: 3 :2020,,,,,,2020 5000, : 20,10 %,,,,2008,,,, 30, 2020,,,(2005),,, (2008),,56 %,,, 2 ;2020 60 %,2. 5 1. 25,,,,,, 3,, :361005, :xphe2005 @yahoo. com. cn,xiyinglvm @126. com,jennifer2y2lin @hotmail. com, (08BJL050) 118
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
:,,,, ;,,,,,,, Galli (1998) 10, ( 3945 ) Kenneth (2001) 28 1978 1995,,,,,,, :,,;,Galli (1998) Kenneth (2001),,,, 1. (1) : GDP (,2003b) : (2003b),,,,,, : 70 %,60 %,,, GDP :, :,,,, 120
2009 1,,, (2), : Q t = f ( GDP t, CI t, S t, E t, P t ) (1), Q t,gdp, CI, S, E, P,1978 2006, (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, - 01182, - 01041) ( ) : Q = 01631 GDP + 11103 CI + 11701 S - 01182 E - 01041 P - 61756 (3) (01163) (01382) (01205) (01096) (01063) (3),1978 2006 GDP,,, 1170, GDP 1, 1170 ; 1, 1110 ; GDP 1, 0163 0118 5 % t 1 0104,,,,,,,: 121
: Q = 01563 GDP + 11205 CI (01096) (0121) (4) 1, 1 %, 1161 %, 1 % 1121 %, 0156,- 0117,,, 2 0146 %,, Granger, 5 %, Granger, + 11607 S - 01169 E - 61331 (01155) (01091) (4) ADF PP ADF PP ADF PP Q - 1. 3158-0. 5737-2. 9253-2. 2966-5. 1839 333-4. 5294 333 GDP - 3. 9488 33-2. 4042-3. 8750 33-2. 6605-4. 9034 333-4. 8656 333 CI - 4. 5333 333-1. 8833-3. 79860 33-3. 8678 33-9. 5052 333-9. 9337 333 S - 1. 5921-1. 9047-3. 2153 33-3. 2153 33-7. 2730 333-9. 5730 333 E - 1. 5217-1. 0299-2. 6456 3-2. 6125-6. 1662 333-7. 9454 333 P - 3. 7631 33-2. 2136-3. 1297-3. 1194-6. 5051 333-13. 7744 333 : 3 10 %, 33 5 %, 333 1 % Johansen Trace Max2Eigen 145. 6554 33 95. 7537 42. 3711 33 40. 0776 1 103. 2842 33 69. 8189 39. 9837 33 33. 8769 2 63. 3005 33 47. 8561 27. 0654 27. 5843 3 36. 2352 33 29. 7971 22. 2005 21. 1316 4 14. 0347 15. 4947 13. 2367 14. 2646 5 0. 7980 3. 8415 0. 7980 3. 8415 : 33 5 % ; :, ; :1 1 Granger 3 Q GDP CI S E P 1. 00000-0. 63147-1. 10349-1. 70053 0. 18179 0. 04119 (0. 16292) (0. 32846) (0. 20537) (0. 09627) (0. 06318) 2. 4,, F P Granger 41729 01020 Granger 21265 01127 ;,, - 29 ( ),,, 29 ( ) 4, 19 : ; ;, 1997,, 122
2009 1 ( ),, : (1), 1980 300, 2000 1000 :,, 2006,2175, 2288 1883 1763 ; GDP 13285 (2000 ), GDP 17178 9841 6496 (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 2 + 2 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
: 2000 2006 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 = 1513975 %,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,,
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 273131 4138, 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 = 1-1 2-2 (1) (11) + t t t P - 0. 028-1. 596-0. 037-1. 543-0. 660-2. 522 Y 2. 616 2. 955 2. 156 3. 916 2. 523 1. 302 Y2-0. 099-2. 851-0. 079-3. 359-0. 081-0. 813 POPU 0. 201 2. 727 0. 215 2. 388 0. 217 2. 327 ZGY 0. 159 1. 267 0. 292 1. 978 0. 485 2. 042 EC( - 1) 0. 225 0. 713 0. 242 0. 832-0. 019-0. 091 P - 0. 055-0. 049-0. 521 Y 3. 042 2. 843 4. 471 Y2-0. 115-0. 104-0. 191 POPU 0. 334 0. 283 0. 255 ZGY 0. 276 0. 385 0. 410 Adjusted R 2 0. 992 0. 994 0. 990 :t, (+ ) Y, 5 %,Y, Eviews610 (10),,(2SLS), GDP 5 R 2,,,, > 1,< 0,U :,,,,,, 125
