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

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

    Research output: Contribution to journalArticlepeer-review

    14 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)1392-1402
    JournalEuropean Journal of Operational Research
    Volume303
    Issue number3
    Early online date1 Apr 2022
    DOIs
    Publication statusPublished - 16 Dec 2022

    Keywords

    • Organic rice
    • OR in agriculture
    • Productivity
    • Production risk
    • Semiparametric model
    • Management
    • Operations Research & Management Science
    • Business & Economics

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