Measuring willingness to pay to improve municipal water in southeast Anatolia, Turkey

Water Resources Research

Volumn 46, Issue 12, 2010, Pages

  Bilgic, Abdulbaki ^a  

^a HARRAN UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

ENDOGENEITY; EXPLANATORY VARIABLES; HOUSEHOLD SURVEYS; MUNICIPAL WATER; PROBIT MODELS; SAMPLE SELECTION; UNIVARIATE; WATER INFRASTRUCTURE; WILLINGNESS TO PAY;

MATHEMATICAL MODELS; WATER SUPPLY;

SURVEYS;

NUMERICAL MODEL; WATER DEMAND; WATER ECONOMICS; WATER QUALITY; WILLINGNESS TO PAY;

ANATOLIA; TURKEY;

EID: 78650454231     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2009WR009010     Document Type: Article

References (59)

1. Alvarez, R. M., and G. Glasgow (2000), Twostage estimation of nonrecursive choice models, Polit. Anal., 8, 147-165.
2. Berrens, R. P., A. K. Bohara, K. Gawande, and P. Wang (1997), Testing the invertedU hypothesis for US hazardous waste: An application of the generalized gamma model, Econ. Lett., 55, 435-440, doi:10.1016/ S0165-1765(97)00088-8.
3. Boyes, W. J., L. D. Hoffman, and S. A. Low (1989), An econometric analysis of the bank credit scoring problem, J. Econometrics, 40, 3-14, doi:10.1016/0304-4076(89)90026-2.
4. Briscoe, J., P. F. de Castro, C. Griffin, J. North, and O. Olsen (1990), Toward equitable and sustainable rural Water. supplies: A contingent valuation study in Brazil, World Bank Econ. Rev., 4, 115-134, doi:10.1093/ wber/4.2.115.
5. Brox, J. A., R. C. Kumar, and K. R. Stollery (2003), Estimating willingness to pay for improved Water. quality in the presence of item nonresponse bias, Am. J. Agric. Econ., 85, 414-428, doi:10.1111/1467-8276.00130.
6. Butler, J. S. (1996), Estimating the correlation in censored probit models, Rev. Econ. Stat., 78, 356-358, doi:10.2307/2109940.
7. Cameron, T. A. (1991), Interval estimates of nonmarket resource values from referendum contingent valuation surveys, Land Econ., 67, 413-421, doi:10.2307/3146548.
8. Cantor, K. P. (1997), Drinking Water. and cancer, Cancer Causes Control, 8, 292-308, doi:10.1023/A:1018444902486.
9. Choe, K., D. Whittington, and D. Lauria (1996), The economic benefits of surface Water. quality improvements in developing countries: A case study of Davao, Philippines, Land Econ., 72, 519-537, doi:10.2307/ 3146913.
10. Cooper, J. (1994), A comparison of approaches to calculating confidence intervals for benefit measures from dichotomous choice contingent valuation surveys, Land Econ., 70, 111-122, doi:10.2307/3146445.
11. Crutchfield, S. R., J. C. Cooper, and D. Hellerstein (2000), Benefits of safer drinking water: The value of nitrate reduction, pp. 1-15, Econ. Res. Serv., U.S. Dep. of Agric., Washington, D. C.
12. Desvousges, W. H., M. Naughton, and G. Parsons (1992), Benefits transfer: Conceptual problems in estimating Water. quality benefits using existing studies, Water. Resour. Res., 28, 675-683, doi:10.1029/91WR02592.
13. Dong, D., B. W. Gould, and H. M. Kaiser (2004), Food demand in Mexico: An application of the AmemiyaTobin approach to the estimation of a censored food system, Am. J. Agric. Econ., 86, 1094-1107, doi:10.1111/ j.0002-9092.2004.00655. x.
14. Dubin, J. A., and D. Rivers (1989), Statistical bias in linear regression, logit and probit models, Sociol. Methods Res., 18, 360-390, doi:10.1177/ 0049124189018002006.
15. Edwards, S. F. (1988), Option prices for ground water protection (1988), J. Environ. Econ. Manage., 15, 475-487, doi:10.1016/0095-0696(88) 90040-X.
16. Eklöf, J. A., and S. Karlsson (1999), Testing and correcting for sample selection bias in discrete choice contingent valuation studies, SSE/ EFI Work. Pap. Ser. Econ. Finance 171, Stockholm Sch. of Econ., Stockholm.
17. Eren, G. (2008), GAP Bölgesinde kaliteli ime suyunun fiyatlandirilmasina etki eden faktörler, M.S. thesis, Harran Univ., Sanliurfa, Turkey.
18. Genius, M., and K. P. Tsagarakis (2006), Water. shortages and implied Water. quality: A contingent valuation study, Water. Resour. Res., 42, W12407, doi:10.1029/2005WR004833.
