Impact of training vegetable farmers in Bangladesh in integrated pest management (IPM)
This study quantifies the impact of training vegetable farmers in integrated pest management (IPM) in Bangladesh. Data come from a random sample of 300 trained and 300 non-trained farmers producing either bitter gourd (Momordica charantia L.) or eggplant (Solanum melongena L.). Propensity score matching and inverse probability weighting was employed to correct for selection bias in observable characteristics. A range of outcome indicators along the impact pathway was used. The study finds that trained farmers had better knowledge about insect pests and the proper use of pesticides, adopted more IPM practices, and reduced the frequency of spraying and mixing different pesticides. For eggplant, but not for bitter gourd, trained farmers reduced the quantity of pesticide use and achieved a significantly higher crop yield and gross margin. The effect on consumptive expenditures, which we used as a proxy of income, was insignificant. We conclude that further promotion of IPM adoption among farmers is needed and that it should be a priority to increase the profitability of IPM practices for gradual reduction in synthetic pesticide misuse and a sustainable agricultural production.
| Main Authors: | , , , |
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| Format: | Article biblioteca |
| Language: | English |
| Published: |
Elsevier
2017
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| Subjects: | AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Propensity Score Matching, Inverse Probability Weighting, VEGETABLES, FARMERS, INTEGRATED PEST MANAGEMENT, DEVELOPING COUNTRIES, EGGPLANTS, CUCURBIT VEGETABLES, STATISTICAL METHODS, |
| Online Access: | https://hdl.handle.net/10883/19357 |
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