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Farmers preferences for incentives on solar pumps: Evidence from a choice experiment in Punjab

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  • Kaur, S.
  • Pollitt, M. G.

Abstract

Diesel and electric pumps have dominated groundwater irrigation in Punjab since the advent of intensive agriculture in 1966. National policies offer a range of subsidies for solar pumps, but there is limited empirical evidence of their effectiveness in promoting adoption. To address this need, a discrete choice method is applied to estimate the level of financial incentives for solar pumps preferred by farmers. The results show that enhanced subsidies combined with energy buyback have a significant impact on adoption decisions. The impact of contextual factors on the acceptance of grid-connected solar pumps is also estimated. Additionally, willingness to pay estimates and economic evaluations are improved with the use of flexible mixed logit formulation. The findings confirm that low subsidy limits the diffusion of solar pumps in Punjab agriculture. Further, the results from the statistical models indicate high public acceptance of individual solar agriculture pumps. We suggest that solar subsidies combined with grid purchases of surplus solar electricity can both reduce emissions and reduce the over-use of ground water, by indirectly introducing a price of electricity for water pumping.

Suggested Citation

  • Kaur, S. & Pollitt, M. G., 2024. "Farmers preferences for incentives on solar pumps: Evidence from a choice experiment in Punjab," Cambridge Working Papers in Economics 2435, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:2435
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    1. Scarpa, Riccardo & Willis, Ken, 2010. "Willingness-to-pay for renewable energy: Primary and discretionary choice of British households' for micro-generation technologies," Energy Economics, Elsevier, vol. 32(1), pages 129-136, January.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    3. 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.
    4. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    5. Mohammad Al-Saidi & Nisreen Lahham, 2019. "Solar energy farming as a development innovation for vulnerable water basins," Development in Practice, Taylor & Francis Journals, vol. 29(5), pages 619-634, July.
    6. Batley, S. L. & Colbourne, D. & Fleming, P. D. & Urwin, P., 2001. "Citizen versus consumer: challenges in the UK green power market," Energy Policy, Elsevier, vol. 29(6), pages 479-487, May.
    7. Wasi, Nada & Carson, Richard T., 2013. "The influence of rebate programs on the demand for water heaters: The case of New South Wales," Energy Economics, Elsevier, vol. 40(C), pages 645-656.
    8. Higgins, Andrew & McNamara, Cheryl & Foliente, Greg, 2014. "Modelling future uptake of solar photo-voltaics and water heaters under different government incentives," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 142-155.
    9. Best, Rohan & Chareunsy, Andrea, 2022. "The impact of income on household solar panel uptake: Exploring diverse results using Australian data," Energy Economics, Elsevier, vol. 112(C).
    10. Zhang, Da & Chai, Qimin & Zhang, Xiliang & He, Jiankun & Yue, Li & Dong, Xiufen & Wu, Shu, 2012. "Economical assessment of large-scale photovoltaic power development in China," Energy, Elsevier, vol. 40(1), pages 370-375.
    11. Uz, Dilek & Mamkhezri, Jamal, 2024. "Household willingness to pay for various attributes of residential solar panels: Evidence from a discrete choice experiment," Energy Economics, Elsevier, vol. 130(C).
    12. Yamaguchi, Yohei & Akai, Kenju & Shen, Junyi & Fujimura, Naoki & Shimoda, Yoshiyuki & Saijo, Tatsuyoshi, 2013. "Prediction of photovoltaic and solar water heater diffusion and evaluation of promotion policies on the basis of consumers’ choices," Applied Energy, Elsevier, vol. 102(C), pages 1148-1159.
    13. Ek, Kristina, 2005. "Public and private attitudes towards "green" electricity: the case of Swedish wind power," Energy Policy, Elsevier, vol. 33(13), pages 1677-1689, September.
    14. 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.
    15. Chapman, Andrew J. & McLellan, Benjamin & Tezuka, Tetsuo, 2016. "Residential solar PV policy: An analysis of impacts, successes and failures in the Australian case," Renewable Energy, Elsevier, vol. 86(C), pages 1265-1279.
    16. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
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    More about this item

    Keywords

    Renewable energy; solar pumps; feeder level solarization; energy water nexus; energy subsidies; irrigation water; electricity; groundwater depletion; Punjab;
    All these keywords.

    JEL classification:

    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • P48 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Legal Institutions; Property Rights; Natural Resources; Energy; Environment; Regional Studies

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