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1 32«4ByÁ 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 ( z Á Áw œ» l Áœw ( z Á w w z» lœw ( w w w Á w ( 32«4By

2 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 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 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

3 (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

4 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 ), ƒ w

5 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 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 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 Q β I β F β F-Statistic t 3. w y w t t-value P-Value β Q β F β F-Statistic 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 = Q F 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

6 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 N ( β 2 1 )Q + ( 0 β + 0 β 2 F)Q 0 ( ) β 0 = , β 2 = 2.716, β 2 = Q 0 = q days Q 1 = q days», 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) 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

7 ( 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 ( t ) ( ) 309, , , ,500 (%) »k (m 3 / ) 4,460 4,510 4,510 ƒ (m 3 / ) 4,500 7,900 11, (lpcd) 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 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

8 03 (» ) z ( ) (%) 1 1 (lpcd) (%)»k ƒ ƒ y y (+) t 5. y ( : m 3 / ) ( œ) ( t) 128, ,383125,841124,300123,320122,340121,360120, , , , , , , , , , , , , , , , ,140107,880106,620105,360104, , ,210 2,210 2,210 2,210 2,210 2, , ,900 8,600 9,300 10,000 10,700 11, ,160 2,170 2,180 2,190 2,200 2,210 2,210 2,210 2,210 2,210 2, ,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, ,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 (» ) ,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 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) (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 ,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 %, ù % w, r 90, œ,,, k x, œ sww 240

9 » 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) 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, , , , , , , , , , , , , % 66.47% 66.96% 67.42% 67.86% % 60.65% 62.76% 64.64% 66.32% 67.83% 923, , , , , , , , , ,951 1,009,541 1,039, , , , , , , , , , , , ,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 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 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

10 œ r y wš w. y w w «1,000ƒ d w š, w y w w ù 1 ü z (x ) w. œ z r w»» w w d ƒe w š ƒ. y w mw r w w. 1.» ƒ w { k w w j w w ƒ v w. w. 2. «w w. w e z w t w w» w. ù p w, k w w w v w., y ƒe ( )ƒ ƒ t»w w. 3. ù œœ œ w ƒe ù w sww ƒ. w w w ƒ q ƒ. š x m (2001) z š. m (2004) Ÿ œ» z. m Áw œ (2004) k š., z(2010) y ƒe sƒ: ƒ ƒ, w wz, w wz, 43«11y, pp ,», ½» (2004) x yƒ e w,,, 5«3y, pp ½Ÿ (1996) d w œ w : x. w y». ½ (2004) r.. ½, k (2001) mw w w w - y. m. ½ (1991) y w. w, w. ½y,, ½ y, ½ x, (2008) ƒ, w wz w tz, w wz, pp », ½, ½x (1987) w y. m. y, (2007) ƒ y y ƒe, w wz w tz, w wz, pp v(2003) (14), w wz, w wz, 36«1y. z(1996)»w w w, w, w. z, Ÿ (2006) ƒ œ r, w wz, w wz, 39«12y, pp (2004) e w, w wz, w wz, 37«2y, pp ,,, v(2006) vww mw y, w wz, w wz, 39«5y, pp x (2003) ƒ š w. w, w w, pp m (2000) Á k š. w (2007) k Õ e( 4q)Ö Á : z w. w (2008) k w w e ( 5q). w œ (1998). y (2002) m y (2006) m y (2007) w z. Bartczak, A., Kopanska, A. and Raczka, J. (2009) Residential water demand in a transition economy: Evidence from Poland, Water Science and Technology: Water Supply, Vol. 9, No. 5, pp Billings, R.B. and D.E. Agthe (1980) Price elasticities for water: A case of increasing block rates, Land Economics, Vol. 56, No. 1, pp Bithas, K. and Stoforos, C. (2006) Estimating urban residential water demand determinants and forecasting water demand for athens metropolitan area, , South-Eastern Europe Journal of Economics, Vol. 1, pp Dalhuisen, J.M., Florax, R.J.G.M., de Groot, H.L.F.M. and Nijkamp, P. (2001) Price and Income Elasticities of Residential Water Demand, Tinbergen Institute Discussion Paper, TI /3, Tinbergen Institute. Espey, M.J. and Shaw, W.D. (1997) Price elasticity of residential demand for water: A meta-analysis, Water Resource Research, Vol. 33, No. 6, pp Foster, H.S. and Beattie, B.R. (1979) Urban residential demand for water in the United States, Land Economics, Vol 55, Np. 1, pp Foster, H.S. and Beattie, B.R. (1981) On the specification of price in studies of consumer demand under block price scheduling, Land Economics, Vol. 57, No. 2, pp Howe, C.W. and Linaweaver, F.P. (1967) The impact of price on residential water demand and its relationship to system design and price structure, Water Resources Research, Vol. 3, No. 1, pp Morgan, W.D. and Smolen, J.C. (1976) Climatic indicators in the estimation of municipal water demand, Water Resources Bulletin, Vol. 12, No. 3, pp Renzetti, S. (1992) Estimating the Structure of Industrial Water Demands: The Case of Canadian Manufacturing, Land Economics, Vol. 68, No. 4, pp Zhou, Y. and Tol, R.S.J. (2005) Economic analysis of domestic, industrial and agricultural water demands in China, Water Science and Technology: Water Supply, Vol. 5, No. 6, pp m DB( ( : / : / : ) 242

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