IDEAS home Printed from https://ideas.repec.org/p/ags/aaea18/274474.html
   My bibliography  Save this paper

What Drives (No) Adoption of New Irrigation Technologies: A Structural Dynamic Estimation Approach

Author

Listed:
  • Li, Haoyang
  • Zhao, Jinhua

Abstract

No abstract is available for this item.

Suggested Citation

  • Li, Haoyang & Zhao, Jinhua, 2018. "What Drives (No) Adoption of New Irrigation Technologies: A Structural Dynamic Estimation Approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274474, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea18:274474
    DOI: 10.22004/ag.econ.274474
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/274474/files/Abstracts_18_05_23_10_18_23_17__111_227_226_27_0.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.274474?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Foltz, Jeremy D, 2003. "The Economics of Water-Conserving Technology Adoption in Tunisia: An Empirical Estimation of Farmer Technology Choice," Economic Development and Cultural Change, University of Chicago Press, vol. 51(2), pages 359-373, January.
    2. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    3. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 497-529.
    4. Doug J. Chung & Thomas Steenburgh & K. Sudhir, 2014. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans," Marketing Science, INFORMS, vol. 33(2), pages 165-187, March.
    5. Dinar, Ariel & Yaron, Dan, 1992. "Adoption and abandonment of irrigation technologies," Agricultural Economics, Blackwell, vol. 6(4), pages 315-332, April.
    6. Patrick Bajari & C. Lanier Benkard & Jonathan Levin, 2007. "Estimating Dynamic Models of Imperfect Competition," Econometrica, Econometric Society, vol. 75(5), pages 1331-1370, September.
    7. Pfeiffer, Lisa & Lin, C.-Y. Cynthia, 2014. "Does efficient irrigation technology lead to reduced groundwater extraction? Empirical evidence," Journal of Environmental Economics and Management, Elsevier, vol. 67(2), pages 189-208.
    8. Patrick Bayer & Robert McMillan & Alvin Murphy & Christopher Timmins, 2016. "A Dynamic Model of Demand for Houses and Neighborhoods," Econometrica, Econometric Society, vol. 84, pages 893-942, May.
    9. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    10. Janis M. Carey & David Zilberman, 2002. "A Model of Investment under Uncertainty: Modern Irrigation Technology and Emerging Markets in Water," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 171-183.
    11. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    12. Rajagopal, 2014. "Technology Diffusion and Adoption," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 6, pages 148-173, Palgrave Macmillan.
    13. David Zilberman & Jinhua Zhao & Amir Heiman, 2012. "Adoption Versus Adaptation, with Emphasis on Climate Change," Annual Review of Resource Economics, Annual Reviews, vol. 4(1), pages 27-53, August.
    14. Margarita Genius & Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2014. "Information Transmission in Irrigation Technology Adoption and Diffusion: Social Learning, Extension Services, and Spatial Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 328-344.
    15. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    16. Ariel Dinar & Dan Yaron, 1992. "Adoption and abandonment of irrigation technologies," Agricultural Economics, International Association of Agricultural Economists, vol. 6(4), pages 315-332, April.
    17. Margriet F. Caswell & David Zilberman, 1986. "The Effects of Well Depth and Land Quality on the Choice of Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(4), pages 798-811.
    18. Shrestha, Rajendra B & Gopalakrishnan, Chennat, 1993. "Adoption and Diffusion of Drip Irrigation Technology: An Econometric Analysis," Economic Development and Cultural Change, University of Chicago Press, vol. 41(2), pages 407-418, January.
    19. Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2006. "Technology Adoption under Production Uncertainty: Theory and Application to Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 657-670.
    20. Alvin Murphy, 2018. "A Dynamic Model of Housing Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 10(4), pages 243-267, November.
    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. Xie, Yang & Zilberman, David, 2014. "The Economics of Water Project Capacities and Conservation Technologies," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169820, Agricultural and Applied Economics Association.
    2. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    3. Hanming Fang & Yang Wang, 2015. "Estimating Dynamic Discrete Choice Models With Hyperbolic Discounting, With An Application To Mammography Decisions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(2), pages 565-596, May.
    4. Xie, Yang & Zilberman, David, 2015. "Water-Storage Capacities versus Water-Use Efficiency: Substitutes or Complements?," 2015 Conference, August 9-14, 2015, Milan, Italy 211894, International Association of Agricultural Economists.
    5. Jean-Louis Fusillier & Lionel Richefort, 2010. "Imitation, rationalité et adoption de technologies d’irrigation améliorées à l’île de la Réunion," Économie et Prévision, Programme National Persée, vol. 193(2), pages 59-73.
    6. Konstantinos Chatzimichael & Dimitris Christopoulos & Spiro Stefanou & Vangelis Tzouvelekas, 2020. "Irrigation practices, water effectiveness and productivity measurement [Toward an understanding of technology adoption: risk, learning, and neighborhood effects]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 467-498.
    7. Konstantinos Chatzimichael & Dimitris Christopoulos & Spyro Stefanou & Vangelis Tzouvelekas, 2015. "Irrigation Technology Adoption, Water Effectiveness and Productivity Measurement," Working Papers 1506, University of Crete, Department of Economics.
    8. Hema Yoganarasimhan, 2013. "The Value of Reputation in an Online Freelance Marketplace," Marketing Science, INFORMS, vol. 32(6), pages 860-891, November.
    9. Gautam, Tej K. & Bhatta, Dependra, 2017. "Determinants Of Irrigation Technology Adoptions And Production Efficiency In Nepal’S Agricultural Sector," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252856, Southern Agricultural Economics Association.
    10. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    11. Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    12. KOUNDOURI Phoebe & NAUGES Céline & TZOUVELEKAS Vangelis, 2009. "The Effect Of Production Uncertainty And Information Dissemination On The Diffusion Of Irrigation Technologies," LERNA Working Papers 09.06.282, LERNA, University of Toulouse.
    13. Linda Steinhübel & Johannes Wegmann & Oliver Mußhoff, 2020. "Digging deep and running dry—the adoption of borewell technology in the face of climate change and urbanization," Agricultural Economics, International Association of Agricultural Economists, vol. 51(5), pages 685-706, September.
    14. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    15. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
    16. Schiraldi, Pasquale & Levy, Matthew R., 2020. "Identification of intertemporal preferences in history-dependent dynamic discrete choice models," CEPR Discussion Papers 14447, C.E.P.R. Discussion Papers.
    17. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
    18. Taylor, Rebecca & Zilberman, David, 2015. "The Diffusion of Process Innovation: The Case of Drip Irrigation in California," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205320, Agricultural and Applied Economics Association.
    19. A. Norets & X. Tang, 2014. "Semiparametric Inference in Dynamic Binary Choice Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1229-1262.
    20. Sara Amoroso, 2014. "The hidden costs of R&D collaboration," JRC Working Papers on Corporate R&D and Innovation 2014-02, Joint Research Centre.

    More about this item

    Keywords

    Risk and Uncertainty; Production Economics; Productivity Analysis and Emerging Technologies;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:ags:aaea18:274474. See general information about how to correct material in RePEc.

    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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.