IDEAS home Printed from
   My bibliography  Save this paper

Can agricultural aspirations influence preferences for new technologies? Cropping systems and preferences for high-efficiency irrigation in Punjab, Pakistan


  • Bell, Andrew R.
  • Ward, Patrick S.
  • Ashfaq, Muhammad
  • Davies, Stephen


In the face of increasing environmental stresses, there is a critical need to improve water-use efficiency in many arid and semiarid agroclimatic zones. Drip irrigation is a high-efficiency irrigation technology that can improve water-use efficiency in currently irrigated areas and transform areas that are not otherwise irrigable in practice. Although adoption of drip irrigation is growing rapidly in India, adoption is low in neighboring Pakistan. The authors of this paper undertook a discrete choice experiment framed around the hypothetical subsidized purchase of a drip irrigation system in four districts of Punjab, Pakistan. The nonrepresentative sample of adopters and nonadopters in the study districts identified a clear increase in the valuation of drip systems in the first several years following adoption. This finding suggests that farmers may be unaware of the opportunities for the use of drip irrigation on their farms or the benefits that may accrue from such use. In addition, farmers’ aspirations for cropping systems under drip were better predictors of the valuation of drip systems than were current cropping patterns, implying that a different agricultural landscape might reasonably emerge under improved adoption of drip. Aspirations differed across the different agroecological zones and water regimes captured by this study. Aspirations to substitute wheat crops for fruits and vegetables were associated with a higher appreciation of the subsidy level, whereas aspirations to expand wheat were associated with a higher appreciation of the area covered by the drip initiative; together, these findings imply a degree of control over the extent of wheat production in the landscape via careful design of the drip subsidy program. Although the penetration of drip irrigation is not yet sufficient to draw inferences from a representative sample, these results suggest a number of ways in which drip irrigation may transform Pakistan’s agricultural landscape

Suggested Citation

  • Bell, Andrew R. & Ward, Patrick S. & Ashfaq, Muhammad & Davies, Stephen, 2017. "Can agricultural aspirations influence preferences for new technologies? Cropping systems and preferences for high-efficiency irrigation in Punjab, Pakistan," IFPRI discussion papers 1636, International Food Policy Research Institute (IFPRI).
  • Handle: RePEc:fpr:ifprid:1636

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Chandrakanth, M.G. & Priyanka, C.N. & Mamatha, P. & Patil, Kiran K., 2013. "Economic Benefits from Micro Irrigation for Dry Land Crops in Karnataka," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 68(3), pages 1-13.
    2. Mushtaq, S. & Maraseni, T.N. & Reardon-Smith, K., 2013. "Climate change and water security: Estimating the greenhouse gas costs of achieving water security through investments in modern irrigation technology," Agricultural Systems, Elsevier, vol. 117(C), pages 78-89.
    3. Barker, Randolph & Molle, François, 2004. "Evolution of irrigation in South and Southeast Asia," IWMI Research Reports H035439, International Water Management Institute.
    4. Hess, Stephane & Hensher, David A., 2010. "Using conditioning on observed choices to retrieve individual-specific attribute processing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 781-790, July.
    5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, February.
    7. Morey Burnham & Zhao Ma & Delan Zhu, 2015. "Erratum to: The human dimensions of water saving irrigation: lessons learned from Chinese smallholder farmers," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 32(2), pages 361-362, June.
    8. Morey Burnham & Zhao Ma & Delan Zhu, 2015. "The human dimensions of water saving irrigation: lessons learned from Chinese smallholder farmers," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 32(2), pages 347-360, June.
    9. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    10. A. Narayanamoorthy, 2004. "Impact Assessment of Drip Irrigation in India: The Case of Sugarcane," Development Policy Review, Overseas Development Institute, vol. 22, pages 443-462, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    2. Ward, Patrick S. & Makhija, Simrin, 2018. "New modalities for managing drought risk in rainfed agriculture: Evidence from a discrete choice experiment in Odisha, India," World Development, Elsevier, vol. 107(C), pages 163-175.
    3. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    4. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    5. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    6. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    7. Ju-Hee Kim & Younggew Kim & Seung-Hoon Yoo, 2021. "Using a choice experiment to explore the public willingness to pay for the impacts of improving energy efficiency of an apartment," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1775-1793, October.
    8. Tong Wu & Shida Rastegari Henneberry & John N. Ng’ombe & Richard T. Melstrom, 2020. "Chinese Demand for Agritourism in Rural America," Sustainability, MDPI, Open Access Journal, vol. 12(7), pages 1-11, April.
    9. Ching-Fu Chen & Wen-Chieh Cheng, 2016. "Sustainability SI: Exploring Heterogeneity in Cycle Tourists’ Preferences for an Integrated Bike-Rail Transport Service," Networks and Spatial Economics, Springer, vol. 16(1), pages 83-97, March.
    10. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    11. Shimokawa, S. & Niiyama, Y. & Kito, Y. & Kudo, H. & Yamaguchi, M., 2018. "No-tolerant Consumers, Information Treatments, and Demand for Stigmatized Foods: the Case of Fukushima Nuclear Power Plant Accident in Japan," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277198, International Association of Agricultural Economists.
    12. Useche, Pilar & Barham, Bradford & Foltz, Jeremy, 2006. "A Trait Specific Model of GM Crop Adoption by Minnesota and Wisconsin Corn Farmers," Working Papers 201525, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    13. Christian A. Oberst & Reinhard Madlener, 2015. "Prosumer Preferences Regarding the Adoption of Micro†Generation Technologies: Empirical Evidence for German Homeowners," Working Papers 2015.07, International Network for Economic Research - INFER.
    14. Czajkowski, Mikołaj & Bartczak, Anna & Giergiczny, Marek & Navrud, Stale & Żylicz, Tomasz, 2014. "Providing preference-based support for forest ecosystem service management," Forest Policy and Economics, Elsevier, vol. 39(C), pages 1-12.
    15. Stefania Troiano & Daniel Vecchiato & Francesco Marangon & Tiziano Tempesta & Federico Nassivera, 2019. "Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?," Energies, MDPI, Open Access Journal, vol. 12(13), pages 1-19, July.
    16. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    17. Koo, Yoonmo & Kim, Chang Seob & Hong, Junhee & Choi, Ie-Jung & Lee, Jongsu, 2012. "Consumer preferences for automobile energy-efficiency grades," Energy Economics, Elsevier, vol. 34(2), pages 446-451.
    18. Fiebig, Denzil G. & Haas, Marion & Hossain, Ishrat & Street, Deborah J. & Viney, Rosalie, 2009. "Decisions about Pap tests: What influences women and providers?," Social Science & Medicine, Elsevier, vol. 68(10), pages 1766-1774, May.
    19. Staus, Alexander, 2008. "Standard and Shuffled Halton Sequences in a Mixed Logit Model," Working Papers 93856, Universitaet Hohenheim, Institute of Agricultural Policy and Agricultural Markets.
    20. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.

    More about this item


    trickle irrigation; irrigation systems; experimentation; water supply; water use efficiency; choice experiment; Punjab Irrigated-agriculture Productivity Improvement Project (PIPIP); drip irrigation;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fpr:ifprid:1636. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.