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Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding

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  • Bert Lenaerts
  • Yann de Mey
  • Matty Demont

Abstract

Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision‐making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi‐stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies.

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  • Bert Lenaerts & Yann de Mey & Matty Demont, 2022. "Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 277-300, February.
    • Handle: RePEc:bla:jageco:v:73:y:2022:i:1:p:277-300
    DOI: 10.1111/1477-9552.12450
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    as
    1. Lorenzo Cappellari & Stephen P. Jenkins, 2006. "Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation," Stata Journal, StataCorp LLC, vol. 6(2), pages 156-189, June.
    2. Marra, Michele & Pannell, David J. & Abadi Ghadim, Amir, 2003. "The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve?," Agricultural Systems, Elsevier, vol. 75(2-3), pages 215-234.
    3. Bardsley, Peter, 1999. "The optimal management of research portfolios," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 43(3), pages 1-13, September.
    4. Jensen, Kimberly L. & Lambert, Dayton M. & Clark, Christopher D. & Holt, Caroline & English, Burton C. & Larson, James A. & Yu, T. Edward & Hellwinckel, Chad, 2015. "Cattle Producers’ Willingness To Adopt Or Expand Prescribed Grazing In The United States," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 47(2), pages 213-242, May.
    5. Hubbell, Bryan J. & Marra, Michele C. & Carlson, Gerald A., 2000. "Estimating The Demand For A New Technology: Bt Cotton And Insecticide Policies In The Southeast," Transitions in Agbiotech: Economics of Strategy and Policy, June 24-25, 1999, Washington, D.C. 26016, Regional Research Project NE-165 Private Strategies, Public Policies, and Food System Performance.
    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    7. Sunding, David & Zilberman, David, 2001. "The agricultural innovation process: Research and technology adoption in a changing agricultural sector," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 4, pages 207-261, Elsevier.
    8. Matin Qaim & Alain de Janvry, 2003. "Genetically Modified Crops, Corporate Pricing Strategies, and Farmers' Adoption: The Case of Bt Cotton in Argentina," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 814-828.
    9. Cooper, Joseph C., 1997. "Combining Actual And Contingent Behavior Data To Model Farmer Adoption Of Water Quality Protection Practices," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 22(01), pages 1-14, July.
    10. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    11. Madhu Khanna & Jordan Louviere & Xi Yang, 2017. "Motivations to grow energy crops: the role of crop and contract attributes," Agricultural Economics, International Association of Agricultural Economists, vol. 48(3), pages 263-277, May.
    12. Elaine M. Liu, 2008. "Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China," Working Papers 1064, Princeton University, Department of Economics, Industrial Relations Section..
    13. William J. Burke & Robert J. Myers & Thomas S. Jayne, 2015. "A Triple-Hurdle Model of Production and Market Participation in Kenya's Dairy Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(4), pages 1227-1246.
    14. Joseph Terza, 2009. "Parametric Nonlinear Regression with Endogenous Switching," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 555-580.
    15. Besley, Timothy & Case, Anne, 1993. "Modeling Technology Adoption in Developing Countries," American Economic Review, American Economic Association, vol. 83(2), pages 396-402, May.
    16. Gine, Xavier & Klonner, Stefan, 2005. "Credit constraints as a barrier to technology adoption by the poor : lessons from South Indian small-scale fishery," Policy Research Working Paper Series 3665, The World Bank.
    17. William J Burke, 2019. "Evidence against Imposing Restrictions on Hurdle Models as a Test for Simultaneous versus Sequential Decision Making," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(5), pages 1473-1481.
    18. Madden, David, 2008. "Sample selection versus two-part models revisited: The case of female smoking and drinking," Journal of Health Economics, Elsevier, vol. 27(2), pages 300-307, March.
    19. Zorn, Christopher, 2005. "A Solution to Separation in Binary Response Models," Political Analysis, Cambridge University Press, vol. 13(2), pages 157-170, April.
    20. Bryan J. Hubbell & Michele C. Marra & Gerald A. Carlson, 2000. "Estimating the Demand for a New Technology: Bt Cotton and Insecticide Policies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(1), pages 118-132.
    21. Patrick Puhani, 2000. "The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    22. Hartman, Raymond S, 1991. "A Monte Carlo Analysis of Alternative Estimators in Models Involving Selectivity," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 41-49, January.
    23. David Pannell & David Zilberman, 2020. "Understanding Adoption of Innovations and Behavior Change to Improve Agricultural Policy," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 3-7, March.
    24. Elaine M. Liu, 2013. "Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1386-1403, October.
    25. Julia Bailey-Serres & Jane E. Parker & Elizabeth A. Ainsworth & Giles E. D. Oldroyd & Julian I. Schroeder, 2019. "Genetic strategies for improving crop yields," Nature, Nature, vol. 575(7781), pages 109-118, November.
    26. Rodolfo Hoffmann & Ana Lucia Kassouf, 2005. "Deriving conditional and unconditional marginal effects in log earnings equations estimated by Heckman's procedure," Applied Economics, Taylor & Francis Journals, vol. 37(11), pages 1303-1311.
    27. Bocquého, G. & Jacquet, F., 2010. "The adoption of switchgrass and miscanthus by farmers: Impact of liquidity constraints and risk preferences," Energy Policy, Elsevier, vol. 38(5), pages 2598-2607, May.
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