19. Genius, M., E. Hatzaki, E. M. Kouromichelaki, G. Kouvakis, S. Nikiforaki, and K. P. Tsagarakis (2008), Evaluating consumers willingness to pay for improved potable Water. quality and quantity, Water. Resour. Manage., 22, 1825-1834, doi:10.1007/s11269-008-9255-7.
20. Gourieroux, C., and A. Monfort (1981), On the problem of missing data in linear models, Rev. Econ. Stud., 48, 579-586, doi:10.2307/2297197.
21. Greene, W. H. (2003), Econometric Analysis, Prentice Hall, Upper Saddle River, N. J.
22. Griffin, C., J. Briscoe, B. Singh, R. Ramasubban, and R. Bhatia (1995), Contingent valuation and actual behavior: Predicting connections to new Water. systems in the state of Kerala, India, World Bank Econ. Rev., 9, 373-395, doi:10.1093/wber/9.3.373.
23. Hole, A. R. (2007), A comparison of approaches to estimating confidence intervals for willingness to pay measures, Health Econ., 16, 827-840, doi:10.1002/hec.1197.
24. Jordan, J. L., and A. H. Elagheeb (1993), Willingness to pay for improvements in drinking Water. quality, Water. Resour. Res., 29, 237-245, doi:10.1029/92WR02420.
25. Katuwal, H., and A. K. Bohara (2007), Coping with unreliable Water. supplies and willingness to pay for improved Water. supplies in Kathmandu, Nepal, paper presented at the Second Annual Himalayan Policy Research Conference, Nepal Study Cent., Madison, Wis.
26. Kim, H. J., and Y. Cho (2001), Estimating willingness to pay for reduced copper contamination in southwestern Minnesota, J. Agric. Resour. Econ., 27, 450-463.
27. Krupnick, A., A. Alberini, N. Simon, B. O'Brien, R. Goeree, and M. Heintzelman (2002), Age, health and the willingness to pay for mortality risk reductions: A contingent valuation survey of Ontario residents, J. Risk Uncertainty, 24, 161-186, doi:10.1023/A:1014020027011.
28. Kwak, S., and C. Russell (1994), Contingent valuation in Korean environmental planning: A pilot application to the protection of drinking Water. quality in Seoul, Environ. Resour. Econ., 4, 511-526, doi:10.1007/ BF00691926.
29. Larson, B. A., and E. D. Gnedenko (1999), Avoiding health risks from drinking Water. in Moscow: An empirical analysis, Environ. Dev. Econ., 4, 565-581, doi:10.1017/S1355770X99000339.
30. Lewbel, A. (2007), Coherence and completeness of structural models containing a dummy endogenous variable, Int. Econ. Rev., 48, 1379-1392, doi:10.1111/j.1468-2354.2007.00466.x.
31. Lockwood, M., J. Loomis, and T. deLacy (1994), The relative unimportance of a nonmarket willingness to pay for timber harvesting, Ecol. Econ., 9, 145-152, doi:10.1016/0921-8009(94)90096-5.
32. McPhail, A. (1994), Why don't households connect to the piped Water. system? Observations from Tunis, Tunisia, Land Econ., 70, 189-196, doi:10.2307/3146321.
33. Messonnier, M. L., J. C. Bergstrom, C. M. Cornwell, R. J. Teasley, and H. K. Cordell (2000), Survey responserelated biases in contingent valuation: Concepts, remedies, and empirical application to valuing aquatic plant management, Am. J. Agric. Econ., 82, 438-450, doi:10.1111/0002-9092.00037.
34. Mitchell, R., and R. Carson (1989), Using Surveys to Value Public Goods: The Contingent Valuation Method, Resour. for the Future, Washington, D. C.
35. Organization for Economic Cooperation and Development (2003), Social Issues in the Provision and Pricing of Water. Services [electronic], Paris.
36. PerezPineda, F. (1999), Estimating the willingness to pay for Water. services in developing countries: A case study of the use of a contingent valuation survey in El Salvador, Central America, Ph.D. dissertation, Purdue Univ., West Lafayette, Indiana.
37. Piper, S. (1998), Using contingent valuation and benefit transfer to evaluate Water. supply improvement benefits, J. Am. Water. Resour. Assoc., 34, 311-320, doi:10.1111/j.1752-1688.1998.tb04137.x.
38. Poe, G. L. (1993), Information, risk perceptions, and contingent values: The case of nitrates in groundwater, Ph.D. dissertation, Dep. of Agric. Econ., Univ. of Wis.Madison, Madison.
