IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v303y2022i3p1392-1402.html
   My bibliography  Save this article

Does risk management affect productivity of organic rice farmers in India? Evidence from a semiparametric production model

Author

Listed:
  • Lien, Gudbrand
  • Kumbhakar, Subal C.
  • Mishra, Ashok K.
  • Hardaker, J. Brian

Abstract

This study analyzes the effects of farmers’ risk on productivity where the production function is generalized to be specific to risk variables. This resulted in a semiparametric smooth-coefficient (SPSC) production function. The novelty of the SPSC approach is that it can explain the direct and indirect channels through which risk can affect productivity. The study uses several measures of risk, including attitudes toward risk, perceptions of risk, and risk management skills of farmers. It then shows how these risk-related variables affect productivity both directly and indirectly via the inputs. Using 2015 farm-level data from organic basmati rice (OBR) smallholders in India, the study finds that OBR farmers with high degrees of risk aversion had lower productivity than less risk-averse or risk-neutral OBR farmers. Additionally, OBR farmers who were most concerned about production risks (i.e., weather and pest risks) had higher productivity than their counterparts. Finally, the study reveals that OBR farmers can reduce production costs by increasing farm size.

Suggested Citation

  • Lien, Gudbrand & Kumbhakar, Subal C. & Mishra, Ashok K. & Hardaker, J. Brian, 2022. "Does risk management affect productivity of organic rice farmers in India? Evidence from a semiparametric production model," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1392-1402.
    • Handle: RePEc:eee:ejores:v:303:y:2022:i:3:p:1392-1402
    DOI: 10.1016/j.ejor.2022.03.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722002764
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2022.03.051?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dercon, Stefan & Christiaensen, Luc, 2011. "Consumption risk, technology adoption and poverty traps: Evidence from Ethiopia," Journal of Development Economics, Elsevier, vol. 96(2), pages 159-173, November.
    2. Ragnar Tveteras & Ola Flaten & Gudbrand Lien, 2011. "Production risk in multi-output industries: estimates from Norwegian dairy farms," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4403-4414.
    3. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    4. Hans P. Binswanger, 1980. "Attitudes Toward Risk: Experimental Measurement in Rural India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(3), pages 395-407.
    5. Henderson, Daniel J. & Kumbhakar, Subal C. & Parmeter, Christopher F., 2012. "A simple method to visualize results in nonlinear regression models," Economics Letters, Elsevier, vol. 117(3), pages 578-581.
    6. Mishra, Ashkok K. & Kumar, Anjani & Joshi, Pramod Kumar & D’Souza, Alwin & Tripathi, Gaurav, 2018. "Can contract farming in organic basmati rice be a boon to smallholders? Evidence from India:," IFPRI discussion papers 1712, International Food Policy Research Institute (IFPRI).
    7. Serra, Teresa & Oude Lansink, Alfons, 2014. "Measuring the impacts of production risk on technical efficiency: A state-contingent conditional order-m approach," European Journal of Operational Research, Elsevier, vol. 239(1), pages 237-242.
    8. Greg Traxler & Jose Falck-Zepeda & J.I. Ortiz-Monasterio R. & Ken Sayre, 1995. "Production Risk and the Evolution of Varietal Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(1), pages 1-7.
    9. Céline Nauges & Christopher J. O'Donnell & John Quiggin, 2011. "Uncertainty and technical efficiency in Finnish agriculture: a state-contingent approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(4), pages 449-467, October.
    10. Serra, Teresa & Chambers, Robert G. & Oude Lansink, Alfons, 2014. "Measuring technical and environmental efficiency in a state-contingent technology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 706-717.
    11. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    12. Teresa Serra & David Zilberman & Jose Gil & Allen Featherstone, 2009. "The effects of decoupling on land allocation," Applied Economics, Taylor & Francis Journals, vol. 41(18), pages 2323-2333.
    13. Bhavani Shankar & Richard Bennett & Stephen Morse, 2008. "Production risk, pesticide use and GM crop technology in South Africa," Applied Economics, Taylor & Francis Journals, vol. 40(19), pages 2489-2500.
    14. Baležentis, Tomas & Sun, Kai, 2020. "Measurement of technical inefficiency and total factor productivity growth: A semiparametric stochastic input distance frontier approach and the case of Lithuanian dairy farms," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1174-1188.
