to stakeholders and authorities in the nation’s energy sector.


Energy ◽  
2004 ◽  
Vol 29 (7) ◽  
pp. 979-1000 ◽  
Author(s):  
A DEALMEIDA ◽  
A LOPES ◽  
A CARVALHO ◽  
J MARIANO ◽  
A JAHN ◽  
...  

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