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Electricity demand analysis and forecasting: The tradition is questioned


  • N. Vijayamohanan Pillai

    (Centre for Development Studies)


The present paper seeks to cast scepticism on the validity and value of the results of all earlier studies in India on energy demand analysis and forecasting based on time series regression, on three grounds. (i) As these studies did not care for model adequacy diagnostic checking, indispensably required to verify the empirical validity of the residual whiteness assumptions underlying the very model, their results might be misleading. This criticism in fact applies to all regression analysis in general. (ii) As the time series regression approach of these studies did not account for possible non-stationarity (i.e., unit root integratedness) in the series, their significant results might be just the misleading result of spurious regression. They also failed to benefit from an analytical framework for a meaningful long-run equilibrium and short-run `causality' in a cointegrating space of error correction. (iii) These studies, by adopting a methodology suitable to a developed power system in advanced economies, sought to correlate the less correlatables in the context of an underdeveloped power system in a less developed economy. All explanations of association of electricity consumption in a hopeless situation of chronic shortage and unreliability with its generally accepted `causatives' (as in the developed systems) of population, per capita income, average revenue, etc., all in their aggregate time series, might not hold much water here. Our empirical results prove our secepticism at least in the context of Kerala power system. We find that the cost of dispensing with model adequacy diagnosis before accepting and interpreting the seemingly significant results is very high. We find that all the variables generally recognised for electricity demand analysis are non-stationary, I(1). We find that all the possible combinations of these I(1) variables fail to be explained in a cointegrating space and even their stationary growth rates remain unrelated in the Granger-`causality' sense.

Suggested Citation

  • N. Vijayamohanan Pillai, 2001. "Electricity demand analysis and forecasting: The tradition is questioned," Centre for Development Studies, Trivendrum Working Papers 312, Centre for Development Studies, Trivendrum, India.
  • Handle: RePEc:ind:cdswpp:312

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    References listed on IDEAS

    1. Pierre Perron & Serena Ng, 1996. "Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties," Review of Economic Studies, Oxford University Press, vol. 63(3), pages 435-463.
    2. Sims, Christopher A., 1988. "Bayesian skepticism on unit root econometrics," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 463-474.
    3. Nelson, Charles R & Kang, Heejoon, 1981. "Spurious Periodicity in Inappropriately Detrended Time Series," Econometrica, Econometric Society, vol. 49(3), pages 741-751, May.
    4. Engle, Robert F & Hendry, David F & Richard, Jean-Francois, 1983. "Exogeneity," Econometrica, Econometric Society, vol. 51(2), pages 277-304, March.
    5. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    6. Plosser, Charles I. & Schwert*, G. William, 1978. "Money, income, and sunspots: Measuring economic relationships and the effects of differencing," Journal of Monetary Economics, Elsevier, vol. 4(4), pages 637-660, November.
    7. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    8. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    9. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    10. DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
    11. Perron, Pierre, 1988. "Trends and random walks in macroeconomic time series : Further evidence from a new approach," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 297-332.
    12. DeJong, David N & Whiteman, Charles H, 1991. "The Temporal Stability of Dividends and Stock Prices: Evidence from the Likelihood Function," American Economic Review, American Economic Association, vol. 81(3), pages 600-617, June.
    13. Sims, Christopher A & Uhlig, Harald, 1991. "Understanding Unit Rooters: A Helicopter Tour," Econometrica, Econometric Society, vol. 59(6), pages 1591-1599, November.
    14. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    15. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    16. Dolado, Juan J & Jenkinson, Tim & Sosvilla-Rivero, Simon, 1990. " Cointegration and Unit Roots," Journal of Economic Surveys, Wiley Blackwell, vol. 4(3), pages 249-273.
    17. Nelson, Charles R & Kang, Heejoon, 1984. "Pitfalls in the Use of Time as an Explanatory Variable in Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(1), pages 73-82, January.
    18. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    19. Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-364, Oct.-Dec..
    20. David A. Dickey & Dennis W. Jansen & Daniel L. Thornton, 1991. "A primer on cointegration with an application to money and income," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 58-78.
    21. Engle, Robert F, 1983. "Estimates of the Variance of U.S. Inflation Based upon the ARCH Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 15(3), pages 286-301, August.
    22. Francis X. Diebold & Marc Nerlove, 1988. "Unit roots in economic time series: a selective survey," Finance and Economics Discussion Series 49, Board of Governors of the Federal Reserve System (U.S.).
    23. Johansen, Soren, 1992. "Testing weak exogeneity and the order of cointegration in UK money demand data," Journal of Policy Modeling, Elsevier, vol. 14(3), pages 313-334, June.
    24. Dickey, David A & Pantula, Sastry G, 1987. "Determining the Ordering of Differencing in Autoregressive Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 455-461, October.
    25. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    26. Crafts, N.F.R. & Leybourne, S.J. & Mills, T.C., 1988. "Economic Growth In Nineteeth Century Britain: Comparisons With Europe In The Context Of Gerschenkron'S Hypotheses," The Warwick Economics Research Paper Series (TWERPS) 308, University of Warwick, Department of Economics.
    27. Gonzalo, Jesus, 1994. "Five alternative methods of estimating long-run equilibrium relationships," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 203-233.
    28. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    29. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    30. Koop, Gary, 1992. "'Objective' Bayesian Unit Root Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 65-82, Jan.-Marc.
    31. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    32. Robert F. Engle & David F. Hendry & David Trumble, 1985. "Small-Sample Properties of ARCH Estimators and Tests," Canadian Journal of Economics, Canadian Economics Association, vol. 18(1), pages 66-93, February.
    33. Schmidt, Peter & Phillips, C B Peter, 1992. "LM Tests for a Unit Root in the Presence of Deterministic Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 257-287, August.
    34. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. N. Vijayamohanan Pillai, 2003. "A contribution to peak load pricing theory and application," Centre for Development Studies, Trivendrum Working Papers 346, Centre for Development Studies, Trivendrum, India.
    2. Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
    3. Pillai N., Vijayamohanan, 2008. "Strengthening Infrastructure: Power Sector Reforms- Some Viable Proposals For Kerala," MPRA Paper 8869, University Library of Munich, Germany.
    4. Sreekanth, K.J., 2016. "Review on integrated strategies for energy policy planning and evaluation of GHG mitigation alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 837-850.
    5. Siddiqui, Md Zakaria & de Maere d'Aertrycke, Gauthier & Smeers, Yves, 2012. "Demand response in Indian electricity market," Energy Policy, Elsevier, vol. 50(C), pages 207-216.

    More about this item


    India; Kerala; demand analysis; forecasting; non-stationarity;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices


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