    15. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
    16. Richard E. Just & Rulon D. Pope, 1979. "Production Function Estimation and Related Risk Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 276-284.
    17. Teresa Serra & David Zilberman & Barry K. Goodwin & Allen Featherstone, 2006. "Effects of decoupling on the mean and variability of output," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 33(3), pages 269-288, September.
    18. Henderson,Daniel J. & Parmeter,Christopher F., 2015. "Applied Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521279680.
    19. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    20. Stephen R. Boucher & Michael R. Carter & Catherine Guirkinger, 2008. "Risk Rationing and Wealth Effects in Credit Markets: Theory and Implications for Agricultural Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 409-423.
    21. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521785235, January.
    22. Christopher O’Donnell & Robert Chambers & John Quiggin, 2010. "Efficiency analysis in the presence of uncertainty," Journal of Productivity Analysis, Springer, vol. 33(1), pages 1-17, February.
    23. Mishra, Ashok K. & Kumar, Anjani & Joshi, Pramod K. & D'Souza, Alwin & Tripathi, Gaurav, 2018. "How can organic rice be a boon to smallholders? Evidence from contract farming in India," Food Policy, Elsevier, vol. 75(C), pages 147-157.
    24. Uri Regev & Nikolaus Gotsch & Peter Rieder, 1997. "Are Fungicides, Nitrogen And Plant Growth Regulators Risk‐Reducing? Empirical Evidence From Swiss Wheat Production," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1‐3), pages 167-178, January.
    25. Bjorn Van Campenhout & Emmanuel Bizimungu, 2018. "Risk and returns of sustainable crop intensification: The case of smallholder rice and potato farmers in Uganda," Development Policy Review, Overseas Development Institute, vol. 36(S2), pages 605-633, September.
    26. Li, Qi, et al, 2002. "Semiparametric Smooth Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 412-422, July.
    27. G. H. Wan & J. R. Anderson, 1990. "Estimating Risk Effects In Chinese Foodgrain Production," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(1), pages 85-93, January.
    28. J. M. Antle & W. J. Goodger, 1984. "Measuring Stochastic Technology: The Case of Tulare Milk Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(3), pages 342-350.
    29. Li, Qi & Racine, Jeffrey S., 2010. "Smooth Varying-Coefficient Estimation And Inference For Qualitative And Quantitative Data," Econometric Theory, Cambridge University Press, vol. 26(6), pages 1607-1637, December.
    30. Boucher, Stephen R. & Carter, Michael R. & Guirkinger, Catherine, 2008. "AJAE Appendix: Risk Rationing and Wealth Effects in Credit Markets: Theory and Implications for Agriculture Development," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(2), pages 1-6.
    31. Gudbrand Lien & Subal C. Kumbhakar & J. Brian Hardaker, 2017. "Accounting for risk in productivity analysis: an application to Norwegian dairy farming," Journal of Productivity Analysis, Springer, vol. 47(3), pages 247-257, June.
    32. Catherine C. Eckel & Philip J. Grossman, 2008. "Forecasting Risk Attitudes: An Experimental Study Using Actual and Forecast Gamble Choices," Monash Economics Working Papers archive-01, Monash University, Department of Economics.
    33. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
    34. Charness, Gary & Gneezy, Uri & Imas, Alex, 2013. "Experimental methods: Eliciting risk preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 43-51.
    35. Sumon Kumar Bhaumik & Ralitza Dimova & Subal C. Kumbhakar & Kai Sun, 2018. "Is Tinkering with Institutional Quality a Panacea for Firm Performance? Insights from a Semiparametric Approach to Modeling Firm Performance," Review of Development Economics, Wiley Blackwell, vol. 22(1), pages 1-22, February.
    36. Salvatore Di Falco & Jean‐Paul Chavas & Melinda Smale, 2007. "Farmer management of production risk on degraded lands: the role of wheat variety diversity in the Tigray region, Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 36(2), pages 147-156, March.
    37. Ashok K. Mishra & Anthony N. Rezitis & Mike G. Tsionas, 2019. "Estimating Technical Efficiency and Production Risk under Contract Farming: A Bayesian Estimation and Stochastic Dominance Methodology," Journal of Agricultural Economics, Wiley Blackwell, vol. 70(2), pages 353-371, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Khanal, Aditya R. & Mishra, Ashok K. & Lien, Gudbrand, 2022. "Risk Aversion, Perceived Climatic and Pest Risks, and the Adoption of Management Strategies: Evidence from an Emerging Economy," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322239, Agricultural and Applied Economics Association.

