32«4ByÁ 2012 7 pp. 233 ~ 242 œ w w w y œ r Estimation of Domestic Water Supply Benefit Using Demand Function Approach ³ Á Á½¼yÁ Yeo, Kyu DongÁYi, Choong SungÁKim, Gil HoÁLee, Sang Won Abstract In the past, the domestic water supply benefit of dam has been estimated by replacement dam cost approach. But it is logically inappropriate that we use the second priority dam as a replaced facility. Therefore, this study aims to suggest the estimation method of the domestic water supply benefit by using demand function, which is deduced from Willingness-To-Pay (WTP) of consumers. For this purpose, a survey concerning the marginal WTP is carried out according to the change of water use amount used, targeted 1,000 households in metropolitan area. And by using the marginal WPT, we estimated the demand function of a family. Finally, the monthly benefit equation is derived. The approach is demonstrated and discussed for an example, the Song-Li-Won dam project which is now renamed Young-Ju dam. From the example study, the total benefit for the durable years (50 years), was about 90 billion won. The method proposed herein is expected to be practical and useful in the economic analysis of the domestic water supply project including dam construction, as well as in further studies. Keywords : domestic water supply benefit, demand function, willingness-to-pay, economic analysis» y œ r w. ù w 2 w w. y œ z w z d wš, w w r w. w «1,000ƒ y y w w d w. š w w ƒ w wš, œ w s³ r w. m w (x ) w., ü 50 r 900. wz, w y œ y ƒ w». w : y œ r, w,, 1. œ, y n m w 2006 l 2009 ¾ s³ 2, š w j. w n z r k z sƒw k w w. ù» z zz (social welfare) w d œ d, š ƒed š w y š». wr, r w r w z ƒeƒ w d w wù, w» y œ ƒ e w w š. ƒ m š» š, k sƒ z (replacement cost approach) w». ù d y œ d t, w ƒ zz w. y œ w r w w. y w (demand function) z Á w w z» lœw (E-mail : yeokd94@gmail.com) z Á Áw œ» l Áœw (E-mail : sung@kwater.or.kr) z Á w w z» lœw (E-mail : kgh0518@gmail.com) w w w Á w (E-mail : swlee@inha.ac.kr) 32«4By 2012 7 233
