Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-20T15:18:27.720Z Has data issue: false hasContentIssue false
  • English
  • Français

Valuing irrigation water using a choice experiment: an ‘individual status quo’ modelling of farm specific water scarcity

Published online by Cambridge University Press:  26 February 2010

DAVID N. BARTON  and
OLVAR BERGLAND
DAVID N. BARTON
Affiliation:
Norwegian Institute of Nature Research (NINA), Gaustadalleen 21, N-0349 Oslo, Norway and Norwegian Institute for Water Research (NIVA). Email: [email protected]
OLVAR BERGLAND
Affiliation:
Institute of Economics and Resource Studies, University of Life Sciences (IØR- UMB) Postboks 5003, N-1432 Ås, Norway.
Get access Rights & Permissions [Opens in a new window]

Abstract

We use a choice experiment to evaluate a hypothetical irrigation water pricing regime in Karnataka State, India. The proposed regime includes increasing the availability of water in the dry season, increasing irrigation frequency, water sharing with downstream water users, set against the introduction of a semi-volumetric irrigation price. The majority of farmers chose the status quo (SQ) option. Given the large heterogeneity in farmers’ SQ water availability, irrigation practices and current water tax payments, the SQ could not be given a unique baseline interpretation. This poses a potential problem for choice model estimation. By coding the individual SQ situation of farmers, we observed considerable increase in the explanatory power of the choice experiment models. The results may be of general interest for choice experiments of environmental goods and services with heterogeneous spatial distribution, heterogeneous respondents and/or contentious policies that are expected to elicit considerable SQ response.

