2009 1,,,,,,,,,,,,,,,,, ;,,, ;,,:, (),, ;,,,,,, ;,,,,, (AR) (MR) (ARMA) (ARIMA),,Granger ( ECM) Kraft (1978) GNP,Silk Joutz (1997),Shiu (2004),, :,,Bu

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1 : 3 :2020,,,,,, , : 20,10 %,,,,2008,,,, 30, 2020,,,(2005),,, (2008),,56 %,,, 2 ; %, ,,,,,, 3,, :361005, com. com, (08BJL050) 118

2 2009 1,,,,,,,,,,,,,,,,, ;,,, ;,,:, (),, ;,,,,,, ;,,,,, (AR) (MR) (ARMA) (ARIMA),,Granger ( ECM) Kraft (1978) GNP,Silk Joutz (1997),Shiu (2004),, :,,Burney (1995), Lariviere Lafrance (1999), Holtedal Joutz (2004), (2003a,2003b),,GDP,,,,,, 119

3 :,,,, ;,,,,,,, Galli (1998) 10, ( 3945 ) Kenneth (2001) ,,,,,,, :,,;,Galli (1998) Kenneth (2001),,,, 1. (1) : GDP (,2003b) : (2003b),,,,,, : 70 %,60 %,,, GDP :, :,,,, 120

4 2009 1,,, (2), : Q t = f ( GDP t, CI t, S t, E t, P t ) (1), Q t,gdp, CI, S, E, P, , (3) :ADF PP, ADF ( PP ) >, H0 :, ; ADF (PP ) <, H0, : Y t, X t,,i (1) Y t - X t, I (0), Y t X t, E2G Johansen, Johansen Johansen : trace max max max : max ( r, r + 1) = - T 3 LN (1 - r+1 ) (2) H0 :r, H1 : r + 1 max, r, max, q, q, max ( r, r + 1), max ( r + 1, r + 2), max ( r + 2, r + 3) Johansen 1 2 :, ADF PP, 1 %, I(2), Max2Eigen ( 2), 5 %,,, : = (110,01631,11103,11701, , ) ( ) : Q = GDP CI S E P (3) (01163) (01382) (01205) (01096) (01063) (3), GDP,,, 1170, GDP 1, 1170 ; 1, 1110 ; GDP 1, % t ,,,,,,,: 121

5 : Q = GDP CI (01096) (0121) (4) 1, 1 %, 1161 %, 1 % 1121 %, 0156,- 0117,,, %,, Granger, 5 %, Granger, S E (01155) (01091) (4) ADF PP ADF PP ADF PP Q GDP CI S E P : 3 10 %, 33 5 %, % Johansen Trace Max2Eigen : 33 5 % ; :, ; :1 1 Granger 3 Q GDP CI S E P ( ) ( ) ( ) ( ) ( ) 2. 4,, F P Granger Granger ;,, - 29 ( ),,, 29 ( ) 4, 19 : ; ;, 1997,, 122

6 ( ),, : (1), , :,, 2006,2175, ; GDP (2000 ), GDP (2) Kenneth(2001),, : : ec 3 t = A P b 1 t y b 2 + b 3 ln y t t (5),A, ec t P t y t, 3 (5) : ln ec 3 t, i = a i, j + b 1 ln P t, i + b 2 ln y t, i + b 3 (ln y t, i ) 2 (6) (6), Galli (1998) Kenneth (2001), Kenneth (2001) :,,: ln ec t, i - ln ec t - 1, i = (ln ec 3 t, i - ln ec t - 1, i ) (7) ln ec t, i = a i, j + 1 ln P t, i + 2 ln y t, i + 3 (ln y t, i ) 2 + (1 - ) ln ec t - 1, i + t (8), b k = k Π, k = 1,2,3 (6) (8) (6),b b 3 ln y t, j ( ) ( b 2-1) + 2 b 3 ln y t, j b 2, b 3 b 2 > 1, b 3 > 0, ;b 2 > 1, b 3 < 0,,,U, 0,, y t, j = exp ( - b 2 Π2 b 3 ) ;1,, y t, j = exp ( (1 - b 2 )Π2 b 3 ) Kenneth (2001) (6) (8),, :,,,: ln ec 3 t, i = a i, j + b 1 ln P t, i + b 2 ln y t, i + b 3 (ln y t, i ) 2 + b 4 ln popu t, i + b 5 ln zgy t, i (9) ln ec t, i = a i, j + b 1 ln P t, i + b 2 ln y t, i + b 3 (ln y t, i ) 2 + b 4 ln popu t, i + b 5 ln zgy t, i + b 6 ln ec t, i - 1, ec ti, popu ti zgy ti, P ti, y ti (3) (10) 123

7 : GDP ; ; ;, :,,,,;,,,,,,,,, (),, 5,,: Π, GDP GDP 2000 (4),,,, (OLS),,, (Analysis of covariance) : H 1 :, ; H 2 :, OLS1 2, : S 1 = 0135, S 2 = 01370, S 3 = %,F, F 2 > 1169, F (162,28) = 1169, F 1 < 1172, F(135,128) = 1172,H 2,H 1,, H 1, ( Random Effects) (Fixed Effects),,,,,, 124,,