d w w w ƒ k (price elasticity) w. r,» (1987) ƒ ƒ (+), ƒ ( ) ƒ x, p ƒ y. ½ (1991) Cobb-Douglas w ƒ w z, Translog x z w y w w. ½Ÿ (1996), yww yw x w š y w ƒ,, k, œœ w ƒƒ w w. w œ (1998) y w w Á» k, m (2001) ü x(lagged endogenous variable model) w w w w. ½ k (2001) y w ³ w -ARIMA x, w œ z (cointegration regression analysis) yw x, š mw SUR(Seemingly Unrelated Regression) x w w. (2004) - w w w w e» q z wš, x mw y wz y dw. (2004) š z x w w ƒ k w. z Ÿ (2006) 11 y w ƒ k ƒe w. y (2007) ƒ ƒ w mw w. z(2010) w mw y w ƒ e w. ƒ k k š w w ƒ w. Howe and Linaweaver(1967) y dw š, z Morgan and Smolen(1976), Foster and Beattie(1979; 1981), Billings and Agthe(1980) ƒ t ƒ k ƒ. Renzetti(1992) eù z w y œ s³ƒ w w š, w w w. Espey et al.(1997) y ƒ k w» k ww,,»z, ƒ zá w w e,, ƒ,» w e w. Dalhuisen et al.(2001) k mw y ƒ k y w» w. wr ƒ w y ƒ ù ƒ w dw w (Zhou and Tol, 2005; Bithas and Stoforos, 2006; Bartczak et al.). ü ƒ ù,» z d ù ƒ z w ƒ k.» (raw water)» œ wì y r ƒœ w., y (WTP: Willingness To Pay) š (compensated demand curve) wš, w. w d œ d w w» wš, zz w œœ z sƒ w. w w y r wš, y ù ü (x ) y œ r w. 2. 2.1 y œ r w y ƒ x ü œ y ƒ œœ» š. y ƒ w ƒƒ û k š ƒ w œ š. x ƒ y w wš ƒ w r ƒ w. ƒ y w y y r j ƒ w, s³ w, vw w w, w w w. 4ƒ ƒ w w w œ w ww ƒ w. œ d, ƒ r ƒ j ƒ. w, œ q w ƒ œ r Ár ƒ. s ³ w yƒ ƒ d ƒ w ù, s³ ƒ 419 /m 3 (y, 2006) ƒ 704.4 e w w ƒ wš š» ƒ. w, x y t w w w d ƒ». vww w y œ r w ù œ w w vw l š ƒ w w. ù ¾ ù y œ w vw ƒ ù w x w. w d z w w w l 234
(consumer surplus) wš y r. y r w x j 4ƒ ³ w, ƒ ƒ š w w ƒ w š x w l y r wš w. 2.2 w w d z w w w l w (CS) y r. ù ƒ w m w ƒ y z ƒ sw (Marshall) z wš» yw z y d w w ƒ., (Hicks) z w w z w w z y yw d w. y w w w wš w. y ƒ w, y ƒ w w. y w ƒ ùkü w š w š w y» w w ƒ ƒ w w w r ( z Ÿ, 2006). ü š ùkü 1 mw r, ƒ P š Q, ƒ Q j w r š ýacqo. w, š ýacqo ýpcqo ÿapc ƒ, w ƒ w r w. x w y l w w. ù ù œ œ œ w ƒ» w ƒ š w. w w ƒ (shadow price) w w, ƒ š»z, w z 1. Demand Function and Consumer Surplus ƒe w ƒ š w (½, 2004). y sƒw w x y (revealed preference method) ƒ y mw w y (stated preference method). w (TCM: Travel Cost Method) x y w, k y ƒed (CVM: Contingent Valuation Method) t y. t y CVM w zz y w ƒe, ñ ü., w ö z ƒ j»é w r. ù y œ r z y y q w w. ƒ w w š». w w mw y d w w. ü w ƒ w w y w w ü w w. 3. y w 3.1 y d w y w w w y w ö z w w.õ k w w e Á ( 5q)Ö(w, 2008) x r» w e d w x w 250~500, s x w 500~1,000 t e wš. šw 1000 t w š, Á» t w. ù tw w w t w w. «w w, ù 40% wš w «ù w tw š q w». t 1 x ƒ d w š. x w w ƒ w» ù j r. mw w w ƒ š y, w š s³, s³, w s, y, ù œ e w 32«4By 2012 7 235
