Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Comparison of Forecasting Ability for Energy Consumption in BRICS: ARIMA (1,1,1) and FGM (1, 1) Models

Version 1 : Received: 2 April 2021 / Approved: 5 April 2021 / Online: 5 April 2021 (13:51:38 CEST)

A peer-reviewed article of this Preprint also exists.

Khan, A.M.; Osińska, M. How to Predict Energy Consumption in BRICS Countries? Energies 2021, 14, 2749. Khan, A.M.; Osińska, M. How to Predict Energy Consumption in BRICS Countries? Energies 2021, 14, 2749.

Journal reference: Energies 2021, 14, 2749
DOI: 10.3390/en14102749

Abstract

Brazil, Russia, China, India, and the Republic of South Africa (BRICS) represent developing economies facing different energy and economic development challenges. The current study aims to forecast energy consumption in BRICS at aggregate and disaggregate levels using the annual time series data set from 1992 to 2019 and to compare results obtained from a set of models. The time-series data are from the British Petroleum (BP-2019) Statistical Review of World Energy. The forecasting methodology bases on a novel Fractional-order Grey Model (FGM) with different order parameters. This study contributes to the literature by comparing the forecasting accuracy and the forecasting ability of the FGM(1,1) with traditional ones, like standard GM(1,1) and ARIMA(1,1,1) models. Also, it illustrates the view of BRICS's nexus of energy consumption at aggregate and disaggregates levels using the latest available data set, which will provide a reliable and broader perspective. The Diebold-Mariano test results confirmed the equal predictive ability of FGM(1,1) for a specific range of order parameters and the ARIMA(1,1,1) model and the usefulness of both approaches for energy consumption efficient forecasting.

Subject Areas

Energy consumption; BRICS; GM (1, 1); Fractional-order; GREY; Forecasting accuracy

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