Selection of forecast model for consumption (four sectors) and transmission (two Piplines) of natural gas in Punjab (Pakistan) based on ARIMA model

  • Authors

    • Maliha Butt Department of StatisticsGC University, Lahore, Pakistan
    2015-05-30
    https://doi.org/10.14419/ijasp.v3i1.4635
  • ARIMA Model, Box Jenkins [3] Approach, Consumption of Natural Gas, Time Series Forecasting, Transmission of Natural Gas.

  • Abstract

    The main purpose of this study is to select an appropriate forecast model for Natural Gas Consumption and Transmission System. For ARIMA model, Box-Jenkins Approach (1976) has been adopted i.e. Stationarity of the series has been checked for each data set, correlogram has been estimated for identification of order of ARIMA model and a class of models has been estimated. Then, most adequate and appropriate model is selected by analyzing diagnostics checks. Later on, by comparing values of Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and Standard Error (S.E.) of Regression, Root Mean Square Error (RMSC) and Theil Inequality Coefficient (TIC) for each model, forecast model has been finalized. In the end, forecasts have been made using models and compared these forecast values with the actual values for 2010 in order to check the accuracy of the model.

  • References

    1. [1] S.E. Alna and F. Ahiakpor, ARIMA approach to predicting inflation in Ghana, Journal of Economics and International Finance 3(5) (2011) 328-336.

      [2] H. Bailly, A report by A Global Management Consulting Firm (Islamabad), (2011). Retrieved from: http://www.pakistantoday.com.pk/2011/09/gas-shortage-adversely-impacting-economy/

      [3] J.E.P Box and G.M. Jenkins, The time series analysis: Forecasting and control (revised edition), Holden-day, San-Francisco, 2011.

      [4] G. Edward, P. Box and G.M. Jenkins, Time series analysis: Forecasting and control, Prentice Hall PTR, USA, 2011.

      [5] E. Erdogdu, Natural gas demand in Turkey, Applied Energy 87(1) (2010) 211-219. http://dx.doi.org/10.1016/j.apenergy.2009.07.006.

      [6] M. Forouzanfar, A. Doustmohammadi, M.B. Menhaj and S. Hasanzadeh, Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran, Applied Energy 87(1) (2010) 268-274. http://dx.doi.org/10.1016/j.apenergy.2009.07.008.

      [7] Z.Y. Han and W.G. Weng, An integrated quantitative risk analysis method for natural gas pipeline network, Journal of Loss Prevention in the Process Industries 23(3) (2010) 428-436. http://dx.doi.org/10.1016/j.jlp.2010.02.003.

      [8] H.G. Huntington, Industrial natural gas consumption in the United States: An empirical model for evaluating future trends, Energy Economics 29(4) (2007) 743-759. http://dx.doi.org/10.1016/j.eneco.2006.12.005.

      [9] C.K. Lee, H.J. Song and J.W. Mjelde, The forecasting of international expo tourism using quantitative and qualitative techniques, Tourism Management 29(6) (2008) 1084-1098. http://dx.doi.org/10.1016/j.tourman.2008.02.007.

      [10] P.I. Nwosa and I.O. Oseni, Monetary policy, exchange rate and inflation rate in Nigeria, Research Journal on Finance and Accounting 3(3) (2012) 62-69.

      [11] S. Pandian, The political economy of trans-Pakistan gas pipeline project: Assessing the political and economic risks for India, Energy Policy 33(5) (2005) 659-670. http://dx.doi.org/10.1016/j.enpol.2003.09.011.

      [12] M. Radetzki, World Demand for Natural Gas: History and Prospects, the Energy Journal 15(Special Issue) (1994) 219-236. http://dx.doi.org/10.5547/issn0195-6574-ej-vol15-nosi-12.

      [13] A. Sen, Natural gas imports into South Asia a study in international relations, Energy Policy 28(11) (2000) 763-770. http://dx.doi.org/10.1016/S0301-4215(00)00061-6.

      [14] J.S. Simonoff, C.E. Restrepo and R. Zimmerman, Risk management of cost consequences in natural gas transmission and distribution infrastructures, Journal of Loss Prevention in the Process Industries 23(2) (2010) 269-279. http://dx.doi.org/10.1016/j.jlp.2009.10.005.

      [15] Z. Wadud, H.S. Dey, M.A. Kabir and S.I. Khan, Modeling and forecasting natural gas demand in Bangladesh, Energy Policy 39(11) (2011) 7372-7380. http://dx.doi.org/10.1016/j.enpol.2011.08.066.

      [16] K. Wong, H. Song, S.F. Witt and D.C. Wu, Tourism forecasting: To combine or not to combine? Tourism Management 28 (2007) 1068-1078. http://dx.doi.org/10.1016/j.tourman.2006.08.003.

      [17] G. Xu and W. Wang, Forecasting China's natural gas consumption based on a combination model, Journal of Natural Gas Chemistry 19(5) (2010) 493-496. http://dx.doi.org/10.1016/S1003-9953(09)60100-6.

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  • Received date: 2015-04-16

    Accepted date: 2015-05-18

    Published date: 2015-05-30