8 2009 1,Greene (1997) : Hausman (1978) ( Hausman test) Breush2Pagan (1980) (LM test) Breush2Pagan H 0 : 2 u = 0 Cov[ it, is ] = 0, t s, H 1 : 2 u 0, LM,,LM 1 2 : LM = nt 2 ( T - 1) e it OLS 5 LM, H 0,, Breush2Pagan, (9) (10) OLS LM , 95 % 2 (1) 3184,, ( Wooldridge Test),,, (Cross section weights) n 2 e it i = 1 n T t = 1 T e 2 it i = 1 t = (1) (11) + t t t P Y Y POPU ZGY EC( - 1) P Y Y POPU ZGY Adjusted R :t, (+ ) Y, 5 %,Y, Eviews610 (10),,(2SLS), GDP 5 R 2,,,, > 1,< 0,U :,,,,,, 125

9 :,,, : GDP :,,,, U GDP,,, GDP , 2006 GDP (2000 ), :,, ;,,,, :,, ( ), GDP 7293, 1999 GDP,,, ( ) 1. GDP, GDP, %, 61 %78 % %, % GDP % %,( 6) 2. 7,, ( ),5,,, :, %, % ,, % ( ) :GDP % 50 %, %, GDP :2010, 1316 ;2020,

10 GDP :GDP % 9 % 8 %, GDP 9 % 8 % 7 % GDP 8 % 7 % 6 % UR % % %, S % % % E 3. 0 % 2. 8 % 2. 6 % : , % %, % % : ( ) ( %) ( ) ( ) :, 1,0, 2007,, :, , GDP (813 %) 117 %, GDP 1 %, 015,0105 :,, 5,GDP, 0105 :, , GDP 115, 5,, 75 % ;, 10, GDP 110 %, 0105, ,2020 GDP (2000 ),4850,2020,GDP, ;GDP,

11 : 1415,, ,, 2020, (5096 Π ) ( ) 10, () ,5191,4850, , 4 %, , , , GDP ( ) GDP( ) ( ) ( ) ( ) ( ) , % % %, 14 20,, %, 61 % 78 %, ( ), 2020,3 ( ) 315 4,,,2006, 515 % GDP, 30 % 54 %, , 11 %,, 2006,, 72 % 19 % 9 % kWh ;2007, , , kWhΠ 128

12 2009 1,(),,, FT,2009, 17 %,,,, ,, ,,,,?,,, 2020,, , %,,, U,;,-, U,, U,, U,,,,, ; ( ),,,,,,,,,,,,,,,,, 12 ( 2020 ), 129

13 :,2006 :,,,1982 :,,,2003a : :,11,2003b : :,5,2005 : ,http :ΠΠwww. 21page. netπhtmlπ π htm,2008 :, , http :ΠΠopinion. hexun. comπ π html,2006 :,,,1992 :,,,2007 : ( ) (Wooldridge, J. M.,Econometric Analysis of Cross Section and Panel Data), Alice Shiu, Pun, Lee Lam, 2004, Electricity Consumption and Economic Growth in China, Energy Policy, 32 : Isabelle Larivi re, Ga? tan Lafrance,1999, Modelling the Electricity Consumption of Cities : Effect of Urban Density, Energy Economics, Vol. 21, Issue 1, Feb., PP Judson, Ruth A.,Richard Schmalensee and Thomas M. Stoker,1999, Economic Development and the Structure of the Demand for Commercial Energy. Energy Journal 20 (2) : Julian I. Silk, Frederick L. Joutz,1997, Short and Long2run Elasticities in US Residential Electricity Demand : A Co2integration Approach, Energy Economics, Vol. 19, Issue 4, Oct., PP Kraft, J., Kraft, A., 1978, On the Relationship between Energy and GNP, Journal of Energy and Development 3, Kenneth B Medlock III ; Ronald Soligo, 2001, Economic Development and End2Use Energy Demand, Energy Journal, Vol, 22, No. 2. Rossana Galli, 1998, The Relationship between Energy Intensity and Income Levels : Forecasting Long Term Energy Demand in Asian Emerging Countries, Energy Journal ; 19, 4 ; p. 85. William H. Greene, 1997, Econometric Analysis (Third Edition), Prentice Hall, Upper Saddle River, New Jersey. China s Electricity Demand Forecast under Urbanization Process He Xiaoping,Liu Xiying and Lin Yanping (China Center for Energy Economics Research, Xiamen University) Abstract :The rapid urbanization process in China will likely end in 2020 and China will then become a middle income country. Previous studies in related literature on electricity demand gave no consideration on the role of urbanization process. To obtain reliable China s power demand forecast, we for the first time introduce factor of urbanization into the models of electricity demand and use the methods of co2integration analysis and nonlinear regression applying to panel data. The results from both approaches are consistent and in fact, very close. The results of both methods indicate that there exists a significant correlation between the electricity demand and urbanization. We found that the recent rapid growth of electricity demand in China comes mainly from its accelerating process of urbanization and the industrialization that required in a rapid urbanization process. According to our demand forecasting, the electricity consumption in China will still be increasing significantly and the per capita consumption in 2020 will be about 5000 kwh. In its urbanization process, China s electricity demand will have some similar characteristics as those once appeared in their urbanization processes of other developed countries. Key Words : Electricity Demand ; Urbanization ; Industrialization JEL Classification :O18,Q ( : ) (: )

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(),,,,;, , (Π, ), , , 5162 %, U , ,,1992, , : ; : 3 :,,,,,, : : 1992 6,,1992 2003, 8156 %,,: (1) ; (2) () ; (3),, (1994) (2004) 267, (2004), (2005) (2005),1992 2002,,,,,, :, ;; 3,, : gunaihua @126. com ;,, :510275, :lijf @scnu. edu. cn ( :05BJL015)