t 1. y d w w 1. x s³ ƒ ƒ 1,000 l(2 l rp 500 ) 419. ƒ y w, w ƒ wƒ ƒw e ù ƒ ¾? eƒ eƒ eƒ eƒ û * 2. ƒw e ƒ w ù ¾? 3. wƒ w e ƒƒ ƒ w s³ % ¾? 10%, 20%, 50%, 100% w ƒƒ w. e x ( )% w 10% 95% 90% 85% 80% 75% 70% 65% 60% 20% 95% 90% 85% 80% 75% 70% 65% 60% 50% 95% 90% 85% 80% 75% 70% 65% 60% 100% 95% 90% 85% 80% 75% 70% 65% 60% * ƒeƒ x ƒ û ƒ ù w ƒ w» w, û v e w. t 1 w s w w (1 m 3 ) ƒ w w w y ƒe ƒ w w. w Ñ ƒe w w w ƒe d w. w y d w» w w» w ƒ y w. ƒ e» w ƒ w ü š w š, ƒ k š xk. v w ƒ k û v w j w k. w y ƒ k w». ù w w w ƒ w, w ƒ ƒ w ƒ w. p w m ƒ û ù w. ƒ w ù y ƒ k 0.229~1.064,»» w k ùkùš. w w y ƒ k w š š ( v, 2003). 3.2 w w t 1 w w ƒ k w» w ƒƒ w ƒƒ 10%, 20%, 50%, 100% 2. WTP w š 3. w w ƒ d w. mw 1,000 l z w (t 1 1 2 ), ƒ w 762 236
k w w. wr, d 2» 5 œw. x ƒ wš y w 2 š a ùký, x 10%, 20%, 50%, 100% w ƒƒ b, c, d, e ùký. d 3 w w, s l w w x w y w w. 3.3 y w 3.3.1 k w x w» w k., x mw wš w wš w e kw w. w xk wš w e w. ù y r w š, w x w w r d ƒ ( ) ( ) w. ƒ sƒw ƒe sƒ w ƒ, ½y (2008) ƒ 1 1 ƒ ƒw ƒ w ùk ùš š w ƒ w. wr, xk w w š w ù, xk w j ƒ š w e w j q w ƒ ƒ w w. 3.3.2 w w w w š w ù, 2 w ƒ ùkü w z e w. w w xk (1) xxk w š w, w t 2. P = β 0 + β 1 Q + β 2 I + β 3 F + ε», P y 1 ƒ ( /m 3 / ), Q 1 s³ y (m 3 / / ), I 1 s³ ( ), F ƒ ƒ. t 2 ùkù, x w x F- ƒ»ƒ j β 2 wš t- ƒ»ƒw. Q β 1 y ùkü e w. ƒ (1) t 2. y w t t-value P-Value β 0 512.261 12.064 42.461 0.000 Q β 1-2.712 0.260-10.437 0.000 I β 2 0.003 0.006 0.450 0.652 F β 3-64.694 2.191-29.534 0.000 F-Statistic 469.065 0.000 t 3. w y w t t-value P-Value β 0 516.336 7.977 64.724 0.000 Q β 1-2.716 0.260-10.459 0.000 F β 2-65.137 1.957-33.277 0.000 F-Statistic 706.643 0.000 F β 3 y ùkü Q ƒ w., ƒ ƒ ƒw 1 w. ƒ ü ƒ w» w y ƒ ùkü ½y (2008) d mw ww ew. I β 2 2 w x ƒ w w ùkû., x ƒ wš ƒ ƒ ƒ ƒw w ùkü, ƒ w š w w.» k ƒ w e w w ƒ q. t 2 x w x w (2) w w. x t 3 ùkù. P = 516.336 2.716Q 65.137F 3.3.3 w w y œ r w l y œ r w» w (individual demand) (market demand) w w. ƒ w, ƒ w w. w (2) y k w w w w. w r š l š w w. x z x w (2) w w š yw. w ƒ y œ r (3) w Q w w w., y œ r B 4 ùkù œ z CS 1 P 1 Q 1 w (2) 32«4By 2012 7 237
