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Modeling and Forecasting Energy Consumption in the Manufacturing Industry in South Asia

Author

Listed:
  • Muslima Zahan

    (Faculty of Economics, University of Turin, Italy)

  • Ron S. Kenett

    (Faculty of Economics, University of Turin, Italy)

Abstract

The aim of this study is to model energy consumption and Manufacturing Value Added (MVA) in the industry level of five South Asian countries. Firstly, a cross-sectional model was developed by using R-statistical software to estimate the MVA with energy consumption being the independent variable. Secondly, a twenty years data series was analyzed to forecast volume of energy consumption in the manufacturing industry for five countries in a comparative manner. Thus, a prediction model was developed by using the time series forecasting system of the SAS statistical software and evaluated using Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percent Error (MAPE) with forecasts made up to year 2021. The forecasted energy consumption data might be used in the cross-sectional model to forecast MVA. Besides, based on the increasing trends in volume of energy, industry should prepare now for using efficient and clean energy in order to achieve an environment friendly and sustainable manufacturing industry.

Suggested Citation

  • Muslima Zahan & Ron S. Kenett, 2013. "Modeling and Forecasting Energy Consumption in the Manufacturing Industry in South Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 3(1), pages 87-98.
    • Handle: RePEc:eco:journ2:2013-01-9
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    Cited by:

    1. Köppelová, J. & Jindrová, A., 2017. "Comparative Study of Short-Term Time Series Models: Use of Mobile Telecommunication Services in CR Regions," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(1), March.
    2. Irina A. Firsova & Dinara G. Vasbieva & Nikolay N. Kosarenko & Maria A. Khvatova & Lev R. Klebanov, 2019. "Energy Consumption Forecasting for Power Supply Companies," International Journal of Energy Economics and Policy, Econjournals, vol. 9(1), pages 1-6.

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    More about this item

    Keywords

    Energy Consumption; Manufacturing Value Added (MVA); Cross-sectional model; Time Series Model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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