1. 1 ECONOMIC REGULATORS CONFERENCE NERSA & TIPS AUGUST 2012 The sensitivity of the South African industrial sector’s electricity consumption to electricity price fluctuations Dr Roula Inglesi-Lotz

2. 2 Structure of presentation Introduction Motivation Purpose Methodology Data Results Conclusion

3. Introduction In South Africa, choosing the correct and appropriate electricity price regime has been an issue for discussion during the last decade. Imperative for the policy makers to be able to understand and in a way, “predict” the reactions of consumers to price changes. 3

4. Introduction (2) Different price structures as well as different electricity profiles are the main reasons why different economic sectors should be examined separately and treated accordingly. The South African industrial sector is responsible for an average of approximately 58% of the total electricity consumption, making this sector one of the most important ones from an energy consumption point of view. 4

5. Motivation Inglesi-Lotz and Blignaut (2011) found out that among various economic sectors such as agriculture and transport, the industrial sector was the only one whose electricity consumption behaviour was found sensitive to price fluctuations on average during the period 1993 to 2006. Inglesi-Lotz (2011) found out that the sensitivity of electricity consumption to price fluctuations changes over time by using the Kalman filter econometric methodology for the period 1970 to 2007 5

6. Purpose This paper proposes that the sensitivity of the industrial sector’s electricity consumption to price fluctuations (price elasticity) has been changing through the years. The purpose of this paper is to estimate the time- varying sensitivity of the industrial sector’s electricity consumption to price changes by using the Kalman filter econometric methodology for the period 1970 to 2007. 6

7. Literature AuthorsYearCountry/regionSectorPrice elasticity Pindcyck1979Group of countries Industrial & Commercial -0.07 to -0.16 Lynk1989UKIndustrial-0.69 Caloghirou et al.1997GreeceIndustrial-0.90 Beenstock et al.1999IsraelIndustrial0.123 Hunt et al.2003UKManufacturing -0.20 Kamerchen, Porter2004OmanIndustrial-0.34 to -0.55 Dimitropoulos et al.2005UKManufacturing-0.159 Roy et al.2006Country panelIndustrial-0.80 to -1.76 Enevoldsen et al.2007 Denmark, Norway and Sweden Industrial-0.35 to -0.44 Agnolucci2007UKIndustrial-0.60 Agnolucci2009UK and GermanyIndustrial-0.64 Inglesi-Lotz and Blignaut 2011South AfricaIndustrial-0.869 He et al.2011China Industrial & Commercial -0.018 7

8. Literature (2) 8 South Africa (Industrial sector) –Inglesi-Lotz and Blignaut (2011): Estimating the price elasticity of demand for electricity by sector in South Africa. –Ziramba (2009): Disaggregate energy consumption and industrial production in South Africa. –Inglesi-Lotz and Blignaut (2011): South Africa’s electricity consumption: A sectoral decomposition analysis

9. Methodology 1.Hansen test for stability of parameters Testing whether the coefficients are statistically varying over time or not. 2.Kalman filter estimation Estimating the equation with the assumption of time-varying coefficients (from Hansen test). 9

10. Methodology 10

11. Methodology 11

12. Methodology 12

13. Data 13

14. Data (2) VariableSourceUnits Industrial electricity consumption (cons) National Energy council and Energy Balances (DoE) kWh Average electricity price for the industry (p) Energy price report (DoE)c/kWh Real output of the industrial sector (y) QuantecConstant 2005 prices ZAR Employment of the industrial sector (n) Quantecnumber 14

15. Results Lc statistic p-valueConclusion ly, ln0.192>0.2 The null hypothesis (H 0 : parameter stability) cannot be rejected  the parameters are constant Lp0.4000.077The null hypothesis (H 0 : parameter stability) can be rejected  the parameter is not constant 15 Hansen test results

16. Results (2) 16 Kalman filter results SSpace model Sample 1976-2007 Included observations 32 Number of iterations to convergence 9 Variables Estimated coefficientsp-values c(1) (output coefficient) 0.6900.000 c(2) (employment coefficient) 0.2520.061 c(3) -4.0650.000 Final statep-values sv1 (price coefficient) -0.9520.000

17. Results (3) 17 Kalman filter results

18. Conclusion The findings of the exercise show that indeed price sensitivity changed since the 1970s: it has decreased in absolute values from -1 in 1980 to -0.953 in 1990. Since then, the elasticity stabilised around -0.95 showing that the industrial sector has experienced an inelastic demand. In other words, the behaviour of the industrial consumers did not vary significantly in the 2000s. Sensitivity of consumers to price fluctuations becomes smaller in absolute terms while the real prices of electricity declined over the last half of the sample examined. 18

19. Conclusion (2) As the prices increase, probably reaching the levels of the 1970s or even before, the industrial sector’s behaviour might change and the elasticity might end up at levels higher than one (elastic). Although, the price elasticity of electricity consumption is high, the historically low level of electricity prices was a factor for the unchanged sensitivity of the industrial sector in the last decade. This low level of prices is indicative made the electricity costs of the economy to contribute little in the total cost of operation of all the economic sectors. 19

20. Thank you for your time and attention Dr Roula Inglesi-Lotz roula.inglesi-lotz@up.ac.za Department of Economics University of Pretoria 20