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Adoption and economic impacts of laser land leveling in the irrigated rice‐wheat system in Haryana, India using endogenous switching regression

By: Contributor(s): Material type: ArticleLanguage: English Publication details: United Kingdom : Wiley, 2020.ISSN:
  • 0165-0203
  • 1477-8947 (Online)
Subject(s): In: Natural Resources Forum United Kingdom : Wiley, 2020. v. 44, no. 3, p. 255-273Summary: This study assesses the factors affecting the adoption of laser land leveling (LLL) and its impact on crop yields and net returns. It uses household survey data collected from 621 randomly selected farmers in Karnal District of Haryana, India, and applies endogenous switching regression models. Unbiased model results show that the adoption of LLL has significant positive impacts on yields (rice +549 kg ha−1; wheat +471 kg ha−1) and net returns (an aggregate increase of US$230/ha) in the rice‐wheat production system, thereby raising farmers' income substantially. Our results show that LLL adoption at the farm level is influenced by land size and quality, tenure system, availability of farm machinery (tractor), access to finance and farm cooperatives, gender of household head, level of education and training and access to extension services. Therefore, LLL scaling strategies need to consider these bio‐physical and socio‐economic parameters to reach adoption at scale and generate large social, economic, and environmental benefits.
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This study assesses the factors affecting the adoption of laser land leveling (LLL) and its impact on crop yields and net returns. It uses household survey data collected from 621 randomly selected farmers in Karnal District of Haryana, India, and applies endogenous switching regression models. Unbiased model results show that the adoption of LLL has significant positive impacts on yields (rice +549 kg ha−1; wheat +471 kg ha−1) and net returns (an aggregate increase of US$230/ha) in the rice‐wheat production system, thereby raising farmers' income substantially. Our results show that LLL adoption at the farm level is influenced by land size and quality, tenure system, availability of farm machinery (tractor), access to finance and farm cooperatives, gender of household head, level of education and training and access to extension services. Therefore, LLL scaling strategies need to consider these bio‐physical and socio‐economic parameters to reach adoption at scale and generate large social, economic, and environmental benefits.

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