4. w y œ r œ CS 0 P 0 Q 0 w w, š Q 0 Q 1 ¾ w w. w 1 w w r w w. Q 1 B = ( CS 1 + P 1 Q 1 ) ( CS 0 + P 0 Q 0 ) = PdQ (3) Q 0 (3) ƒw r ùkü. ù ù Ÿ œ ƒ t w. t ù w ³ w» w. y w w y ƒƒ ƒ d t w. w r w ƒ d š w w. ƒ d w y j y œ r ƒ d ƒ ƒ ù ƒw. ƒ w r ƒ w ƒ ö z ƒ r w, œ d ƒ w. ƒ š ùkù., ƒ w r y ƒ r w, œ d ƒ w. 5 r ùküš. ƒ d š D x w y ƒ P 0 š Q 0 š w y Q 1 ƒ r Q 0 Q 1 š w., ƒ d š D x w y ƒ P 0 w w ƒ w š D' s w w r Q 0 Q 0 ' š w. r ƒ ww w. w ƒ ƒ w š D' 0 Q 1 ' š D 0 Q 0 w., ü x y r w. w y œ w s³ r B (4.5) w. Q 1 B = F N ( β + 1 β 1 Q + β 2 F) dq F N ( β + 0 β 1 Q + β 2 F) dq 0 0 = F 5. w w y œ r N ( β 2 + ( 1 β + 1 β 2 F)Q ) 1 ( )Q 1 2 2 N ( β 2 1 )Q + ( 0 β + 0 β 2 F)Q 0 ( ) β 0 = 516.336, β 2 = 2.716, β 2 = 65.137 Q 0 = q 0 0.001 30days Q 1 = q 1 0.001 30days», N œ t, N», F s³ ƒ, Q 0 Q 1 ƒƒ» t 1 s³ y (m 3 / / ), q 0 q 1 ƒƒ» t 1 1 (lpcd). 4. 4.1 w w y œ r w w w» œ t š w mw wš v w ƒ œ w w. w wš w. w w x ù ü (x ) ù w» w y ù ü y w, (,, ) œ. y w œ w z. w Õ k š Ö Q 0 (4) 238
( m Áw œ, 2004) k w x ü ƒ. wr, w w «w, w ew w e. w z w œ». ù w w 3 w «ù tw w š ƒ w, «. w y ƒ w ùkù z w» w. x (2003)ƒ û» s w w w, 2001 ƒw w xw û w ƒ ùkû. û s s³» w (, 2006). œ w w ù y ( ) ƒe ƒ. 4.2» xy» (2003 ) t (2016 ) œ z w w. t 4 Õ k š Ö x z w» t w. w ƒ ƒ» z z w w. wr, t y w w œ, Ÿ,, œw y sw»k e ƒ z z ƒ w ƒ w w. z ƒ š w»k w ƒ š w. t ƒ sww š w.õ k š Ö w»k ƒ ùkü.»k ƒ» ƒ ƒ t w» t 4.,,»k, ƒ 2001 2006 2011 2016 ( t ) ( ) 309,418 292,000 273,200 256,500 (%) 62.2 76.9 82.2 85.4»k (m 3 / ) 4,460 4,510 4,510 ƒ (m 3 / ) 4,500 7,900 11,400 1 1 (lpcd) 295 334 359 371 yw z, t 1 1 ù w. 1 1 w š w, lpcd t y w ùkü y w w. w z(y, 2007) s³ xy e šw. t 2016 e 2015 (84.3%) w. 2001 z, m (y, 2002), 2006 z z 2006 z Ÿ œ» z( m, 2004) šw, 2006 z w. ƒ w š (4) y r w w s³ƒ w. s³ƒ 5 k y w, Á k š (m, 2000) ƒ r /ƒ ƒ ( ƒ ) šw, s³ ƒ ƒƒ 2.9, 2.7. t ƒ w œ j y œ w r w. (4) w r t œ w w r w. œ (5) w. t œ (%)= t w y œ -------------------------------------------------------------------------------------------------------- (5) ( t» ) (5) t» w 1 1 w w, t w y œ w w., t y œ w y w z, w y œ w w. w t ¾ y œ y z w w. 4.3 w œ» mw r w» w y w w. t 5 k y w. z,, 1 1,,»k ƒ (»k+ ƒ ) w ƒ x w. w r w. y œ r œ l w ƒ r ƒw ƒ t 2016 z l w. y w» 2003 r 2011 z 32«4By 2012 7 239
03 (» ) z ( ) (%) 1 1 (lpcd) (%)»k ƒ ƒ y y (+) t 5. y ( : m 3 / ) 04 05 06 07 08 09 10 11 ( œ) 12 13 14 15 16 ( t) 128,924 127,383125,841124,300123,320122,340121,360120,380 119,400 118,320 117,240 116,160 115,080 114,000 122,277 120,751 119,226 117,700 116,240 114,780 113,320 111,860 110,400 109,140107,880106,620105,360104,100 76.3 78.5 80.6 