39. Poe, G. L., and R. C. Bishop (1992), Prior information, general information, and specific information in the contingent valuation of environmental risks: The case of nitrates in groundwater, Staff Pap. 9311, Dep. Of Agric. Econ., Cornell Univ., Ithaca, N. Y.
40. Reddy, V. R. (1999), Quenching the thirst: The cost of Water. in fragile environments, Dev. Change, 30, 79-113, doi:10.1111/1467-7660.00108.
41. Rivers, D., and H. Vuong (1988), Limited information estimators and exogeneity testing for simultaneous probit models, J. Econometrics, 39, 347-366, doi:10.1016/0304-4076(88)90063-2.
42. Rosado, M. A., M. A. CunhaESa, M. M. DuclaSoares, and L. C. Nunes (2006), Combining averting behavior and contingent valuation data: An application to drinking Water. treatment in Brazil, Environ. Dev. Econ., 11, 729-746, doi:10.1017/S1355770X0600324X.
43. Shultz, S., and B. Lindsay (1990), Willingness to pay for ground water protection, Water. Resour. Res., 26, 1869-1875, doi:10.1029/ WR026i009p01869.
44. Shultz, S., and B. Soliz (2007), Stakeholder willingness to pay for watershed restoration in rural Bolivia, J. Am. Water. Resour. Assoc., 43, 947-956, doi:10.1111/j.1752-1688.2007.00076.x.
45. Singh, B., R. Ramasubban, R. Bhatia, J. Briscoe, C. Griffin, and C. Kim (1993), Rural Water. supply in Kerala, India: How to emerge from a lowlevel equilibrium trap, Water. Resour. Res., 29, 1931-1942, doi:10.1029/92WR02996.
46. Sun, H., J. C. Bergstrom, and J. R. Dorfman (1992), Estimating the benefits of ground Water. contamination protection, South. J. Agric. Econ., 19, 63-71.
47. Sutherland, R. J., and R. G. Walsh (1985), Effect of distance on the preservation value of Water. quality, Land Econ., 61, 281-291, doi:10.2307/ 3145843.
48. Tapio, S., and B. Grosche (2006), Arsenic in the aetiology of cancer, Mutat. Res., 612, 215-246, doi:10.1016/j.mrrev.2006.02.001.
49. Tuan, T. H., and S. Navrud (2009), Applying the dissonanceminimising format to value cultural heritage in developing countries, Aust. J. Agric. Resour. Econ., 53, 327-343, doi:10.1111/j.1467-8489.2009.00452.x.
50. Tümay, A. B., and R. Brouwer (2007), Nonmarket valuation of Water. quality in a rural transition economy in Turkey applying a posteriori bid design, Water. Resour. Res., 43, W05436, doi:10.1029/2006WR004869.
51. Whitehead, J. C. (2005), Combining willingness to pay and behavior data with limited information, Resour. Energy Econ., 27, 143-155, doi:10.1016/j.reseneeco.2004.07.002.
52. Whitehead, J. C. (2006), Improving willingness to pay estimates for quality improvements through joint estimation with quality perceptions, South. Econ. J., 73, 100-111, doi:10.2307/20111876.
53. Whitehead, J. C., P. A. Groothuis, and G. C. Blomquist (1993), Testing for nonresponse and sample selection bias in contingent valuation, Econ. Lett., 41, 215-220, doi:10.1016/0165-1765(93)90200-V.
54. Whittington, D., and X. Mu (1990), Estimating the willingness to pay for Water. services in developing countries: A case study of the use of the contingent valuation surveys in southern Haiti, Econ. Dev. Cult. Change, 38, 293-311, doi:10.1086/451794.
55. Whittington, D., D. Lauria, and X. Mu (1991), A study of Water. vending and willingness to pay for Water. in Onitscha, Nigeria, World Dev., 19, 179-198, doi:10.1016/0305-750X(91)90254-F.
56. Whittington, D., V. K. Smith, A. Okorafor, A. Okore, J. L. Liu, and A. McPhail (1992), Giving respondents time to think in contingent valuation studies: A developing country application, J. Environ. Econ. Manage., 22, 205-225, doi:10.1016/0095-0696(92)90029-V.
57. Wooldridge, J. (2002), Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, Mass.
58. Yoo, S.H., and H. J. Yang (2001), Application of sample selection model to doublebounded dichotomous choice contingent valuation studies, Environ. Resour. Econ., 20, 147-163, doi:10.1023/A:1012625929384.
59. Yoo, S.H., H.J. Lim, and S.J. Kwak (2009), Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias, Appl. Energy, 86, 460-465, doi:10.1016/j.apenergy. 2008.08.023.