Structural Breaks, Price and Income Elasticity, and Forecast of the Monthly Italian Electricity Demand

Dicembrino, Claudio and Trovato, Giovanni (2013): Structural Breaks, Price and Income Elasticity, and Forecast of the Monthly Italian Electricity Demand.

Abstract

Insights about electricity demand dynamics is fundamental for investment capacity, optimal energy policies, and a balanced electricity system. This paper presents an empirical analysis of the monthly Italian electricity demand since January 2001 to June 2012. In the first section we conduct the analysis of structural breaks in the electricity demand finding that the series has two structural breaks in August 2002 and August 2004 as market liberalization effects on consumption. In the second part of the paper we estimate demand price elasticities both for residential and industrial sector. As expected from the electricity economics literature concerning elasticities estimates, we find that the long run price and income elasticities are more price elastic than the short run both in industrial and residential consumption. In the third and last section, we compare two different forecasting models: the Hidden Markov Models (HMM) and the Holt Winters (H-W) seasonal smoothing method. Considering the Mean Absolute Percentage Error (MAPE), the HMM approach seems to show a superiority in forecasting the monthly electricity demand compared to the H-W methodology.

• Item Type: MPRA Paper
• Language: English
• Keywords: Electricity Demand, Price and Income Elasticity, Hidden Markov Models, Holt-Winters Seasonal Filter Smoothing
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q47 - Energy Forecasting; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R21 - Housing Demand

References

Ahlburg, D. A., "Error Measures and the Choice of a Forecast Method", International Journal of Forecasting, n. 1, vol. 8, pp 99-100, 1992.

Andrews D. Zivot E., "Further Evidence on the Great Crash, the Oil Price Shock, and the Unit-Root Hypothesis", Journal of Business and Economic Statistics, pp. 251-270, Vol. 10, 1992.

Armstrong J.S. and Collopy F, "Error Measures for Generalizing about Forecasting Methods: Empirical Comparisons" International Journal of Forecasting, vol. 8, 1992

Bernstein, M.A Griffin J., "Regional Differences in Price-Elasticity of demand for Energy", The Rand Corporation Technical Report, 2005.

Blazquez L., Boogen N., Filippini, M., "Residential Electricity Demand for Spain: New Empirical Evidence Using Aggregated Data", CEPE Working Paper, pp. 1-23, 2012.

Bohi D., Zimmerman M., "An Update on Econometric Studies of Energy Demand Behavior", Annal Review Energy, 119-39, 26, 1984.

Borenstein S., "To What Electricity Price Do Consumers Respond? Residential Demand Elasticity Under Increasing-Block Pricing", Working Paper - University of California, Berkeley, 2009.

Cipra. T., "Robust Exponential Smoothing", Journal of Forecast, vol 11, pp. 57-69, 1992.

Cipra. T., Romera. R., "Kalman Filter with Outliers and Missing Observations", Test vol. 6 n.2, pp. 379-395, 1997.

Clemente, J., Montanes, A., Reyes, M., "Testing for a Unit Root in Variables with a Double Change in the Mean," Economics Letters, Vol. 59, pp. 175-182, 1998.

Considine, J.T., "The Impacts of Weather Variations on Energy Demand and Carbon Emissions", Resource and Energy Economics, vol. 22, 295-314, 2000.

Dickey, D.A., Fuller, W.A., "Distribution of the Estimators for Autoregressive Time Series With a Unit Root", Journal of the American Statistical Association, pp. 427-431, Vol. 74, 1979.

Engle R.F. Granger C.W., Rice, John, Weiss, Andrew, "Semiparametric Estimates of the Relation betweenWeather and Electricity Sale", Journal of the American Statistical Association, n.394, vol. 81, pp. 310-320, 1986.

Erdogdu E., "Electricity Demand analysis Using Cointegration and ARIMA Modelling: A Case Study of Turkey", Energy Policy, n. 2, vol.35, pp.1129-1146, 2007.

Espey, J.A. Espey, M., "Turning on the Lights: A Meta Analsysis of Residential Electricity Demand Elasticities", Journal of Agricultural and Applied Economics, vol.36, pp. 65-81, 2004.

Fildes R., "The Evaluation of Extrapolative Forecasting Methods", International Journal of Forecasting, vol. 8 pp 88-98, 1992.

Filippini. M., "Swiss Residential Demand for Electricity by Time-of-Use", Resource and Energy Economics, n.3, vol.17, pp. 281-290, 1995.

Filippini. M., "Swiss Residential Demand for Electricity", Applied Economic Letters, n.8, vol.6, pp. 533-538, 1999.

Fruhwirth-Schnatter, S., "Finite Mixture and Markov Switching Models", Springer Series in Statistics, Springer, New York., 2006.

Garcia-Cerutti, L. Miguel, "Estimating Elasticities of Residential Energy Demand from Panel County Data Using Dynamic Random Variables Models with Heteroskedastic and Correlated Error Terms", Resource and Energy Economics, vol.22, pp.355-366, 2000.

Gelper S.E.C Fried R. Croux C., "Robust Forecasting with Exponential and Holt Winters Smoothing", Journal of Forecasting, vol. 29, pp. 285-300, 2010.