82.8 83.7 84.6 85.6 86.5 87.4 88.2 89.1 89.9 90.8 91.6 59.4 64.5 69.7 74.8 76.2 77.5 78.9 80.2 81.6 83.1 84.6 86.2 87.7 89.2 269 292 316 339 345 351 358 364 370 372 374 376 378 380 299 313 326 340 345 349 354 358 363 365 368 370 373 375 78.4 78.4 79.0 79.6 80.3 80.9 81.5 82.1 82.5 83.0 83.4 83.9 84.3 84.7 78.4 78.4 79.0 79.6 80.3 80.9 81.5 82.1 82.5 83.0 83.4 83.9 84.3 84.7 - - - 2,160 2170 2180 2190 2200 2,210 2,210 2,210 2,210 2,210 2,210 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 4,500 5180 5860 6540 7220 7,900 8,600 9,300 10,000 10,700 11,400 - - - 2,160 2,170 2,180 2,190 2,200 2,210 2,210 2,210 2,210 2,210 2,210 - - - 4,500 5,180 5,860 6,540 7,220 7,900 8,600 9,300 10,000 10,700 11,400 26,461 29,220 32,031 37,050 37,810 38,567 39,322 40,073 40,822 41,049 41,270 41,484 41,691 41,891 21,717 24,365 27,105 34,433 35,687 36,931 38,165 39,389 40,601 41,748 42,884 44,008 45,121 46,221 0 3,000 6,006 4,148 5,256 6,340 7,403 8,446 9,470 9,696 9,915 10,128 10,335 10,535-7,449-4,816-2,087 4,819 6,070 7,311 8,543 9,764 10,974 12,119 13,253 14,375 15,486 16,586 y œ 9,470 9,696 9,915 10,128 10,335 10,535 11,001 12,148 13,284 14,408 15,521 16,621 y (m 3 ) t 6. y œ ( : %) 2003 (» ) 2011 2012 2013 2014 2015 2016 26,461 40,822 41,049 41,270 41,484 41,691 41,891 21,717 40,601 41,748 42,884 44,008 45,121 46,221-9,470 9,696 9,915 10,128 10,335 10,535 œ (m 3 ) - 11,001 12,148 13,284 14,408 15,521 16,621 œ - 65.95 66.47 66.96 67.42 67.86 68.28-58.26 60.65 62.76 64.64 66.32 67.83 r w t 2016 z l r z 50 z 2060 ¾ w r.» œ ( )», 1 1 w š w w. z w w» ƒ š w. ƒ ƒ 1 1 ù w. ƒ (6). 1 s³ 1 1 (30 ) w w. œ (2011) 110,329, 111,849, t (2016) 110,240, 123,257. ƒ (m ƒ 3 / ) ( ) = ------------------------------------------------------------------ (6) 0.01 1 1 (l/ / ) œ z r l t ¾ w y œ (5) w w, t 6. w v w» t y w œ t 5 w. 4.4 r s³ r w, s³ r, s³ ƒ (4) w s³ r wš, œ (12 ) w z, œ w. t 7 s³r, s³r œ 2011 5,792,041 ƒw ƒ t 2016 z 7,886,555. t 8 s³r x ƒeyw r w, x ƒey w w Õ k Õ e( 4q)Ö Á : z w Ö(w, 2007) z 30 5.5%, ù 20 4.5% w, r 90,075.2. œ,,, k x, œ sww 240
