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Ali, A.

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Ali
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Ali, A.

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  • Impact of direct rice-sowing technology on rice producers' earnings: empirical evidence from Pakistan
    (Taylor & Francis, 2014) Ali, A.; Erenstein, O.; Rahut, D.B.
    Using the comprehensive data set collected from 238 rice producers during 2011, this study estimates the impact of direct seeding of rice-sowing technology on rice and wheat crop yields and farmers' earnings in Pakistan. The propensity score-matching approach was employed to correct for potential sample selection bias that may arise due to systematic differences between the adopters and non-adopters of the direct rice-sowing technology. The empirical results indicate that the adopters of the direct rice-sowing technology have higher rice and wheat crop yields as compared to non-adopters. The rice yields are high, in the range of 8–9 maunds per acre, while the wheat yields are higher, in the range of 2–3 maunds per acre, indicating that the direct rice-sowing technology also has a positive impact on the following wheat crop. Results show that the adopter households have a higher income compared to non-adopter households. Most importantly, the new technology is a water-saving technology and on average it requires four times less irrigation than the traditional rice transplanting method. With the direct rice-sowing technology, the demand for skilled labor was less compared to the traditional transplanting method. However, the new technology is associated with a weed control problem, which needs to be addressed in order to maximize the benefits from the new technology.
    Publication
  • Enhancing smallholder access to agricultural machinery services: lessons from Bangladesh
    (Taylor & Francis, 2016) Mottaleb, K.A.; Rahut, D.B.; Ali, A.; Gerard, B.; Erenstein, O.
    Resource poor smallholders in developing countries often lack access to capital goods such as farm machinery. Enabling adequate access through machinery services can thereby significantly contribute to food security and farm incomes. At the core of the service provision model is the lead farmer, who makes the initial investment in agricultural machinery, and provides services to others on a fee-for-service basis. Profiling the lead farmers can thereby provide important lessons and scaling implications. The present paper provides a case study of Bangladesh, using primary data to characterise the lead farmers. General education, credit availability and risk taking attitude play significant roles in whether or not a farm household will be a lead farmer in Bangladesh.
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