Ghysels, E., "On the Economics and Econometrics of Seasonality", in C.A Sims (ed.), Advances in Econometrics - Sixth World Congress of the Econometric Society," Cambridge University Press, Cambridge, 1994.

Goodwin P, Lawton R, "On the Asymmetry of the Symmetric MAPE", International Journal of Forecasting, vol.15 pp. 405-408, 1999.

Hamzacebi C., "Forecasting of Turkey's Net Electricity Energy Consumption on Sectoral Bases", Energy Policy, vol. 35, pp. 2009-2016, 2007.

Henley, A., Peirson, J, "Non-linearities in Electricity Demand and Temperature: Parametric versus non Parametric Methods" Oxford Bulletin of Economics and Statistics, vol. 59, pp. 1149-1162, 1997.

Henley, A., Peirson, J, "Residential Energy Demand and the Interaction of Price and Temperature: British experimental Evidence", Energy Economics, vol.20, pp. 157-171, 1998.

Holt C., "Forecasting Seasonals and Trends by Exponentially Weighted Moving Average", Office of Naval Research Memorandum, vol. 52, 1969.

Johnsen, Tor Arnt, "Demand, Generation and Price in the Norwegian Market for Electric Power" Energy Economics, vol. 23, pp. 227-251, 2001.

Labandiera, X., Labeaga Azcona, J., Rodriguez Mendez, M., "A Residential Energy Demand System for Spain" Energy Journal, vol. 27, pp. 87-112, 2006.

Labandiera, X., Labeaga Azcona, J., Rodriguez Mendez, M., "Estimation of Elasticity Price of Electricity with Incomplete Information" n.3 vol. 34, Energy Economics, 2012.

Langeheine, R., Van de Pol, F., "A Unifying Framework for Markov Modeling in Discrete Space and Discrete Time" Social Methods and Research, n.4, vol. 18, pp 416-441, 1990.

Lee. C. C. Chiu. Yi-Bin, "Electricity Demand Elasticities and Temperature", Australian Conference of Economists, 2011.

Kim, C.-J., "Dynamic Linear Models with Markov-switching", Journal of Econometrics, vol. 60, pp 1-22, 1994.

Miller, G. A., Chomsky, N., New York, Wiley, "Finitary models of language users" (chap 13), In R. Luce, R. R. Bush, E. Galanter (Eds.), Handbook of mathematical psychology, 1963.

Miller, E.K. Rainer, G., "Neural ensemble states in prefrontal cortex identified using a hidden Markov Model with a modified EM algorithm" Neuralcomputing, vol. 32-33, pp. 961-966, 2000.

Neeland H., "The Residential Demand for Electricity in the United States", Economic Analysis and Policy, n.2, vol. 39, 2009

Newbold P., "The Competition to End all Competitions" Journal of Forecasting, vol.2, pp. 276-279, 1983.

Pardo A. Meneu V. Valor E., "Temperature and Seasonality Infuences on Spanish Electricity Load", Energy Economics, vol.24, pp. 55-70, 2002.

Phillips P.C.B Perron P., "Testing for Unit Roots in Time Series Regression" Biometrika, vol.75, pp. 335-346, 1988.

Prais, S.J., Winstein, C.B., "Trend Estimators and Serial Correlation", Cowles commission discussion paper: statistics no. 1954.

Rabiner, L.R., "A tutorial on hidden Markov models and selected applications in speech recognition" Proceedings of IEEE, n. 2, vol.77, pp. 267-295, 1989.

Reiss. P.C., "Household Electricity Demand, Revisited", Review of Economic and Studies, vol.72, pp. 853-883, 2005.

Sailor, D.J., Munoz, J.R, "Sensitivity of Electricity and Natural Gas Consumption to climite in the U.S.A: Methodology and Results for Eight States" Energy, pp. 987-998, vol, 22, 1997.

Schmittmann, V. D., Visser, I., Raijmakers, M. E. J., "Multiple learning modes in the development of rule-based category-learning task performance", Neuropsychologi, n. 11, vol. 44, pp. 2079-2091, 2006.

Taylor J.W., "Short-term Electricity Demand Forecasting Using Double Seasonal Exponential Smoothing", Journal of the Operational Research Society, vol. 54, pp. 799-805, 2003.

Taylor. L., "The Demand for Electricity", Bell Journal of Economics, vol.6, pp. 71-110, 1975.

Thompson P.A., "A MSE statistic for comparing mean square forecast errors", Journal of Forecasting, vol. 6, pp. 219-227, 1990.

Valor, E., Meneu, V., Caselles, V., "Daily Air Temperature and Electricity Load in Spain", Journal of Applied Meteorology, vol.40, pp. 1413-1421, 2001.

Wickens, T. D., "Models for behavior: Stochastic processes in psychology" San Francisco: W. H. Freeman and Company., 1982.

Winters P., "Forecasting Sales by Exponentially Weighted Moving Averages" Management Science, vol. 6, pp.324-342, 1960.

Yan, Y.Y., "Climate and Residential Electricity Consumption in Hong Kong", Energy n. 1, vol 23. pp. 17-20, 1998.