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 language | English (US) |
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Pages (from-to) | 1392-1402 |
Number of pages | 11 |
Journal | European Journal of Operational Research |
Volume | 303 |
Issue number | 3 |
DOIs | |
State | Published - Dec 16 2022 |
Keywords
- OR in agriculture
- Organic rice
- Production risk
- Productivity
- Semiparametric model
ASJC Scopus subject areas
- General Computer Science
- Modeling and Simulation
- Management Science and Operations Research
- Information Systems and Management
- Industrial and Manufacturing Engineering