» N ( ) r N' ( ) s³ ƒ F ( )» 1 s³ Q 0 (m 3 ) r 1 s³ Q 1 (m 3 ) r œ (%) r s³ r ( )» s³ r ( ) y w s³r ( ) t 7. y œ w s³ r 2011 ( œ) 2012 2013 2014 2015 2016 z ( t) 98,369 98,369 98,369 98,369 98,369 98,369 72,633 72,633 72,633 72,633 72,633 72,633 110,329 110,346 110,346 110,329 110,293 110,240 111,849 114,253 116,595 118,876 121,097 123,257 2.9 2.9 2.9 2.9 2.9 2.9 2.7 2.7 2.7 2.7 2.7 2.7 6.327 6.327 6.327 6.327 6.327 6.327 7.032 7.032 7.032 7.032 7.032 7.032 9.162 9.261 9.360 9.459 9.560 9.660 8.989 9.096 9.205 9.313 9.423 9.533 65.95% 66.47% 66.96% 67.42% 67.86% 68.28 58.26% 60.65% 62.76% 64.64% 66.32% 67.83% 923,378 933,072 942,660 952,137 961,497 970,737 891,061 920,701 950,335 979,951 1,009,541 1,039,094 575,477 575,477 575,477 575,477 575,477 575,477 456,374 456,374 456,374 456,374 456,374 456,374 4,174,813 4,291,144 4,406,199 4,519,919 4,632,246 4,743,121 5,216,241 5,571,919 5,927,522 6,282,925 6,638,005 6,992,634 2,753,222 2,852,131 2,950,184 3,047,300 3,143,403 3,238,414 w w s³r ( ) 3,038,819 3,379,174 3,719,988 4,061,050 4,402,165 4,743,152 5,792,041 6,231,305 6,670,171 7,108,350 7,545,568 7,886,555 t 8. r ( : ) r x ƒer r x ƒer r x ƒer r x ƒer 2011 5,792.0 3,774.1 2024 7,981.6 2,592.9 2037 7,981.6 1,292.7 2050 7,981.6 708.9 2012 6,231.3 3,848.6 2025 7,981.6 2,457.7 2038 7,981.6 1,225.3 2051 7,981.6 678.4 2013 6,670.2 3,904.9 2026 7,981.6 2,329.6 2039 7,981.6 1,161.4 2052 7,981.6 649.2 2014 7,108.3 3,944.5 2027 7,981.6 2,208.2 2040 7,981.6 1,100.9 2053 7,981.6 621.2 2015 7,545.6 3,968.8 2028 7,981.6 2,093.0 2041 7,981.6 1,053.5 2054 7,981.6 594.5 2016 7,981.6 3,979.3 2029 7,981.6 1,983.9 2042 7,981.6 1,008.1 2055 7,981.6 568.9 2017 7,981.6 3,771.8 2030 7,981.6 1,880.5 2043 7,981.6 964.7 2056 7,981.6 544.4 2018 7,981.6 3,575.2 2031 7,981.6 1,782.5 2044 7,981.6 923.2 2057 7,981.6 520.9 2019 7,981.6 3,388.8 2032 7,981.6 1,689.5 2045 7,981.6 883.4 2058 7,981.6 498.5 2020 7,981.6 3,212.2 2033 7,981.6 1,601.5 2046 7,981.6 845.4 2059 7,981.6 477.0 2021 7,981.6 3,044.7 2034 7,981.6 1,518.0 2047 7,981.6 809.0 2060 7,981.6 456.5 2022 7,981.6 2,886.0 2035 7,981.6 1,438.8 2048 7,981.6 774.1 2023 7,981.6 2,735.5 2036 7,981.6 1,363.8 2049 7,981.6 740.8 w 90,075.2 sww x ƒeyw w, 693,884.» w» (2003, m ) œ 0.5% w. š, k (2004.9) r mw w œ 86.82%, y 11.34%, 1.85%. œ 86.82% y ƒ w 5.066% š w y 4.398%, 693,884 y 30,519.6 w. 5.» œ r ù, w d ƒ»ƒ ñ.,» ( ) mw w k 2 w» ƒ ù. y w y w w 32«4By 2012 7 241
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