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Individual status quo modelling for a rural water service in Rwanda: application of a choice experiment

Published online by Cambridge University Press:  01 December 2015

Claudine Uwera
Affiliation:
Department of Economics, University of Gothenburg, Sweden; and Department of Economics, University of Rwanda, Rwanda. E-mail: [email protected]
Jesper Stage
Affiliation:
Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, 971 87 Luleå, Sweden; and Department of Business, Economics and Law, Mid Sweden University, Sweden. Tel:+46 (0)920 49 34 45. E-mail: [email protected]

Abstract

In Rwanda, rural water supply is not uniformly distributed. Rural areas are characterized by differences in the distance to the nearest water point and in water quality for domestic water, by watering frequency and water availability for irrigation water, and by the price for both. A household's perception of further improvements in water supply will, therefore, depend heavily on the situation it currently faces. The authors used a choice experiment to model how the individual status quo (SQ) affects preferences. Accounting for individual SQ information improves model significance relative to simply using the generic SQ parameter in the model, and the willingness to pay increases. Not using this information leads to a downward bias – and, in some cases, statistical insignificance – in estimates of households’ valuation of health improvements linked to improved domestic water availability, as well as of increased watering frequency linked to the improved availability of irrigation water.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2015 

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References

Abramson, A., Becker, N., Garb, Y., and Lazarovitch, N. (2011), ‘Willingness to pay, borrow, and work for rural water service improvements in developing countries’, Water Resources Research 47: W11512.Google Scholar
Banzhaf, M.R., Reed, F., and Kristy, J. (2002), ‘Opt-out alternatives and anglers’ stated preferences’, in Bennett, J. and Blamey, R. (eds), The Choice Modeling Approach to Environmental Valuation, Cheltenham: Edward Elgar, pp. 157177.Google Scholar
Barton, D. and Bergland, O. (2010), ‘Valuing irrigation water using a choice experiment: an “individual status quo” modeling of farm specific water scarcity’, Environment and Development Economics 15: 321340.Google Scholar
Bhaduri, A. and Kloos, J. (2013), ‘Getting the water prices right using an incentive-based approach: an application of a choice experiment in Khorezm, Uzbekistan’, European Journal of Development Research 25: 680694.Google Scholar
Brebbia, C.A., Marinov, A.M., and Bjornlund, H. (eds) (2010), Sustainable Irrigation Management, Technologies and Policies III, WIT Transactions on Ecology and the Environment Vol. 134, Ashurst: WIT Press.Google Scholar
Carlsson, F., Frykblom, P., and Liljenstolpe, C. (2003), ‘Valuing wetland attributes: an application of choice experiments’, Ecological Economics 47: 95103.CrossRefGoogle Scholar
Chellattan Veettil, P., Speelman, S., Frija, A., Buysse, J., Mondelaers, K., and van Huylenbroeck, G. (2011a), ‘Price sensitivity of farmer preferences for irrigation water pricing method: evidence from a choice model analysis in Krishna River Basin, India’, Journal of Water Resources Planning and Management 137(2): 205214.Google Scholar
Chellattan Veettil, P., Speelman, S., Frija, A., Buysse, J., and van Huylenbroeck, G. (2011b), ‘Complementarity between water pricing, water rights and local water governance: a Bayesian analysis of choice behavior of farmers in the Krishna River Basin, India’, Ecological Economics 70: 17561766.Google Scholar
Echenique, M. and Seshagiri, R. (2009), ‘Attribute-based willingness to pay for improved water services: a developing country application’, Environment and Planning B 36: 384397.CrossRefGoogle Scholar
Gasore, G., Munyaneza, J.d.D., Ngendabanga, J.P., and Twibanire, A. (2015), ‘Design of automatic irrigation system for small farmers in Rwanda’, Agricultural Sciences 6: 291294.Google Scholar
Kremer, M., Leino, J., Miguel, E., and Peterson Zwane, A. (2011), ‘Spring cleaning: rural water impacts, valuation, and property rights institutions’, Quarterly Journal of Economics 126: 145205.CrossRefGoogle ScholarPubMed
Louvière, J., Hensher, D., and Swait, J. (2000), Stated Choice Methods: Analysis and Applications, Cambridge: Cambridge University Press.Google Scholar
McFadden, D. (1974), ‘Conditional logit analysis of qualitative choice behavior’, in Zarembka, P. (ed.), Frontiers in Econometrics, New York: Academic Press, pp. 105142.Google Scholar
Meyerhoff, J. and Liebe, U. (2009), ‘Status quo effect in choice experiments: empirical evidence on attitudes and choice task complexity’, Land Economics 85(3): 515528.Google Scholar
Nahayo, D. (2008), ‘Feasible solutions for an improved watershed management in sloping areas, Rwanda’, Paper presented at the Water and Land Session, 9th WATERNET/WARFSA/GWP-SA Symposium, 29–31 October 2008, Johannesburg.Google Scholar
Narayanan, K. (2014), ‘Impact of participatory irrigation management – case study: Cocurirwa Cooperative, Rwamagana Rice Project, Rwanda’, Advances in Plants & Agriculture Research 1(3): 00013.Google Scholar
Republic of Rwanda (2010), Rwanda Irrigation Master Plan, Kigali: Ministry of Agriculture and Animal Resources, Ebony Enterprises Limited and World Agroforestry Centre (ICRAF).Google Scholar
Republic of Rwanda (2012), National Policy and Strategy for Water Supply and Sanitation Services, Kigali: Republic of Rwanda.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: 647657.Google Scholar
Samuelson, W. and Zeckhauser, R. (1988), ‘Status quo bias in decision making’, Journal of Risk and Uncertainty 1(1): 759.Google 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. 247274.Google Scholar
Soto Montes de Oca, G. and Bateman, I.J. (2006), ‘Scope sensitivity in households' willingness to pay for maintained and improved water supplies in a developing world urban area: investigating the influence of baseline supply quality and income distribution upon stated preferences in Mexico City’, Water Resources Research 42: W07421.Google Scholar
Tarfasa, S. and Brouwer, R. (2013), ‘Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment’, Applied Economics 45: 10991108.Google Scholar
Whittington, D. (2004), ‘Ethical issues with contingent valuation surveys in developing countries: a note on informed consent and other concerns’, Environmental and Resources Economics 28(4): 507515.Google Scholar
Whittington, D. and Adamowicz, W. (2011), ‘The use of hypothetical baselines in stated preference surveys’, EfD Discussion Paper No. 11–11, Environment for Development, Washington, DC.Google Scholar
Young, R.A. (2005), Determining the Economic Value of Water: Concepts and Methods, Washington, DC: Resources for the Future Press.Google Scholar