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Benefit-Cost Analysis with Local Residents’ Stated Preference Information: A Study of Non-Motorized Transport Investments in Pune, India

Published online by Cambridge University Press:  19 January 2015

Hua Wang ,
Ke Fang  and
Yuyan Shi
Hua Wang
Affiliation:
World Bank
Ke Fang
Affiliation:
World Bank
Yuyan Shi
Affiliation:
World Bank
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Abstract

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One of the major difficulties in doing benefit-cost analyses of a development project is to estimate a total economic value of the project benefits, which are usually multi-dimensional and include goods and services that are not traded in the market, and challenges also arise in aggregating the values of different benefits, which may not be mutually exclusive. This paper presents an analysis of a non-motorized transport project in Pune, India, which uses the contingent valuation method to estimate the total value of the project benefits across beneficiaries. A sample of the project beneficiaries are presented with a detailed description of the project and then are asked to vote on whether such a project should be undertaken given different specifications of costs to their households. A function of willingness-to-pay for the project is then derived from the survey answers and the key determinants are found to include household income, distance to the project streets, current use of the transportation modes, future use of the project streets, predicted impacts of the project, and level of trust in the government. The total willingness-to-pay of the local residents is found to be smaller than the total cost of an initial design of the project. Heteroskedasticity is also found to present in the willingness-to-pay models.

Keywords

benefit-cost analysistransport projectcontingent valuation
Type
Article
Information
Journal of Benefit-Cost Analysis , Volume 2 , Issue 3 , 25 August 2011 , pp. 1 - 37
Copyright
Copyright © Society for Benefit-Cost Analysis 2011

References

(1) Alberini, A, Kanninen, B. and Carson, T.R.. Modeling response incentive effects in dichotomous choice contingent valuation data. Land economics 73(1997), 309-324.Google Scholar
(2) Alberini, A., Boyle, K. and Welsh, M. P.. Analysis of contingent valuation data with multiple bids and responses options allowing respondents to express uncertainty. Journal of Environmental Economics and Management 45(2003), 40-62.CrossRefGoogle Scholar
(3) Afroz, Rafia, Mohd, Hassan Nasir, Muhamad, Awang, Noor, Ibrahim Akma. Willingness to pay for air quality improvements in Klang Valley Malaysia. American Journal of Environmental Sciences 1 (2005) 194-201.Google Scholar
(4) Cameron, T.A., Poe, L. G., Ethier, G.R., Schulze, D.W.. Alternative non-market value-elicitation methods: are the underlying preferences the same? Journal of Environmental Economics and Management 44(2002), 391-425.Google Scholar
(5) Carlsson Fredrik, Johansson-Stenman Olof. Willingness to pay for improved air quality in Sweden. Applied Economics 32 (2000), 661-669.Google Scholar
(6) Feitelson, E., Hurd, R., and Mudge, R.. The impact of airport noise on willingness to pay for residences. Transportation Research D: Transport and Environment, 1 (1996), 1-14.Google Scholar
(7) Gourieroux, C., Monfort, A., Trognon, A.. Pseudo maximum likelihood methods: theory. Econometrica 52 (1984), 681-700.Google Scholar
(8) Halvorsen, B, Soelensminde, K.. Differences between willingness-to-pay estimates from open-ended and discrete-choice contingent valuation methods: the effects of heteroskedasticity. Land Economics 74(1998), 262-282.CrossRefGoogle Scholar
(9) Hanemann Michael, John Loomis. Statistical efficiency of doubled-bounded dichotomous choice contingent valuation. American Journal of Agricultural Economics 73 (1991), 1255-1263.Google Scholar
(10) Horowitz, J.L. Semiparametric and nonparametric estimation of quanta response models” in Handbook of Statistics, vol 11, Maddala, G.S., Rao, C.R. and Vinod, H.D.. Elsevier Science Publisher, B.V. Google Scholar
(11) Krinsky, Itzhak, Leslie, Robb A.. On approximating the statistical properties of elasticity. The Review of Economics and Statistics 68 (1986), 715-719.Google Scholar
(12) Langford, H. Ian. Using a generalized linear mixed model to analyze dichotomous choice contingent valuation data. Land Economics 70 (1994), 507-514.Google Scholar
(13) Mitchell, R.C., Carson, R.T.. An experiment in determining willingness to pay for national water quality improvements. Draft Report to the US Environmental Protection Agency, Washington, DC. Google Scholar
(14) Painter, M. Kathleen, Robert Douglas, Scott II, Philip, Wandschneider R., Kenneth, Casavant L.. Using contingent valuation to measure user and nonuser benefits: An application to public transit. Review of Agricultural Economics 24 (2002), 394-409.Google Scholar
(15) Smith, V. Kerry. Fifty years of contingent valuation. International Yearbook of Environmental and Resource Economics 2004-2005, 1-60.Google Scholar
(16) Verhoef, T. Erik, Peter, Nijkamp, Piet, Rietveld. The social feasibility of road pricing: A case study for the Randstad area. Journal of Transport Economics and Policy 31 (2002), 255-276.Google Scholar
(17) Wang, Hua. Treatment of “don’t-know” responses in contingent valuation surveys: a random valuation model. Journal of Environmental Economics and Management 32(1997), 219-232.Google Scholar
(18) Wang, Hua, and Whittington, Dale. Measuring individuals’ valuation distributions using a stochastic payment card approach. Ecological Economics 55 (2005), 143-154.Google Scholar
(19) Wang, Hua and , Jie He. Estimating individual valuation distributions with multiple bounded discrete choice data, Applied Economics, July, 2010.Google Scholar
(20) Walton, D., Thomas, J.A., Cenek, P.D.. Self and others’ willingness to pay for improvements to the paved road surface. Transportation Research Part A 38 (2004) 483-494.Google Scholar
(21) Welsh, M. P. and Bishop, R. M.. Multiple bounded discrete choice model, in Bergstrom, J. (ed.), Benefits & costs transfer in natural resource planning, Western Regional Research Publication, W-133, Sixth Interim Report, Department of Agricultural and Applied Economics, University of Georgia, 331-352.Google Scholar
(22) Welsh, M. P. and Poe, G. L.. Elicitation effects in contingent valuation: comparisons to a multiple bounded discrete choice approach. Journal of Environmental Economics and Management 36(1998), 170-185.Google Scholar
(23) World Bank. Sustainable urban transport program of India: Pune -Integration of NMT with BRT. Internal project preparation document, Washington, DC. June, 2008.Google Scholar