Type
Research Article
Information
Environment and Development Economics , Volume 15 , Issue 3 , June 2010 , pp. 321 - 340
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Banzhaf, M.R., Johnson, F.R., and Mathews, K.E. (2002), ‘Opt-out alternatives and anglers’ stated preferences’, in Bennett, J. and Blamey, R. (Eds.), The Choice Modelling Approach to Environmental Valuation, Cheltenham, UK: Edward Elgar, pp. 157–177.Google Scholar
Barton, D.N., Raju, K.V., and McNeill, D. (2008a), ‘Water valuation and pricing – when are they useful in water management?’, STRIVER Policy Brief No.3, available at, [online] http://kvina.niva.no/striver/Disseminationofresults/STRIVERTechnicalBriefs/tabid/79/Default.aspx, posted November 2008, verified February 12, 2010.Google Scholar
Barton, D.N., Taron, A., and Alvarez, B. (2008b), ‘Using choice experiments to value irrigation water’, STRIVER Technical Brief No. 4, available at, [online] http://kvina.niva.no/striver/Disseminationofresults/STRIVERTechnicalBriefs/tabid/79/Default.aspx, posted November 2008, verified February 12, 2010.Google Scholar
Bateman, I.J., Brouwer, R., Ferrini, S., Schaafsma, M., Barton, D.N., Binner, A., Day, B.H., Dubgaard, A., Fezzi, C., Hasler, B., Hime, S., Liekens, I., Navrud, S., De Nocker, L., Ščeponavičiūtė, R., and Semėnienė, D. (2009), ‘Making benefit transfers work: transferring theoretically derived, spatially explicit, value functions for the non-market benefits of water quality improvements across Europe’, Paper presented at the 17th EAERE Annual Conference, 24–27 June, Amsterdam.Google Scholar
Bateman, I., Carson, R.T., Day, B., Hanemann, M., Hanley, N., Hett, T., Jones-Lee, M., Loomes, G., Mourato, S., Ozdemiroglu, E., Pearce, D.W., and Swandon, J. (2002), Economic Valuation with Stated Preferences Techniques. A Manual, Cheltenham: Edward Elgar.CrossRefGoogle Scholar
Birol, E., Karousakis, K., and Koundouri, P. (2006), ‘Using a choice experiment to account for preference heterogeneity in wetland attributes: the case of Cheimaditida wetland in Greece’, Ecological Economics 60: 145–156.CrossRefGoogle Scholar
Birol, E., Rayn Villalba, E., and Smale, M. (2009), ‘Farmer preferences for milpa diversity and genetically modified maize in Mexico: a latent class approach’, Environment and Development Economics 14 (4): 521–540.CrossRefGoogle Scholar
Chamberlain, G. (1980), ‘Analysis of covariance with qualitative data’, Review of Economic Studies 47: 225–238.CrossRefGoogle Scholar
Colombo, S., Hanley, N., and Calatrava-Requena, J. (2005), ‘Designing policy for reducing the off-farm effects of soil erosion using choice experiments’, Journal of Agricultural Economics 56 (1): 81–96.CrossRefGoogle Scholar
Easter, K.W. and Liu, Y. (2005), Cost Recovery and Water Pricing for Irrigation and Drainage Projects, Agriculture and Rural Development Discussion Paper 26, World Bank.CrossRefGoogle Scholar
Efron, B. and Tibshirani, R. (1993), An Introduction to the Bootstrap, New York: Chapman & Hall.CrossRefGoogle Scholar
GoI (2008), National Water Mission under National Action Plan on Climate Change. Government of India, Ministry of Water Resources, Vol. II, Appendix-V Report of the Sub-Committee on “Efficient Use of Water for Various Purposes”, December 2008.Google Scholar
Griffin, R.C. (2006), Water Resource Economics. The Analysis of Scarcity, Policies and Projects, Cambridge, MA: MIT Press.Google Scholar
Haab, T.C. and Hicks, R.L. (1997), ‘Accounting for choice set endogeneity in random utility models of recreation demand’, Journal of Environmental Economics and Management 34 (2):127–147.CrossRefGoogle Scholar
Haan, P. and Uhlendorff, A. (2006), ‘Estimation of multinomial logit models with unobserved heterogeneity using maximum simulated likelihood’, The Stata Journal 6 (2): 229–245.CrossRefGoogle Scholar
Hanley, N., Wright, R.E., and Alvarez-Farizo, B. (2006), ‘Estimating the economic value of improvements in river ecology using choice experiments: an application to the water framework directive’, Journal of Environmental Management 78 (2): 183–93.CrossRefGoogle Scholar
Hensher, D., Rose, J.M., and Greene, W.H. (2005a), Applied Choice Analysis. A Primer, Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hensher, D., Shore, N., and Train, K. (2005b), ‘Households’ willingness to pay for water service attributes’, Environmental and Resource Economics 32: 509–531.CrossRefGoogle Scholar
Hole, A.R. (2007a), ‘Fitting mixed logit models using maximum simulated likelihood’, The Stata Journal 7 (3): 388–401.CrossRefGoogle Scholar
Hole, A.R. (2007b), ‘A comparison of approaches to estimating confidence intervals for willingness to pay measures’, Health Economics 16: 827–840.CrossRefGoogle ScholarPubMed
India PES Project (2008), ‘Evaluating irrigation water pricing using choice experiments—experiences from the Malaprabha Command Area, Karnataka, India. Development of Tools and Methodologies to Implement the Payment for Environmental Services Concept in Watersheds in India (PES India Project)’, available at, [online] http://malaprabha.org/publications/TechBrief7.pdfGoogle Scholar
Johnston, R.J., Swallow, S.K., and Bauer, D.M. (2002), ‘Spatial factors and stated preference values for public goods: considerations for rural land use’, Land Economics 78 (4): 481–500.CrossRefGoogle Scholar
Johnston, R.J., Swallow, S.K., Tyrrell, T.J., and Bauer, D.M. (2003), ‘Rural amenity values and length of residency’, American Journal of Agricultural Economics 85 (4): 1000–1015.CrossRefGoogle Scholar
Kahneman, D. and Tversky, A. (1979), ‘Prospect theory: an analysis of decision under risk’, Econometrica 47: 263–291.CrossRefGoogle Scholar
Krinsky, I. and Robb, A.L. (1986), ‘On approximating the statistical properties of elasticities’, Review of Economics and Statistics 68: 715–719.CrossRefGoogle Scholar
Krinsky, I. and Robb, A.L. (1990), ‘On approximating the statistical properties of elasticities: a correction’, Review of Economics and Statistics 72: 189–190.CrossRefGoogle Scholar
McFadden, D. (1974), ‘Conditional logit analysis of qualitative choice behavior’, in Zarembka, P. (Ed.), Frontiers in Econometrics, New York: Academic Press, pp. 105–142.Google Scholar
Molle, F. (2009), ‘Water scarcity, prices and quotas: a review of evidence on irrigation volumetric pricing’, Irrigation Drainage Systems 23: 43–58.CrossRefGoogle Scholar
Ostrom, E. (1990), Governing the Commons: The Evolution of Institutions for Collective Action, New York: Cambridge University Press.CrossRefGoogle Scholar
Peterson, J.M., Fox, J.A., Leatherman, J.C., and Smith, C.M. (2007), ‘Choice experiments to assess farmers’ willingness to participate in a water quality trading market’, Paper presented at Agricultural and Applied Economics Association, July 29-August 1, 2007, Portland, Oregon.Google Scholar
Revelt, D. and Train, K. (1998), ‘Mixed logit with repeated choices: households’ choices of appliance efficiency level’, Review of Economics and Statistics 80: 647–657.CrossRefGoogle Scholar
Samuelson, W. and Zeckhauser, R. (1988), ‘Status quo bias in decision making’, Journal of Risk and Uncertainty 1 (1): 7–59.CrossRefGoogle Scholar
Scarpa, R., Ferrini, S., and Willis, K. (2005), ‘Performance of error component models for status-quo effects in choice experiments’, in Scarpa, R. and Alberini, A. (Eds.), Applications of Simulation Methods in Environmental and Resource Economics, Dordrecht: Springer, pp. 247–274.CrossRefGoogle Scholar
Train, K.E. (2003), Discrete Choice Methods with Simulation, Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Watershed Atlas of India, available at, [online] http://cgwb.gov.in/watershed/about-ws.html.Google Scholar
Willis, K.G., Scarpa, R., and Acutt, M. (2005), ‘Assessing water company customer preferences and willingness to pay for service improvements: a stated choice analysis’, Water Resource Research 41: 1–11.CrossRefGoogle Scholar
Young, R.A. (2005), Determining the Economic Value of Water: Concepts and Methods, Washington, D.C.: Resources for the Future Press.Google Scholar
Supplementary material: File

Barton supplementary material

Appendix.doc

Download Barton supplementary material(File)
File 705 KB