    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. Ragnar Tveteras & Ola Flaten & Gudbrand Lien, 2011. "Production risk in multi-output industries: estimates from Norwegian dairy farms," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4403-4414.
    2. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    3. Hurley, Terrance M., 2010. "A review of agricultural production risk in the developing world," Working Papers 188476, HarvestChoice.
    4. Patil, V. & Veettil, P.C., 2018. "Experimental Evidence of Risk Attitude of Farmers from Risk-Preference Elicitation in India," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277331, International Association of Agricultural Economists.
    5. Li, Zheng & Rejesus, Roderick M. & Zheng, Xiaoyong, 2018. "Nonparametric Estimation and Inference of Production Risk with Categorical Variables," 2018 Annual Meeting, August 5-7, Washington, D.C. 274400, Agricultural and Applied Economics Association.
    6. Serra, Teresa & Oude Lansink, Alfons, 2014. "Measuring the impacts of production risk on technical efficiency: A state-contingent conditional order-m approach," European Journal of Operational Research, Elsevier, vol. 239(1), pages 237-242.
    7. Theodoros Skevas & Teresa Serra, 2016. "The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 139-153, December.
    8. Nolan, Elizabeth & Santos, Paulo, 2012. "Insurance premiums and GM traits," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125942, International Association of Agricultural Economists.
    9. Zheng Li & Roderick M. Rejesus & Xiaoyong Zheng, 2021. "Nonparametric Estimation and Inference of Production Risk," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1857-1877, October.
    10. Nauges, Céline & Bougherara, Douadia & Koussoubé, Estelle, 2021. "Fertilizer use and risk: New evidence from Sub-Saharan Africa," TSE Working Papers 21-1266, Toulouse School of Economics (TSE).
    11. Amer Ait Sidhoum, 2023. "Measuring farm productivity under production uncertainty," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 672-687, October.
    12. Petraud, Jean & Boucher, Stephen & Carter, Michael, 2015. "Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru," 2015 Conference, August 9-14, 2015, Milan, Italy 211383, International Association of Agricultural Economists.
    13. de Brauw, Alan & Eozenou, Patrick, 2014. "Measuring risk attitudes among Mozambican farmers," Journal of Development Economics, Elsevier, vol. 111(C), pages 61-74.
    14. Kim, Kwansoo & Chavas, Jean-Paul, 2003. "Technological change and risk management: an application to the economics of corn production," Agricultural Economics, Blackwell, vol. 29(2), pages 125-142, October.
    15. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.
    16. François-Charles Wolff, 2020. "The intergenerational transmission of risk attitudes: Evidence from Burkina Faso," Review of Economics of the Household, Springer, vol. 18(1), pages 181-206, March.
    17. Boyd, Chris M. & Bellemare, Marc F., 2022. "Why not insure prices? Experimental evidence from Peru," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 580-631.
    18. Bhaumik, Sumon K. & Dimova, Ralitza & Kumbhakar, Subal C. & Sun, Kai, 2014. "More Is Better! What Can Firm-Specific Estimates of the Impact of Institutional Quality on Performance Tell Us?," IZA Discussion Papers 7886, Institute of Labor Economics (IZA).
    19. Amer Ait Sidhoum, 2023. "Assessing the contribution of farmers’ working conditions to productive efficiency in the presence of uncertainty, a nonparametric approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8601-8622, August.
    20. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.

    More about this item

    Keywords

    OR in agriculture; Productivity; Production risk; Semiparametric model; Organic rice;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures

    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:eee:ejores:v:303:y:2022:i:3:p:1392-1402. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.