:,,, : GDP :,,,, U GDP,,, GDP 567788, 2006 GDP 13285 (2000 ), :,, ;,,,, :,, ( ), GDP 7293, 1999 GDP,,, ( ) 1. GDP, GDP,2006 43 %, 61 %78 %2006 43 %,2020 60 % GDP 2010 2020 45130 % 44132 %,( 6) 2. 7,,2020 5583 5191 4824 ( ),5,,, :, 2010 43 %,2020 52 % 2010 2006,,2020 60 % 2001 8 25 (2001 8 ) :GDP 2010 2020 5115 % 50 %, 88164 %, GDP 2007 7 11 :2010, 1316 ;2020, 1415 126
2009 1 1. GDP :GDP 6 2008 2010 2011 2015 2016 2020 10 % 9 % 8 %, GDP 9 % 8 % 7 % GDP 8 % 7 % 6 % UR 2. 26 % 2. 26 % 2. 26 %, S 1. 13 % - 0. 22 % - 0. 22 % E 3. 0 % 2. 8 % 2. 6 % : 7 2010 2020, 1991 54 % 2006 70 %, 2007 8 2010 70 % 2011 2020 65 % : ( ) ( %) 2010 42331 41470 40618 2008 2010 9. 82 9. 25 8. 69 2015 59253 56560 53967 2011 2015 6. 96 6. 4 5. 85 2020 80947 75273 69948 2016 2020 6. 44 5. 88 5. 32 ( ) ( ) 2015 13. 9 4220 4028 3844 2020 14. 5 5583 5191 4824 :, 1,0, 2007,, :,1980 2006, GDP (813 %) 117 %, GDP 1 %, 015,0105 :,, 5,GDP, 0105 :,1980 2006, GDP 115, 5,, 75 % ;, 10, GDP 110 %, 0105,0110 2. 9,2020 GDP 34827 (2000 ),4850,2020,GDP, ;GDP, 2020 2020 127
: 1415,, 2020 1014 2181 1129,, 2020, (5096 Π ) ( ) 10, () 2020 2020,5191,4850,5096 5000, 4 %,2020 5000 6000 50 70 80 60 80 90, 2020 9 5000, 70 70 90 90 10 2200 5000, GDP ( ) GDP( ) ( ) ( ) 2015 25596 3800 35971 18961 11505 4139 3517 3516 2020 34827 4850 51290 25800 14932 5338 4444 4567 10 12 2020 ( ) 70322 73894 75273 14 2020 ( ) 4850 5096 5191, 19 5000-310 % + 1192 % + 318 %, 14 20,, 2006 43 %, 61 % 78 %, ( ), 2020,3 ( ) 315 4,,,2006, 515 % GDP, 30 % 54 %, 2000 2007, 11 %,, 2006,, 72 % 19 % 9 % 2006 2175kWh ;2007,2007 32632, 132129,2007 2470kWhΠ 128
2009 1,(),,, FT,2009, 17 %,,,, 2020 3,, 2003 2007,,,,?,,, 2020,,2020 5000,2007 2020 6 %,,, U,;,-, U,, U,, U,,,,, ; ( ),,,,,,,,,,,,,,,,, 12 ( 2020 ), 129
:,2006 :,,,1982 :,,,2003a : :,11,2003b : :,5,2005 : 2005210216,http :ΠΠwww. 21page. netπhtmlπ2005210218π17393. htm,2008 :, 21 2008211217, http :ΠΠopinion. hexun. comπ2008211215π 111259680. 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 : 47 54. Isabelle Larivi re, Ga? tan Lafrance,1999, Modelling the Electricity Consumption of Cities : Effect of Urban Density, Energy Economics, Vol. 21, Issue 1, Feb., PP53 66. 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) : 29 57. 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., PP493 513. Kraft, J., Kraft, A., 1978, On the Relationship between Energy and GNP, Journal of Energy and Development 3, 401 403. 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,Q43 130 ( : ) (: )