1. Demand Elasticities of residential electricity demand in South Korea, 2003-2012 Yejin Keum* (Depart of Economics, Chungbuk National University)

2. I. Introduction II. Model specification and data III. Empirical results IV. Conclusion Index

3. I. Introduction The large-scale blackout in Korea on September 15, 2011. - By unexpected electricity demand increasing because of a heat waves, Electricity supply cut off to about 1.6 million households for over four hours. To make a stable energy policy, We need the accurate prediction of electricity demand. - A limit to existing energy policies for efficient energy demand management.

4. I. Introduction Country Observation period Price elasticityModel Degiades and Tsoulfidis (2008) The United State1965-2006Long run:1.07 Autoregressive distributed lag (ARDL) Pual et al.(2009)The United State1990-2006 Short run:0.05 Long run:0.14 Partial adjustment model Doowhan Won(2012)korea1965-2010 Short run:0.39 Long run:0.32 Error correction model (ECM) Seulye Im et al.(2013)Korea2012Short run:0.68Least Absolute Deviation (LAD) Hyunjin Lim et al.(2013)Korea1966-2011 Short run:0.32 Long run:1.07 Autoregressive distributed lag, Error correction model Okajima(2013)Japan1990-2007 Short run:0.39 Long run:0.48 the first-difference generalized me thods of moment (FD GMM) Table 1. Literature review

5. II. Model Specification and data Data * All the variables are log variables by estimating elasticities.

6. II. Model Specification and data Data Mean Std. dev. MinMax Data name (unit) sourcesvariable Electricity consumption (gwh) KEEI (Korea Energy Economics Institute) EC 3.034687.5587532.044.85 Electricity real price (won/kwh) KEPCOEP 35.19185.06737526.0692849.35179 Household income (million won) Statistics KoreaIC 124.22856.536467114.823135.5549 Index of aging (%) Statistics KoreaAG 11.110963.6990634.66188220.8883 Heating degree days (base : 18 ℃ ) Korea Meteorological Administration HDD 2391.358403.50031422.73357.1 Cooling degree days (base : 24 ℃ ) Korea Meteorological Administration CDD 138.333156.6661218.1317.8 Table 2. Descriptive statistics.

7. II. Model Specification and data Model Specification - Dynamic Panel GMM(generalized method of moment) : The consumption of the last period can affect the current consumption. - Obtain the consistence estimator : Using the first-difference model applied instrument variables.

8. III. Empirical results VARIABLES lnEC Constant 3.3473*** (0.366) ΔlnEC(t-1) 0.2874*** (0.080) ΔlnTD 0.1420*** (0.010) ΔlnIC 0.2435*** (0.051) ΔlnEP -0.5893*** (0.060) ΔlnAG -0.2031** (0.087) ΔlnCDD 0.0144*** (0.003) ΔlnHDD -0.0505*** (0.012) Observations 128 Number of cty_id 16 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 4. Empirical results. The coefficient of ΔlnEP : -0.589 increase in the electricity price of 1% lead to decrease in electricity consumption of 0.589% The coefficient of ΔlnIC is 0.244 growth in the income of 1% lead to increase in electricity consumption of 0.244% The coefficient of ΔlnAG is -0.203 increase in the aging of 1% lead to decrease in electricity consumption of 0.203% The coefficient of ΔlnCDD is 0.014 increase in the cooling degree days of 1% lead to increase in electricity consumption of 0.014% The coefficient of ΔlnHDD is -0.051 increase in the heating degree days of 1% lead to decrease in electricity consumption of 0.051% The coefficient of ΔlnTD is 0.142 Electricity consumption increase as time passes.

9. III. Empirical results price elasticities of residential electricity demand. - Short-run and long-run price elasticities of residential electricity consumption are inelastic. - The long-run elasticity of residential electricity demand is larger than short-run elasticity.

10. III. Empirical results Testing over-identifying restrictions Tests for first-order and second-order serial correlation - H0 : over-identifying restrictions are valid. - H0 : no serial autocorrelation. H0: overidentifying restrictions are valid chi2(35)15.85019 Prob > chi20.9978 OrderzProb > z 1-1.7350.0827 21.25570.2092 H0 : no autocorrelation do not reject the null hypothesis, so all instruments are valid. null is rejected for the first-order, but cannot be rejected for the second-order correlation.

11. IV. Conclusion 1.Price elasticities of residential electricity demand. - No significant changes in electricity consumption for the price change, because electricity is ‘a necessary.’ - The effect of the additional price charges for energy consumption reduction will be slight. 2. Population aging reduces residential electricity demands. 3. Increase in heating degree days lead to decrease in electricity consumption.